Saimm 202205 may by SAIMM

VOLUME 122 NO. 5 MAY 2022

Hydrogen Truck Technology will deliver improvements in safety, efficiency, and sustainability

Source: https://www.angloamerican.com/~/media/Files/A/Anglo-American-Group/PLC/media/presentations/2022pres/bank-of-america-duncan-wanblad-presentation-2022.pdf

SPECIAL THEMED EDITION – CALL FOR PAPERS

DATA SCIENCE – ENABLING AND ENHANCING FUTURE INTELLIGENT MINING AND METALLURGY

he Journal of the SAIMM has pleasure in inviting papers for a special edition to be published during late 2022 or early 2023. Authors are invited to submit papers that would fit into the theme ‘Data Science – Enabling and Enhancing Future Intelligent Mining and Metallurgy.’ The Fourth Industrial Revolution (4IR) or Industry 4.0 has enabled the mining and metallurgical industry to extract meaningful information from structured and unstructured (raw) data for enhanced decision-making. This extraction process utilizes Data Science. Data Science is a multidisciplinary approach that uses fields such as machine learning (ML), artificial intelligence (AI), statistics, and predictive analytics to model the ever-increasing amount of data that the 4IR has made possible. Real-time data is now accessible with the ability to derive real-time knowledge and insight throughout the mining value chain. The use of dynamic models and predictive ML algorithms has allowed the industry to make data-driven decisions and add value to each component of the value chain, ultimately benefitting all the stakeholders, by visualizing complexity and adding simplicity to complicated or ambiguous challenges. Application of 4IR and Data Science offers opportunities for innovative solutions and optimization throughout the extractive value chain of mining and mineral processing. Innovation and technological transformation was identified by KPMG in the 2021 Global Mining Survey Report as a strategy for growth to ensure continued resilience of the mining sector. In this regard, papers covering the above enabler of Data Science in the 4IR are invited. The themes include, but are not limited to, the following.  Digital twin and Internet-of-Things (IoT), with examples of systems, new technologies employed, and key insights.  Process flow / value chain, e.g. Drill and blast, load and haul, processing, value chain optimization, mine planning optimization.  Seismic surveys / slope monitoring e.g. slope failure forecasting, accuracy of targeting resource deposits.  AI/ ML – usage in predictive analysis, forecasting and contribution to Data Science to optimize asset maintenance, mine planning, and health and safety.  Geological modelling, such topics to include mineral deposit modelling, drill and blast method selection, mapping, and exploration.  Addressing significant risks and challenges of the industry such as (but not limited to) tailings management, environmental risks, community relations, ability to access and replace reserves, health and safety.

Anglo American - VOXEL™ industry-first digital transformation platform for data-driven decisions

Source: https://im-mining.com/2021/05/11/anglo-americans-technology-based-new-trajectory-mining/

Artificial intelligence, machine learning, and data science

Source: Elsevier book Vijay Kotu, Bala Deshpande, in Data Science (Second Edition), 2019 Figure 1.1. https://www.sciencedirect.com/topics/physics-and-astronomy/artificial-intelligence

Papers should be submitted to: Kelly Matthee | Journal Coordinator | SAIMM Email: kelly@saimm.co.za | Tel: +27 11 538-0238 | www.saimm.co.za

The Southern African Institute of Mining and Metallurgy OFFICE BEARERS AND COUNCIL FOR THE 2020/2021 SESSION Honorary President

Nolitha Fakude President, Minerals Council South Africa

Honorary Vice Presidents

Gwede Mantashe Minister of Mineral Resources, South Africa Ebrahim Patel Minister of Trade, Industry and Competition, South Africa Blade Nzimande Minister of Higher Education, Science and Technology, South Africa

President

I.J. Geldenhuys

President Elect Z. Botha

Senior Vice President W.C. Joughin

Junior Vice President E. Matinde

Incoming Junior Vice President G.R. Lane

Immediate Past President V.G. Duke

Honorary Treasurer W.C. Joughin

Ordinary Members on Council Z. Fakhraei B. Genc K.M. Letsoalo S.B. Madolo F.T. Manyanga T.M. Mmola G. Njowa

S.J. Ntsoelengoe S.M. Rupprecht A.J.S. Spearing M.H. Solomon S.J. Tose A.T. van Zyl E.J. Walls

Co-opted to Members M. Aziz M.I. van der Bank

Past Presidents Serving on Council N.A. Barcza R.D. Beck J.R. Dixon R.T. Jones A.S. Macfarlane M.I. Mthenjane C. Musingwini

S. Ndlovu J.L. Porter S.J. Ramokgopa M.H. Rogers D.A.J. Ross-Watt G.L. Smith W.H. van Niekerk

G.R. Lane–TPC Mining Chairperson Z. Botha–TPC Metallurgy Chairperson A.T. Chinhava–YPC Chairperson M.A. Mello––YPC Vice Chairperson

Branch Chairpersons Johannesburg Namibia Northern Cape Pretoria Western Cape Zambia Zimbabwe Zululand

D.F. Jensen N.M. Namate Jaco Mans Vacant A.B. Nesbitt Vacant C.P. Sadomba C.W. Mienie

PAST PRESIDENTS *Deceased

* W. Bettel (1894–1895) * A.F. Crosse (1895–1896) * W.R. Feldtmann (1896–1897) * C. Butters (1897–1898) * J. Loevy (1898–1899) * J.R. Williams (1899–1903) * S.H. Pearce (1903–1904) * W.A. Caldecott (1904–1905) * W. Cullen (1905–1906) * E.H. Johnson (1906–1907) * J. Yates (1907–1908) * R.G. Bevington (1908–1909) * A. McA. Johnston (1909–1910) * J. Moir (1910–1911) * C.B. Saner (1911–1912) * W.R. Dowling (1912–1913) * A. Richardson (1913–1914) * G.H. Stanley (1914–1915) * J.E. Thomas (1915–1916) * J.A. Wilkinson (1916–1917) * G. Hildick-Smith (1917–1918) * H.S. Meyer (1918–1919) * J. Gray (1919–1920) * J. Chilton (1920–1921) * F. Wartenweiler (1921–1922) * G.A. Watermeyer (1922–1923) * F.W. Watson (1923–1924) * C.J. Gray (1924–1925) * H.A. White (1925–1926) * H.R. Adam (1926–1927) * Sir Robert Kotze (1927–1928) * J.A. Woodburn (1928–1929) * H. Pirow (1929–1930) * J. Henderson (1930–1931) * A. King (1931–1932) * V. Nimmo-Dewar (1932–1933) * P.N. Lategan (1933–1934) * E.C. Ranson (1934–1935) * R.A. Flugge-De-Smidt (1935–1936) * T.K. Prentice (1936–1937) * R.S.G. Stokes (1937–1938) * P.E. Hall (1938–1939) * E.H.A. Joseph (1939–1940) * J.H. Dobson (1940–1941) * Theo Meyer (1941–1942) * John V. Muller (1942–1943) * C. Biccard Jeppe (1943–1944) * P.J. Louis Bok (1944–1945) * J.T. McIntyre (1945–1946) * M. Falcon (1946–1947) * A. Clemens (1947–1948) * F.G. Hill (1948–1949) * O.A.E. Jackson (1949–1950) * W.E. Gooday (1950–1951) * C.J. Irving (1951–1952) * D.D. Stitt (1952–1953) * M.C.G. Meyer (1953–1954) * L.A. Bushell (1954–1955) * H. Britten (1955–1956) * Wm. Bleloch (1956–1957) * H. Simon (1957–1958) * M. Barcza (1958–1959)

* R.J. Adamson (1959–1960) * W.S. Findlay (1960–1961) * D.G. Maxwell (1961–1962) * J. de V. Lambrechts (1962–1963) * J.F. Reid (1963–1964) * D.M. Jamieson (1964–1965) * H.E. Cross (1965–1966) * D. Gordon Jones (1966–1967) * P. Lambooy (1967–1968) * R.C.J. Goode (1968–1969) * J.K.E. Douglas (1969–1970) * V.C. Robinson (1970–1971) * D.D. Howat (1971–1972) * J.P. Hugo (1972–1973) * P.W.J. van Rensburg (1973–1974) * R.P. Plewman (1974–1975) * R.E. Robinson (1975–1976) * M.D.G. Salamon (1976–1977) * P.A. Von Wielligh (1977–1978) * M.G. Atmore (1978–1979) * D.A. Viljoen (1979–1980) * P.R. Jochens (1980–1981) * G.Y. Nisbet (1981–1982) A.N. Brown (1982–1983) * R.P. King (1983–1984) J.D. Austin (1984–1985) * H.E. James (1985–1986) H. Wagner (1986–1987) * B.C. Alberts (1987–1988) * C.E. Fivaz (1988–1989) * O.K.H. Steffen (1989–1990) * H.G. Mosenthal (1990–1991) R.D. Beck (1991–1992) * J.P. Hoffman (1992–1993) * H. Scott-Russell (1993–1994) J.A. Cruise (1994–1995) D.A.J. Ross-Watt (1995–1996) N.A. Barcza (1996–1997) * R.P. Mohring (1997–1998) J.R. Dixon (1998–1999) M.H. Rogers (1999–2000) L.A. Cramer (2000–2001) * A.A.B. Douglas (2001–2002) S.J. Ramokgopa (2002-2003) T.R. Stacey (2003–2004) F.M.G. Egerton (2004–2005) W.H. van Niekerk (2005–2006) R.P.H. Willis (2006–2007) R.G.B. Pickering (2007–2008) A.M. Garbers-Craig (2008–2009) J.C. Ngoma (2009–2010) G.V.R. Landman (2010–2011) J.N. van der Merwe (2011–2012) G.L. Smith (2012–2013) M. Dworzanowski (2013–2014) J.L. Porter (2014–2015) R.T. Jones (2015–2016) C. Musingwini (2016–2017) S. Ndlovu (2017–2018) A.S. Macfarlane (2018–2019) M.I. Mthenjane (2019–2020) V.G. Duke (2020–2021)

Honorary Legal Advisers M H Attorneys

Auditors

Genesis Chartered Accountants

Secretaries

The Southern African Institute of Mining and Metallurgy Fifth Floor, Minerals Council South Africa 5 Hollard Street, Johannesburg 2001 • P.O. Box 61127, Marshalltown 2107 E-mail: journal@saimm.co.za

Editorial Board S.O. Bada R.D. Beck P. den Hoed I.M. Dikgwatlhe R. Dimitrakopolous* M. Dworzanowski* L. Falcon B. Genc R.T. Jones W.C. Joughin A.J. Kinghorn D.E.P. Klenam H.M. Lodewijks D.F. Malan R. Mitra* H. Möller C. Musingwini S. Ndlovu P.N. Neingo M. Nicol* S.S. Nyoni M. Phasha P. Pistorius P. Radcliffe N. Rampersad Q.G. Reynolds I. Robinson S.M. Rupprecht K.C. Sole A.J.S. Spearing* T.R. Stacey E. Topal* D. Tudor* F.D.L. Uahengo D. Vogt* *International Advisory Board members

Editor /Chairman of the Editorial Board R.M.S. Falcon

Typeset and Published by The Southern African Institute of Mining and Metallurgy P.O. Box 61127 Marshalltown 2107 E-mail: journal@saimm.co.za

Printed by

Camera Press, Johannesburg

VOLUME 122 NO. 5 MAY 2022

Contents Journal Comment: Battery metals – The Next Big Thing? by M. Dworzanowski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

President’s Corner: The right thing to do and the hard thing to do are usually the same thing by I.J. Geldenhuys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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NEWS OF T SINER SAMCODES News: SAMESG Guideline by A. McDonald . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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PROFESSIONAL TECHNICAL AND SCIENTIFIC PAPERS Overview of mine rescue approaches for underground coal fires: A South African perspective by M. Onifade, B. Genc, K.O. Said, M. Fourie, and P.O. Akinseye . . . . . . . . .

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This study reviews the various technological safety systems and principles that are used for safe-rescue and self-escape of miners in underground coal fires, particularly in South Africa. The outcome of the review shows that practising safety culture has been given priority across many South African underground coal mines. Stability analysis of a free-standing backfill wall and a predictive equation for estimating the required strength of a backfill material – a numerical modelling approach by J.L. Porathur, S. Sekhar, A.K. Godugu, and S. Bhargava . . . . . . . . . . . . .

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Three-dimensional numerical modelling was conducted to study the effect of various stoping parameters on the stability of a free-standing backfill wall. A strength reduction technique was employed to arrive at a minimum stable strength value of the backfill. From the simulations, an equation was developed to predict the required strength parameters for a backfill mix to ensure a stable free-standing wall.

Advertising Representative Barbara Spence Avenue Advertising Telephone (011) 463-7940 E-mail: barbara@avenue.co.za ISSN 2225-6253 (print) ISSN 2411-9717 (online)

Directory of Open Access Journals

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THE INSTITUTE, AS A BODY, IS NOT RESPONSIBLE FOR THE STATEMENTS AND OPINIONS ADVANCED IN ANY OF ITS PUBLICATIONS. Copyright© 2022 by The Southern African Institute of Mining and Metallurgy. All rights reserved. Multiple copying of the contents of this publication or parts thereof without permission is in breach of copyright, but permission is hereby given for the copying of titles and abstracts of papers and names of authors. Permission to copy illustrations and short extracts from the text of individual contributions is usually given upon written application to the Institute, provided that the source (and where appropriate, the copyright) is acknowledged. Apart from any fair dealing for the purposes of review or criticism under The Copyright Act no. 98, 1978, Section 12, of the Republic of South Africa, a single copy of an article may be supplied by a library for the purposes of research or private study. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without the prior permission of the publishers. Multiple copying of the contents of the publication without permission is always illegal. U.S. Copyright Law applicable to users In the U.S.A. The appearance of the statement of copyright at the bottom of the first page of an article appearing in this journal indicates that the copyright holder consents to the making of copies of the article for personal or internal use. This consent is given on condition that the copier pays the stated fee for each copy of a paper beyond that permitted by Section 107 or 108 of the U.S. Copyright Law. The fee is to be paid through the Copyright Clearance Center, Inc., Operations Center, P.O. Box 765, Schenectady, New York 12301, U.S.A. This consent does not extend to other kinds of copying, such as copying for general distribution, for advertising or promotional purposes, for creating new collective works, or for resale.

MAY 2022

VOLUME 122

The Journal of the Southern African Institute of Mining and Metallurgy

PROFESSIONAL TECHNICAL AND SCIENTIFIC PAPERS Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines by A. Tekin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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A field study was conducted to evaluate the vibration risks to the operators using mining machines in open pit mines. The vibration levels and whole-body vibration (WBV) measurements were compared to the criteria specified in the EU 2002/44/EC directive and ISO 2631-1 (1997). The data collected and the recommended improvements that need to be made to reduce WBV exposures are presented. Investigation of the mixing characteristics of industrial flotation columns using computational fluid dynamics by I. Mwandawande, S.M. Bradshaw, M. Karimi, and G. Akdogan . . . . . . . . . . . . . . .

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The mixing characteristics of industrial flotation columns were investigated using computational fluid dynamics (CFD), with particular emphasis on the relationship between the liquid and solids mixing parameters and the effects of particle size and bubble size on liquid dispersion in the column. The simulated axial velocity profiles confirmed the similarity between the liquid and solids axial dispersion coefficients in column flotation. Study on the ideal location of a bottom drainage roadway by H. Chen, F. An1, Z. Wang, and X. Chen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The bottom drainage roadway plays a crucial role in preventing coal and gas outbursts by using underground gas drainage methods. We studied the ideal position of the bottom drainage roadway using geological data and numerical simulation, taking the gas drainage at a mine in Shanxi Province, China as an example. The results of this study are expected to provide a reference for the selection of the ideal position of the bottom drainage roadway in field engineering.

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Journ

ent Comm

Battery metals – The Next Big Thing?

ining and metallurgy have been linked throughout time to the development of the human race. You can argue that the First Big Thing was precious metals. Gold and silver have been symbols of wealth since at least Egyptian times. Then the Bronze Age signalled the Second Big Thing, base metals. This started initially with copper and tin to make bronze. Lead was also used during the Bronze Age. Then after this, the Iron Age brought on the Third Big Thing – ferrous metals. Initially this involved only iron. Over time platinum group metals were included with the precious metals and zinc, nickel, and aluminium with the base metals. Ferrous metals have certainly expanded the most via a vast array of alloys, notably steel and stainless steel.

So, what is the Next Big Thing? It has to be battery metals. After the interruption caused by the Covid-19 pandemic, the world has become engulfed by a green revolution. The most prominent aspect of this is rechargeable batteries, especially those for electric vehicles. These batteries require mainly lithium, nickel, cobalt, and manganese. Nickel and manganese were well established within the ferrous metals sector but lithium and cobalt were previously considered minor metals. Now, of course, lithium in particular is viewed as the ’flavour of the month’. Skyrocketing prices of lithium and cobalt in particular have caused an exploration boom, with geologists all over the world looking for lithium and cobalt, amongst many other metals. From a metallurgical perspective battery metals bring new challenges. All battery metals have to be supplied as very pure salts, usually a minimum of 99.9%, with lithium in the form of carbonate or hydroxide and the others in the form of sulphates. This has resulted in considerable process development research to meet the ever-increasing purity requirements. The demand for battery metals has had, and will continue to have, an enormous impact on the global mining industry. Geologists, mining engineers, and metallurgists will continue to face greater challenges in the discovery, mining, and processing of battery metals. It is also fair to say that battery metals have really highlighted the contribution of the mining industry to global economic development. And long may this continue!

M. Dworzanowski

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The right thing to do and the hard thing to do are usually the same thing

s dent’

Presi

Corn

he devastation caused by severe flooding in KwaZulu-Natal in April 2022 caused untold hardship. More than 450 people lost their lives, thousands were displaced, losing their homes, and their dignity as the flood waters destroyed houses, washed away roads, and triggered mudslides in densely populated areas. The economic impact on the region and the country is yet to be tallied, but the pictures of homes and businesses destroyed or damaged by the raging waters tells the story. In a period of just 24 hours, spanning 11 to 12 April 2022, Virginia Airport (10 km northeast of Durban) recorded 304 mm of precipitation. Along the coast 450 millimetres was recorded over the two days.

The deluge followed days of high rainfall, leading to a disaster that not only devastated the communities in the province but also impacted the national grid’s capacity. Eskom’s already fragile generation capacity was directly and indirectly affected. A hydroelectric dam operated by Eskom was overwhelmed by rising waters, rendering it inoperable. Eskom CEO Andre de Ruyter announced on 12 April that rolling blackouts would occur due to issues in the network caused by the excessive rains. At the Drakensberg Pumped Storage Scheme, debris on grids protecting the turbines needed clearing and on the Ingula Pumped Storage Scheme, both the upper and lower dam were at full capacity, and emptying the upper dam could have resulted in more flooding. The impact of the storm caused many more ripple effects. Transnet, for example, was forced to suspend port operations in Durban. The heavy rains damaged roads leading into the port and the city. Shipping into the port was suspended and freight transport companies were told not to send cargo to Durban. The floods in KwaZulu-Natal show clearly how an extreme weather event can have an impact through ripple effects on a much broader scale. Perhaps extreme weather events will not happen where you live, but the indirect impact will be felt by all. Thus, while the severe rainfall recorded in KwaZulu-Natal is in line with the levels of precipitation expected during a tropical cyclone, the frequency of such events will increase as climate change shifts weather patterns. The storm may not be directly attributed to climate change, but one can only imagine the impact if these types of storms occur more often. With so many pressing issues, locally and globally, a mission-oriented approach is required. We must be mission-driven to tackle grand challenges The most recent UN climate change report laid out in devastating detail the past, present, and future impacts of climate change on people and the planet they depend on. In April 2022, the people of KwaZuluNatal experienced the impact of extreme weather in a devastating tragedy. Scientists now consider it unequivocal that humans are responsible for this accelerating climatic upheaval. One hardly hears climate-sceptic commentary any more, but there is still a significant ‘delay discourse’ advocated by many. We recognize that climate change is a reality and that it is of human origin, but everyone seeks to justify minimal action or no action in the interest

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President’s Corner (Continued) of a ‘just transition’. Our focus should be on tackling these challenges through a grand scheme of change – a mission – because just as we have come to accept global warming on the scientific evidence, there is no doubt that a well-managed transformation is needed to ensure socio-economic stability. If we all do not have food, water, and housing security, the economy cannot thrive – we cannot thrive. The Intergovernmental Panel on Climate Change (IPCC) report focuses on how we might get ourselves out of the mess we have created, and the message is clear – we need transformation at a large scale in all major systems: energy, transport, infrastructure, buildings, agriculture, and food. How we build our cities, how we provide energy, how we travel – all these things require grand missions to address. The floods in KwaZulu-Natal also highlighted the weaknesses in local stormwater infrastructure and urban development, and even the impact of plastic pollution on stormwater systems as plastic waste blocked drains and waterways. This tragic event should be seen as an opportunity to make the right choices going forward. We are at a crossroads and, depending on the decisions taken, we can contribute to making the impact of climate change worse or we can contribute towards the mission of addressing the grand challenge. We can only hope that the tragedy triggers an important conversation about how we are preparing for the impact of climate change in general. The damage in KwaZulu-Natal was exacerbated due to the lack of proper infrastructure development and maintenance and haphazard and desperate urbanization through informal and semi-informal housing built on flood-prone land. As pointed out by President Cyril Ramaphosa, the disaster has national implications and other parts of the country are just as vulnerable to severe weather. The President established the Presidential Climate Commission in December 2020, made up of all stakeholders, including businesses. The Commission was tasked with ensuring that the so-called ‘just transition’ from our fossil-fuel-based economy to a greener future is managed effectively. However, the flood disaster highlights the fact that we need to also apply ourselves urgently to the challenges that climate change presents to the economy – from agriculture to manufacturing – and that we need to accelerate and implement real change now. We all should support the fossil fuel transition to ensure we mitigate global climate change, but we also must be realistic about the fact that climate change is already materially threatening our lives and livelihoods. The message from the UN is that it is never too late to start the transition to a green economy, but we cannot expect a free ride, especially if we continue to delay for another 10, 20, or 30 years. ‘It is never too late to be what you might have been.’ - George Eliot.

I.J. Geldenhuys President, SAIMM

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Overview of mine rescue approaches for underground coal fires: A South African perspective by M. Onifade1,2, B. Genc2, K.O. Said3, M. Fourie4, and P.O. Akinseye2 Affiliation:

Department of Mining and Metallurgical Engineering, University of Namibia, Namibia. 2 School of Mining Engineering, University of the Witwatersrand, Johannesburg, South Africa. 3 Mining and Mineral Processing Engineering Department, Taita Taveta University, Voi, Kenya. 4 Mines Rescue Services – SA, Carletonville, South Africa. 1

Correspondence to: B. Genc

Email:

Bekir.genc@wits.ac.za

Dates:

Received: 10 Sep. 2021 Revised: 17 Jan. 2022 Accepted: 17 Mar 2022 Published: May 2022

Synopsis Coal is mined by both surface and underground methods and its extraction is normally characterized by numerous hazards that can lead to catastrophic accidents, which result in devastating effects such as injuries or fatalities, damage to mining assets, and destruction of mineral resources. These hazards exist due to the ability of coal to support combustion and its association with toxic, flammable, and explosive gases. Underground coal mining entails higher safety risks than opencast coal mining, chiefly because of issues relating to mine ventilation and mine collapse. Furthermore, coal mine collapses mostly occur due to crumbling of mining supports, especially in room and pillar mining systems. To avoid such adverse occurrences, safety management systems need to be in place. This study reviews the various technological safety systems and principles that are used for safe-rescue and self-escape of miners in underground coal fires, particularly in South Africa, using data obtained from Mines Rescue Services in Carltonville, South Africa. The outcome of the review shows that practising safety culture has been given priority across many South African underground coal mines through setting up safety management systems and encouraging workers to stay committed to safety principles.

Keywords mine rescue, self-escape, underground coal fires, toxic gases, coal mining.

How to cite:

Onifade, M., Genc, B. Said, K.O., Fourie, M., and Akinseye, P.O. 2022 Overview of mine rescue approaches for underground coal fires: A South African perspective. Journal of the Southern African Institute of Mining and Metallurgy, vol. 122, no. 5, pp. 213-226 DOI ID: http://dx.doi.org/10.17159/24119717/1738/2022 ORCID: B. Genc https://orcid.org/0000-00023943-5103 P.O. Akinseye https://orcid.org/0000-00020519-5957

Introduction The success of any industry is measured not only by its production capacity, but also the ability to conduct operations in a sustainable and safe manner. The maintenance of safe operations requires continuous, accurate identification of hazards, correct evaluation of related risks, and the application of an appropriate treatment thereof in order to eliminate the chances of accidents occurring. It is generally widely accepted within industries that various risk assessment methods aid in ensuring the safety of complex operations and equipment use. There is a statutory provision in many industries for risk assessment of all dangerous structures, machinery, and facilities, considering the methods used for production, repair, supervision and management (Tripathy and Ala, 2018). This is most important in the mining industry as the operations are characterized by significant risks that can compromise the health and safety of miners. Keen attention is required from the workers as the hazards in any mining environment can be extremely harmful due to the sophisticated machinery and equipment used (Zhou et al., 2018). While external safety agents are normally used in many other industries, the coal mining industry requires in-house safety personnel, commitment, practises, and culture, which should be promoted on a daily basis by the workers. In the mining business, safety has been a major concern for decades, especially in underground mining. Although today's mining is significantly safer than in previous decades, there are still mining accidents. Underground coal mining has traditionally posed some of the greatest risks for the health and safety of the workers (Graber et al., 2014). However, this situation has been greatly improved due to frequent safety training exercises conducted to educate the workers about the relevance of occupational health and safety. In some countries, the regulatory emphasis has followed a commitment to hazard identification, risk evaluation, treatment, and regulation, while in others a prescriptive approach prevails, and yet in other places, there is a lack of national safety and health legislation. Ventilation is the greatest hurdle that compromises safety in underground coal mines. Poor ventilation design exposes miners to harmful gases, heat, and dust that can harm them by affecting their

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Overview of mine rescue approaches for underground coal fires: A South African perspective respiratory systems. The quantity of harmful gases and airborne contaminants in underground spaces can be reduced by diluting them, capturing them before reaching the air host stream, or by isolating the environment through seals and stoppings (National Institute for Occupational Safety and Health (NIOSH), 2015). Coal dust explosions in coal mines are normally caused by methane ignition. Mining equipment can produce sparks that are capable of igniting accumulated methane gas in coal mines. Over time, many major incidents have been averted or ameliorated by the self-escape of miners from dangerous environments. Self-escaping has been facilitated by using various aids. Currently, the passive self-escape techniques being used comprise signs, markers for indicating primary and secondary escape routes, as well as lifelines. More safety tools to help in selfescaping in the dark, such as safety canes for locating mine ribs and handheld laser pointers, have also been examined. Lifelines are important in underground coal mines to aid self-escaping miners by directing them to the escape routes. The physical and geological complexities of underground coal mines, together with mineworkers’ poor understanding of the underground structures or workings, could damage the environmental and operational resources of the mines. Despite the accurate mineral exploration technologies that are used to locate minerals, unexpected geological structures remain a critical hazard to miners working in such underground spaces, which increase the exposure of miners to hazards. Due to the numerous hazard exposures in the underground coal mine environment, this study reviews the various technological safety systems and principles that are used for safe-rescue and self-escape of miners in underground coal fires, particularly in South Africa, and to minimize, control, or eliminate hazards in an effort to promote mine safety. The paper focuses on data obtained from Mines Rescue Services in Carltonville, South Africa, together with analyses from previous studies to investigate and evaluate the various technological safety systems and principles that are used for safe-rescue and self-escape of miners in underground coal fires. Considerations of the total number of underground fires, the number of fires dealt with by Mines Rescue Services, and the number of coal mine fire fatalities that Mines Rescue Services has dealt with over the years, were captured in this report.

Fires in underground coal mines Fires in coal mines can be difficult, if not impossible, to extinguish as the combustion of coal itself can supply enough oxygen gas to sustain fires for years or decades, even if the mine is flooded with water or inert gases. Examples of fires that lasted for years include the incidents at Mount Wingen, Pennsylvania and Saarland. The fire at Mount Wingen in New South Wales Australia was located 30 m below the surface, and it is believed that the coal seam had been burning for 6000 years (Loughnan and Roberts, 1981). The coal fire in Pennsylvania occurred in a former open cut coal mine in 1962 after a neighbouring community accidentally ignited it, and because it has been burning ever since, the town has had to be abandoned (Pratt, 1987). Lastly, in the state of Saarland of Germany, coal spontaneous combustion started in the middle 17th century and has been burning to date (Singh, 2013). In South Africa, coal spontaneous combustion has been established as the main cause of fire in coal mines (Gouws and Knoetze, 1995). It was difficult to collect data from the South African coal mines on the number of occurrences of spontaneous 214

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combustion and coal dust explosions. One reason for this could be the fact that incidents of self-heating may also be treated by loading out hot coal before a fire takes hold. Hence it is likely that reports on spontaneous combustion document only those incidents that progressed to the point that a report to the Mining Inspector was required. Statistics often represent only accidents in underground collieries and do not show the extent of the problem regarding strip mines, dumps, stocks, abandoned mines, or ships, as shown in Figures 1–3. There are also problems in isolating cases of coal-dust explosions. Data is typically available for recorded ignitions and explosions, or fires caused by flammable gases. In most situations, methane is responsible for the accident. The cause of the accident is thoroughly investigated only in the case of especially violent accidents, and in those situations a secondary coal-dust explosion is typically assumed (Gouws and Knoetze, 1995). Spontaneous combustion is the primary cause of underground fires, and a coal-dust explosion has the ability to turn an accident or explosion occurrence into a major disaster. While there have been no fatalities or recorded injuries due to spontaneous combustion for more than 20 years in South Africa, there is still a potential for serious accidents, as this phenomenon has been the main cause of fires in South African collieries over the same period (Gouws and Knoetze, 1994). Underground fires, possibly caused by spontaneous combustion, have been burning in some abandoned coal mines for several years. Such fires cause subsidence of the surface, by the collapse of either the pillars or the bords, rendering the land unsuitable for residential or agricultural purposes (Phillips, Chabedi, and Uludag, 2011; Gouws and Knoetze, 1995). An underground fire has also recently threatened the rail link between South Africa and Mozambique. Subsidence in shallow abandoned mines also results in cracks propagating to the surface, allowing the ingress of air and water. Mines Rescue Services provides emergency response services to the South African mining industry. The underground fire statistics shown in Figures 1–3 indicate the underground fire occurrences that Mines Emergency Services has dealt with over the years. While total number of underground fires is shown in Figure 1, Figure 2 illustrates the number of coal mine fires in South Africa. From the statistics in Figure 3 it is evident that such fires certainly represent the single highest risk on any coal mine. Mines Rescue Services have had to deal with several fatalities during underground coal mine fires over the years. The other risk that is seen in the same light as underground coal mine fires is most certainly flammable gas explosions, which have claimed more lives over the years than any other miningrelated risk (Table I). Most of these explosions result in multiple fatalities and can be regarded as disasters.

Emergency response planning for safe rescue in underground coal mines As indicated previously, underground coal mines are characterized by numerous life-threatening hazards such as fires, explosions, toxic gases, dust, and mine collapse, but the major problem, which has the most devastating effects, is coal mine fires (Azam and Mishra, 2019; Stracher and Taylor, 2004; Wang, Yang, and Li, 2018). When such emergencies occur, it is required that miners evacuate the mine premises immediately and in a safe manner. To achieve this, this study proposes the seven steps indicated in Table II in order to achieve an optimum, safe rescue/escape operation. The Journal of the Southern African Institute of Mining and Metallurgy

Overview of mine rescue approaches for underground coal fires: A South African perspective

Figure 1—The total number of underground fires dealt with by Mines Rescue Services in South Africa

Figure 2—The total number of coal mine fires dealt with by Mines Rescue Services in South Africa

Figure 3—The number of coal mine fire fatalities that Mines Rescue Services have dealt with in South Africa over the years

Additionally, for any coal mine there should be a rescue team on standby to respond to any emergencies from hazards. However, the effectiveness of these rescue teams depends on the timely execution of self-escape procedures.

Safety measures for self-escape from underground coal mines Coal mining is characterized by numerous hazards such as noise, dust, risk of electrocution, diesel emissions, rockfalls, The Journal of the Southern African Institute of Mining and Metallurgy

explosions, and spontaneous combustion, which require adequate management to avoid devastating accidents. Fire and explosion are the leading hazards in hard coal mines, and normally lead to serious injuries and fatalities. It is worth mentioning that exogenous fires are more hazardous than coal mine fires, but they are rare with very minimal possibility of occurrence. In this vein, whenever a fire breaks out in longwall mining, miners should evacuate to the surface using escape routes are not affected by toxic gases emitted from the fires. VOLUME 122

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Overview of mine rescue approaches for underground coal fires: A South African perspective resulting from an explosion or fire, so they may have difficulty locating a lifeline (Gouws and Phillips, 1995). It is important to note that the literature does not clearly state the conditions that must be complied with in designing escape routes, but only specifies that one must note the safe ways of evacuating workers from the mining zones in case of fire outbreaks that cause poor visibility. In light of this, the efficiency and effectiveness of any escape route depends on numerous human and technical factors (Badura, Grodzicka, and Musioł, 2017). The technical elements include design of the escape route heading, machinery or equipment in the route heading such as conveyors, withdrawing direction, the upwards or downwards inclination angle, the position of communication systems, marking of the escape route, and escape respirators. The human factors include the skills to use escape respirators, the knowledge of how to carry on through the escape route, resistance to stressrelated conditions arising in the heading, and decision-making capabilities in the course of a staff self-rescue operation. Despite intensive research towards improving the occupational health and safety of workers in coal mines, there is still a need to look for better solutions to improve safety, especially for miners escaping from emergencies that are lifethreatening. The study by NIOSH (2016), which involved miners, rescue crews, safety officers, and researchers, indicated that escaping very early during underground mine emergencies is critical in order to survive such adverse occurrences. Thereafter, researchers at NIOSH conducted a study that considered behavioural and environmental conditions as well as miners’ skills that facilitate successful escape from underground coal mines. The study by Badura, Grodzicka, and Musioł (2017) analysed crew evacuations during fire hazards between 1990 and 2013 in Poland. The study indicated that 2574 miners were evacuated from affected headings. Out of this number, 1312 evacuations were due to coal spontaneous combustion fires and 1262 due to exogenous fires. The largest number of miners evacuated

Table I

atalities due to flammable gas explosions occurrences in F underground coal mines on human lives over the years Mine

Year

Casualties

Hlobane coal mine Hlobane coal mine Middelbult colliery Ermelo coal mine St Helena gold mine Middlebult colliery Mponeng gold mine Beatrix gold mine Beatrix gold mine Gloria gold mine

1944 1983 1985 1987 1987 1993 1999 2000 2001 2019

57 64 33 34 63 53 18 7 12 28

Over time, many major incidents in coal mines have been averted or ameliorated by the self-escape of miners from dangerous environments. Self-escaping has been facilitated by using various aids. Currently, the passive self-escape techniques being used consist of signs, markers for indicating primary and secondary escape routes, as well as lifelines. Other safety tools to help miners self-escaping in the dark, such as safety canes for locating mine ribs and handheld laser pointers, have also been considered. Lifelines are important in underground coal mines to aid self-escaping by directing miners to the escape routes. Lifelines function by providing signals using cones, spheres, and cylinders that can be felt with the hands to direct miners to escape routes in dark areas where visibility is poor. Other lifelines are used to warn of critical emergencies lying ahead of an escape route such as pitfalls and blockages (Brenkley, Lewis, and Jozefowicz, 1998; Mine Safety and Health Administration (MSHA), 1999). However, lifelines must be within the reach of the miners, which can be difficult under critical emergency situations. For example, miners can typically become disorientated due to poor visibility

Table II

Steps to be taken in planning for optimum safe rescue Response planning for safe rescue (Escape strategy)

Key issues to consider

1. Clearly understand the ongoing mining situation.

• • • • • • • • • • • • • • • • • • • • • • •

2. Factor in all the natural hazards present in the mine.

3. Identify all risky activities. 4. Consider occurrence of unexpected incidents. 5. Identify possible hazards.

6. Assess all the possible risks. 7. Develop an emergency response plan.

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Type of mining method used. Mine map and the major exits. Safety operation procedures. Total number of miners working in the underground mine. The distance and conditions of escape routes. Heat and humidity. Water inundation. Dust production. Harmful gases present. Handling of harmful substances such as fuels and detonators. Storage of explosives. Blasting activities. Failing of ventilation system(s). Leaking of gases and eruption. Heat from machinery and friction. Insufficient breathable air. Fires. Explosions. Mine collapse. List and evaluate all risks according to degree of damage. Prepare an emergency plan. Provide emergency equipment. Ensure appropriate emergency training. The Journal of the Southern African Institute of Mining and Metallurgy

Overview of mine rescue approaches for underground coal fires: A South African perspective was 488 at the Bielszowice hard coal mine in 2005. The fire was caused by short-circuiting of a 6 kV cable duct on the surface connected to the downcast shaft. A huge amount of smoke occurred in the heading of escape routes and reduced visibility . This necessitated equipping escape routes with directional signage to provide guidance during escape. Mining companies utilize various techniques to mark escape routes and directions for crew evacuation, but metal signs that are well labelled according to the heading location and direction of evacuation for escape are mostly preferred. However, such methods are not effective in dense smoke, and therefore an alternative method works better in poor visibility is required.

Self-escape procedures/processes Successful self-escape from emergencies in underground mines cannot be just by a personal effort but rather involves a collective effort from numerous crews and personnel. However, there is a need to emphasize self-escape in order to motivate each miner to make as much effort as possible to rescue his/ herself rather than waiting to be helped. Even though scenarios of self-escaping normally occur in operations where there is a group of workers, the ability to follow the instructions of a safety officer also requires one’s initiative to survive the emergency. It is necessary that all workers in any underground mine be fully ready to respond immediately whenever an emergency occurs, either to prevent it from escalating or to escape. The main issue here is the ability to escape well in advance before an accident occurs. Therefore, every mine should ensure the best conditions possible that will aid in attaining successful self-escape. This is only possible by ensuring that all safety facilities are adequately available and installed as well as keeping workers informed and aware of these facilities. The workers should also be assisted in comprehending and complying with safety laws. The process of self-escaping with regard to mine safety can be describer in terms of eight connected steps, which are generally divided into four phases, namely prevention or preparation, detection, assessment, and escape, as indicated in Figure 4. The first phase – prevention or preparation – is a crucial stage that constitutes the efforts to reduce the occurrence of hazards that could lead to incidents and maximize preparation against devastating effects. Performing safety drills for workers also has a positive impact in preparing workers to escape. Following the first phase are the detection and assessment phases, where all miners

need to recognize and consider the available safety resources, and decide on the extent of the emergency and which escape route to use. After detecting and confirming hazardous situations, evacuation of miners must be done immediately. An important aspect of self-escape is the ability to react in a timely manner to evacuate successfully (Sultana, Anderson, and Haugen, 2019).

Human-systems integration approach The process of self-escape entails teamwork either directly or indirectly, before and during the evacuation process in a dynamic environment. Achieving a successful escape depends directly on the safety resources available, the response of the rescue team, and the miners. The human-systems interaction approach evaluates the quality of interaction between people, tasks, and technology in order to attain a goal, which is a safe self-escape operation (Czaja and Nair, 2006; Booher, 2003). The most important aspect of human-systems interaction is maintaining the communication of information during the interaction, which will aid in successfully completing the mission. However, when these systems are considered individually or in isolation, messages may be lost. Hence this approach should take into account the fact that that people differ in cognitive, perceptual and physical capabilities, which affects how they engage during such missions. It is also significant to know that these interactions arise in an organization and are affected by both contextual and environmental factors that can either aid or limit the successful use of equipment and technology in facilitating the completion of tasks (Henriksen et al., 2008). Human abilities and limits exist in a dynamic system that may differ based on both external and internal factors, as indicated in Figure 5.

Mine emergencies: The human-systems aspects of self-escape Over a long period of time, the mining industry and its workers have been keeping up with ever-evolving technology in order to prevent or respond to mining emergencies. This section focuses on describing the miners (people, individual miners, group or teams) and technologies used in responding to mining emergencies.

People During any emergency in underground mines, the successful escape of any miner requires the cooperation of several people, which include the individual miner, the group or team, and the

Figure 4—Timeline indicating phases for escaping from an underground coal mine (Australian Building Codes Board, 2005) The Journal of the Southern African Institute of Mining and Metallurgy

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Figure 5—Human-systems integration model for self-escape (National Research Council, 2013)

communication crew. This section discusses the role of the individual miner, group(s), or crew(s), and the communication centre(s) in ensuring the successful escape of an individual miner from an underground mine during emergencies. It is worth noting that several other personnel also play important roles prior to the escape of an individual miner from an underground mine, such as those involved in maintaining conducive safe working conditions and preparing the mines for rapid emergency response. This needs a continuous and dedicated effort before any emergency occurs to ensure that the mine has all the safety facilities necessary for adequate response to emergencies.

The individual miner An individual miner entering the mining industry normally undergoes intensive training for his or her role, as well as safety induction. In some countries, like the USA, new miners are required to wear different coloured hard-hats to distinguish them for a period of six months until they understand their roles and the safety codes of conduct. An important aspect worth noting is that the health of miners is crucial in contributing towards a successful escape. For example, some miners may be suffering from chronic illnesses or lifestyle diseases. Such miners will be significantly challenged in terms of their capability to escape without being helped. Thus, this requires that assistance equipment is provided in the mines. Additionally, when creating the self-escape strategy for any mine, the safety officer needs to factor in the various physical abilities of miners, any contingencies that may occur when miners are injured in the process of escaping, and all other possible situations arising from emergencies.

Groups or teams The solidarity of any group of coal miners in any underground mining operation contributes largely to how an individual responds when faced with an emergency (Vaught, 1991; Vaught et al., 2000). When any emergency occurs, such as a fire outbreak in an underground mine, a new group known as the escape group will be immediately formed, consisting of miners who may or may not have previously worked together to handle activities that are different from their daily work tasks. In such an emergency, miners tend not to work as a properly established team that has been trained to cooperate well. This is mainly due to the fact that the training and organization of miners are primarily geared towards the mining and production of coal, whereas that 218

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of a safety officer is to respond to emergencies. This may hinder miners from forming an effective escape group. Also, the mindshift that occurs as a result of exposure to a hostile, hazardous, and life-threatening situation adds to the challenge of forming an effective escape group (this statement should not be construed as a criticism of the miners). However, this does not necessarily limit the ability of miners to escape safely, and historically, many miners have worked well in escape groups to achieve successful missions. This is because during such scenarios, the surrounding environment and the emergency tasks will determine the group dynamics and the decision-making process during evacuation. With teamwork and group support being important attributes of a successful self-escape mission, miners should quickly form escape teams and delegate roles amongst the team members towards achieving the common goal of escaping. This will not only save time but also allows for effective brainstorming for all the possible solutions on how to quickly escape and pick the safest strategy.

Communication centres and responsible persons Communication centres are important support systems in the decision-making procedure for miners escaping during emergencies. Such centres can be positioned immediately within the surface infrastructure of the mine or far from the site, where reception is good. Despite their location, they are important in relaying and processing information during emergencies. These centres must be installed at all underground mines in order to pass information to escaping miners so as to guide them during that process. The most important person in any of these centres is the ‘responsible person’ at the surface, who can clearly decipher information and can communicate clearly with the miners to update them about the rescue operation. Such people require extensive training, especially in decision-making and other nontechnical skills.

Technologies Emergency scenarios normally tend to stress miners and this may adversely affect their basic reasoning abilities. Despite this fact, miners working in underground coal mines must understand well enough how to correctly use various items of safety equipment such the self-contained self-rescuer (SCSR) and compressed air breathing apparatus (CABA) in harsh conditions – for example, in complete darkness and smoky environments, even when they cannot think rationally or clearly. This is achievable through ensuring that workers undergo extensive training so that the safety response becomes habitual. Beilock and Carr (2011) reported that an individual’s ability to acquire skills increases through various stages, which are characterized by the differences in the operations of the memory. During the initial stages of learning, skills and execution are normally supported by functional memory, which is monitored in a stepwise manner (Fitts and Posner, 1967). Procedural awareness unique to the assignment, however, evolves with practice. Procedural awareness primarily functions outside of working memory and needs no continuous control (Beilock et al., 2002; Beilock and Gonso, 2008). Thus, unlike the earlier stages, once a skill is reasonably well learned the step-by-step regulation of execution may not require attention. Another technique to classify the various types of thinking that occur at different skills levels is the ‘skill, rule, knowledge’ approach (Rasmussen, 1983; Reason, 1990). The terms skill, rule, The Journal of the Southern African Institute of Mining and Metallurgy

Overview of mine rescue approaches for underground coal fires: A South African perspective and knowledge generally define the degree of a person's conscious control over their actions. Therefore, it is advisable to train miners how to use various items of safety equipment frequently, so that they form a habit of automatically using them when the need arises. For example, miners need to be properly trained on how to use breathing systems automatically, so that when working memory has been affected by stress, the miner does not make poor decisions. In order to build up habitual responses, the miner needs to know what is to be expected from using various safety gadgets. In addition, it is important that miners are trained to solve problems on the spot so that they get used to finding solutions when faced with unexpected events. Beilock et al. (2002) reported that when procedures are clearly stipulated for every task, humans are left with some cognitive resources to deal with other problems. Therefore, the usage of every item of safety equipment needs to be clearly stipulated in a procedure, so that miners have the reasoning capacity to deal with other problems while in self-escape situations. Various technologies assist miners when escaping during emergencies. Some of these include the technologies for daily mining but some are intended for occupational safety purposes such as self-escape. A few examples of these are briefly described below with their limitations, to allow for improvement.

Sources of oxygen To survive any underground mine emergency, it is important to have access to breathable air. Most mining emergencies normally result in the production of toxic gases and lack of ample breathable air, which leads the miners to suffocate. To overcome this hazard, technologies have been developed to provide miners with ample amount of breathable air in any emergency. Bollinger and Schutz (1987) classified types of respiratory escape equipment as indicated in Figure 6. The systems can be classified as either those operating in a closed circuit or those operating in an open circuit. The closed-circuit systems are known as SCSR systems and function by providing oxygen to miners while removing moisture and carbon dioxide produced during exhalation. These include the long-duration self-contained self-rescuer (LDSCSR), which has a 60-minute operational time and the SCSR, which has a 30-minute operational time. Weighing between three to

six pounds, a SCSR begins functioning after the miner inserts a mouthpiece into the mouth. This exposes the SCSR to moisture, which then triggers a chemical reaction that produces oxygen. When using these systems, breathing resistance increases with time and heat is generated due to the production of oxygen. The mouthpiece also hinders talking, thereby hampering communication. Open-circuit systems, on the other hand, normally supply oxygen from a compressed gas cylinder. This type of system is also known as a CABA (compressed air breathing apparatuses). These systems have a full-face mask, unlike the SCSR, which only has a mouthpiece. CABAs are gaining popularity in many countries such as Australia. Whereas the open systems last for only 30 minutes, the closed systems can last up to 4 hours. CABAs are open air systems. They supply compressed air to the user, and the exhaled air is dispersed into the atmosphere. This is the reason why the duration of the cylinder is only 30 minutes as the cylinder size restricts the amount of compressed air that the user can carry on his back. The long-duration breathing apparatus (LDBA) is a closed loop system, hence it can last for 4 hours. It incorporates a soda-lime canister that filters the air exhaled by the user, removing all the carbon dioxide and other impurities. The system also has an oxygen cylinder that through a pressure reducer and flow sensor, adds pure oxygen into the circuit, which improves the purity of breathable air for the user.

Gas monitoring Real-time gas measurement is important in underground mines to alert the miners when threshold limits are almost reached or to guide miners during escape or evacuation (Brady, 2008). It is important for every miner to know the air quality at every point in the underground mine, especially at escape routes. The air quality is determined with the help of personal gas monitors, which can quantify the main gases of concern such as methane, CO, CO2, and O2. Where possible, such devices should be issued to all underground miners and if only a limited number are available, then the senior workers in various areas should have these devices readily at hand. Fixed air quality monitors should also be installed at various points. For example, in the USA, such fixed gas monitors are normally installed on conveyor belts to enable detection of CO generated by conveyor belt heating. Also in the

Figure 6—Categories of respiratory escape equipment (Bollinger and Shutz, 1987) The Journal of the Southern African Institute of Mining and Metallurgy

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Overview of mine rescue approaches for underground coal fires: A South African perspective USA, coal mines have methane monitors on longwalls as well as on all machines such as shearers, at midfaces, and in tailgate drives. Stationary CO detectors are also installed in batterycharging stations and fuel storage areas, and more gas information can be obtained from fan charts found in air shafts and mine seals. Similarly, Australian safety regulations require the installation of gas detection systems in all operating parts of mines and at unsealed goaf areas in return airways (Queensland Parliamentary Counsel, 2001). These systems consist of a series of sensors or tubes that extract the air from the mine and transport it to the surface for analysis. This enables continuous monitoring of mine gases such as methane, CO, CO2, and O2.

Refuge stations/safe havens When wearing a self-rescuer of any sort, the distance that can be covered depends more on a miner's physiological abilities (fitness, breathing rate, stress level, body posture etc.) and the terrain to be crossed (visibility, footing) than on the efficiency of the self-rescuer. In mines where the places of safety are far apart, self-rescuers need to have longer lifespans. Due to the limited timespans of self-rescuers, there is a growing tendency for Emergency Escape Plans (EEPs) not to rely on the use of these devices. The provision of refuge stations is very important as distance limits the escape of employees all the way to the surface, especially in older and more mined-out workings. The workforce shelters in sealed, fireproof structures that provide safe havens for evacuating personnel to rest in and change. Caution should be applied in the selection of conventional refuge bays or new movable ones. Refuge stations have been installed in South African and Canadian mines.

Route finding Efficient route finding out of an underground mine relies heavily on whether the miners know their location, as well as the safest routes to take to self-escape. As mentioned earlier, technologies that assist with this process include signs, lifelines, headlamps, and communication systems. However, such technologies are liable to be affected by smoke, fire, and other harsh conditions. For instance, headlamps have a limited battery life, signs can be blown off during an explosion, and lifelines can be destroyed.

To overcome such problems, these technologies can be complemented with the use of chemical glow- sticks that can last up to 12 hours. Metal configurations can be used to show signage riveted on the doors. Canes can also be used to assist miners in comprehending what structures are around them, such as crushers and conveyor belts, when in total darkness. The common practice in numerous mines of marking escape routes with reflective signs and symbols has disadvantages. It is important to keep the signs clean, in good shape, and up to date, because mine personnel often pay little attention to reflective route/way markings and reflective markings are of little use in lowvisibility environments. To overcome these disadvantages, passive lifeline technologies and active electronic audiovisual guidance systems have been used (Thyer and Weyman, 1997). Whichever method is considered, it must achieve the following to the greatest extent possible: ➤ Significantly increase the speed of egress ➤ Be useful in extremely low-visibikity conditions ➤ Provide precise directional information ➤ Provide audible, visual, and tactile signals ➤ Be inexpensive, with minimum requirements for maintenance ➤ Accommodate differences in mine layout, working practices, culture, and language. ➤ Offer a high-integrity and preferably fail-safe operation ➤ Not depend on background lighting [idem] ➤ All employees familiar with and trained on these devices. Other guidance systems for route finding in low-visibility conditions have been developed, including passive and active guidance systems and instrument meteorological conditions (IMC) egress beacon systems.

Lifelines Lifelines are common safety aids used for guiding miners to designated escape ways using directional cones to show the correct travelling direction. These cones can be seen in dim light or can be felt by hand in darkness. Safety regulations for every country normally stipulate the minimum distance between cones. Lifelines may also be used to indicate other safety facilities such as personnel doors and refuge chambers, as illustrated in Figure 7.

Figure 7—Lifeline indictors (Badura, Grodzicka, and Musioł, 2017) 220

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Overview of mine rescue approaches for underground coal fires: A South African perspective Vision aids Inadequate visibility due to power outages or dense smoke from fire is a common hazard during mining emergencies. This necessitates appropriate lighting technologies and equipment to be installed to provide lighting needed for vision during such emergencies. Currently, miners use cap lamps. The latest lamps require frequent charging, but those using older technology can last for more than 20 hours, but they are heavier due to the bigger batteries (Lewis, 1986). Other types of vision-aiding equipment include goggles and eyeglasses that protect miners from eye irritation, especially in dusty, smoky, or polluted underground spaces. However, these do not aid vision in extreme darkness. A worthwhile technological invention would be goggles that incorporate thermal imaging to assist miners with vision in dark spaces.

Communication and tracking equipment The maintenance of communication inside the mine and to the surface during operations is usually a tough task. Due to the continuous mining operations advancing daily, communication systems need to progress together with the mining crew. Communication systems therefore need to be robust enough to withstand harsh environments such as extreme humidity, corrosive water, and electrical characteristics of coal that can hamper communication signals and cause interference (Schiffbauer and Brune, 2006). These systems should also be safe for use in underground mines and not pose any hazards. To overcome all such limitations, a combination of both wired and wireless connections is needed to create a robust communication system. Personnel detection devices (RFD tags, high or low frequency) fitted to the cap lamps are becoming more common and can assist greatly.

Functional design of technologies Technology is crucial in ensuring efficient self-escape from any underground mine emergency. A human-systems integration approach places primary importance on the person operating the system by placing the use of these technologies as the centre of the design process (Norman, 1993; Wickens, Gordon, and Liu, 2004). Despite the advent of new technological trends in mine safety, complete reliance on these technologies may not be the best choice for the miner involved. For example, a miner being limited in space and strength cannot monitor, comprehend, and synthesise information from numerous safety devices delivered in many formats. Therefore, when considering the design of technological systems for safety in underground mines, the user should be placed at the centre and the human behaviour factor should be fully taken into consideration. Examples of such factors include the human aspect in decision-making, comprehending, and assimilating information as well as responding in the required manner. However, safety technologies must meet several requirements, including size and weight, before they can be considered suitable for underground mines. A miner can only carry a limited amount of equipment during an emergency. This equipment must be easy to deploy and easy to use. If miners cannot understand how to use these technologies they will not use them. South Africa has advanced systems for rescue from underground refuge chambers. Mines in some cases predrill 660 mm rescue boreholes from the surface into these chambers to speed up the process of rescue should there be an emergency. The Journal of the Southern African Institute of Mining and Metallurgy

Should such holes not be available they would call upon Mines Rescue Services, who will then deploy their rescue drill unit, supply winder, colliery rescue winder with rescue capsule, and specialized rescue teams.

Safety training requirements for safe rescue operations in underground coal fires The process of mine rescue and recovery is normally complex and involves numerous interconnected activities.

Rescue teams During any emergency, the rescue of persons is the highest priority and therefore the provision of rescue teams is the most urgent requirement. Depending on the size of the operation, the rescue teams can be voluntary employees or dedicated rescue personnel/teams from either a neighbouring mine or a centralized rescue provider. Since each mine emergency is different and the number of suitable rescue teams is contingent on the type of emergency, a formal reciprocal aid agreement between either neighbouring mines or with a centralized rescue organization, is hugely beneficial to provide all mines with access to more rescue teams they would otherwise be able to access. It is an accepted rule-of-thumb that a correlation exists between the number of persons employed underground and the number of rescue teams available as per the guidelines in Table III. In further determining the number of rescue teams, cognisance must be taken of the fact that when a rescue team is working in a non-respirable atmosphere, there must always be a secondary backup team available. Where rescue teams from neighbouring mines or centralized rescue providers are used, the availability of these teams will depend on location, occurrence of other emergencies nearby, travelling distance, and response time. Where a secondary backup rescue team is not available, the original rescue team has limited capabilities, and these mines are advised to remedy this deficit. Furthermore, any rescue team is limited by the time for which they can be deployed, as this depends on the capability of the breathing apparatus (no more than 4 hours) together with a period of rest between deployments (minimum 12 hours). From Table III and Figure 8, it is evident that Mines Rescue Services needs to cater for all types of mines in relation to the number of employees working in mines. Mines Rescue Services have two methodologies of service delivery namely ‘A’ and ‘B’ class member mines. ‘B’ class members have less than 100 employees, and such mines are not required to have their own rescue teams and rescue equipment on site, but they have the option to call for assistance from ‘A’ class member mines, with Mines Rescue Services acting as the liaison. ‘A’ class member mines employ more than 100 employees and are therefore required to have Table III

T he amount of rescue teams in relation to the number of employees Number of persons employed on the mine

Less than 100 persons Between 100 and 500 persons Between 500 and 1000 persons Greater than 1000 persons VOLUME 122

Number of rescue teams

One rescue team At least two rescue teams At least three rescue teams More than three rescue teams MAY 2022

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Figure 8—The number of mine members that subscribe to an emergency preparedness and response service from Mines Rescue Services South Africa

their own trained rescue team members on site in relation to the number of employees, as stipulated in Table III with their relevant specialized rescue equipment. The way mine rescue teams respond to any situation depends on the type of emergency and the kind of mine being accessed. The condition inside an underground mine will dictate what the emergency crew should do to rescue miners and control hazards, where possible. Rescue teams are tasked with numerous roles such as exploring the affected mine areas, searching for and rescuing survivors, administering first aid, and firefighting, among other things.

Requirements to become a rescue team member Physical requirements Ideally, a rescue team member must not be younger than 21 or older than 45 years. The minimal age is to ensure that the person has obtained some experience and simple life-skills and is mature and responsible enough to be placed in a position of responsibility. The maximum age has been scientifically determined as it is accepted that generally, persons above this age begin to deteriorate physically, and more importantly, their oxygen consumption (VO2max) increases, thus reducing the period for which they can benefit from an oxygen breathing apparatus. The potential member will be subjected to a full medical examination, but the initial requirement is that they be physically fit, have no obvious disabilities, and are not obese. The person must have a reasonable level of intellectual capability and sufficient numeric and literacy skills in order to communicate effectively.

Pre-assessment of the individual Before a rescue team member begins training, they will be required to undergo a full medical examination and be tested for heat tolerance. The medical examination must be conducted by a professional medical examiner and the following minimum tests should be carried out: ➤ Not suffering from diabetes mellitus, any form of seizures, or hypertension ➤ Not receiving any drug treatment (or if so, this must be specified) ➤ Not receiving regularly prescribed medication ➤ Within height/mass nomogram limit (BMI between 25 and 35) 222

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➤ No abnormalities detected from an X-ray ➤ Blood pressure (systolic 90–145 mm and diastolic 50– 90 mm) ➤ Physical screening of temperature, mouth, lips, throat, abdomen, herniation, defect of limbs etc. ➤ Urine analysis (normality and drug dependency) ➤ Spirometry ➤ Optometry (minimum 6/9 both left and right eyes) ➤ Audiology (reject if greater than 40 dB average loss). The purpose of the heat tolerance test, which in cooler regions may appear to be superfluous, is because rescue teams can be exposed to excessive heat, especially during fires. This test will be conducted in a climatic chamber, where the environment is saturated (high humidity with a wet bulb temperature of 31.7°C and dry bulb temperature of 33.2°C), and the person is subjected to 60 minutes of physical work (bench stepping to obtain a work rate of 54 W), after which the core body temperature is measured. The candidate will be rejected if the core body temperature is greater than 39.0°C.

Initial training The primary purpose of the initial training is to ensure that a rescue team member is fully competent in the use of a breathing apparatus. This should take at least five days of both theoretical and practical training. During this period, other relevant core competencies are dealt with, including fire chemistry, firefighting techniques, gases, communications, rescue, and recovery. The competencies and a brief description of the training are listed below. ➤ Long-duration closed-circuit breathing apparatus ➤ Fresh air base (FAB) for the backup rescue team should the operational rescue team proceed beyond the last point of fresh air ➤ Known modus operandi that was briefed to the rescuer by the manager in the control/ emergency management room ➤ Hazard identification risk assessment ➤ Rescue protocols, policies, procedures, special instructions, and systems of works. ➤ Gas measurements and understandings ➤ Communication between rescue teams, rescuers, and management in control/emergency centre The Journal of the Southern African Institute of Mining and Metallurgy

Overview of mine rescue approaches for underground coal fires: A South African perspective ➤ Firefighting methods. ➤ Accident scene management ➤ Specialised rescue and/or recovery equipment ➤ First aid.

Physical capacity test After completing the pre-selection, medical examination, and the training course, the member is subjected to a physical capacity test. This will determine the individual’s ability to perform physical work in the arduous conditions normally encountered during deployment. Typically, this test will include stoop walking, carrying of 25 kg items, crawling in confined spaces, and climbing. The test must be completed in a pre-determined time while wearing a breathing apparatus.

Quarterly refresher training All rescue team members must undergo a refresher training every three months, preferably in a simulated mine that has been filled with smoke. The members are required to wear their breathing apparatus during this training, which can also serve to familiarize them with any new technologies or developments. Similarly, routine planned maintenance can be performed on equipment during this training.

Specialized skills While the core competencies of the rescue team have traditionally been firefighting, entering non-respirable atmospheres, and search and rescue, there are circumstances that require additional skills that have subsequently been included in the proficiency requirements. These additional skills include emergency medical care (paramedic or medical first responder) and rope rescue skills for working at depths and heights. Ideally, each member of the rescue team should have some basic life-support skills and, where possible, certain members could have either intermediate or advanced life-support skills. The latter two are, however, to be possessed by highly skilled and trained personnel. It is likely and more reasonably accepted that a skilled person (with advanced life support) be trained as a member to be used only in cases involving a medical emergency. Depending on the type of operation (deep-level mines or shaft structures), certain members can be skilled in rope access or rope rescue techniques, and be able to ascend or descend shafts,

buildings, orepasses, silos, or any structure in which the height can become a concern, in order to perform a rescue. Mine rescuers can also be assigned as surface fire responders to cater for all surfacerelated emergencies and/or incidents. The number of rescue team members in South Africa to cover underground mines is shown in Figure 9.

Composition of a mine rescue team An operating rescue team cannot consist of less than five members, but in order to ensure readiness of a team, there should be at least seven members to allow for leave of absence, sickness, non-availability, non-conformance to operational requirements, etc. The team should also consist of a mix of production, engineering, and health, safety, and environmental personnel. This will ensure that all relevant disciplines (mining issues, engineering installations, or ventilation control) or problems that could be encountered during an incident are catered for. Furthermore, the team will include a captain and vice-captain. These positions are normally permanent as these members have specific duties. During deployment, an additional sixth or seventh member can be included, either due to the requirements of the operation or simply to improve the experience of newer members. The appointment of a rescue team manager or liaison officer is considered beneficial as this person can manage the team, prepare and submit budgets, liaise with executive management, or assist with emergency preparedness. Figure 10 shows the number of active rescue teams available to cover underground mines in South Africa.

Deployment of rescue teams When an emergency call is initiated, a sense of urgency, anxiety and possible apprehension are normal emotions experienced by rescue team members. A team’s state of emergency preparedness and readiness has a direct bearing on their ability to control these emotions. A rescue team manager/designated officer must provide the team captain with the following information: ➤ Type of emergency e.g., fire, rescue etc. ➤ Possible number of persons involved and (if known) their condition ➤ Time to report to the mine and time to go underground e.g., 06:00 for 07:00

Figure 9—The number of rescue team members in South Africa to cover underground mines The Journal of the Southern African Institute of Mining and Metallurgy

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Figure 10—The number of active rescue teams to cover underground mines in South Africa

Figure 11—The number of rescue teams used during all underground fires that Mines Rescue Services have dealt with in South Africa

➤ Place to report to (the rescue room) ➤ Transport arrangements ➤ Plan for pre-operational medical examination, or in the case of an emergency ASAP callout, the rules applicable to the use of declaration of fitness. Mines should be able to call upon multiple rescue teams and have enough rescue teams available as many underground fires can grow in extent over time. This will have a direct effect on the rescue teams’ performance and efficiency, because after a few callouts, rescue teams may be affected by fatigue and this can have adverse safety implications for both rescuers and employees requiring rescue. From Figure 11, it is evident that during fires, multiple rescue teams would be required. The complexity of underground fires can also have a direct bearing on the number of rescue teams that a mine would deploy. 224

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Summary Coal mining is characterized by numerous hazardous activities that require proper safety management systems to be set in all coal mining companies. Coal mining accidents have longlasting, devastating effects on all stakeholders as poor mining practises can not only damage the equipment and machinery but can also lead to loss of human life. This demands that adequate safety management systems that are effective and prepared to handle emergencies be put in place in a timely manner to avoid devastating accidents. Old technologies should be replaced with modern ones in order to ensure efficient and effective management of mine safety. With stringent safety measures adopted to eliminate the possibility of catastrophic accidents, the safe mining environment that is created will not only save miners’ lives but will also The Journal of the Southern African Institute of Mining and Metallurgy

Overview of mine rescue approaches for underground coal fires: A South African perspective protect the main mining assets from being ravaged. To this end, miners should be provided with adequate personal protective equipment (helmets, safety boots, gloves, dust masks, glasses, and breathing aids) that will safeguard them from injury. Appropriate safety facilities should be installed in all mines (fire alarms, gas monitoring devices, and mine ventilation. Where blasting is required, water-based emulsions and electronic detonators should be used due to their advantage of allowing the miners to verify the blasting system before firing. Mines should have clear signs that can guide their workers during situations that require evacuation via the nearest escape routes. All working areas and any other areas where employees may travel should have lifelines installed. Where visibility is poor, lifelines should be used to direct miners for self-escape. Lifelines should be placed within the miners’ reach and they must be able to understand their indicative directional signals. Miners should also be trained on how to communicate clearly with the central communication centre in case of an emergency to enable the rescue crew to evacuate trapped miners. All miners should be well conversant with the various safety gadgets such as SCSR and CABA, so that they can promptly put them on if they encounter toxic gases. Any development in the underground spaces should be updated on the mine plans and shared among all miners so they know about hazardous areas to avoid, escape routes, and the locations of refuge chambers. Communication systems should always be kept running to allow miners to seek help from the response centres in case of emergencies. Above all, it is important that all miners promote a safety culture within the mines to create a safe and conducive working environment.

Concluding remarks

Badura, H., Grodzicka, A, and Musioł, D. 2017. Study of the “lifeline” as the measure allowing for safe self-rescue of miners in conditions of lack of visibility caused by underground fire. IOP Conference Series: Materials Science and Engineering, vol. 268, no. 1. doi: 10.1088/1757-899X/268/1/012015 Beilock, S.L. and Carr, T.H. 2011. On the fragility of skilled performance: What governs choking under pressure? Journal of Experimental Psychology: General, vol. 130, no. 4. pp. 701-725. Beilock, S., Carr, T., MacMahon, C., and Starkes, J. 2002. When paying attention becomes counterproductive: Impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology: Applied, vol. 8, no. 1. pp. 6-16. Beilock, S. and Gonso, S. 2008. Putting in the mind versus putting on the green: Expertise, performance time, and the linking of imagery and action. Journal of Experimental Psychology, vol. 1, no. 6. pp. 920-932. Bennet, J.D. 1982. Relationship between workplace and worker characteristics and severity of injuries in USA underground bituminous coal mines. PhD thesis, Pennsylvania State University. Booher, H.R. 2003. Human systems integration. Handbook of Human Systems Integration. Wiley, Hoboken, NJ. pp. 1-30. Bollinger, N.J. and Schutz, R.H. 1987. NIOSH Guide to Industrial Respiratory Protection, A NIOSH Technical Guide. Department of Health and Human Services, Centres for Disease Control, Pittsburgh, PA. Brady, D. 2008. The role of gas monitoring in the prevention and treatment of mine fires. Proceedings of the Coal Operators’ Conference. University of Wollongong, New South Wales, Australia. Australasian Institute of Mining and Metallurgy. pp. 202-208. Brenkley, D., Lewis, D., and Jozefowicz, R. 1998. Assisting evacuation from underground mine workings under conditions of poor visibility. United Kingdom Health and Safety Executive, London. Czaja, S.J. and Nair, S.N. 2006. Human factors engineering and systems design. Handbook of Human Factors and Ergonomics. Wiley, New York.

Coal mining companies should continue to promote a safety culture within the mines, right from top management down to the casual workers. This will encourage miners to abide by the safety rules and suggest any measures that can be implemented to improve safety in the mining environment. In many activities or operations in coal mines, it might not be feasible to completely remove some inherent hazards or avoid exposure to such hazards, and therefore some risks may never be completely eliminated. However, it is necessary for the employer to manage and control such hazards so as to minimize the consequences for the health and safety of all affected stakeholders. All miners should be trained regularly on safety practices so that they are continuously equipped with the necessary skills to maintain safety in underground spaces. They also need regular training on how to employ self-escape techniques during emergencies.

Fitts, P.M. and Posner, M.I. 1967. Human Performance. Brooks/Cole, Belmont, CA.

Acknowledgments

Loughnan, F.C. and Roberts, F.I. 1981. The natural conversion of ordered kaolinite to halloysite (10Å) at Burning Mountain near Wingen, New South Wales. American Mineralogist, vol. 66. pp. 997-1005.

The authors wish to express their gratitude to Coaltech for their financial support for this study. The portion of the work presented here was part of a Coaltech 2020/2021 annual report.

References Azam, S. and Mishra, D.P. 2019. Effects of particle size, dust concentration and dust-dispersion-air pressure on rock dust inertant requirement for coal dust explosion suppression in underground coal mines. Process Safety and Environmental Protection, vol. 126. pp. 35-43. Australian Building Codes Board. 2005. International Fire Engineering Guidelines. Canberra, Australia. The Journal of the Southern African Institute of Mining and Metallurgy

Graber, J.M., Stayner, L.T., Cohen, R.A., Conroy, L.M., and Attfield, M.D. 2014. Respiratory disease mortality among US coal miners; Results after 37 years of follow-up. Occupational and Environmental Medicine, vol. 1, no. 71. pp. 30-39. Gouws, M. J. and Knoetzef, T.P. 1995. Coal self-heating and explosibility. Journal of the South 4frican Institute of Mining and Metallurgy, vol. 95, no. 1. pp. 37-43.94. Gouws, M.J. and Phillips, H.R. 1995. Post-explosion guidance systems. Proceedings of the 26th International Conference on Safety in Mines Research Institute, Katowice, Poland. Central Mining Institute, Katowice. Henriksen, K., Dayton, E., Keyes, M., Carayon, P., and Hughes, R. 2008. Understanding adverse events: A human factors framework. Patient Safety and Quality: An Evidence-based Handbook for Nurses. Agency for Healthcare Quality and Research, Rockville, MD. Lewis, W. 1986. Underground Coal Mine Lighting Handbook. Information Circular 9073. US Bureau of Mines.

Mine Safety and Health Administration (MSHA). 1999. Accident investigation. Safety Manual no. 10. Arlington, VA.. National Institute for Occupational Safety and Health (NIOSH). 2015. Improve drill dust collector capture through better shroud and inlet configurations. Department of Health and Human Services, Center for Disease Control and Prevention, DHHS 2015 No. 2006–108. National Institute for Occupational Safety and Health (NIOSH). 2016. Occupational exposure to respirable crystalline silica. Occupational Health and Safety Administrationm 81(04800). Occupational Safety and Health Administration (OSHA), Department of Labor. Fed. Regist. 2016 Mar 25; 81(58):16285-890. PMID: 27017634. VOLUME 122

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Overview of mine rescue approaches for underground coal fires: A South African perspective Norman, D. 1993. Things That Make Us Smart: Defending Human Attributes in the Age of the Machine. Perseus, Cambridge, MA. Phillips, H., Chabedi, K., and Uludag S. 2011. Best practice guidelines for South African Collieries. Coaltech, Johannesburg. 129 pp. Pratt, J.A. 1987. Unseen Danger: A Tragedy of People, Government, and the Centralia Mine Fire. University of Pennsylvania Press, Philadelphia. 299 pp. https://doi.org/10.2307/3115362 Queensland Parliamentary Counsel. 2001. Queensland Consolidated Regulations. 2001. Coal Mining Safety and Health Regulation. Section 222. https://www.legislation.qld.gov.au/view/pdf/repealed/2017-07-01/sl-2001-0015 Reason, J. 1990. Human Error. Cambridge University Press, Cambridge, UK. Rasmussen, J. 1983. Skills, rules, and knowledge; Signals, signs, and symbols, and other distinctions in human performance models. IEEE Transactions on Systems, Man, and Cybernetics, SMC, vol. 13, no. 3. pp. 257-266. Schiffbauer, W.H. and Brune, J.F. 2006. Underground coal mine communications for emergencies and everyday operation. Presentation at the Energy Forum: A Discussion of West Virginia’s New Mine Safety Rules, Charleston, WV, 1 March 2006. Department of Health and Human Services, Centers for Disease Control and Prevention, Pittsburgh, PA. Singh, R.V.K. 2013. Spontaneous heating and fire in coal mines. Procedia Engineering, vol. 62, pp. 78-90, https://doi.org/10.1016/j.proeng.2013.08.046 Stracher, G.B. and Taylor, T. P. 2004. Coal fires burning out of control around the world: Thermodynamic recipe for environmental catastrophe. International Journal of Coal Geology, vol. 59, no. 1. pp. 7-17. Sultana, S., Anderson, B.S., and Haugen, S. 2019. Identifying safety indicators for safety performance measurement using a system engineering approach. Process Safety and Environmental Protection, vol. 128. pp. 107-120.

Thyer, A. and Weyman, A. 1997. Investigating the scope for improvements in navigational aids to assist evacuation from underground mine workings under poor visibility conditions. Mine Safety. Proceedings of 27th International Conference of Safety in Mines Research Institutes, New Delhi, India, 20-22 February 1997, vol. 1. Oxford & IBH, New Delhi. pp. 947-953. Tripathy, D.P. and Ala, C.K. 2018. Identification of safety hazards in Indian underground coal mines. Journal of Sustainable Mining, vol. 17, no. 4. pp. 175-183. Vaught, C., Brnich, M., Mallett, L., Cole, H., Wiehagen, W., Conti, R., Kowalski, K., and Litton, C. 2000. Behavioral and organizational dimensions of underground mine fires. Information Circular 9450. Department of Health and Human Services, Center for Disease Control and Prevention, Pittsburgh, PA. Vaught, C. 1991. Patterns of solidarity: A case study of self-organization in underground mining. PhD thesis, Department of Sociology, University of Kentucky, Lexington, KY. Wang, C., Yang, S., and Li, X. 2018. Simulation of the hazard arising from the coupling of gas explosions and spontaneously combustible coal due to the gas drainage of a gob. Process Safety and Environmental Protection, vol. 118. pp. 296-306. Wickens, C., Gordon, S., and Liu, Y. 2004. An Introduction to Human Factors Engineering. Pearson Prentice-Hall Upper Saddle River, NJ., Zhou, L., Cao, Q., Yu, K., Wang, L., and Wang, H. 2018. Research on occupational safety, health management and risk control technology in coal mines. International Journal of Environmental Research and Public Health, vol. 15, no. 5. pp. 868. u

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Stability analysis of a free-standing backfill wall and a predictive equation for estimating the required strength of a backfill material – a numerical modelling approach by J.L. Porathur1, S. Sekhar1, A.K. Godugu2, and S. Bhargava1 Affiliation:

CSIR-Central Institute of Mining and Fuel Research, Nagpur Research Centre, Nagpur, Maharashtra, India. 2 Hindustan Zinc Limited, Dariba, Rajsamand, Rajasthan, India. 1

Correspondence to: J.L. Porathur

Email: johnlouip@gmail.com

Dates:

Received: 26 Feb. 2021 Revised: 24 Feb. 2022 Accepted: 22 Mar. 2022 Published: May 2022

Synopsis Cemented backfilling has enabled underground hard rock mines to extract orebodies more safely with improved ore recovery. It is important to estimate the minimum required strength parameters for a backfill mix by optimizing the binder percentage to enable cost-effective and safe stoping operations. We conducted three-dimensional numerical modelling to study the effect of various stoping parameters on the stability of a free-standing backfill wall. A Mohr-Coulomb material model was used for the backfill material and the rock-fill interface. A strength reduction technique, excluding friction angle, was employed to arrive at a minimum stable strength value for the backfill. For a given combination of strength values, the stability state of the backfill wall could be demarcated using a displacement and yield zone tracking method. The numerical modelling results are compared to some earlier theoretical models. From the simulations, a predictive equation is developed to predict the required strength parameters for a backfill mix to ensure a stable free-standing wall. Examples are given of the successful use of the predictive equation at some underground hard rock mine sites in India.

Keywords cemented backfill, underground stoping, backfill wall stability, numerical modelling, predictive equation.

How to cite:

Porathur, J.L., Sekhar, S., Godugu, A.K., and Bhargava, S. 2022 Stability analysis of a free-standing backfill wall and a predictive equation for estimating the required strength of a backfill material – a numerical modelling approach. Journal of the Southern African Institute of Mining and Metallurgy, vol. 122, no. 5, pp. 227-234 DOI ID: http://dx.doi.org/10.17159/24119717/1544/2022 ORCID: J.L. Porathur https://orcid.org/0000-00021168-7640 S. Sekhar https://orcid.org/0000-00019289-4803

Introduction Underground mines in various parts of the world have adopted open stoping with cemented backfilling for better ground stability, increased ore recovery, and improved efficiency of ventilation (Hartman, 1992; Hassani and Archibald, 1998; Darling, 2011; Potvin, Grant, and Mungur, 2015). The method enables mines to extract the orebody without locking up ore in pillars to a considerable extent. The use of mine tailing and waste rock for filling the voids makes the mining more eco-friendlier by reducing the amount of waste rock to be dumped (Aubertin, Bussière, and Bernier, 2002; Bussière, 2007; Simms, Grabinsky, and Zhan, 2007; Benzaazoua et al., 2008; Zhang et al., 2011, 2015; Yang et al., 2015). The rock walls of the stopes undergo confinement due to the backfill, which prevents the wall or roof collapsing, thereby providing regional stability and subsidence control (Brady and Brown, 2004). Open stoping with backfilling is done by dividing the orebody into an alternate primary-secondary sequence or a continuous sequence. In both these situations, the opening of a neighbouring stope will create a free-standing backfill wall. For the stability of this free-standing wall, estimation of the required strength of the back-fill material is of paramount importance. The type of the fill material, filling method, dimensions of the exposed fill, stress arching, and wall confinement are the factors that determine the stability of an exposed fill wall. Various researchers have proposed methods to assess the stability of the free-standing backfill wall. The most commonly used prediction equation is a theoretical concept put forth by Mitchell, Olsen, and Smith (1982) based on limit equilibrium mechanics along a critical plane. The theoretical equation was modified later by Li (2014) by incorporating a surcharge loading factor. Dirige, McNearny, and Thompson (2009) further extended Mitchell, Olsen, and Smith’s (1982) equation to inclined orebodies. Several researchers studied the stress build-up in a fill column using theoretical and numerical approaches (Li and Aubertin, 2009; Yu et al., 2018) and proposed the required uniaxial compressive strength (UCS) of a stable fill column based on the vertical stress development. They found that vertical stress varied from zero at the top to a maximum at the bottom of the column (Mitchell Olsen, and Smith, 1982; Liu et al., 2018). The 2D plane strain model studies conducted by Duncan and Wright (2005) considered the

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Stability analysis of a free-standing backfill wall and a predictive equation paste-filled stopes as two-dimensional vertical slopes consisting of cohesive frictionless material, and the authors proposed that the required UCS is equivalent to half the product of the unit weight of the backfill material and the backfill column height. Caceres Doerner (2005) made a comprehensive study of the effect of various parameters, including orebody dip, on the maximum vertical stress at the bottom of the backfill column, which could also be considered as the required UCS. However, these earlier methods were oversimplified and appeared to overestimate the required strength of the backfill mix, as they ignored the effects of the confining sidewalls and the stress arching phenomenon (Liu et al., 2018). Numerical modelling is a far superior method for estimating the strength requirement of a backfill material in a given situation more realistically (Caceres Doerner, 2005; Dirige, McNearny, and Thompson, 2009). Although several researchers have studied the stress build-up and stability of the backfilled wall using numerical modelling, a comprehensive parametric study or a prediction equation using numerical modelling techniques could not be found in the literature. Mostly the designs were carried out using theoretical equations. In this paper, 3D numerical modelling is employed to study the effect of various stoping parameters on the backfill wall stability and devise a predictive equation that will enable mine management to decide the amount of binder content based on the strength requirement. Examples of implementing the model in some underground metalliferous mines in India are also presented.

Numerical modelling methodology The numerical modelling was performed in FLAC3D, which computes using the finite difference numerical modelling method. Various parameters such as height (H), width (w), and length (L) of the backfill column, the inclination of the orebody (q), and the ratio of interface cohesion to the cohesion of backfill material (rc) were varied in the modelling. The stability of the system was studied using Mohr-Coulomb elastoplastic analysis. During the study, various models corresponding to a hard rock mining scenario were simulated. A transverse stoping configuration was modelled, as shown in Figure 1. Although when L<w, the stope dimension corresponds to that of a longitudinal stope, the nomenclature followed in this paper is consistent with that of a transverse stope. The dimensions of the stopes considered in the models are H = 25 m, 35 m, 60 m, 75 m, and 100 m, L = 10 m, 30 m,

Figure 1—Schematic representation of an inclined cemented backfilled stope 228

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46 m, 60 m, and 80 m, w = 10 m, 20 m, 30 m, 40 m, and 50 m, and q = 45°, 60°, 75°, and 90°. Those combinations commonly practised in the real mining scenario are simulated for the study. Separate finite difference grids were created for each orebody dip. The grid starts from the surface and extends to a depth of about 600 m. The boundaries were kept a sufficient distance (more than 150 m) from the stoping region. A vertical plane of symmetry was applied passing through the centre of the secondary stope. Extraction of the secondary stope results in exposure of the primary stope paste-fill wall. Moderate in-situ stress values were applied; those measured in Indian hard rock mines (Gowd , Rao, and Gaur, 1992). A ‘fair’ rock mass rating (RMR between 40 and 60) was used in all the models. The pertinent rock mass properties used include a Young’s modulus of 25 GPa, Poisson’s ratio of 0.25, cohesion 5.0 MPa, friction angle 35°, and tensile strength 2.0 MPa. These are the typical values found in Indian hard rock mines. During modelling the interface between the rock mass and the fill material was simulated along the footwall, hangingwall, stope bottom, and the wall contact of the adjacent stope. The cohesion ratio (rc) was varied between 0.25 and 1.0, and the tensile strength of the interface was considered to be zero. Tight filling of the stope is complicated in practice, hence in the simulations, a gap of 1 m is provided between the fill top and the stope back. The backfill properties assigned during the numerical modelling were devised partly based on previous laboratory testing and partly from the literature. The laboratory testing divulged that the friction angle does not vary significantly with changes in the UCS, cohesion, and Young’s modulus. Terzaghi (1943) postulated that the angle of internal friction of the paste fill and the rock-fill interface friction angle might be considered equal, while Marston (1930) suggested that the interface friction angle varies from 1/3 to 2/3 times the internal friction angle of the paste fill material. Some researchers have suggested that the interface friction angle can be greater than 2/3 of the friction angle of the paste fill material (Nasir and Fall, 2008; Fall and Nasir, 2010). In the current study, the friction angle at the interface is taken as 2/3 of the internal friction angle of the backfill material for all simulations. Once the backfill wall is exposed, its stability is very similar to that of a slope stability problem. The Mohr-Coulomb model has been widely used for solving such problems, as it is more simplified, and predicts the stability with reasonable accuracy. The strength reduction technique is a standard procedure used for arriving at a safety factor for a highwall or a slope. A similar approach is followed here to estimate the limiting strength values of the backfill wall material. Failure of the backfill system can be observed from accelerated backfill wall displacement along with the formation of a large yield zone at the bottom portion of the backfill column. Various researchers have successfully used a similar strategy (Yang and Li, 2017; Liu et al., 2018; Porathur et al., 2018). The cohesion and tension of the backfill material are reduced in steps, and the model is equilibrated after each strength reduction step. The friction angle of the backfill is kept constant as it does not vary much with the other strength parameters. For vertical orebodies (q = 90°), instability of the system is identified by a steep increase in the displacement history graph and the wedge-shaped failure formed in the backfill column at an angle approximately equal to the critical angle (a), with subtle curvilinear trajectory. According to the Mohr-Coulomb theory, a = 45° + f/2, where a is the critical angle of the critical plane with the horizontal and f is the angle of internal friction of the backfill The Journal of the Southern African Institute of Mining and Metallurgy

Stability analysis of a free-standing backfill wall and a predictive equation material. When the orebody is inclined, the failure path can be seen originating at the footwall contact and the floor of the fill column. In contrast, the hangingwall contact portion remains more or less unyielded except for some tensile separation at the interface. Hence, from the numerical modelling results, it may be said that the concept of the critical plane may not apply to inclined orebodies. This can be seen just before the time of wall failure, as shown in Figure 2. Figure 3 shows the displacement history plots during strength reduction – accelerated vertical displacements indicate failure of the backfill wall. The minimum cohesion value resulting in a stabilizing displacement is taken as the ‘minimum stable cohesion’, which may be considered as the ‘required cohesion’. Various such models are simulated with several combinations of the stoping parameters. The effect of each stoping parameter on the wall stability is analysed.

Effects of fill wall height Prior to the 1980s, the UCS requirement of a backfill material at a certain depth was determined theoretically based on the weight of the material (Mitchell, Olsen, and Smith, 1982; Liu et al., 2018). Based on the equation proposed by Mitchell, Olsen, and Smith (1982) and the modified equation by Li (2014), the required cohesion was found to be directly proportional to the height of the backfill column for a free-standing backfill wall. The effect of the height of the backfill column is studied in the numerical modelling by varying the height from 25 m to 100 m for various stope widths, lengths, and dip angles. Figure 4 shows the effect of fill height on the minimum stable cohesion for various stope widths. With increasing height of the backfill column, the minimum required cohesion increases steeply. The trend is in accordance with the theoretical equation of Mitchell, Olsen, and Smith (1982) and Caceres Doerner (2005). Mitchell, Olsen, and Smith’s (1982) equation was proposed for stopes of lower widths as compared to height, and hence for higher w/H ratios; the equation is used here by applying a critical width (wc) restriction [1] The equation proposed by Mitchell, Olsen, and Smith (1982) agrees with the numerical modelling results for lower stope heights. As anticipated, both the theoretical equations overestimate the required cohesion as they neglect the interface friction, cohesive bonding at the interstope wall, and make other simplifications.

Effect of stope width

Figure 2—Mode of failure in an inclined backfilled stope wall

In transverse stoping, the width is the lateral extension of the stope along the strike (Figure 1). The effect of stope width is studied by simulating the models for various stope widths (10 m, 20 m, 30 m, 40 m, and 50 m) for various heights, lengths, and dip angles. From the studies, it is clear that the width does not have a significant impact on the stability of the backfill wall. The graph (Figure 5) shows a slightly decreasing trend of the required cohesion as the stope width increases, tending to flatten at large stope widths.

Effect of stope length Based on the study by Li and Aubertin (2009), for narrow

Figure 3—Displacement history plot showing stable and failure states The Journal of the Southern African Institute of Mining and Metallurgy

Figure 4—Effect of stope height on the minimum stable cohesion VOLUME 122

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Stability analysis of a free-standing backfill wall and a predictive equation Effect of interface cohesion ratio

Figure 5—Effect of stope width on the minimum stable cohesion

orebodies the stress developed in the backfill material is transferred to a considerable extent to the walls. A similar effect can be seen from the numerical modelling results. Figure 6 shows the effect of stope length on the minimum stable cohesion for various orebody inclinations. The required cohesion increases with the stope length, but tends to flatten at higher stope lengths. This trend is concurrent with the theoretical equations of Mitchell, Olsen, and Smith (1982) and Caceres Doerner (2005). From Figure 6, it can be seen that the effect of orebody inclination is more pronounced for smaller stope lengths (narrow orebodies). When the stope length is larger, the central portions of the backfill behave similarly to the case of a vertical stope. When the orebody is narrow, the backfill is held firmly by the footwall and the hangingwall, thus improving overall wall stability.

The experimental studies conducted by Koupouli, Belem, and Rivard. (2016) confirmed that the interface cohesion would be 50– 60% of the backfill cohesion, while on the other hand, parametric studies by Li and Aubertin (2014) concluded that the best results in stress analysis were obtained when the interface cohesion was about 25% of the backfill cohesion. According to Koupouli, Belem, and Rivard (2017), the surface roughness of the contact between rock and backfill impacts the cohesion at the interface, and in some cases the interface cohesion ratio could be as high as 1.0 or even more. In this study, the cohesion ratio (rc) is varied between 0.25 and 1.0. When the ratio of the interface-to-backfill cohesion increases, the minimum stable cohesion decreases, as shown in Figure 8 for various stope lengths. Although the influence of rc on the overall backfill wall stability is not that pronounced, it cannot be neglected. In the absence of data from test work, it will be safer to assume rc = 0.25.

Prediction equation For a field engineer, it will be useful to have a prediction equation to determine the required strength of the backfill based on the stoping parameters. From the numerical modelling exercise, 96 data-sets were created to assess the required cohesion for a stable backfill wall at various heights, widths, lengths, dip angles, and cohesion ratios. Power equations were found to fairly represent the effect of the various parameters involved on the required cohesion. The general form of predictive equation chosen, after several-hit and-miss trials, is

Effect of orebody dip The numerical modelling studies conducted by Li and Aubertin (2009) on stress distribution within the paste fill column revealed that the inclination did not have much influence on the horizontal stresses, while the vertical stress near the hangingwall side reduced significantly for lower orebody inclination (less than 60°). The theoretical equation proposed by Mitchell, Olsen, and Smith (1982) did not incorporate orebody inclination. This equation was later modified by Dirige, McNearny, and Thompson (2009) for inclined stopes by reducing the vertical load acting on the critical plane and transferring it to the footwall contact plane. The theoretical prediction equation for the required UCS proposed by Caceres Doerner (2005) also incorporated orebody dip as a parameter. In the current study, various models with varying orebody dips are simulated. The variation in the minimum stable cohesion with respect to the orebody dip is presented for various stope lengths in Figure 7. It can be seen that the minimum stable cohesion increases in a curvilinear fashion for an increase in orebody dip, with the maximum obtained for the 90° (vertical) scenario. A similar trend can be seen for the earlier theoretical equations of Caceres Doerner (2005) and Dirige, McNearny, and Thompson (2009). However, while the Dirige, McNearny, and Thompson (2009) equation underestimates the required cohesion, the Caceres Doerner (2005) equation overestimates the same, as shown in Figure 7. It may be noted that the Caceres Doerner (2005) equation essentially predicts the required UCS. In our calculation, the required cohesion is evaluated using the Mohr-Coulomb theory [2] 230

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Figure 6—Effect of stope length (orebody width) on the minimum stable cohesion

Figure 7—Effect of orebody dip on minimum stable cohesion The Journal of the Southern African Institute of Mining and Metallurgy

Stability analysis of a free-standing backfill wall and a predictive equation

Figure 8—Effect of the cohesion ratio (rc) on the minimum stable cohesion

[3] where creq = required cohesion (kPa) H = backfill wall height (m) w = transverse stope width (m) L = transverse stope length (m) q = inclination of the orebody or stope with respect to the horizontal (radian) rc = ratio of rock-fill interface cohesion to backfill cohesion A = backfill strength coefficient having units kPa/m(B+C+D) B, C, D, E and F are exponents. Using Equation [3], the best-fitting values for the backfill strength coefficient (A) and exponents B, C, D, E and F were obtained using a C++ code employing mean squared error (MSE) minimization and search methods. The combination of values for these constants yielding the minimum MSE is found to be [4] where A = 0.57 kPa/m1.24. The accuracy of the prediction from Equation [4] can be seen from Figure 9. The correlation between the predicted and numerical results has an R2 of 0.975, a mean absolute percentage error of ±7.9%, and an RMSE value of 9.16. The angle of internal friction (f) for cemented backfill samples generally varies between 30° and 40° (Li and Aubertin, 2014; Koupouli et al., 2016; Liu et al., 2017); if not established from laboratory testing, a value in the above range may be assumed. From laboratory testing of the backfill specimen the actual relationship can be drawn between UCS and the cohesion of the backfill at a given site. However, this will require triaxial testing or a direct shear test. In the absence of such a site-specific relationship, the Mohr-Coulomb theory (Equation [2]) may be applied to obtain the required UCS. The design UCS may then be decided based on a factor of safety (FoS). [5] The FoS in a design should be carefully chosen for each mine site depending on the level of confidence of mine management as regards several other pertinent issues, such as the uncertainty in maintaining backfill mixing ratio, actual strength gain after emplacement in the stopes, effect of blasting-induced vibration, formation of cold joints in the backfill due to unscheduled stoppages, error in the prediction, etc. A FoS of 1.5–2.0 may generally be acceptable in most situations. Applicability of the prediction equation in real cases is limited to the range of stoping parameters considered in this modelling study. If the maximum stope length L (width of the orebody) is less than 10 m, it may The Journal of the Southern African Institute of Mining and Metallurgy

Figure 9—Comparison of the minimum required cohesion from the numerical modelling and the prediction equation

be taken as 10 m in the predictive equation. Theta is the actual inclination of the stope geometry and not necessarily the orebody dip. Hence it should be judiciously used, especially when the stope geometry is altered during mining. The rock mass rating considered in the modelling studies falls in the category ‘fair’ (RMR 40 and above) (Bieniawski, 1976). For very weak rock mass or under squeezing ground conditions there could be additional stresses acting on the backfill, and the predictive equation (Equation [4]) may not be applicable. A case-to-case numerical modelling study may be performed. Equation [4] is used in a few mining scenarios, as described the case examples. The case examples are not individually modelled. They are presented as application and validation of the developed prediction equation.

Case example 1: Cemented hydraulic fill for a chromite mine The chromite mine is situated in an ultramafic complex in the eastern part of India. The rock mass is highly jointed and weathered at shallow depth with an RMR of about 40. The orebody is steeply dipping, at 75–84°, and has a width ranging from 6 m to 25 m. The mine employs a blast-hole open stoping method in conjunction with cemented hydraulic fill composed of river sand and ordinary Portland cement (OPC). The mine requires a strong sill to optimize ore recovery from the lower stopes. Hence a plug of about 7.0 m is formed in the first stage of hydraulic filling with higher cement content for greater fill strength. The remaining height of about 43 m is bulk backfill, where the cement percentage needs to be optimized. The applicable stoping parameters for this case example are H = 43 m, w = 18 m, L = 25 m (maximum), q = 75° and rc = 0.25. The predictive equation (Equation [4]) yields a required cohesion of 79.55 kPa and design cohesion of 119.3 kPa for a FoS of 1.5. The corresponding design UCS is 413.4 kPa. From laboratory tests of hydraulic fill specimens with various cement contents and curing times it was found that with 6% OPC and 28 days of curing the UCS achieved is about 450 kPa, which is sufficient for the backfill wall. The mine has successfully extracted and backfilled over 25 stopes so far in primary-secondary sequence with hydraulic fill containing 6% OPC mixed with river sand in the bulk fill. The plug fill was made in all the stopes with 10% cement content, which had a laboratory tested UCS of 1225 kPa after VOLUME 122

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Figure 10—Exposed cemented hydraulic fill wall in the chromite mine

28 days of curing. In-situ samples of cured hydraulic fill were also tested after 28 days of emplacement, and showed 373 kPa for the bulk fill and 1096 kPa for the plug fill. The UCS of the in-situ samples was found to be about 10–17% lower than the laboratory prepared samples. Some backfill wall failure was observed initially due to blast vibration, especially when the slot opening was adjacent to the backfill wall. The mine management mitigated this issue by making the slot in the middle of the stope. Figure 10 shows a stable exposed backfill wall during secondary stoping. As considered in the numerical modelling, Figure 10 also demonstrates that a considerable gap between the fill top and the stope back remains after filling.

Case example 2: Cemented rock fill (CRF) for a lead-zinc mine At this mine site, located in the northern part of India, the Zn– Pb mineralization is hosted in quartzite-mica schist (QMS) in contact with calc-silicate. The orebody is 3–15 m thick with a steep dip (70–90°) at shallow depth, flattering to 0–20°) at greater depth. The mining method is longhole open stoping (LHOS) in longitudinal configuration in the steeper sections and a transverse configuration in the flatter part. Applicable stoping parameters of the steeper part are H = 25 m, w = 25 m, and L = 15 m (maximum), q = 90° and rc = 0.25; and for the flatter part H = 25 m, w = 15 m, L = 25 m (maximum transverse stope length exposure at a time), q = 90° (applicable dip of a stope), and rc = 0.25. Due to greater uncertainty in the homogeneity of the CRF mix a design safety factor of 2.0 is recommended. The required cohesion by using the prediction equation is 40.56 kPa for the steeper part of the orebody and 54.27 kPa for the flatter part. The design UCS should then be 348 kPa and 486 kPa for the steeper and flatter parts, respectively. Laboratory testing of 300 mm × 300 mm × 300 mm cubical samples of CRF revealed a UCS varying from 485 kPa to 1329 kPa for 5% cement content and 28 days curing, depending on the percentage of fines in the rock fill (10–25 %). The tests also revealed that the maximum strength of the CRF is reached at a fines content of about 15%. However, there are practical difficulties in controlling the percentage of fines during actual filling operations and hence it will be prudent to consider the lowest strength value. The mine currently practices CRF filling in both the steeper and flatter sections with 5% cement content. Apart from occasional minor chipping of the backfill wall during blasting, no major backfill wall failure has been observed so far in the mine.

Case example 3: Paste fill in a lead-zinc mine with a moderately dipping orebody The lead-zinc mine is situated in the northern part of India 232

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and occurs within a Precambrian banded gneiss complex with the host rock mostly comprising graphite-mica-sillimanite gneiss. The orebody dips at an average angle of about 60° and has a width of 10–50 m. The mine uses longhole open stoping (LHOS) in transverse or longitudinal configuration, depending on the orebody width, with a level interval of 25 m. The mine practises underhand as well as overhand mining using paste fill. The applicable stoping parameters for paste fill wall design in overhand stoping are H = 25 m, w = 15 m, L = 50 m, (maximum), q = 60°, and rc = 0.25. The required cohesion using Equation [4] is 62.6 kPa, which corresponds to the design UCS of 361 kPa for a safety factor of 1.5. A series of laboratory tests conducted using the mill tailings from the mine site mixed with various percentages of OPC as well as pozzolana Portland cement (PPC) was found that a UCS of 360–400 kPa can be achieved with either 6% PPC or 11% OPC. The requirement for underhand stoping will be different, but this is beyond the scope of this paper. The mine currently practises paste filling in overhand mining stopes with 10% OPC, 2% fly ash, and 88% mill tailings, which has a laboratory tested UCS in the range of 360–400 kPa.

Conclusion The study proved that numerical modelling is a versatile tool compared to simplified theoretical models, which more accurately represents the effect of various stoping parameters on the required backfill strength. The pattern of yielding in a backfill column at the time of failure roughly agrees with the critical plane postulated in the earlier theoretical models (Mitchell, Olsen, and Smith, 1982; Dirige, McNearny, and Thompson, 2009; Liu et al., 2018) for vertical orebodies (q = 90°), but was found to differ widely for inclined ones (q < 90°). The theoretical equations generally appear to overestimate the required strength of a backfill material as they ignore some key aspects such as interface friction, cohesive bonding at the inter-stope wall, and the stress arching phenomenon. From the parametric study, it was found that the stope height is the parameter with the most influence in determining the required strength of the backfill, whereas the stope width has the least influence. The stope length (L), stope inclination (q), and cohesion ratio (rc) have a significant influence on the wall stability for thinner orebodies but are mostly trivial for wider orebodies. The numerical modelling methodology developed by tracking the wall displacement and the plasticity state was very effective for estimating the required strength for a cemented backfill material in a variety of practical underground stoping scenarios. The predictive equation developed based on the numerical modelling results has good accuracy and should be a useful tool for field engineers for calculating the required cohesion and UCS quickly and fix the optimum binder percentage in the backfill mix accordingly. The Journal of the Southern African Institute of Mining and Metallurgy

Stability analysis of a free-standing backfill wall and a predictive equation Acknowledgements The authors would like to thank the Director of CSIR-Central Institute of Mining and Fuel Research for the permission to publish this work. The help and support offered by the officers of Hindustan Zinc Limited and Indian Metals and Ferro Alloys Limited during field implementation are greatly appreciated. The authors’ views are not necessarily of the institute to which they belong.

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Li, L. 2014. Generalized solution for mining backfill design, International Journal of Geomechanics, vol. 14, no. 3. doi: 10.1061/(ASCE)GM.1943-5622.0000329. Li, L. and Aubertin, M. 2009. Numerical investigation of the stress state in inclined backfilled stopes. International Journal of Geomechanics, vol. 9, no. 2. pp. 52-62. doi: 10.1061/(asce)1532-3641 Li, L. and Aubertin, M. 2014. An improved method to assess the required strength of cemented backfill in underground stopes with an open face. International Journal of Mining Science and Technology, vol. 24, no. 4. pp. 549-558. doi: 10.1016/j.ijmst.2014.05.020 Liu, G., Li, L., Yang, X., and Guo, L. 2017. Numerical analysis of stress distribution in backfilled stopes considering interfaces between the backfill and rock walls, International Journal of Geomechanics, vol. 17, no. 2. doi: 10.1061/(ASCE) GM.1943-5622.0000702 Liu, G., Li, L., Yang, X., and Guo, L. 2018. Required strength estimation of a cemented backfill with the front wall exposed and back wall pressured, International Journal of Mining and Mineral Engineering, vol. 9, no. 1. pp. 1-20. doi: 10.1504/IJMME.2018.091214 Marston, A. 1930. The theory of external loads on closed conduits in the light of the latest experiments. Bulletin 96, Iowa Engineering Experiment Station, Iowa State College, Ames, IA. Mitchell, R.J., Olsen, R.S., and Smith, J.D. 1982. Model studies on cemented tailings used in mine backfill. Canadian Geotechnical Journal, vol. 19, no. 1. pp. 14-28. doi: 10.1139/t82-002 Nasir, O. and Fall, M. 2008. Shear behaviour of cemented pastefill-rock interfaces, Engineering Geology, vol. 101, no. 3-4. pp. 146-153. Porathur, J. L., Jose, M., Bhattacharjee, R., and Tewari, S. 2018. Numerical modeling approach for design of water-retaining dams in underground hard rock mines—A case example. Arabian Journal of Geosciences, vol. 11, no. 23. p. 750. Potvin, Y., Grant, D., and Mungur, G. 2015. Towards a practical stope reconciliation process in large-scale bulk underground stoping operations, Olympic Dam, South Australia. CIM Journal, vol. 6, no. 2. pp. 102-110. Simms, P., Grabinsky, M., and Zhan, G. 2007. Modelling evaporation of paste tailings from the Bulyanhulu mine. Canadian Geotechnical Journal, vo;. 44, no. 12., pp. 1417-1432. Terzaghi, K. 1943. Bearing capacity. Theoretical Soil Mechanics. Wiley, New York. pp. 118-143. Yang, P. and Li, L. 2017. Numerical and limit equilibrium stability analyses of cemented mine backfill upon vertical exposure. UMT 2017: Proceedings of the First International Conference on Underground Mining Technology. Hudyma, M. and Potvin, Y. (eds). Australian Centre for Geomechanics, Perth. pp. 399-408. doi: 10.36487/acg_rep/1710_31_yang Yang, Z., Zhai, S., Gao, Q., and Li, M. 2015. Stability analysis of large-scale stope using stage subsequent filling mining method in Sijiaying iron mine. Journal of Rock Mechanics and Geotechnical Engineering, vol. 7, no. 1. pp. 87-94. Yu, Q., Chen, X., Dai, Z., Nei, L., and Soltanian, M.R. 2018. Numerical investigation of stress distributions in stope backfills. Periodica Polytechnica Civil Engineering, vol. 62, no. 2. pp. 533-538. doi: 10.3311/PPci.11295. Zhang, J., Zhang, Q., Huang, Y., Liu, J., Zhou, N., and Zan, D. 2011. Strata movement controlling effect of waste and fly ash backfillings in fully mechanized coal mining with backfilling face. Mining Science and Technology (China). vol. 21, no. 5. pp. 721-726. Zhang, Q., Zhang, J., Guo, S., Gao, R., and Li, W. 2015. Design and application of solid, dense backfill advanced mining technology with two pre-driving entries. International Journal of Mining Science and Technology, vol. 25, no. 1. pp. 127-132. u

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SAMCODES Environmental, Social and Governance (ESG) Working Group constituted to revise the current South African Guideline for the reporting of ESG parameters (SAMESG Guideline). The SAMCODES Standards Committee (SSC) has constituted a multi-disciplinary working group to update the existing SAMESG Guideline (and other elements of SAMCODES, if required) in order to ensure alignment with the rapidly evolving expectations of investors (and society) for disclosure of environmental, social and governance (ESG) considerations as an integral part of Mineral Reporting disclosures. An organization’s approach to the management of ESG considerations is rapidly becoming a defining feature in the market. Investors continue to demand accurate and transparent information on ESG performance to identify and prioritise funding for top tier investments. The SAMESG Guideline was an industry first when it was published in 2017. Since then, lessons in respect of its implementation have been learnt and the world of investor expectations in respect of ESG reporting has evolved. It is now an ideal time to future proof the SAMCODES to accommodate these lessons and the evolving ESG requirements. To date, the Working Group has been assimilating the outcomes of the Geological Society of South Africa’s (GSSA) ESG Inquisition that was held in 2021 in order to develop inputs that need to be considered when updating the ESG guidance. In addition, direct engagements have been held with a select group of key stakeholders to obtain their views on the issues that need to be addressed in the update. The outcomes of the above processes have been distilled in a communications document which the Working Group is now issuing for broad public review. One of the criticisms that has been leveraged against the current SAMESG Guideline is that there was inadequate consultation ahead of its publication. It is important to the Working Group that we therefore attempt to solicit the views of as many stakeholders as possible to inform the scope of work going forward. All parties who are directly or indirectly involved with Mineral Reporting and sustainability reporting are urged to review the initial consultation document from the Working Group and to provide feedback via the survey that has been prepared for this purpose. Persons working in the following disciplines are likely to be well-placed to provide comments: geologists; authors of Competent Persons Reports; environmental, social or governance subject matter experts; authors of corporate sustainability reports; mineral resource valuators; financial managers; institutional investors; private investors; investment analysts and stock exchange regulators as a minimum. The full report is available on the SAMCODES website at https://www.samcode.co.za/. Please create awareness of this report and the associated survey within your network! Comments should be submitted via the survey link by no later than 24 June 2022. The SAMCODES ESG Working Group looks forward to receiving your input.

Andrew McDonald 234 MAY 2022 122 Chairperson, SAMCODES StandardsVOLUME Committee

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Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines by A. Tekin1 Affiliation:

Department of Machinery and Metal Technology, Soma Vocational School, Manisa Celal Bayar University, Turkey.

Synopsis

Received: 2 Jul. 2021 Revised: 5 Jan. 2022 Accepted: 24 Jan. 2022 Published: May 2022

In almost all branches of industry, machinery and equipment in operation cause vibration. Some sources of vibration affect only the operator’s hands, fingers, and arms, while others have adverse effects on the entire -body. Various types and numbers of machines are utilized in the mining sector, and operators with them are exposed to mechanical vibrations caused by the mining machinery they use. A field study was conducted to evaluate the vibration risks to the operators using mining machines in open pit mines. Vibration levels and whole-body vibration (WBV) measurements using various types brands, and models of construction equipment were evaluated in three different mines in the west of Turkey and compared to the the criteria specified in the EU 2002/44/EC directive and ISO 2631-1 (1997) standards. The results showed that operators using mining machinery for 8 hours were exposed to WBV levels below the EU limit (1.15 m/s2), while 44% of these operators were exposed to levels above the EU action limit (0.5 m/s2). Measurement data collected from the working environment and the recommended improvements that need to be made to reduce WBV exposures are presented.

How to cite:

Keywords

Correspondence to: A. Tekin

Email: ayla.tekin@cbu.edu.tr

Dates:

Tekin, A. 2022 Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines. Journal of the Southern African Institute of Mining and Metallurgy, vol. 122, no. 5, pp. 235-244 DOI ID: http://dx.doi.org/10.17159/24119717/1728/2022 ORCID: A. Tekin https://orcid.org/0000-00022547-0872

health and safety, machine operators, open-pit mines, whole-body vibration (WBV), machine vibration.

Introduction Technological developments in recent years have led to the use of larger, more complex, and more expensive equipment in the mining sector. The constantly changing ambient conditions, as well as different geological and climatic situations during mining activities, adversely affect the employees, as well as the operators who use open-pit mine machinery, who are subjected to mechanical vibrations in the working environment. Various researches (Cann, Salmoni, and Eger, 2004; Kumar, 2004; Aye and Heyns, 2011; Mandal, Pal, and Sishodiya, 2013; Akinnuli et al., 2018) have found that high levels of whole-body vibration (WBV) exposure are experienced by workers in the mining and construction sectors (European Union 2002/44/EC, 2002). Operators exposed to vibration experience effects such as interference with activities, impaired health, and discomfort (Griffin, 1994). Numerous standards have been introduced to provide procedures for the evaluation of WBV and shock. At the operator's seat interface, measuring and assessing the WBV of a seated driver of mobile equipment is mostly performed according to the International Organization for Standardization report (ISO 2631-1); this is also mandated for use across Europe (Directive 2002/44/EC). British Standard Institution (BS 6841, 1987) is also widely used across the world. Both ISO 2631-1 and BS 6841 use methods based on calculations of an overall dose value from measurements of acceleration at the input to the whole body. These two standards are generally applicable to and designed to be used for a wide range of environments in which people are exposed to WBV. The ISO 5805 (1997) standard is speciﬁcally designed to evaluate exposure to mechanical shock only. ISO 2631-1 (1997) describes assessments of WBV risk based on measurements of the frequency-weighted root mean square (RMS) acceleration in the most severe axis and the time of exposure (Rantaharju et al., 2015). In the ISO 2631-5 standard, exposure is determined using shocks, age, and work experience of the employee. There are several studies available in which health hazards related to WBV are predicted in accordance with the methodologies introduced in ISO 2631-5 and ISO 2631-1. Aye (2009) attempted to identify health risks from various items of mining machinery according to ISO 2631-1 (1997) and ISO

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Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines 2631-5 (2004) for determination of WBV exposure. Smets, Eger, and Grenier (2010) measured WBV induced by three different types of 35, 50, and 150 t trucks through the operator's seat during one hour according to the ISO 2631-1 and ISO 2631-5 standards. They stated that the operators are exposed to vibrations above the daily exposure value but the probable health effect is low according to the ISO 2631-1 limits, and that there is some inconsistency between the two standards. Gryllias et al. (2016) compared health effects based on ISO 5349:2001, ISO 2631-1:1997, and ISO 2631-5:2004 standards for both whole body and handarm vibrations. Eger et al. (2008a) compared the health risks predicted by ISO 2631-1 and ISO 2631-5 criteria on load-haul-dump (LHD) machine operators and found that ISO 2631-1 consistently predicted higher health risks. In another study, Eger et al. (2008b) measured pressure, neck loads, and joint rotations of operators performing LHD and investigated the effect of operator work postures on the musculoskeletal system during working hours when exposed to vibration. Marin et al. (2017) described WBV exposures in a series of vehicles operating in open-pit mines. Three different daily exposure parameters were compared according to the ISO 2631-1:1997 and ISO 2631–5:2004 standards. Hoz-Torres et al. (2019) analysed WBV transmitted to agricultural tractor drivers by comparing ISO 2631-1 and ISO 2631-5 standards. They emphasised that both standards provide similar assessments and stated that the probability of adverse health effects is low. Thousands of workers in the open-pit mining sector are exposed to WBV on a daily basis (Eger et al., 2006, 2008a; Smets, Eger, and Grenier, 2010; Chaudhary, Bhattacherjee, and Patra, 2015). Factors causing WBV are vehicle activity, engine vibration, and uneven roads (McPhee, Foster, and Long, 2009). Another important factor is the frequent and intensive use of open-pit mining equipment (OPME) over a long period of time (Griffin, 1994). Kumar (2004) stated that WBV exposure levels of drivers operating different open-pit trucks, recorded along the x-, y-, and z-axes, exceeded the threshold values according to ISO 2631-1. Hagberg et al. (2006) investigated vibrations of machines operated in Sweden between 1999 and 2003, and found a strong relationship between WBV-induced back pain and spinal degeneration. Mandal and Srivastava (2010) investigated WBV exposure among dump truck operators in a coal mine in India, and observed that the vibration value varied from 0.644 m/s2 to 1.82 m/s2 in

terms of the dominant z-axis RMS acceleration value. They found that all dumper vehicles carried a high health risk according to ISO 2631-1 standards. Aye and Heyns (2011) conducted measurements using the methods and parameters given in ISO 2631-1 to determine the WBV level of operators on 34 different machines used in open-pit mines in South Africa. They foud that 95% of the machines assessed caused a vibration below the exposure limit value, and 50% caused vibration exceeding the effective value of the exposure. On the other hand, human vibration exposures were investigated for mine/quarry transport trucks during loading, handling and unloading activities (Mayton et al. (2018). Erdem, Dogan, and Duran (2020) analysed WBV exposure measurements taken from the driver's seat in 105 trucks of different types, brands, and models deployed in various open pits and an underground mining operation in Turkey. Chaudhary et al. (2019) investigated the relationship between exposure to WBV and occupational and personal factors among 39 drilling operators in Indian iron ore mines. They found that 70% of the operators were exposed to high levels of vibration, above the limit values recommended by ISO 2631-1. Sharma et al. (2020) conducted an extensive literature review and revealed the known harmful health effects of short- and long-term WBV exposure for operators of heavy earthmoving machinery (HEMM) operators in open pit mining. In this study, we investigated vibration exposures of heavyduty machine operators in open-pit mines and the precautions that can be taken to mitigate the severity thereof. We first present general information on the measurement methods, followed by the results of WBV exposure measurements for operators of heavy-duty machines at three different mines in the west of Turkey. Finally, directions for for further work to reduce the vibration exposures of machine operators to below the legal exposure limits are recommended.

Methods Location of vibration measurements and features of machines Vibration measurements were taken from three separate coal mine sites in western Turkey (Figure 1). All three mines operate with a fleet of approximately 200 and a large number of earthmovers, mobile mining equipment, and vehicles. Briefly,

Figure 1—Google Maps views of three different mining sites 236

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The Journal of the Southern African Institute of Mining and Metallurgy

Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines open-pit mining entails loosening of the overburden by drilling and blasting; extraction of coal from the seams by bulldozers, front end loaders, and wheel dozers; loading the coal with hydraulic or electric excavators; transport to the unloading area by 85 and 170 t trucks; and lightly spraying the road surfaces with water trucks to minimize dust. The machine types and operations from which WBV measurements were taken are shown in Figure 2. The machines that regularly move on unpaved and uneven surfaces consist of 41 different brands and models, including earthmoving trucks, hydraulic excavators, crawler dozers, graders, and hydraulic hammer drills. The distribution and technical specifications of the machines from which measurements were taken in this study are given in Table I.

WBV measurements Before any WBV exposure measurements were made, information such as the duration of the work, the sources causing the

exposure, action steps affecting the work done, the exposure time, and the status of the workstation were recorded. Machine operators work 6 days a week, 8 hours a day. Before the operators start work, they first undergo an entrance examination. A health file is prepared for each employee, and employees undergo a health screening every year. In addition, 16 hours of occupational health and safety trainings are given to the operators every year. During this training, the subject of vibration is explained. An accelerometer attached to an electronic instrument is used to detect and measure vibrations, and to analyse and store vibration data. For this purpose, a SVAN 958 model triaxial noisevibration measuring device was used for WBV measurements on operators using trucks, dozers, drills, graders and excavators (Figure 3). Records of vibration measurements were easily downloaded to a PC with SvanPC++ software via USB port. In addition, with the SvanPC++_RC remote communication software, device settings and data are easily accessed remotely from the internet (Figure 4).

Figure 2—Types of machines and operations The Journal of the Southern African Institute of Mining and Metallurgy

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Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines Table I

Machines and their specifications working at opencast mining sites (Tekin, 2020). Machine Types

Machine models

Average Capacity power

Numbers of machines

Field of usage

Truck

KOMATSU 1600 HP 170 ton 2 630 ES KOMATSU 875 HP 85 ton 6 HD 785 KOMATSU 702 HP 50 ton 2 HD 465

Earthmoving truck used in ore or overburden transport.

Electric excavator Hydraulic excavator

MARION 1250 kW 17yd3 4 191M HITACHI 655 HP 5m3 3 EX 1200

Electric and hydraulic excavator used in ore or overburden excavation and loading.

Dozer

KOMATSU 320 HP 9 D155 KOMATSU 446 HP 2 D275 KOMATSU 410 HP 2 D355 KOMATSU 448 HP 2 WD600

Crawler dozer and paydozer, powerful tracked machines that is used for ground leveling, to move material and short distance excavation or support operations in open-pit mining) use a variety of front mounted blades. Large dozers often do pioneering work, such as moving dirt in preparation.

Grader

KOMATSU 180 HP 2 GD 705R VOLVO 265 HP 1 G990 CAT 290 HP 1 16H KOMATSU 280 HP GD 825 A

Grader is a construction machine with a long blade used to prepare the base course to create a wide flat surface upon which to place the road surface.

Hydraulic breaker and drill

ING. RAND REEDRILL

Hydraulic breakers and drills are used in blasting hole drilling drilling.

Paydozer

455 Hp 400 HP

9.5 inch 9.9 inch

2 2

Figure 3—View of operators' cabin Figure 4—SVAN 958 four-channels sound and vibration analyser

Direction of vibration measurements There are many sources of vibration in the mining industry that are encountered all phases of a mining operation. The impact on human health depends on the transmission characteristics of the vibration from the movement of the various parts of the machinery to the operator's seat, and depends on the working 238

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time, sitting position, seating arrangement, and road conditions. The vibration value in each of these stages is different. Also, depending on whether the operators are standing or sitting, vibration can act on the body along the x-, y-, or z-axis. Vibration on employees was measured in all three axes (WBV The Journal of the Southern African Institute of Mining and Metallurgy

Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines measurements) in accordance with the principles specified in the TS ISO 2631-1 standard. The measurement device was fixed to the operator's seat cushion and each operator was briefed about the purpose of the measurement. The transducer was positioned so as to point in the x-dimension (back to chest), y-transverse (left to right), and z-vertical (seat to head position) (Figure 5).

Evaluation of WBV exposure Vibration analysis for WBV is calculated according to the formulae in the ISO 2631-1 (1997) standard. For each of these measurements, all frequency-weighted root mean square (WRMS) values in the x-, y-, and z-axes were calculated separately for each vehicle using Equation [1]. [1] where aw (t) = WRMS acceleration at a particular time t (m/s2) T = Duration of measurement (seconds) The individual RMS values of the accelerations measured along the x, y, and z directions by the precision vibration meter are represented by awx, awy, and awz, respectively. For triaxial measurements (Figure 5), the peak accelerations (maximum instantaneous acceleration during the measurement period) are also calculated together with the WRMS vector sum value

(Equation [2]). [2] Since the risk of damage differs along the three axes, WRMS accelerations (awx; awy; awz) are calculated using appropriate weighting factors defined in ISO 2631-1 (k = 1.4 for x-axis and y-axis, k = 1.0 for z-axis). The value of A(8) is found using Equation [3]. [3] The A(8) value is calculated using the daily exposure times (tn) of each phase, the WRMS vibration associated with each phase (awn), the N number , and the estimated daily exposure equivalent to an 8-hour continuous exposure level. The calculated values were used to ascertain the potential health risk to workers using the health guidance caution zone (HGCZ) consistent with Annex B of the ISO 2631-1 standard (ISO 2631,1-1997).

Results Effects of vibration on the human body Vibration affects the human body in many ways. The response to vibration exposure depends primarily on the frequency, amplitude, and duration of exposure. Other factors include the direction of vibration input, body mass, level of fatigue, and ground conditions. Humans can respond both mechanically and physiologically to vibration. The measured vibration values are compared with the ISO 2631-1 HGCZ to determine the recommended exposure times (Figure 6). The frequency-weighted acceleration values corresponding to the 8 hours exposure time HGCZ low (attention) and high (risk) limits are 0.45 m/s2 and 0.90 m/s2 respectively according to ISO 2631-1 (Table II). On the other hand, A(8) daily exposure action and the daily exposure threshold values of ISO 2631-1 are 0.5 m/s2 and 1.15 m/s2 respectively.

Vibration analysis

Figure 5—Direction of basi-centric x, y and z axes for WBV measurement

WRMS acceleration values of the data along three vibration axes of each operator group of the mining machines at mines A, B, and C are presented in Table III. At every stage of the work cycle (dozing or digging, loading, hauling, and unloading) the working

Figure 6—Health Guidance Caution Zone (HGCZ) [ISO 2631-1:1997] The Journal of the Southern African Institute of Mining and Metallurgy

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Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines Table II

Daily exposure limits of WBV of ISO 2631-1 (1997) Assesement of health risks

Predicted health risks

A(8) m/s2

Low Moderate High

<0.45 0.45-0.90 >0.90

Exposures below HGCZ* Exposure within HGCZ* Exposures above HGCZ* *Health Guidance Caution Zone (HGCZ) [ISO 2631-1:1997] Table III

Exposure to vibration characteristics of mining machine operators Open-pit Vehicle Frequency-weighted RMS Acceleration ValuesA test mine Driver’s estimated daily exposureB [h] awx [m/s2] awy [m/s2] awz [m/s2] awxyz [m/s2]

A A B B B B B B C C A A A B B B B B B B B B B C C A A B C A B B C C A A B B B B C

Truck-1 Truck-2 Truck-3 Truck-4 Truck-5 Truck-6 Truck-7 Truck-8 Truck-9 Truck-10 Dozer-1 Dozer-2 Dozer-3 Dozer-4 Dozer-5 Dozer-6 Dozer-7 Dozer-8 Dozer-9 Dozer-10 Dozer-11 Dozer-12 Dozer-13 Dozer-14 Dozer-15 Drill-1 Drill-2 Drill-3 Drill-4 Grader-1 Grader-2 Grader-3 Grader-4 Grader-5 Excavator-1 Excavator-2 Excavator-3 Excavator-4 Excavator-5 Excavator-6 Excavator-7

5 5 3 5 5 5 5 5 3 5 3 3 5 3 5 3 3 3 5 3 3 3 3 3 3 5 3 3 3 3 3 3 3 3 3 3 3 3 3 1 3

0.32 0.43 0.26 0.25 0.11 0.15 0.21 0.31 0.32 0.49 0.79 0.63 0.56 0.27 0.80 0.32 0.73 0.69 0.65 0.61 0.50 0.56 0.29 0.71 0.81 0.52 0.32 0.31 0.10 0.14 0.51 0.16 0.36 0.57 0.34 0.13 0.36 0.16 0.17 0.13 0.16

0.35 0.33 0.24 0.14 0.16 0.17 0.21 0.29 0.26 0.64 0.69 0.58 0.56 0.27 0.81 0.29 0.69 0.56 0.71 0.70 0.58 0.54 0.36 0.75 0.84 0.14 0.18 0.14 0.11 0.29 0.45 0.16 0.34 0.59 0.24 0.25 0.42 0.19 0.18 0.14 0.18

0.67 0.62 0.58 0.47 0.32 0.41 0.49 0.66 0.65 0.81 0.67 0.91 0.74 0.33 0.97 0.63 1.05 1.24 0.97 0.39 0.89 0.80 0.89 0.68 0.90 0.90 0.46 0.71 0.69 0.36 1.04 0.61 0.77 1.13 0.33 0.28 0.40 0.33 0.23 0.38 0.19

0.94 0.98 0.76 0.62 0.43 0.52 0.64 0.89 0.84 1.39 1.61 1.50 1.33 0.63 1.87 0.88 1.75 1.76 1.66 1.36 1.39 1.35 1.10 1.60 1.87 1.18 0.69 0.85 0.72 0.57 1.41 0.69 1.04 1.61 0.66 0.48 0.87 0.48 0.42 0.46 0.39

Dominant axis

z z z z z z z z z z x z z z z z z z z y z z z y z z z z z z z z z z x z y z z z z

A: Dominant axis values are bolded. B: Calculations were performed for every 5min duration within the total measurement period. The average of all 5 min values is reported.

machines transmit vibrations to the operators continuously. Operators were regularly exposed to WBV levels that exceed safety limits as dictated by the ISO 2631-1 standard. The highest WBV exposure levels were found among dozer operators, because they work on the roughest surfaces in the open-pit mine. Excavator operators were exposed the lowest vibration levels. Operators of different brands, models and capacity mine 240

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machinery were exposed to changing WBV levels between 0.11 and 1.24 m/s2 in terms of RMS. Variations in measurement amplitudes were recorded for the same type of mining machine operating at the same environment. The daily WBV exposures of operators were recorded over periods ranging from 1 to 5 hours. As can be seen in Table III, operatore are mostly exposed to WBV in vertical direction (z). The Journal of the Southern African Institute of Mining and Metallurgy

Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines As it can be seen in Figure 6, the prediction of health risk from exposure to vibration generated with equipment primarily depends on two factors: vibration magnitude along the dominant axis and duration of exposure in a day. The average values (A(8)) and standard deviation of minimum and maximum daily WBV exposures of mining operators are summarized in Table IV. In addition, the health risks based on precaution and risk thresholds are specified as percentages for all machines according to the ISO 2631-1 standard and the EU 2002/44 / EC directive. It can be seen in Table IV and Figure 7 that all machine operators are exposed to WBV under the daily exposure limit value of 1.15 m/s2, predominantly. The measured WBV values were compared with the HGCZ to determine the recommended exposure times for operators using the mining machines. Of the 41 machines, 20 caused vibration below the caution zone, 20 of them were within the HGCZ, and one was above the threshold value. On the other hand, when the results were compared with of the European directive were evaluated ; 23 operators’ WBV values were below the effective exposure value and 18 operators were exposed to vibration between the effective exposure value and the limit value. Since the excavators and the drills mostly generate vibration accelerations

below the exposure action value (0.5 m/s2) the risk can be tolerated except for hypersensitive operators. Trucks, dozers, and graders produce vibrations somewhere between the exposure action and the threshold value and extra efforts should be made to reduce the risk for these machines. According to Figure 7, the dozer operators at the B open-pit area were exposed to higher WBV levels, while the excavator operators working at the C openpit area were exposed to the lowest WBV levels. Since the terrain in open-pit mining locations changes constantly, factors such as operator experience, irregular and/or rough terrain, intensity of work, exposure time, and even tyre pressure of mining machinery affect WBV levels.

Discussion Numerous studies are under way to ensure that open-pit mining machinery is operated with the highest possible efficiency and performance. Operators using these machines may be exposed to long-term high WBV levels that can affect their health. The operator's vibration exposure level depends on several factors, such as the magnitude of the vibration, the duration of exposure, total working hours, terrain conditions, mobility, and machine

Table IV

Determination of health risk of the mining machine operators at the open-pit mine-A, B and C, respectively, according to ISO 2631-1 HGCZ and EU Directive boundaries based on the estimated 8 h exposure duration A(8) The open-pit mine-A Mining machines Number Daily vibration Eexposures A(8) [m/s2] Min Max Mean±sd

Dump-Truck Dozer Drill Grader Excavator Total

2 3 2 1 2 10

0.49 0.56 0.28 0.25 0.21

0.53 0.68 0.71 0.25 0.29

0.51±0.03 0.62±0.06 0.49±0.30 0.25±0.00 0.25±0.13

ISO 2631-1 HGCZ) (based on 8 h exposure duration)A Below Within Above

%50 %100 %100

%100 %100 %50 -

EU Directive (based on 8 h exposure duration)B Below AV Above AV Below LV

%50 %50 %100 %100

%50 %100 %50 -

The open-pit mine-B Mining machines Number Daily vibration exposures A(8) [m/s2] Min Max Mean±sd

Dump-Truck Dozer Drill Grader Excavator Total

6 10 1 2 4 23

0.25 0.23 0.43 0.37 0.13

0.52 0.91 0.43 0.64 0.36

0.37±0.09 0.59±0.2 0.43±0.0 0.50±0.1 0.21±0.1

ISO 2631-1 HGCZA (based on 8 h exposure duration)A Below Within Above

%83.33 %20 %100 %50 %100

%16.67 %70 %50 -

%10 -

EU Directive (based on 8 h exposure duration)B Below AV Above AV Below LV

%83.33 %30 %100 %50 %100

%16.67 %70 %50 -

The open-pit mine-C Mining Machines Number Daily Vibration Exposures A(8) [m/s2] Min Max Mean±sd

Dump-Truck Dozer Drill Grader Excavator Total

2 2 1 2 1 8

0.40 0.64 0.42 0.47 0.15

0.71 0.72 0.42 0.69 0.15

0.55±0.22 0.62±0.06 0.42±0.00 0.58±0.15 0.15±0.00

ISO 2631-1 HGCZ (based on 8h exposure duration)A Below Within Above

%50 %100 %100

%50 %100 %100 -

EU Directive (based on 8h exposure duration)B Below AV Above AV Below LV

%50 %100 %50 %100

%50 %100 %50 -

A: According to ISO 2631-1 the frequency-weighted acceleration values corresponding to the lower and upper limits of the HGCZ (for 8 h of exposure) are 0.45 and 0.90 m/s2, respectively. B: According to EU directive a daily exposure action value(AV) of 0.5m/s2 and daily exposure limit value(LV) of 1.15m/s2 (the frequency-weighted acceleration) The Journal of the Southern African Institute of Mining and Metallurgy

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Figure 7—Comparison of average WBV acceleration values generated by mining machinery at mines A, B and C with exposure threshold values of A(8) ISO 2631-1 standard and EU Directive 2002/44 / EC

type and maintenance. Therefore, when a machine is classified as safe as regards WBV levels under certain operating conditions, it can pose a threat to human health in different operating conditions. This study reveals the role of WBV in the analysis of such problems. For this purpose, WBV levels generated by various types and models of 41 heavy mining machines located at three different open-pit mines in the west of Turkey were studied in accordance with the criteria of ISO 2631-1 standards and EU directive 2002/44/ EC. The mining machines are mainly trucks, dozers, drills, graders, and excavators. The following results were obtained from the study. According to the ISO 2631-1 standards, all operators using open-pit mine working machines are exposed to vibrations below the EU exposure limit of 1.15 m/s2, while 44% of these operators are exposed to WBV levels exceeding the threshold value. Fortynine per cent of the operators are exposed to WBV levels in the range of 0.45–0.90 m/s2, which is within the HGCZ of the vibration levels, apart from a dozer operator at mine B, who was exposed to WBV levels above the acceptable limits. The results are supported by previous studies. In a study of six different track loaders at four different workplaces (Newell, Mansfield and Notini, 2006), it was observed that the most severe general frequency-weighted RMS vibration magnitude, that is, the emission value, was 1.12 m/s2. Burström et al. (2016) studied 95 mining vehicles of different models and capacities, and showed that the daily average vibration exposure was between 1.9 and 6.7 hours, and the average A(8) value was between 0.2 and 1.0 m/s2. Mandal, Pal, and Sishodiya (2013) observed that the daily vibration exposure times (2–7.5 hours) and vibration levels of 157 items of mining equipment in ten open pit mines varied between 0.21 and 1.82 m/s2. High levels of vibration exposure may result from the operation of such machines on uneven floors. However, environmental conditions such as cold and snow in winter and heat in summer affect road and surface conditions in open pit mines, which are known to be critical for WBV exposure (Wolfgang, 2014). So vibration from rough roads and bad roads can be alleviated by implementing a good road maintenance plan, and can also be reduced by providing suspension cabins, and 242

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ensuring that tyre are inflated to the correct pressures and shock absorbers are in good condition. Many researchers on this subject have made similar suggestions (Chaudhary et al, 2019; Marin et al, 2017).

Conclusions and recommendations This study was conducted to examine the exposure of operators of various types and models of construction equipment at open pit mining sites to whole-body vibration (WBV). The results indicate that operators are frequently exposed to WBV levels in the vertical direction that are within or above the HGCZ as defined by ISO 2631-1 standards and EU directive 2002/44/EC. Therefore, it is important to examine the impact of vibration on operators in open pit mine sites, and to collect information that will help design better working conditions that will improve the health of the operators and the efficiency of their work. The following actions are recommended to avoid vibrations above allowable levels for operators. Terrain conditions, speed, seat status, vehicle maintenance, etc. Many factors can affect the vibration of work machines. Therefore, a machine classified as safe in one working environment may pose a threat to human health in another. Since mining is characteristically a constantly changing process, periodic maintenance plans for all these machines, regular checking of tyre pressures and moving parts of the machine, and good maintenance of haul roads can contribute to reducing the health risk caused by vibration. Since the effect of RMS acceleration values on the z-axis is greater than the x-longitudinal and y-transverse axes, risk assessments should be done especially by measuring vertical vibration values in order to prevent adverse effects on health and work performance. Previous studies confirm that A(8) WBV exposures are dominant (z-axis) (Kumar, 2004; Eger et al., 2006, 2008; Smets et al., 2010; Chaudhary, 2015; Burgess-Limerick and Lynas, 2016). Vibration in the z-axis direction is accepted as the most critical aspect for low back pain in drivers (Rehn et al., 2005). Regular health monitoring is recommended for all operators exposed to vibration in mines. Occupational exposure to WBV from operating these vehicles is a significant risk for vehicle drivers' low back pain (Burström et al, 2016). Musculoskeletal The Journal of the Southern African Institute of Mining and Metallurgy

Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines pain is more pronounced in groups of miners exposed to WBV compared to unexposed groups (Mandal et al, 2010; Skandfer et al, 2014). Operator competence also affects WBV acceleration levels due to the use of operating machines. For that reason, operators should be trained on a regular basis by expert trainers on how to minimize vibration levels during operations, especially on uneven ground. As a result, vibration risk assessment is necessary in openpit mining operations and more focus must be addressed to implementing preventive measures to reduce vibration risks significantly.

References Akinnuli, B.O., Dahunsi, O.A., Ayodeji, S.P., and Bodunde, O.P. 2018. Whole-body vibration exposure on earthmoving equipment operators in construction industries. Cogent Engineering, vol. 5, no. 1. pp. 1-14. https://www.tandfonline. com/loi/oaen20 Aye, S.A. 2009. Evaluation of operator whole-body vibration and shock exposure in a South African open cast mine. MSc thesis. Faculty of Engineering, Built Environment and Information Technology, University of Pretoria. 140 pp. Aye, S.A. and Heyns, P.S. 2011. The evaluation of whole-body vibration in a South African opencast mine. Journal of the Southern African Institute of Mining and Metallurgy, vol. 111, no. 11. pp. 751-757. https://repository.up.ac.za/bitstream/ handle/2263/18670/Aye_Evaluation%282011%29. pdf?sequence =1&isAllowed=y British Standards. 1987. Measurement and evaluation of human exposure to whole-body mechanical vibration and repeated shock. BS 6841. British Standards Institution, London. Burgess-Limerick, R. and Lynas, D. 2016. Long duration measurements of wholebody vibration exposures associated with surface coal mining equipment compared to previous short-duration measurements. Journal of Occupational and Environmental Hygiene, vol. 13, no. 5. pp. 339-345. https://www.tandfonline. com/loi/uoeh20 Burström, L., Hyvarinen, V., Johnsen, M., and Pettersson, H. 2016. Exposure to whole-body vibration in open-cast mines in the Barents region. International Journal of Circumpolar Health, vol. 75, no: 29373. https://dx.doi. org/10.3402%2Fijch. v75.29373 Cann, A., Salmoni, A., and Eger, T. 2004. Predictors of whole body vibration exposure in transport truck operators. Ergonomics, vol. 47, no. 13. pp. 1432-1453. https://doi.org/10.1080/0014013041000171 2618 Chaudhary, D.K., Bhattacherjee, A., Patra, A.K. and Chau, N. 2015. Whole-body vibration exposure of drill operators in iron ore mines ,and role of machinerelated, individual, and rock-related factors. Safety and Health at Work, vol. 6. pp. 268-278. Chaudhary, D.K., Bhattacherjee, A., and Patra, A. 2015. Analysis of wholebody vibration exposure of drill machine operators in open pit iron ore mines. Procedia Earth and Planetary Science, vol. 11. pp. 524-530. https://doi. org/10.1016/j.proeps.2015.06.054 Chaudhary, D.K., Bhattacherjee, A., Patra, A.K., Upadhyay, R., and Chau, N. 2019. Associations between whole-body vibration exposure and occupational and personal factors in drill operators in indian iron ore mines. Mining, Metallurgy & Exploration, vol. 36. pp. 495-511. https://doi. org/10.1007/s42461019-0061-y Eger, T., Salmoni, A., Cann, A., and Jack, R. 2006. Whole-body vibration exposure experienced by mining equipment operators. Occupational Ergonomics, vol. 6, no. 3-4. pp. 121-27. Eger, T., Stevenson, J., Boileau, P-E., Salmoni, A., and VibRG. 2008 . Predictions of health risks associated with the operation of load-haul-dump mining vehicles: Part 1 – Analysis of Whole-Body Vibration Exposure Using ISO 2631-1 and ISO 2631-5 Standards. International Journal of Industrial Ergonomics, vol. 38, no. 9-10. pp. 726-738. https://doi.org/10.1016/j.ergon.2007.08.012 Eger, T., Stevenson, J., Callaghan, J.P., Grenier, S., and VibRG1. 2008 . Predictions of health risks associated with the operation of load-hauldump mining vehicles: Part 2—Evaluation of operator driving postures and associated postural loading. International Journal of Industrial Ergonomics, vol. 38, no. 9-10. pp. 801-815. https://doi.org/10.1016/j.ergon.2007.08.012 Erdem, B., Dogan, T., and Duran, Z. 2020. Assessment of whole-body vibration exposure of mining truck drivers. Journal of the Southern African Institute of Mining and Metallurgy. vol. 120, no. 9. pp. 547-559. http://dx.doi. org/10.17159/2411- 9717/1146/2020 EU. 2002. European Parliament and Council Directive, 2002/44/EC on the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (vibration) (sixteenth individual Vibration Research Group, Laurentian University, IRSST, Queen's University, University of Western Ontario, MASHA and CSAO, Canada

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Directive within the meaning of Article 16(1) of Directive 89/391/EEC. Official Journal of the European Communities. 177 pp. Griffin, M.J. 1990. Handbook of Human Vibration. Academic Press, San Diego, CA. Gryllias, K., Yiakopoulos, C., Karamolegkou, S., and Antoniadis, I. 2016. Human-body vibration exposure experienced by tram drivers – An evaluation according to ISO standards & European directives. Proceedings of the 23rd International Congress on Sound & Vibration, Athens, Greece, 10-14 July. International Institute of Acoustics, Aiburn, AL. Hagberg, M., Burström, L., Ekman, A., and Vilhelmsson, R. 2006. The association between whole body vibration exposure and musculoskeletal disorders in the Swedish work force is confounded by lifting and posture. Journal of Sound and Vibration, vol. 298, no. 3. pp. 492-498. Hoz-Torres, M.L., Aguilar-Aguilera, A.J., Martínez-Aires, M.D., and Ruiz, D.P. 2019. A Comparison of ISO 2631-5:2004 and ISO 2631-5:2018. Standards for whole-body vibrations exposure: A case study. Occupational and Environmental Safety and Health. https://doi.org/10.1007/978-3-030-14730-3. ISO 2631-1. 1997. Evaluation of Human Exposure to Whole-Body Vibration – Part 1: General Requirements, ISO Standard Handbook (1995): Mechanical Vibration and Shock, Volume 2: Human Exposure to Vibration and shock; Vibration in Relation to Vehicle, Specific Equipment and Machines, Buildings. 2nd edn. International Organization for Standardization, Geneva. pp. 1-31. ISO 5805. 1997. Mechanical Vibration and Shock – Human Exposure – Vocabulary. International Organization for Standardization, Geneva. Kumar, S. 2004. Vibration in operating heavy haul trucks in overburden mining. Applied Ergonomics, vol. 35, no. 6. pp. 509-520. https://doi.org/10.1016/j. apergo.2004.06.009 Mandal, B.B. and Srivastava, A.K. 2010. Musculoskeletal disorders in dumper operators exposed to whole body vibration at Indian mines. International Journal of Mining, Reclamation and Environment, vol. 24, no. 3. pp. 233-243. Mandal, B.B., Pal, A.K., and Sishodiya, P.K. 2013. Vibration characteristics of mining equipment used in Indian mines and their vibration hazard potential. International Journal of Environmental Health Engineering, vol. 2, no. 4. pp. 1-10. Marin, L.S., Andres, C.R., Estefany, R., Hugo, P., Lope, H.B., Jack, T.D., and Peter, W.J. 2017. Assessment of whole-body vibration exposure in mining earth-moving equipment and other vehicles used in surface mining. Annals of Work Exposures and Health, vol. 61, no. 6. pp. 669-680. Mayton, A.G., Porter, W.L., Xueyan, S.X., Weston, E.B., and Rubenstein, E.N. 2018. Investigation of human body vibration exposures on haul trucks operating at U.S. surface mines/quarries relative to haul truck activity. International Journal of Industrial Ergonomics, vol. 64. pp. 188-198. https://doi. org/10.1016/j. ergon.2017.05.007 McPhee, B., Foster, G., and Long, A. 2009. Bad Vibrations: A Handbook on Whole-Body Vibration Exposure in Mining: The Joint Coal Board Health and Safety Trust, Sydney, Australia. Newell, G.S., Mansfield, N.J., and Notini, L. 2006. Inter-cycle variation in whole-body vibration exposures of operators driving track-type loader machines. Journal of Sound and Vibration, vol. 298, no. 3. pp. 563-579. https:// doi.org/10.1016/j. jsv.2006.06.015 Rantaharju, T., Mansfield, N.J., Ala-Hiiro, J.M., and Gunston, T.P. 2015. Predicting the health risks related to whole-body vibration and shock: A comparison of alternative assessment methods for high-acceleration events in vehicles. Ergonomics, vol. 58, no. 7. pp. 1071-1087. Rehn, B., Nilsson, T., Olofsson, B., and Lundstrom, R. 2005. Whole-body vibration exposure and non-neutral neck postures during occupational use of all-terrain vehicles. Annals of Occupational Hygiene, vol. 49, no. 3. pp. 267-75. doi:10.1093/annhyg/meh077 Sharma, A.S., Mandal, S.K., Suresh, G., Oraon, S., and Kumbhakar, D. 2020. Whole body vibration exposure and its effects on heavy earthmoving machinery (HEMM) operators of opencast mines – A review. Journal of Mines, Metals and Fuels, vol. 68, no. 7. pp. 221-228. Skandfer, M., Talykova, L., Brenn, T., Nilsson, T., and Vaktskjold, A. 2014. Low back pain among mineworkers in relation to driving, cold environment and ergonomics. Ergonomics, vol. 57. pp. 1541-8. https://www.tandfonline.com/loi/ terg20 Smets, M.P.H., Eger, T.R., and Grenier, S.G. 2010. Whole-body vibration experienced by haulage truck operators in surface mining operations: A comparison of various analysis methods utilized in the prediction of health risks. Applied Ergonomics, vol. 41, no. 6. pp. 763-770. https://doi.org/10.1016/j. apergo.2010.01.002 Tekin, A. 2020. Noise exposure estimation of surface-mine - Heavy equipment operators using artificial neural networks. Celal Bayar University Journal of Science, vol. 16, no. 4. pp. 429-436. Turkish Standard - International Organization for Standardization [TSISO]. Mechanical vibration and shock - Assessment of exposure to whole body vibration - Part 1: General rules. TS ISO 2631-1:2013. Ankara. 37 pp. Wolfgang, R. and Burgess-Limerick, R. 2014. Whole-body vibration exposure of haul truck drivers at a surface coalmine. Applied Ergonomics, vol. 45. pp. 1700-1704. u VOLUME 122

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Online Short Course

MINE TO MILL Assessment of vibration exposure of mine machinery operators at three different open-pit coal mines RECONCILIATION: FUNDAMENTALS AND TOOLS FOR PRODUCTIVITY IMPROVEMENT SHORT COURSE DATE: 21-24 JUNE 2022 ONLINE FROM 9AM TO 13PM SAST

Mining is an integrated operation that includes planning, mining (excavation), processing, and metallurgy where metals are extracted. A miningplan of operation forecasts the amount of ore to be mined and/or metal to be produced at the beginning of a year. The model-mine-mill (M3) reconciliation is a set of activities carried out by mining operations in order to measure success and predict success of mine plan. Success in annual production of a mine depends on many factors such as a good mine plan based on a nearly robust resource/ reserve model, execution of mine-plan in the operation supported by reliable laboratory services and disciplined work-culture led by a competent workforce. A model-mine-mill (M3) reconciliation process helps to gain knowledge on the actual (or, likely) reasons for achieving the planned production or, not. When properly implemented, a detailed model-mine-mill (M3) reconciliation process leads to finding out the areas for further improvements leading to substantial enhancements in productivity. A successful mining operation often conducts the reconciliation at regular time intervals.

T H E TA R G E T AU D I E N C E • • • • • •

Mining engineers Geologists Process engineers associated with mining operations. Financial institution professionals working on mining projects Consultants Researchers.

Dr Abani Samal –Program lead

Dr Abani R Samal holds PhD from SIU Carbondale, DIC & MS from Imperial College, London and M Tech (Mineral Exploration) degree from IIT (ISM) Dhanbad, India. He is in the mining industry since 1996. Currently he is the principal and owner of GeoGlobal, LLC and providing consulting services to exploration and mining companies, government agencies and major financial institutions worldwide. Mineral deposit evaluation, applied geostatistics and mine-mill reconciliation are his technical specializations. Dr Samal offers professional development programs to industry professionals and researchers worldwide. Major professional societies including SME, SEG, AIG (online), CIM-IUGS and MEAI have hosted his professional development programs in USA, Canada, Guinea, India and Colombia. Dr Samal also serves in the editorial boards of two international journals: Mining, Metallurgy & Exploration journal (MMEX) and Natural Resources Research Journal.

THE PROGRAMME The program will be offered virtually in 4 sessions each session with three contact hours of virtual meetings and two take home assignments / exercises. The sessions will have multiple Q&A opportunities. Outline of the program: Session 1: Introduction of the program and participants Reconciliation: An introduction to the concept Session 2: Various types and nodes of reconciliation in a mining project: LT Resource/reserve, ST Resource/Reserve, Production, Stock piles and Mill Session 3: Factors in reconciliation Session 4: Error measurements & Q&A

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FOR FURTHER INFORMATION, CONTACT: Camielah Jardine E-mail: camielah@saimm.co.za Head Conferencing Tel: +27 MAYof2022 VOLUME 122 11 834-1273/7 The Journal of the Southern African Institute of Mining and Metallurgy SAIMM Web: www.saimm.co.za

Investigation of the mixing characteristics of industrial flotation columns using computational fluid dynamics by I. Mwandawande1, S.M. Bradshaw1, M. Karimi2, and G. Akdogan1 Affiliation:

niversity of Stellenbosch, Process U Engineering, South Africa. 2 Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Sweden. 1

Correspondence to: G. Akdogan

Email:

gakdogan@sun.ac.za

Dates:

Received: 7 Apr. 2021 Revised: 24 Mar. 2022 Accepted: 31 Mar. 2022 Published: May 2022

How to cite:

Mwandawande, I., Bradshaw, S.M., Karimi, M., and Akdogan, G. 2022 Investigation of the mixing characteristics of industrial flotation columns using computational fluid dynamics. Journal of the Southern African Institute of Mining and Metallurgy, vol. 122, no. 5, pp. 245-258 DOI ID: http://dx.doi.org/10.17159/24119717/1589/2022 ORCID: S.M. Bradshaw https://orcid.org/0000-00016323-8137 M. Karimi https://orcid.org/0000-00021182-1133 G. Akdogan https://orcid.org/0000-00031780-4075

Synopsis The mixing characteristics of industrial flotation columns were investigated using computational fluid dynamics (CFD). Particular emphasis was placed on the clarification of the relationship between the liquid and solids mixing parameters such as the mean residence time and axial dispersion coefficients. The effects of particle size and bubble size on liquid dispersion in the column were also studied. An Eulerian-Eulerian method was applied to simulate the multiphase flow, while additional scalar transport equations were introduced to predict the liquid residence time distribution (RTD) and particle age distribution inside the column. The results obtained show that particle residence time decreases with increasing particle size. The residence time of the coarser particles (112.5 µm) was found to be at least 60% of the liquid residence time, while the finer particles (19 µm) had a residence time similar to the liquid. The results also show that an increase in the particle size of the solids results in a decrease in the liquid vessel dispersion number, while a decrease in the bubble size increases liquid axial mixing. Finally, the simulated axial velocity profiles confirm the similarity between the liquid and solids axial dispersion coefficients in column flotation.

Keywords mixing characteristics, flotation column, computational fluid dynamics, residence time distribution.

Introduction Column flotation is an established mineral concentration technology used in the mineral processing and coal beneficiation industries. The concentration process takes place through the collection of valuable hydrophobic mineral particles by a rising swarm of air bubbles in countercurrent flow against a feed slurry in the collection zone of the column. The bubbles then transport the mineral particles to the top of the column into the froth zone (or cleaning zone) where the particles are eventually recovered in the overflow. Flotation columns differ from conventional flotation cells in a number of ways. For example, in column flotation the bubbles are generated using spargers located at the bottom of the column, while impellers are used in conventional cells for this purpose. In addition, wash water is added into the froth zone at the top of the flotation column to wash down any unwanted particles entrained from the collection zone. This feature is not present in conventional cells. The froth layer formed at the top part of the flotation column is also deeper compared to conventional cells. This is because of the stabilizing effects from the wash water which is added into the froth zone. The main differences between columns and conventional cells are illustrated in Figure 1. Flotation columns are known for their improved metallurgical performance compared to conventional flotation cells. In particular, the addition of wash water enables flotation columns to produce higher concentrate grades compared to conventional cells, which usually produce lower grades due to particle entrainment. In addition, the required concentrate grades are achieved in a single-stage process in flotation columns, whereas conventional cells require several stages to obtain a suitable grade (Finch and Dobby, 1990). However, increased mixing in the column can adversely affect its grade and recovery performance. It has been observed that mineral recovery decreases as the mixing conditions increase from plug flow towards perfectly mixed flow in the column (Finch and Dobby, 1990). As a result,

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Investigation of the mixing characteristics of industrial flotation columns

Figure 1—Schematic diagram of a flotation column (A) compared to a conventional flotation cell (B)

the design and optimization of flotation columns require detailed knowledge of the effects of various geometrical and operational parameters on the mixing characteristics of the column. The mixing characteristics of flotation columns have been studied by several researchers (Dobby and Finch, 1985; Mills, Yionatos, and O’Connor, 1992; Yianatos and Bergh, 1992; Yianatos et al., 2005; Xu and Finch, 1992). However, there are still uncertainties, particularly with regard to solids mixing characteristics in the column. The earlier studies by Dobby and Finch (1985) and Yianatos and Bergh (1992) suggested that the solids and liquid axial dispersion coefficients were equal. On the other hand, several authors have questioned the equivalence of the solids and liquid dispersion, citing various reasons (Ityokumbul, Kosaric, and Bulani, 1988; Mills and O'Connor, 1990; Goodall and O'Connor, 1991; Ityokumbul, 1992). Ityokumbul, Kosaric, and Bulani (1988) argued that the observed equivalence of the solids and liquid axial dispersion coefficients in the work of Dobby and Finch (1985) could have been based on wrong experimental data. In particular, they suggested the possible presence of dead volumes in the column that was used in the experiments and the use of wrong boundary conditions in the subsequent calculations as the main problems. On the other hand, Mills and O'Connor (1990) observed that the feed percentage solids used in the work of Dobby and Finch was too low to highlight differences between the liquid and solids axial dispersion coefficients. They then demonstrated, using their own experimetal work, that the solids axial dispersion coefficient did not equal the liquid one. Other notable arguments against the equivalence of liquid and solids dispersion coefficients are presented by Ityokumbul (1992), who went further to question the applicability of the axial dispersion model for describing the behaviour of solid particles by previous researchers. Some researchers have also investigated the effect of solids on the liquid dispersion in the column (Finch and Dobby, 1991). It has been reported that the liquid dispersion decreases as the percentage of solids in the feed increases, possibly due to viscous effects. However, the effect of particle size on the liquid dispersion has not yet been studied. The studies described above were entirely based on experimental methods in which the solids and liquid velocity fields inside the column were not examined. Computational fluid 246

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dynamics (CFD) is an alternative modelling tool which is based on the flow physics of the process. CFD methodology can therefore be used to study the mixing characteristics of flotation columns, with the additional advantage of basing the interpretation of the results on the detailed velocity fields derived from numerical simulations. Over the last two decades, CFD has emerged as a powerful tool for modelling the flotation separation process. The focus has been mostly on conventional flotation cells, where the hydrodynamics are coupled with flotation sub-processes such as bubble-particle collision, attachment, and detachment (Koh, Manickam, and Schwarz, 2000; Koh and Schwarz, 2009; Liu and Schwarz, 2009; Koh and Schwarz, 2006). Nonetheless, only a limited amount of CFD literature is available for column flotation, as this process is typically modelled through extensive large-scale experimentations. One of the earliest numerical works is that by Deng, Mehta, and Warren (1996), who applied two-phase numerical simulations to study the two-dimensional flow of flotation columns. Using the axis-symmetric assumption, they reported a liquid circulation pattern in which the axial liquid velocity was upward in the centre and downward near the walls of the column. The liquid circulation established in the column was subsequently cited as one of the main reasons for mixing in column flotation. In addition, the effect of superficial gas velocity on the extent of mixing in the column was investigated. An increase in superficial gas velocity was reported to cause more liquid circulation, which would result in increased mixing in the column. However, the actual mixing was not simulated in terms of residence time distributions (RTDs) and the flow was assumed to be laminar, which eliminates the significant effect of turbulent eddies on the mixing. Subsequent studies were conducted by Xia, Peng, and Wolfe (2006) who used a Lagrangian two-dimensional CFD model to simulate the alleviation of liquid back-mixing by baffles and packing in a flotation column. Their study revealed that the liquid back-mixing in an open flotation column could be alleviated by using baffles and packing. In addition, the effects of different operating conditions such as uneven aeration, superficial gas velocity, and bubble size on liquid flow patterns in the column were also studied. In this regard, a decrease in bubble size was reported to cause an increase in the upward axial liquid velocity, The Journal of the Southern African Institute of Mining and Metallurgy

Investigation of the mixing characteristics of industrial flotation columns resulting in a possible increase in liquid back-mixing in the column. However, liquid RTD simulations in order to quantify the effect of the various geometrical and operational conditions on the actual mixing parameters in the column were not conducted. Contrary to Xia, Peng, and Wolfe, Chakraborty, Guha, and Banerjee (2009) applied an Eulerian-Eulerian approach with k-e turbulence model to investigate the influence of geometrical and operational parameters on the hydrodynamics of a tapered column. Their study found that increasing the air flow rate resulted in an increase in gas holdup and complexity in the bubble plume structure. In addition, increasing the column height-todiameter ratio was also observed to bring about a complex flow pattern with multiple staggered vortices in the column. A low height-to-diameter ratio was therefore recommended as one of the required conditions for obtaining good separation in a column flotation cell. Simulations on the scale of bubbles and particles are also reported in literature. For example, Nadeem, Ahmed, and Chughta (2006) and Koh and Schwarz (2009) presented CFD-based models to predict the flotation sub-processes in column flotation and Jameson cells. As regards columns they applied a EulerianLagrangian method to predict the bubble-particle collision rate in a small rectangular shape domain with a stationary bubble positioned at the centre. For Jameson cells, however, they applied a Eulerian-Eulerian framework to account for the rate of collision, attachment, and detachment of bubbles and particles. Rehman et al. (2011) investigated the effect of various perforated baffle designs on air holdup and mixing in a flotation/ bubble column using CFD. The Eulerian-Eulerian multiphase model was utilized in the simulations together with the standard k-e turbulence model. To reduce the computational cost, simulations were performed only for one quarter of the column geometry using a rotational periodic boundary condition to periodically repeat the results for the entire column. The trays (baffles) were observed to significantly increase the overall air holdup compared to the column without baffles. Most of the CFD models in the literature have assumed a constant bubble diameter. However; Sarhan, Naser, and Brooks (2016) incorporated a population balance equation (PBE) into a two-fluid model to predict the number density of different bubble size classes in a flotation column. This study found that the presence of solids reduced the gas holdup in the flotation cell (column). The authors also reported that the size of gas bubbles decreased with increasing superficial gas velocity, causing the gas holdup to increase. Their results further showed that the Sauter mean bubble diameter decreased with increasing solids concentration. More recently, Mwandawande et al. (2019) investigated the application of CFD for predicting not only the average gas holdup, but also the axial gas holdup variation in flotation columns. They applied a Eulerian-Eulerian multiphase model and the realizable k-e turbulence formulation to simulate a cylindrical pilot column that was used in the work of Gomez et al. (1991) and Gomez et al. (1995) on axial gas holdup distribution. Their work further investigated axial bubble velocity profiles to establish possible relationship with the axial gas holdup profile along the column height. The predicted average gas holdup values were found to be in good agreement with experimental data. On the other hand, the axial gas holdup prediction was generally good for the middle and top parts of the column, while the gas holdup was over-predicted for the bottom part of the column. The Journal of the Southern African Institute of Mining and Metallurgy

In another recent study, Mwandawande et al. (2019b) investigated the maximum superficial gas velocity for transition from bubbly flow to churn-turbulent flow in flotation columns using CFD. Their research employed radial gas holdup profiles and gas holdup versus time graphs to identify the loss of bubbly flow in a pilot-scale column flotation cell. The bubbly flow regime was found to be characterized by saddle-shaped profiles with three distinct peaks, or saddle-shaped profiles with two near-wall peaks and a central minimum point, or flat profiles with intermediate features between saddle and parabolic gas holdup profiles. On the other hand, parabolic profiles were observed beyond bubbly flow conditions. For the gas holdup versus time graphs, churn-turbulent flow conditions were characterized by wide variations in the gas holdup versus time graph while gas holdup is almost constant under bubbly flow conditions. From the literature reviewed above, it is clear that CFD modelling has emerged as a vital tool which has been successfully applied to investigate various aspects of the column flotation process. However, there still exists a clear gap in the current literature regarding the mixing characteristics of industrial flotation columns. For example Deng, Mehta, and Warren (1996) presumed that liquid recirculation is the main reason for mixing while neglecting the effects of turbulence in the column. This assumption oversimplifies the actual physics causing the mixing phenomenon. Furthermore, the actual mixing was not simulated in terms of RTDs. The subsequent work of Xia, Peng, and Wolfe (2006) also did not account for the RTD of the liquid within the column. The previous CFD models encountered in the literature are all limited to only two-phase systems (gas-liquid) in which mineral particles are not considered. The mixing characteristics of solids in column flotation have therefore not been studied in the previous CFD models. It is also important to note that the previous CFD research pertaining to mixing in column flotation was conducted on laboratory-scale columns – simulations concerning industrial columns have not yet been reported. The main contribution of the study presented in this paper is therefore to investigate the mixing characteristics of industrial flotation columns using CFD. The mixing characteristics of the flotation column are studied with particular focus on solids mixing and the effects of particle and bubble sizes on the liquid axial dispersion. In this regard, CFD modelling was applied to simulate the 0.91 m diameter cylindrical column from the work of Yianatos and Bergh (1992). The data from these authors is therefore used to validate the present modelling approach. The work presented in this paper involves numerical simulations of RTDs of both the liquid and solid phases in the industrial column. The simulated RTDs are then used to determine the mixing parameters, i.e., the mean residence time and the vessel dispersion number. Both the mean residence time and the vessel dispersion number are useful parameters in the design and scale-up equations for column flotation. In addition, the simulated axial velocity profiles of the solids and liquid phases are compared in order to clarify the relationship between the solids and liquid dispersion characteristics.

Theory The one-dimensional (axial) plug flow dispersion model is applicable to describe the axial mixing process in the collection zone of the flotation column (Finch and Dobby, 1990). In this case, the degree of mixing is quantified by the axial dispersion VOLUME 122

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Investigation of the mixing characteristics of industrial flotation columns coefficient D (units of length2/time) or the dimensionless vessel dispersion number (Nd). The higher the vessel dispersion number, the higher the degree of mixing. The vessel dispersion number is given by: [1] where u is either the liquid interstitial velocity or the particle velocity and H is the height of the collection zone. The axial dispersion coefficient (D) or the vessel dispersion number (Nd) can be calculated from RTD data using two parameters: the mean residence time (τ) and the variance (σ2). The variance is a measure of the spread of the RTD curve, which represents the degree of mixing within the vessel. It has units of (time)2. From the RTD data, the mean residence time (τ) and variance (σ2) are calculated from the following equations: [2]

[3] For a set of discrete data-points, the variance is expressed as:

is then calculated based on the condition that all the volume fractions sum to unity. In the present study, the three-phase flow in the industrial column is modelled considering water as the continuous (or primary) phase while air bubbles and solid particles are treated as dispersed (or secondary phases). In terms of momentum exchange forces between the phases, the drag force between the continuous phase and the dispersed phases is the only significant interfacial force in the multiphase flow. Minor forces such as lift and virtual mass are therefore not included in the model. For the solid phase momentum equations additional terms derived from the kinetic theory of granular flows are also included to account for the behaviour of solid particles in the multiphase flow. These terms account for particle-particle collisions and the kinetic energy contained in the random motion of the particles. The kinetic theory of granular flows is based on the assumption that the behaviour of solid particles in multiphase flow is similar to the motion of molecules in a gas. Classical results from the kinetic theory of gases are therefore employed to formulate transport equations for the solid phase in the granular flow.

Governing equations The general forms of mass and momentum conservation equations for each phase are given in Equations [6] and [7], where q represents the qth phase:

[4]

[6]

D The vessel dispersion number ( uH ) is then calculated from the mean residence time and the variance from the following equation for closed vessel boundary conditions (Levenspiel, 1972):

[7]

[5]

CFD methodology

Multiphase model The CFD simulations in this study are conducted using the Ansys Fluent 14.5 software package in which the finite volume method is applied to convert a system of partial differential equations into algebraic equations that can be solved numerically. In the finite volume method, the computational domain is first discretized into a finite number of control volumes (cells) where general transport equations for mass, momentum, and energy are solved numerically to obtain the solution field. The Eulerian-Eulerian (E-E) multiphase model, in which the continuous (primary) phase and the dispersed (secondary) phases are modelled in an Eulerian frame of reference as interpenetrating continua, is used in this research to simulate the three-phase (gas-liquid-solids) flow prevailing in industrial flotation columns. In the E-E model, the conservation equations for mass and momentum are solved separately for all three phases in the flow, while interactions between the phases areg accounted for with the interphase force exchange term (i.e., R pq) as well as other forces such as the lift force and virtual mass force included in the momentum equations (Equation [7]). On the other hand, the volume fraction of the secondary phases is calculated from the continuity (or mass conservation) equation by dividing all the terms with the volume-averaged density of the respective phase in the solution domain. The volume fraction of the primary phase 248

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In these equations, áq is the volume fraction of phase q, (uq) . is the velocity, ρq is the density, m pq represents mass transfer . from phase p to phase q, and m pq is the mass transfer from phase q to phase p. However, mass transfer between phases was not considered in the present study. On the other hand, the source term Sq was only specified for the gas phase to represent the bubbles entering at the bottom of the column and leaving at the top. g The term R pq in the momentum equation (Equation [7]) is the interaction force between the phases, which in Ansys Fluent represents the drag force, while the other forces such as the g g external body force (F q), the lift force (F lift,q ), and the virtual mass g force (F VM,q) are added separately if required in the simulations, as shown in Equation [7]. In the present study, the external g body force (F q) is included in the momentum equation for the gas phase as a momentum source term associated with the mass source terms representing the entry of the air bubbles at the bottom of the column. However, the lift force and virtual mass force are in most cases insignificant compared to the drag force. The present work therefore considers only the drag force in the simulations gand the lift and virtual mass forces are left out. The drag force (R pq) is given by: [8] The Journal of the Southern African Institute of Mining and Metallurgy

Investigation of the mixing characteristics of industrial flotation columns where Kpq (=Kqp) is the momentum exchange coefficient, which is g described later. The gravity force is included as αρg and p is the = pressure which is shared by all phases while τq is the stress tensor for phase q given by:

closure models are required for the interphase force R pq representing the drag between the primary phase and the secondary phase. The exchange coefficient Kpq for bubbly flows can be written as: [11]

[9] where μeff,q is the effective viscosity, which is the sum of the molecular viscosity (μk) and the turbulent viscosity (mt,q), λq is = the bulk viscosity of phase q, and I is the identity matrix. The molecular viscosity is a single-phase material property, while the turbulent viscosity depends on the characteristics of the flow. In order to determine the turbulent viscosity a turbulence model is employed in the simulations as described in the following section. For the solid phase the governing equations are modified with derivations from the kinetic theory of granular flows to model fluid-solid multiphase systems as mentioned earlier. In Ansys Fluent this is achieved by activating the Eulerian-granular model. In this case, additional terms are incorporated in the solid phase momentum equations to account for the effects of particle collisions based on analogies between the random particle motions arising from interparticle collisions and the thermal motion of gases. The subsequent equations and detailed derivations are available in the Ansys Fluent Theory Guide (Ansys Inc, 2013) and will not be presented here for brevity purposes.

Turbulence model In the present study, the turbulent viscosity in the continuous phase (water) was calculated using the realizable k-e turbulence model as follows:

The drag force is therefore given by: [12] where CD is the is the drag coefficient between the liquid phase (phase q) and the air bubbles (phase p), dp is the bubble diameter, and g up — g uq is the slip velocity. Four different average bubble sizes, including 0.8, 1, 1.5, and 2 mm, were used in the simulations. However, validation of the model results against experimental data was done using the simulations conducted with 0.8 mm bubble size only since this is the typical size of bubbles in industrial flotation columns. There are a number of empirical correlations that can be used to calculate the drag coefficient (CD). In the present study, the drag coefficient is calculated using the universal drag laws (Kolev, 2005). The universal drag coefficient is in this case defined in different ways, depending on whether the prevailing regime is in the viscous regime category, the distorted bubble regime, or the strongly deformed capped bubbles regime. At the moderate superficial gas velocities simulated in the present study, the viscous regime conditions apply and the drag coefficient is calculated from the following equation:

[10]

[13]

where the turbulent kinetic energy k and the turbulent dissipation rate e are computed from their respective transport equations while the variable Cμ is calculated as described by Shih (1997). The present study utilizes the dispersed k-e turbulence model option which is available in Ansys Fluent for simulating multiphase systems where there is clearly one primary continuous phase with dispersed dilute secondary phases. In this case, turbulence in the continuous or primary phase is considered to be the dominant process in the flow. Transport equations for turbulence (k and e) are therefore solved for the continuous phase only, while turbulence quantities for the secondary phases are calculated using Tchen theory, in which the particle or bubble fluctuations are assumed to be driven by the surrounding continuous phase. The dispersed phase properties are thus obtained from continuous phase properties using algebraic relationships as elaborated in the Ansys Fluent Theory Guide (Ansys Inc, 2013). In addition, the dispersed k-e turbulence model accounts for turbulence modification by the secondary phases through additional terms that incorporate interphase turbulent momentum transfer. The turbulence quantities near the column wall were obtained using algebraic correlations (standard wall functions) to avoid the computational effort associated with alternative methods such as mesh refinement of the way region.

The drag coefficient is therefore expressed as a function of the bubble Reynolds number (Re) which is defined as: [14] where μe is the effective viscosity of the primary phase (i.e. water) modified to account for the presence of the secondary phase (air bubbles in this case).

Liquid-solid drag The drag force between the liquid and the solid particles is calculated using the Wen and Yu (1966) drag model. In this case, the fluid-solid exchange coefficient is given by: [15] The drag coefficient is then calculated as: [16] where ds is the diameter of the solid particles and Res is the relative Reynolds number given by [17]

Interphase momentum transfer and drag coefficient Gas-liquid drag In order to solve the governing equations for the E-E model, The Journal of the Southern African Institute of Mining and Metallurgy

The Wen and Yu model is suitable for dilute systems similar to the conditions simulated in the present study. VOLUME 122

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Investigation of the mixing characteristics of industrial flotation columns Model geometry, mesh, and boundary conditions

[18]

Computational domain and mesh Flotation columns are divisible into two distinct zones (refer to Figure 1) – the collection zone and the cleaning zone (or froth zone). It is therefore important to define the computational domain being simulated in the flotation column CFD model. Due to the differences in flow patterns and turbulence characteristics between the collection zone and the froth zone, it still remains a challenge to formulate CFD simulations that combine the two zones. The present research therefore focuses on the collection zone only. Since only the collection zone is modelled, the model geometry is simply a cylindrical vessel of height equal to the collection zone height and radial dimensions similar to the simulated industrial column. A three-dimensional mesh comprising mainly hexahedral elements is generated over the cylindrical column geometry and used in the subsequent CFD simulations. As a preliminary stage for the simulations, a grid independency study is performed in which different flow variables are compared at different mesh sizes in order to check the dependency of the solution on the grid size. The details of the mesh sizes used in the grid independency study are reported Table I. The results are presented in Figure 2, where the water axial velocity profiles are compared as a function of cell numbers. As seen, the choice of element sizes initially yields unrealistic velocity profiles, while after mesh 3 (2.5 cm cell size with 502 098 cells) the velocity profiles show only small variations with regard to the cell size. However, the computational effort required to perform the simulations beyond mesh 3 becomes unreasonably high. The mesh comprising 2.5 cm mesh with 502 098 elements (or cells) is therefore selected for the subsequent simulations in the column, albeit as only a reasonable trade-off between accuracy and computational effort required for the simulations.

Modelling of the spargers The sparging of gas into the column was modelled using mass source terms introduced in the gas-phase continuity equations for the computational cells at the bottom of the column. Corresponding momentum source terms are also included in the gas-phase momentum equations. The gas phase is assumed to enter the column as air bubbles. In industrial flotation columns the spargers distribute bubbles uniformly over the entire column cross-section (Harach, Wates, and Redfearn, 1990). The air bubbles were therefore introduced over the entire column cross-section in the CFD model without including the physical spargers in the model geometry. The mass source terms and their associated momentum in the upward direction are calculated from the superficial gas velocities as follows:

[19] where ρair is the density of air (1.225 kg/m3), Ac is the column cross-sectional area (m2), Jg is the superficial gas (air) velocity (m/s), and V is the volume of the cell zone where the source terms are applied. Corresponding sink terms are also applied at the top of the column to simulate the exit of the air bubbles from the collection zone.

Boundary conditions The top of the collection zone of the column was modelled as a velocity inlet boundary for the liquid and solid phases. Inlet velocity magnitudes normal to the boundary are therefore prescribed together with turbulence parameters to enforce a Dirichlet-type boundary condition at the face. For the liquid phase, the inlet velocity was specified as equal to superficial liquid velocity (Jl). Since the computational domain being considered is the collection zone of the column, the superficial liquid velocity must include the feed rate plus the bias water resulting from wash water addition. The superficial liquid velocity is therefore equal to the superficial tailing rate (Jt). Turbulence parameters at the inlet boundary were prescribed by setting the turbulence intensity equal to 5%. This value is recommended for fully developed turbulent flow upstream of the boundary face (Ansys Inc, 2013). Fully developed flow conditions were therefore assumed at the inlet boundary. The solid particles are assumed to be transported into the column at the same velocity as the surrounding liquid phase. Similar superficial velocity values were therefore used to describe the solids boundary conditions. In addition, the phase volume fractions of the solids in the liquid were specified at the inlet boundaries. The bottom part of the column was also modelled as a velocity inlet boundary for both the liquid and solid phases. The exit velocity of the phases at the bottom of the column was then set equal to the superficial liquid velocity but with a negative sign. At the column wall, no slip boundary conditions were applied for all the three phases (liquid, solids, and air bubbles). The no-slip condition prescribes a tangential velocity equal to the velocity of the wall, which in the present case is zero. The velocities normal to the boundary are also set to zero. The simulation domain and boundary conditions of the column are illustrated in Figure 3.

Table I

esh sizes considered for the grid independency study for M the cylindrical industrial column ID

Element size (cm)

Number of elements

5 3.75 2.5 1.875

70 902 151 985 502 098 1 152 925

Mesh 1 Mesh 2 Mesh 3 Mesh 4 250

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Figure 2—Grid independency study results for the cylindrical industrial column The Journal of the Southern African Institute of Mining and Metallurgy

Investigation of the mixing characteristics of industrial flotation columns species equation is then solved as an unsteady simulation using the computed liquid flow solution.

Tracer injection and monitoring

Figure 3—Simulation domain and boundary conditions for the flotation column

The tracer is injected into the column using the pulse method. The tracer mass fraction at the column inlet is set to unity for time durations similar to the tracer injection time in the experimental column. In this case, the total injection time is 1 second for the industrial column, which was the value used in the work of Yianatos and Bergh (1992). After that, the mass fraction of the tracer is again set to zero and the simulations continued up to about 3600 seconds flow time. The mass fraction of the tracer is subsequently recorded at the outlet every 10 seconds and used to obtain the RTD curves from which the mean residence time (τ) and the vessel dispersion number (Nd) are calculated.

Particle age distribution and mean residence time simulation There are two main methods for simulating RTD using CFD. The first method involves Lagrangian particle tracking, in which a large number of discrete particles representing the tracer fluid are followed to obtain their exit time statistics. The RTD is then obtained as a histogram of time at the outlet of the simulated equipment. However, this method requires a large number of particles to obtain proper statistics. The computational cost of the simulations will therefore increase significantly. The second method considers the tracer fluid as a continuum by solving an additional transport equation for the concentration or mass fraction of the tracer species. Ansys Fluent treats the tracer as a passive scalar convecting and diffusing into the primary phase. The tracer’s concentration is then monitored at the outlet of the equipment to provide the RTD response curve. This method has a relatively lower computational cost and was therefore selected to simulate the liquid RTD in the present study. The species transport equation is a convection-diffusion equation whose solution predicts the local mass fraction of the tracer species (Y) in the liquid phase of the three-phase (gas-liquidsolid) mixture. For an inert tracer species, the equation can be presented as follows:

The particle age distribution and mean residence time are modelled using a transport equation that computes the age (as) of the particles in the column. The particle age is defined as the time t that has elapsed since the particle’s entry into the column such that as = t. This method has been applied in studies of mixing in different reactors in the chemical engineering field (Baléo and Le Cloirec, 2000; Baléo, Humeau, and Le Cloirec, 2001; Ghirelli and Leckner, 2004; Liu and Tilton, 2010; Simcik et al., 2012). However, this study is the first one to introduce particle age transport equations in column flotation modelling. The introduction of the particle age equation offers an attractive method for predicting the solids mean residence time at lower computational cost compared with other methods that are based on Lagrangian particle tracking. In addition, the numerical solution of the particle age equations gives the distribution of particle (solids) residence time in the column, which can be used to understand the effect of liquid recirculation on the mixing behaviour of solids in column flotation. In this method, the particle age as (or local residence time) is considered as a scalar property that is being transported by the particles. The rate of change of the particles age is therefore represented by the substantial (or convective) derivative as follows:

[20]

[22]

Liquid RTD simulation

where αl is the volume fraction of the liquid phase in the mixture, ρl is the density of the liquid, Y is the mass fraction of the tracer g species in the liquid phase, and J is the diffusion flux of the tracer species due to molecular and turbulent diffusion. The diffusion g flux (J ) is obtained from the following equation: [21] where Dm is the molecular diffusion coefficient for tracer species, Sct is the turbulent Schmidt number (μρDt t where μt is the turbulent viscosity), and Dt is the turbulent diffusivity. In this study the molecular diffusion is set to 2×10-9m2/s and Sct is 0.7 (the default value in Ansys Fluent). The properties of the tracer and the background liquid (water) are assumed to be identical. The concentration of the tracer will therefore not have any significant effect on the liquid flow field. In this case, the liquid flow equations (e.g. momentum and turbulence equations) and species equations are solved sequentially starting with the liquid flow solution. The tracer The Journal of the Southern African Institute of Mining and Metallurgy

which is the advection equation for the scalar variable as. For the solid particles in the multiphase flow, the transport equation for the age of the particles (as) can be presented as follows: [23] where αs is the volume fraction of the solid phase (particles) while ρs is the density of the particles. This equation is introduced into the CFD model of the flotation column as a user-defined scalar (UDS) equation which is solved using the already computed velocity field of the solid phase. As for the boundary conditions, the particle age is set to zero at the inlet while a zero flux condition is specified for the particle age at the walls. On the other hand, the particle age at the outlet is extrapolated from the interior solution. The result is the spatial distribution of particle age in the column, which can be used to describe the mixing characteristics of the solid phase. The mean residence time of the solids (particles) is then obtained as the mass-weighted or areaweighted average age of the particles at the outlet of the column. VOLUME 122

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Investigation of the mixing characteristics of industrial flotation columns Results and discussion Three-phase CFD simulations were conducted to model the 0.91 m diameter cylindrical column that was used in the work of Yianatos and Bergh (1992). The operating conditions of the column are presented in Table II. Four different average bubble sizes, including 0.8, 1, 1.5, and 2 mm, were used in the simulations. The simulated RTDs obtained using the different bubble sizes were then compared in order to investigate the effect of bubble size on axial mixing in the column. For the validation of the model, results obtained from the simulations conducted with the 0.8 mm bubble size were compared with the experimental data. The 0.8 mm bubble size was used in the validation because that is the typical size of bubbles used in industrial flotation columns. To simplify the CFD model and reduce the overall computational time, the bubble size is assumed to remain constant throughout the column. In reality, however, the size of the bubble will vary throughout its upward trajectory in the column because of the decrease in hydrostatic pressure, which will cause the bubbles to expand. This expansion of bubbles is the reason for the increase in gas holdup observed along the height of industrial flotation columns. For the simulation of particles, the CFD simulations in this study were conducted using average particle sizes that fall within the range of sizes studied in the corresponding experimental work. Separate simulations were performed for each particle size in order to simplify the model and minimize the computational cost of the simulations. Possible effects of particle size distribution on the hydrodynamics of the column were therefore not captured in this study. The results obtained from the CFD simulations are presented below.

CFD simulations were performed with one particle size at a time in order to simplify the model further.

Liquid residence time distribution (RTD) The simulated liquid RTD is compared with the measured one in Figure 4. Since the particle size in the industrial column was predominantly less than 25 µm, the CFD simulation performed with 19 µm particle size is the one that is compared with the measured liquid RTD data. It can be seen that the CFD results are in good agreement with the measured liquid RTD. The mixing parameters (liquid mean residence time and vessel dispersion number) calculated from the CFD-simulated liquid RTD, together with the predicted air holdup, is compared with the values reported by Yianatos and Bergh (1992) in Table III. It can be seen that the simulated mixing parameters are in reasonable agreement with the literature data.

Effect of particle size and bubble size on liquid axial mixing The effect of particle size on the liquid vessel dispersion number was investigated using liquid RTDs obtained from CFD simulations performed with different particle sizes. The results are shown in Figure 5 for simulations conducted with two different Table II

Geometrical and operational conditions of the column Geometrical parameters

Diameter Collection zone height

0.91 m 10 m

Operational parameters

CFD simulation results CFD simulations were conducted to model the cylindrical industrial flotation column that was used in the work of Yianatos and Bergh (1992). Their work involved measurement of both solids and liquid RTDs in the 0.91 m diameter column using radioactive tracer techniques. For the solids, RTDs were measured for three size classes; fine (–39 µm), medium (–75+38 µm), and coarse (–150+75 µm). However, it is not the aim of the present research to simulate the entire particle size distribution in the column. The present study therefore uses three average particle sizes to represent each of the three size classes present in the column, namely; 19, 56.5, and 112.5 µm. In addition, the subsequent

Water density (kg/m3) Water viscosity (kg/m-s) Superficial liquid velocity (cm/s) Air density (kg/m3) Air viscosity (kg/m-s) Air bubble diameter (mm) Superficial gas velocity (cm/s) Gas holdup (%) Solid density (g/cm3) Feed wt% solid Solid particle (µm)

998.2 0.001 0.92 1.225 1.789×10-5 0.8, 1, 1.5, 2 1.8 18 3 16.2 19, 56.5, 112.5

Figure 4 —Simulated liquid (water) RTD compared with the experimental data of Yianatos and Bergh (1992) 252

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Investigation of the mixing characteristics of industrial flotation columns Table III

Comparison of CFD predicted (simulated) mixing parameters with measured data (Yianatos and Bergh, 1992) Parameter

CFD prediction

Experimental data

15.5 0.561 0.488 17.6

14.3 0.515 0.41 18

Liquid mean residence time in minutes (τl) Relative variance (σθ2) Vessel dispersion number (Nd) Gas holdup, eg (%)

Figure 5—Effect of particle size on the liquid vessel dispersion number. The results are from CFD simulations performed with two different bubble sizes, namely 0.8 and 1 mm

bubble sizes; 0.8 and 1 mm. It can be seen that increasing the particle size results in a decrease in the liquid vessel dispersion number. On the other hand, previous researchers have reported that the liquid vessel dispersion number (i.e., the liquid mixing intensity inside the column) decreased with increasing solids percentage (wt%) in the feed (Finch and Dobby, 1991; Laplante, Yianatos, and Finch, 1988; Xu, 1990). Subsequently, the feed solids percentage has been included in the empirical correlations that are used for estimating the vessel dispersion number for predicting the recovery in column scale up procedures. However, the effect of the particle size on the liquid vessel dispersion number observed in the present research suggests that particle size should also be considered in the correlations for estimating the vessel dispersion number in order to obtain correct predictions of the mineral recovery. Figure 5 also shows that an increase in the bubble diameter reduces the liquid dispersion in the column. A similar result was reported by Xia, Peng, and Wolfe (2006), who observed that a reduction in bubble size resulted in a rise in the axial liquid velocity. The increase in liquid back-mixing can be attributed to the increase in gas holdup resulting from the reduction in bubble size. As the bubble size is reduced, the number of bubbles increases while the bubble rise velocity reduces, causing an increase in bubble residence time. The subsequent increase in gas holdup results in higher axial liquid velocity which will cause a stronger back-mixing effect (Xia, Peng, and Wolfe, 2006; Laplante, Yianatos, and Finch, 1988).

Particle (solids) mixing characteristics Solving the transport equation of the particle age in the column The Journal of the Southern African Institute of Mining and Metallurgy

gives the spatial distribution of the age of the particles in the collection zone of the column. The contour plot of the spatial age distribution of 112.5 µm particles at the vertical mid-plane position in the column is presented in Figure 6 for illustration. The simulated particle age seems to increase from the walls towards the centre of the column. This is a result of the liquid circulation pattern in which the liquid (water) rises in the centre of the column and descends near the walls. The effect of liquid circulation on particle age distribution in the column can be understood by examining the axial velocity profile of water presented in Figure 7. The velocity profile was obtained at the mid-height position in the column. It can be seen that the velocity is positive in the centre and negative near the walls of the column. The water is therefore rising in the centre and descending at the walls. The rising water carries with it ‘older’ particles that had reached the bottom part of the column while the descending water carries with it the ‘younger’ particles entering the column at the top. The particle age distribution in the column is therefore governed by the established liquid circulation prevailing in the column. These observations have important implications for the metallurgical performance of flotation columns because the back-mixing effect resulting from liquid circulation in the column might cause short-circuiting of feed to gangue flow, as earlier suggested by Xia, Peng, and Wolfe (2006). Gangue might also flow back to feed or concentrate flow and thus make separation less selective. From Figure 6 it can be seen that the maximum particle age (red colour) is 637 seconds, i.e., about 10.6 minutes. However, the ‘oldest’ particles in the column are not only found at the outlet but also up to the middle height along the column. This can also VOLUME 122

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Investigation of the mixing characteristics of industrial flotation columns [24]

Figure 6—Contours of simulated particle age distribution in the column; particle size = 112.5 µm, bubble size = 1 mm

be attributed to the liquid circulation pattern established in the column, in which the water rises in the centre of the column and descends near the column walls. The ‘older’ particles that reach the bottom are therefore lifted with the rising flow up to the middle part of the column. To verify this, the water velocity vectors were compared with the particle age contours in the column, as shown in Figure 8. The figure clearly demonstrates that the greatest particle ages (red contours) indeed coincide with two large liquid circulation cells occupying the bottom half of the column. This confirms the influence of the liquid recirculation on the particle age distribution inside the column. The particle mean residence time can also be obtained from the simulated particle age distribution and is given by the areaweighted average or mass-weighted average age of the particles at the outlet of the column. In Figure 9, the predicted particle mean residence times are compared with the experimental values reported by Yianatos and Bergh (1992). The mean absolute relative error (MARE) between the CFD predictions and the experimental data was calculated from the following equation:

With MARE equal to 7% the CFD results compared well with the experimental data. The simulation results in Figure 9 also show that the solids (particle) mean residence time decreases with increasing particle size. This can be explained by the higher settling or terminal velocity of the larger solid particle in the presence of buoyancy. As the settling velocity depends directly on the diameter of particles, the solid particles of larger diameter experience faster downward motion toward the bottom of the column. Moreover, they have a higher probability of being caught in the downward liquid flow leading to the bottom of the tank. Thus, when solving the particle age equation for them they are less likely to stay longer within the tank. This is also evident in the corresponding experimental data. In comparison with the simulated liquid mean residence time of 15.5 minutes (refer to Table III), the predicted mean residence time of 9.6 minutes for the largest particle size (112.5 µm) was at least 60% of the liquid residence time. On the other hand, the smallest particle size (19 µm) had mean residence time (14.35 minutes) similar to the liquid one.

Figure 8—Comparison of water velocity vectors with particle age contours in the column

Figure 7—Axial velocity profile of water showing the circulation pattern with upward flow at the centre and downward flow near the column walls 254

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Investigation of the mixing characteristics of industrial flotation columns

Figure 9—Comparison of CFD predictions (simulation) of particle mean residence time and measurements of Yianatos and Bergh (1992)

Figure 10—Comparison of liquid (water) and solids (56.5 µm) axial velocity profiles. Bubble size was 1 mm

Equivalence of liquid and solids axial dispersion coefficients Some previous researchers (Dobby and Finch, 1985; Yianatos and Bergh, 1992; Yianatos et al., 2005) have studied the relationship between the solids and liquid dispersion in column flotation and concluded that the solids vessel dispersion number (or axial dispersion coefficient) and the liquid one were equal. The solids mixing characteristics can therefore be estimated from the liquid axial dispersion coefficient for column scale-up and design purposes. However, the equivalence of the solids and liquid dispersion has been questioned by other authors citing various reasons (Goodall and O'Connor, 1991; Ityokumbul, 1992; Mills and O'Connor, 1990). To clarify the relationship between the liquid and solids dispersion characteristics, the simulated liquid and solids (56.5 and 112.5 µm) axial velocity profiles at mid-height location are compared in Figure 10 and Figure 11. It can be seen that the solids axial velocities are similar to the liquid ones, even for the 112.5 µm particle size. The assumption of equal solids and liquid dispersion would therefore be applicable for normal operating conditions in an industrial flotation column. Some researchers who have challenged the assumption of equal liquid and solids dispersion coefficients have argued that the solids content (3 wt%) used in the research that led to this conclusion was too small to highlight any differences between the two phases (Goodall and O'Connor, 1991). On the other hand, the solids content (16.2 wt% solids) in the present simulations was much higher than the 3 wt% referred to by Goodall and O'Connor The Journal of the Southern African Institute of Mining and Metallurgy

(1991). It therefore seems reasonable for column flotation design and scale-up purposes to assume the equality of the liquid and solids axial dispersion coefficients.

Conclusion In this research, the mixing characteristics of the liquid and solid phases in industrial flotation columns have been studied using computational fluid dynamics (CFD). The CFD results agreed favourably with the experimental data available from the literature. The results obtained showed that particle residence time decreases with increasing particle size. The residence time of the coarser particles (112.5 µm) was found to be at least 60% of that for the liquid, while the finer particles (19 µm) had a residence time similar to that of the liquid. The research further investigated the effect of bubble and particle sizes on the mixing characteristics of flotation columns. An increase in axial mixing in the column was observed when the bubble size was decreased. On the other hand, increasing particle size resulted in a decrease in the axial dispersion coefficient. Another notable finding was the effect of the liquid recirculation on particle residence time in the column. It was established that the liquid flow pattern determines particle age distribution inside the column. Particle residence time distribution is therefore affected by liquid recirculation in the column. The equivalence of the liquid and solids axial dispersion coefficients (or vessel dispersion numbers) was also investigated VOLUME 122

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Figure 11—Comparison of liquid (water) and solids (112.5 µm) axial velocity profiles. Bubble size was 1 mm

by comparing the water and the solids axial velocity profiles. The axial velocities of the two phases were found to be similar. It is therefore reasonable to assume equality of the solids and liquid dispersion coefficients for column design and scale-up purposes. One of the limitations of this work is that the CFD simulations were performed using one particle size at a time. Any possible effects of particle size distribution on the hydrodynamics of the column are therefore not captured in the simulations. Future studies that incorporate population balance models or other means of incorporating particle size distribution are therefore recommended in order to further understand the mixing behaviour of solids in industrial flotation columns.

Acknowledgements The authors would like to acknowledge the Centre for International Cooperation at VU University Amsterdam (CISVU) and the Copperbelt University (CBU) for providing the scholarship and subsequent funding for this research through the Nuffic-HEART Project. We would also like to acknowledge the Process Engineering Department and Rhasatsha High Performance Computing (HPC) cluster at Stellenbosch University.

Nomenclature D C CD g Rpq Kpq

Axial dispersion coefficient, length2/time Concentration Drag coefficient Drag force between phases p and q, N/m3 Exchange coefficient in the momentum equation

Fq External body force for phase q in the momentum equation (N/m3) g g Gravitational acceleration, 9.81 m/s2 H Height of the collection zone, m g Flift,q Lift force in the momentum equation ((N/m3) u Liquid interstitial velocity or particle velocity, m/s Y Mass fraction of tracer species in the species transport equation Sq Mass source term for phase q, kg/m3s as Particle age, s g us Particle velocity vector, m/s 256

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dp Particle/bubble diameter, m Re Reynolds number (dimensionless) ∆t Time interval, s t Time, s k Turbulent kinetic energy, m2/s2 g uq Velocity of phase q, m/s Nd Vessel dispersion number (dimensionless) g FVM,q Virtual mass force in the momentum equation (N/m3) Greek letters ρ Density, kg/m3 εg Gas (air) holdup τ Mean residence time σθ2 Relative variance =τq Stress-strain tensor for phase q å Turbulent dissipation rate, m2/s3 μt Turbulent viscosity, kg/m-s 2 s Variance μ Viscosity, kg/m-s a Volume fraction Subscripts G Gas phase l Liquid phase P Particle/bubble q Phase s Solid phase

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Ityokumbul, M.T., Kosaric, N., and Bulani, W. 1988. Parameter estimation with simplified boundary conditions. Chemical Engineering Science, vol. 43, no. 9. pp. 2457-2462. Koh, P.T., Manickam, M., and Schwarz, M. 2000. CDF simulation of bubbleparticle collisions in mineral flotation cells. Minerals Engineering, vol. 13, no. 14-15. pp. 1455-1463. Koh, P. and Schwarz, M. 2006. CFD modelling of bubble–particle attachments in flotation cells. Minerals Engineering, vol. 19. pp. 619-626. Koh, P. and Schwarz, M. 2009. CFD models of Microcel and Jameson flotation cells. Proceedings of the 7th International Conference on CFD in the Minerals and Process Industries. [CD-ROM] CSIRO, Melbourne: Kolev, N.I. 2005. Multiphase Flow Dynamics 2: Thermal and Mechanical Interactions. (2nd edn. Vol. 2. Springer, Berlin. Laplante, A.R., Yianatos, J.B., and Finch, J.A. 1988. On the mixing characteristics of the collection zone in flotation columns. Column Flotation '88. SME Annual Meeting, (pp. 69-80). Phoenix, AZ. I Sastry K.V. (ed.), pp. 69-80.

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Yianatos, J.B. and Bergh, L.G. 1992. RTD studies in an industrial flotation column: Use of the radioactive tracer technique. International Journal of Mineral Processing, vol. 36, no. 1. pp. 81-91. Yianatos, J.B., Bergh, L.G., Díaz, F., and Rodríguez, J. 2005. Mixing characteristics of industrial flotation equipment. Chemical Engineering Science, vol. 60, no. 8. pp. 2273-2282. u

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Study on the ideal location of a bottom drainage roadway by H. Chen1,2,3, F. An1,2,3, Z. Wang1, and X. Chen1

Affiliation:

S tate Key Laboratory Cultivation Base for Gas Geology and Gas Control, Henan Polytechnic University, China. 2 Henan Key Laboratory of Coal Green Conversion, Henan Polytechnic University, China. 3 Collaborative Innovation Center of Coal Safety Production of Henan Province, China. 1

Correspondence to: F. An

Email: anfenghua999@126.com

Dates:

Received: 8 Mar. 2021 Revised: 11 Jan. 2022 Accepted: 4 Apr. 2022 Published: May 2022

Synopsis The bottom drainage roadway plays a crucial role in preventing coal and gas outbursts by using underground gas drainage methods. Therefore, it is essential to select the ideal position of the bottom drainage roadway. In this paper use a combination of geological data and numerical simulation to study the ideal position of the bottom drainage roadway, we taking the gas drainage of the first workface of No. 3 coal seam in the Yuxi coal mine in China as an example. The geological study showed a limestone marker layer at an average vertical distance of 14 m from the first mining face. Using this marker layer, the bottom drainage roadway could be excavated without the risk of accidentally exposing the coal seam, and less crosscutting borehole drilling from the bottom drainage roadway would be required. Based on the needs of gas control, the layout of the bottom drainage roadway was selected as an external stagger type. Combined with the numerical simulation results, when located 20 m outside of the mining workface ‘footprint’ on the horizontal projection, the bottom drainage roadway was a sufficient distance from the stress concentration area during mining of workface 1301, which facilitated roadway maintenance. Furthermore, the length of the crosscutting boreholes is also relatively short, which reduces the amount and cost of drilling. The results of this study are expected to provide a reference for the selection of an ideal position of the bottom drainage roadway in field engineering.

Keywords gas drainage; bottom drainage roadway; geological analysis; numerical simulation.

How to cite:

Chen, H., An, F., Wang, Z., and Chen, X. 2022 Study on the ideal location of a bottom drainage roadway. Journal of the Southern African Institute of Mining and Metallurgy, vol. 122, no. 5, pp. 259-266 DOI ID: http://dx.doi.org/10.17159/24119717/1561/2022 ORCID: H. Chen https://orcid.org/0000-00017630-0200 F. An https://orcid.org/0000-00025902-6761 Z. Wang https://orcid.org/0000-00024615-4617 X. Chen https://orcid.org/0000-00030753-5609

Introduction China has one of the highest rates of serious coal and gas outbursts in the world (Chen et al., 2014, 2017; Lu et al., 2017, 2019). Years of coal mining have proven that pre-draining of coal gas effectively prevents coal and gas accidents (Cheng et al., 2010; Guo et al., 2012; Kong et al., 2014; Jiang et al., 2019; Wang et al., 2020). Drilling of boreholes for gas drainage also reduces the in-situ stress in the coal seam. After the gas is extracted, the gas energy storage in the coal body is reduced. Importantly, after the gas pressure decreases, the coal strength would be increased (Cheng et al., 2010). Therefore, by applying technology for pre-draining of coal gas, the main factors related to both coal and gas outbursts are weakened (Xue et al., 2014; Yu et al., 2015; Li et al., 2017; Yang et al., 2018). Among pre-draining methods, a combination of crosscutting boreholes and bedding boreholes extraction is commonly used, as shown in Figure 1 (Wang et al., 2014; Chen et al., 2017). With a combination of crosscutting borehole extraction and bedding borehole extraction, the choice of bottom drainage roadway location is crucial, directly affecting the reliability of outburst elimination measures and the amount of drilling required (Chen et al., 2018; Pan et al., 2019; Yang et al., 2019). When selecting the position of the bottom drainage roadway, the stability of the roadway must be considered. Yang et al. (2017), Bai et al. (2016), Zhang et al. (2013), Whittaker and Singh (1981), Zhang et al. (2015), Jiang et al. (2016), Islam and Shinjo (2009), Dejean (1976), and Xiao et al. (2014) analysed the effect of floor stress evolution, pillar size, and tectonic stress on roadway stability. Coggan et al. (2012) found that the thickness of the relatively weak mudstone in the roadway roof had a significant influence on the extent of failure. Wang et al. (2015) assessed the excavation damaged zone around roadways under dynamic pressure induced by an active mining process. Through numerical and physical simulations, Xie and Xu (2015) studied the feasibility of using ground penetrating radar-based detection to monitor roadway roof separation.

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Figure 1—Combination of outburst prevention measures of crosscutting boreholes extraction and bedding boreholes for gas pre-drainage in the workface (modified from Wang et al., 2014)

As regards the specific selection method for locating of the bottom drainage roadway, Liu, Li, and Pan (2016) analysed the floor stress distribution characteristics of the working face, and studied the layout of the bottom drainage roadway under the condition of closely-spaced coal seam groups. Nan, Li, and Guan (2015) determined the optimal location of the bottom drainage roadway based on the characteristics of roadway deformation obtained by numerical simulation combined with economic factors. Liu and Zhang (2018) established a floor failure depth model, and calculated the vertical distance between the bottom drainage roadway and the coal seam floor through numerical simulation. They also determined the horizontal distance between the bottom drainage roadway and the working face. Li and Li (2015) conducted on-site measurements of the deformation of the roadway during the mining of the workface to provide a basis for the selection of the ideal location of the bottom drainage roadway. Due to the differences in geological characteristics, gas occurrence, and gas control modes in different coal mines, the methods used to determine the location of the bottom drainage roadway would be also be different. In this paper, a combination of geological surveys and numerical simulations is used to determine the location of the bottom drainage roadway for the first mining workface of No. 3 coal seam in the Yuxi coal mine in China,. The results of this study are expected to provide a reference for the selection of the ideal position of the bottom drainage roadway under similar conditions.

Figure 2—Schematic diagram showing the procedure for implementing the outburst prevention measures

Research background This study is based on the mining practice at the Yuxi coal mine in Shanxi Province, China. The main recoverable coal seams are the No. 3 and No. 15 seams with a layer spacing of 87.5 m. The No. 3 coal seam, with a permeability of 13.3416 m2·(MPa2·d)-, was mined first and embodies the risk of coal and gas outbursts. The maximum original gas content and pressure of the No. 3 seam were 25.59 m3/t and 2.90 MPa, respectively. The first mining workface of the No. 3 coal seam is workface 1301, and U-type ventilation is used. Considering the outburst risk of the No. 3 coal seam, a combination of outburst prevention measures compriing crosscutting borehole extraction and bedding borehole extraction was used. The procedure followed is shown in Figure 2. The bottom drainage roadway was excavated first, and 260

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the crosscutting boreholes with spacing of 5-10 m were drilled to 15 m outside the intake airflow roadway contour line though the bottom drainage roadway to drain gas from the intake airflow roadway and surrounding coal. When the residual gas content is reduced to less than 8 m3/t (China State Administration of Work Safety, 2019), the intake airflow roadway can be excavated. Then, by using a ZDY6000 LD hydraulic directional drilling rig, bedding boreholes for draining gas inside the workface could be drilled in the intake airflow roadway, and boreholes with a spacing of 10~15 m were bored to 15 m outside the return airflow roadway and open-off cut. Each drilling operation was designed with one or two branches. The layout of the gas drainage boreholes is shown in Figure 3. The Journal of the Southern African Institute of Mining and Metallurgy

Study on the ideal location of a bottom drainage roadwaysmall-scale mining

Figure 3—Arrangement of outburst prevention measures in workface 1301

Figure 4—Layout styles for bottom drainage roadway

Figures 2 and 3 show the importance of positioning the bottom drainage roadway appropriately. If it is too close to the coal seam, the seam can be easily exposed unintentionally during roadway excavation. If it is too far away from the seam in the vertical direction, the crosscutting boreholes will be too long, which will not only lead to wasteful borehole drilling but also cause safety problems such as creating ’drainage blind areas’ caused by borehole deviations and inaccurate positioning. Owing to the above problems, it is necessary to determine the ideal position of the bottom drainage roadway for gas drainage.

Determination of the ideal position of the bottom drainage roadway There are two layout styles for bottom drainage roadways, as shown in Figure 4: type I and type II. Type I layout requires the bottom drainage roadway to be outside of the mining workface ’footprint’ on the horizontal projection. Conversely, type II locates the bottom drainage roadway inside the mining workface ’footprint’ on the horizontal projection. Determining an ideal location for the bottom drainage roadway involves selecting the appropriate bottom drainage roadway layout style and the vertical and horizontal distances between the bottom drainage roadway and the mining workface. As workface 1301 is the first mining workface of the No. 3 coal seam, the type I layout style was selected for the bottom drainage roadway, which meets the needs of constructing crosscutting boreholes for workface 1301 and the adjacent workface. The Journal of the Southern African Institute of Mining and Metallurgy

Basic principles of selecting the position of bottom drainage roadways When the position of the bottom drainage roadway is selected, the following principles should be followed: (1) Identify a marker bed to easily locate the roadway. (2) Coal seams must not be accidentally exposed during excavation of the bottom drainage roadway. (3) To facilitate maintenance, the bottom drainage roadway should be arranged located in a competent rock formation. (4) Appropriate positioning of the bottom drainage roadway can reduce the number of crosscutting boreholes, saving coal mining costs.

Determination of the vertical distance between the bottom drainage roadway and the mining workface In this section, the results of a geological survey were used to determine the vertical distance between the bottom drainage roadway and the mining workface. Four geological exploration drill-holes were completed around the 1301 workface (Figure 3), namely 12-1, 12-2, 13-1, and 13-3. Data from 13-1 is missing, and schematic logs of the other geological exploration drill-holes are shown in Figures 5-7. Figure 5 and Figure 6 show that limestone is present at 12.59 m and 14.67 m below the No. 3 coal seam. Since the 12-2 geological exploration borehole (Figure 7) was drilled to 11.95 m below the No. 3 coal seam, the limestone was not intersected. VOLUME 122

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Study on the ideal location of a bottom drainage roadway Administration of Work Safety, 2019), namely, that all the rock roadways excavations close to a coal seam with an outburst risk must be explored to ensure a minimum distance of no less than 5 m between the roadway and the coal seams. (2) T he limestone can be used as the marker bed during excavation of the bottom drainage roadway so that the coal seam cannot be exposed inadvertently, resulting in a coal and gas outburst accident. (3) T he bottom drainage roadway is located in sandy mudstone, which is beneficial for the maintenance of the roadway.

Figure 5—Schematic log of geological exploration borehole 12-1

Determination of the horizontal distance between the bottom drainage roadway and mining workface The bottom drainage roadway serves as a site from which to drill not only the crosscutting boreholes for workface 1301, but also those for the adjacent workface. Therefore, in order to ensure that the crosscutting boreholes through workface 1301 and the adjacent workface are as short as is practical, the bottom drainage roadway should be located in the middle of the coal pillar between the two workfaces as far as practical on the horizontal projection. In addition, the roadway should be located away from the stress concentration area to facilitate stability. To clarify the stress distributions of the surrounding rock, FLAC3D numerical simulation software was used. This software uses an explicit finite difference scheme to analyse deformation problems (Itasca Consulting Group, 2005).

Figure 6—Schematic log of geological exploration borehole 13-3

Numerical calculation model and boundary conditions

Figure 7—Schematic log of geological exploration borehole 12-2

Therefore, the bottom drainage roadway is located approximately 14 m below the No. 3 coal seam with a limestone roof. This has the following benefits. (1) The layer thickness between the bottom drainage roadway and the No. 3 coal seam is up to 14 m. This meets the requirements of Detailed Rules for Prevention and Control of Coal and Gas Outburst (China State

The mechanical parameters used in the simulation are shown in Table I. The depth of the coal seam is 600 m, and a compressive stress of 12 MPa was imposed at the top of the model. The other sides of the model were given rolling boundaries with an imposed stress of 10 MPa. A fixed boundary was defined at the bottom of the model. The Mohr-Coulomb model was selected for use, and the numerical calculation model is shown in Figure 8. The length, width, and height of the model are 405 m, 350 m, and 77.02 m, respectively. The mining length simulated is 150 m, extending from 100 m to 250 m in the x-direction. The mining width is 205 m, extending from 100 m to 305 m in the y-direction, and the mining height is 5.85 m. The model contains 78 000 zones and 83 997 grids.

Table 1

Integrated histogram and mechanical parameters of the experimental coal mine Lithology

Medium-granite sandstone Mudstone Medium-granite sandstone Siltstone No. 3 coal seam Siltstone Mudstone Sandy mudstone Limestone Sandy mudstone 262

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Elastic modulus [GPa]

Shear modulus [GPa]

Friction Angle [°]

Cohesion [MPa]

Tensile strength [MPa]

Thickness [m]

12.30 8.30 12.30 11.90 3.30 11.90 8.30 9.63 15.90 9.63

12.50 4.80 12.50 11.40 0.71 11.40 4.80 5.71 11.40 5.71

30.50 22.01 30.50 26.90 30.00 26.90 22.01 28.65 20.90 28.65

25.70 6.53 25.70 16.68 8.00 16.68 6.53 9.12 20.68 9.12

8.00 4.89 8.00 6.86 2.00 6.86 4.89 5.23 10.20 5.23

14.58 5.65 3.93 4.66 5.85 1.38 7.82 4.13 1.21 27.81

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Figure 8—Numerical calculation model

Figure 9—Stress distribution in the z-direction with the 1301 workface mined 15 m away from the reference plane

Figure 10—Stress distribution in the z-direction with the 1301 workface mined 25 m behind the reference plane

Stress evolution of the surrounding rock during mining of the 1301 workface For the purposes of the exercise, the plane at x = 175 m is chosen as the reference plane. Since the stress distributions of the surrounding rock in the x-, y-, and z-directions are similar (Chen et al., 2014), only the stress distributions of the reference plane in the z-direction are shown (Figures 9-11). According to Figures 9-11, the following characteristics will be obtained while mining the 1301 workface. (1) The stress state of the surrounding rock is a stress concentration area, stress increase area, and original stress area from the intake airflow roadway of workface 1301 outward. The Journal of the Southern African Institute of Mining and Metallurgy

(2) When the workface is mined to 45 m behind the reference plane, the 14 m vertical distance from the coal seam floor and the y = 55 m contour exactly intersects the edge of the original stress area. According to the model, the actual location is 55 m away from the intake airflow roadway of workface 1301. The range of the stress concentration area is approximately 0–10 m. The coal pillar between workface 1301 and the adjacent workface is 40 m wide. In line with the previous analysis, the bottom drainage roadway for gas drainage should be located 20 m away from the intake airflow roadway of workface 1301 on the horizontal projection. According to the numerical simulation results, when located 20 m outside the mining workface ’footprint’ VOLUME 122

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Figure 11—Stress distribution in the z-direction with the 1301 workface mined 45 m behind the reference plane

Figure 12—Schematic diagram of borehole sealing and plastic zone (Sun et al., 2015; Hu and Liu 2016; Chen et al., 2020)

on the horizontal projection, the bottom drainage roadway will be outside the stress concentration area during mining of workface 1301, which facilitates roadway maintenance. Furthermore, the length of the crosscutting boreholes is relatively short, which reduces the amount and cost of drilling. This is also consistent with the statistical results for bottom drainage roadway location in outburst-prone mines in China (Cheng, 2010).

Discussion Plastic zone range of the bottom drainage roadway The bottom drainage roadway serves mainly to drain the gas from the No. 3 coal seam. To improve the effectiveness of gas drainage, it is necessary to determine the initial sealing depth of the borehole (the distance between capsular bag 1 and the collar in Figure 12). Generally, to ensure that there is no air leakage during gas drainage, the position of capsular bag 1 should be beyond the edge of the roadway’s plastic zone (Figure 12). Therefore, determining the plastic zone range of the roadway is crucial for ensuring the sealing effect of the borehole. Analysis of drilling chips data is a common method to determine the plastic zone range of roadways. The number and size of drill chips are indicative of the in-situ stress – a smaller number of larger chips indicates less ground stress in the area. During drilling, cuttings can be collected every 1 m, and the depth 264

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of the roadway’s plastic zone can be determined by examining the changes in the size of the drilled chips at different positions. A 42 mm rotary drilling rod was used to obtain the drilling cuttings by drilling crosscutting boreholes perpendicular to the No. 3 coal seam from the bottom drainage roadway of the 1301 workface. The results (average mass of drill cuttings) are shown in Figure 13. When the drilling operations reached 7 m from the roadway’s edge, the mass of drill cuttings increased, indicating that stress concentration occurs around the roadway at this position. At a depth of 8 m, the mass of drill cuttings peaked (indicating maximum fracturing), showing that the stress concentration had also peaked at this position. At a depth of 9 m, the mass of drill chips decreased significantly, indicating that the rock surrounding the roadway at that position was gradually returning to the original stress state. This shows that the plastic zone of the bottom drainage roadway of the 1301 workface extends to 8 m. In the process of gas drainage, to avoid air leakage from the borehole, the initial sealing depth of each borehole should be greater than 8 m.

Technical advantages of underground gas drainage methods Surface wells can also be used for gas drainage. However, for coal and gas outburst-prone coal seams, mines in China mainly adopt underground gas drainage methods. The main reasons are as follows: The Journal of the Southern African Institute of Mining and Metallurgy

Study on the ideal location of a bottom drainage roadwaysmall-scale mining

Figure 13—Drill cuttings masses at different positions around the bottom drainage roadway

➤ Owing to the influence of topography, the surface wells are unevenly arranged, unlike underground boreholes drainage. ➤ The area close to the surface well has a good drainage effect. Conversely, the area far from the surface well has poor drainage effect. When the drainage time is short, the gas drainage balance is poor and the reliability is low. ➤ All measures are implemented on the ground. The State not only does not have test standards for surface well pre-drainage, but it is also difficult to test. ➤ The cost of surface well drainage is also higher than that for underground borehole drainage.

Conclusions The optimum location of the bottom drainage roadway for gas drainage was determined by using a combination of geological surveys and numerical simulations. 1. Geological exploration drilling around the mining workface showed that the vertical distance between the bottom drainage roadway and the mining workface was 14 m. A marker bed exists at this position, and the roadway can be easily maintained. The coal seam would not be accidentally exposed during the excavation of the bottom drainage roadway. 2. According to the statistical data on outburst-prone mines in China, combined with the numerical simulation, the bottom drainage roadway should be located 20 m outside the mining workface ’footprint’ on the horizontal projection. At this position, the bottom drainage roadway will be away from the stress concentration area while the workface is being mined, facilitating roadway maintenance. Also, the length of the crosscutting boreholes is relatively short, which reduces the amount and costs of drilling. 3. In the process of gas drainage, to avoid air leakage from the boreholes, the initial sealing depth of the borehole should be greater than 8 m.

Acknowledgments This work was supported by the National Natural Science The Journal of the Southern African Institute of Mining and Metallurgy

Foundation of China (51804102), the Henan Key Laboratory of Coal Green Conversion (CGCF201809), the State Key Laboratory Cultivation Base for Gas Geology and Gas Control of Henan Province (WS2019B12), the Program for Innovative Research Team of Henan Polytechnic University (T2019-4), and the Fundamental Research Funds for the Universities of Henan Province (NSFRF170901).

Author contributions Haidong Chen and Fenghua An wrote the main manuscript; Haidong Chen carried out the study and prepared all the figures; Zhaofeng Wang and Xiangjun Chen supervised the study. All authors reviewed the manuscript.

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Study on the ideal location of a bottom drainage roadway Coggan, J., Gao, F.Q., Stead, D., and Elmo, D. 2012. Numerical modelling of the effects of weak immediate roof lithology on coal mine roadway stability. International Journal of Coal Geology, vol. 90-91. pp. 100-109. Dejean, M.J.P. 1976. Deformation analysis in underground roadways. International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, vol. 13. pp. 25-30. Guo, H., Yuan, L., Shen, B., Qu, Q., and Xue, J. 2012. Mining-induced strata stress changes, fractures and gas flow dynamics in multi-seam longwall mining. International Journal of Rock Mechanics and Mining Sciences , vol. 54. pp. 129-139. Hu, S. and Liu, H. 2016. Leakage mechanism of coal seam gas drainage borehole and its application research progress. Safety in Coal Mines, vol. 47. pp. 170-173 [in Chinese]. Islam, M.R. and Shinjo, R. 2009. Numerical simulation of stress distributions and displacements around an entry oadway with igneous intrusion and potential sources of seam gas emission of the Barapukuria coal mine, NW Bangladesh. International Journal of Coal Geology, vol. 78. pp. 249-262. Itasca Consulting Group. 2005. FLAC3D User's Guide. Minneapolis, MN. Jiang, L.J., Mitri, H.S., Ma, N.J., and Zhao, X.D. 2016. Effect of foundation rigidity on stratified roadway roof stability in underground coal mines. Arabian Journal of Geoscience, vol. 9. pp. 32-44. Jiang, J.Y., Yang, W.H., Cheng, Y.P., Liu, Z.D., Zhang, Q., and Zhao K. 2019. Molecular structure characterization of middle-high rank coal via XRD, Raman and FTIR spectroscopy: Implications for coalification. Fuel, vol. 239. pp. 559-572.

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Kong, S.L., Cheng, Y.P., and Liu, H. 2014. A sequential approach to control gas for the extraction of multi-gassy coal seams from traditional gas well drainage to mining-induced stress relief. Applied Energy, vol. 131. pp. 67-78.

Xue, S., Yuan, L., Wang, Y., and Xie, J. 2014. Numerical analyses of the major parameters affecting the initiation of outbursts of coal and gas. Rock Mechanics and Rock Engineering, vol. 47. pp. 1505-1510.

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Yang, S.Q., Chen, M., Jing, H.W., Chen, K.F., and Meng, B. 2017. A case study on large deformation failure mechanism of deep soft rock roadway in Xin'An coal mine, China. Engineering Geology, vol. 217. pp. 89-101. Yang, X., Wen, G., Sun, H., Li, X., Lu, T., Dai, L., Cao, J., and Li, L. 2019. Environmentally friendly techniques for high gas content thick coal seam stimulation – multi-discharge CO2 fracturing system. Journal of Natural Gas Science and Engineering, vol. 61. pp. 71-82. Yu, B., Su, C., and Wang, D. 2015. Study of the features of outburst caused by rock cross-cut coal uncovering and the law of gas dilatation energy release. International Journal of Mining Science and Technology, vol. 25. pp. 453-458. Zhang, H.L., Cao, J.J., and Tu, M. 2013. Floor stress evolution laws and its effect on stability of floor roadway. International Journal of Mining Science and Technology, vol. 23. pp. 631-636. Zhang, K., Zhang, G.M., and Hou, R.B. 2015. Stress evolution in roadway rock bolts during mining in a fully mechanized longwall face, and an evaluation of rock bolt support design. Rock Mechanics and Rock Engineering, vol. 48. pp. 333-344. Zhou, H.X., Yang, Q., Cheng, Y.P., Ge, C., and Chen, J. 2014. Methane drainage and utilization in coal mines with strong coal and gas outburst dangers: A case study in Luling mine, China. Journal of Natural Gas Science and Engineering, vol. 20. pp. 357-365. u

The Journal of the Southern African Institute of Mining and Metallurgy

NATIONAL & INTERNATIONAL ACTIVITIES 2022 20–27 May 2022 — 26th ALTA 2022 Nickel-CobaltCopper,Uranium-Rare Earths, Gold-PM, In-Situ Recovery, Lithium & Battery Technology Online Conference & Exhibition Perth, Australia, Tel: +61 8 9389 1488 E-mail: alta@encanta.com.au Website: www.encanta.com.au

8–14 September 2022 — 32nd Society of Mining Professors Annual Meeting and Conference 2022 (SOMP) Windhoek Country Club & Resort, Windhoek, Namibia Contact: Camielah Jardine Tel: 011 538-0238 E-mail: camielah@saimm.co.za Website: http://www.saimm.co.za

23–26 May 2022 — Mine Planning and Design Online School Contact: Gugu Charlie Tel: 011 538-0238 E-mail: gugu@saimm.co.za Website: http://www.saimm.co.za

15–20 September 2022 — Sustainable Development in the Minerals Industry 2022 10th Internationl Hybrid Conference (SDIMI) ´Making economies great through sustainable mineral development´ Windhoek Country Club & Resort, Windhoek, Namibia Contact: Gugu Charlie Tel: 011 538-0238 E-mail: gugu@saimm.co.za Website: http://www.saimm.co.za

13–16 June 2022 — EXPONOR Chile 2022 International Exhibition of Technologies and Innovations for the Mining and Energy Industry Chile Website: https://www.aia.cl/ Website: https://www.exponor.cl/ 14–16 June 2022 — Water | Managing for the Future Online Conference Vancouver, BC, Canada Website: https://www.mineconferences.com Website: http://www.saimm.co.za 20–23 June 2022 — International Exhibition of Technologies and Innovations for the Mining and Energy Industry Chile Website: https://www.aia.cl/ 21–24 June 2022 — Mine to Mill Reconciliation: Fundamentals and tools for productivity improvement Online Short Course Contact: Camielah Jardine Tel: 011 538-0238 E-mail: camielah@saimm.co.za Website: http://www.saimm.co.za 30 June 2022 — Introduction to The SAMREC and SAMVAL Codes Online Course Contact: Gugu Charlie Tel: 011 538-0238 E-mail: gugu@saimm.co.za Website: http://www.saimm.co.za 21–23 August 2022 — International Mineral Processing Congress Asia-Pacific 2022 (IMPC) Melbourne, Brisbane + online Website: https://impc2022.com/ 21–25 August 2022 — XXXI International Mineral Processing Congress 2022 Melbourne, Australia + Online Website: www.impc2022.com 24–25 August 2022 — Battery Materials Conference 2022 Misty Hills Conference Centre, Muldersdrift, Johannesburg, South Africa Contact: Gugu Charlie Tel: 011 538-0238 E-mail: gugu@saimm.co.za Website: http://www.saimm.co.za

The Journal of the Southern African Institute of Mining and Metallurgy

28–29 September 2022 — Thermodynamic from Nanoscale to Operational Scale (THANOS) International Hybrid Conference 2022 on Enhanced use of Thermodynamic Data in Pyrometallurgy Teaching and Research Mintek, Randburg, South Africa Contact: Camielah Jardine Tel: 011 538-0238 E-mail: camielah@saimm.co.za Website: http://www.saimm.co.za 4–6 October 2022 — 18th MINEX Russia Mining and Exploration Forum Moscow Website: https://2021.minexrussia.com/en/contact-forumorganisers/ 12–13 October 2022 — Mine-Impacted Water Hybrid Conference 2022 ´Impacting the Circular Economy´ Mintek Randburg, South Africa Contact: Camielah Jardine Tel: 011 538-0238 E-mail: camielah@saimm.co.za Website: http://www.saimm.co.za 2–4 November 2022 — PGM The 8th International Conference 2022 Sun City, Rustenburg, South Africa Contact: Camielah Jardine Tel: 011 538-0238 E-mail: camielah@saimm.co.za Website: http://www.saimm.co.za 13–17 November 2022 — Copper 2022 Santiago, Chile Website: https://copper2022.cl/ 28 November –1 December 2022 — South African Geophysical Association’s 17th Biennial Conference & Exhibition 2022 Sun City, South Africa Website: https://sagaconference.co.za/ 13-16 December 2022 — 4th International Conference on Science and Technology of Ironmaking and Steelmaking Indian Institute of Technology Bombay (IIT Bombay) Website: http://stis2022.org/

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Company affiliates The following organizations have been admitted to the Institute as Company Affiliates 3M South Africa (Pty) Limited AECOM SA (Pty) Ltd AEL Mining Services Limited African Pegmatite (Pty) Ltd Air Liquide (Pty) Ltd Alexander Proudfoot Africa (Pty) Ltd Allied Furnace Consultants AMEC Foster Wheeler AMIRA International Africa (Pty) Ltd ANDRITZ Delkor (Pty) Ltd Anglo Operations Proprietary Limited Anglogold Ashanti Ltd Arcus Gibb (Pty) Ltd ASPASA Aurecon South Africa (Pty) Ltd Aveng Engineering Aveng Mining Shafts and Underground Axiom Chemlab Supplies (Pty) Ltd Axis House Pty Ltd Bafokeng Rasimone Platinum Mine Barloworld Equipment -Mining BASF Holdings SA (Pty) Ltd BCL Limited Becker Mining (Pty) Ltd BedRock Mining Support Pty Ltd BHP Billiton Energy Coal SA Ltd Blue Cube Systems (Pty) Ltd Bluhm Burton Engineering Pty Ltd Bond Equipment (Pty) Ltd Bouygues Travaux Publics Castle Lead Works CDM Group CGG Services SA Coalmin Process Technologies CC Concor Opencast Mining Concor Technicrete Council for Geoscience Library CRONIMET Mining Processing SA Pty Ltd CSIR Natural Resources and the Environment (NRE) Data Mine SA Digby Wells and Associates DRA Mineral Projects (Pty) Ltd DTP Mining - Bouygues Construction Duraset Elbroc Mining Products (Pty) Ltd eThekwini Municipality ▶ viii

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Ex Mente Technologies (Pty) Ltd Expectra 2004 (Pty) Ltd Exxaro Coal (Pty) Ltd Exxaro Resources Limited Filtaquip (Pty) Ltd FLSmidth Minerals (Pty) Ltd Fluor Daniel SA ( Pty) Ltd Franki Africa (Pty) Ltd-JHB Fraser Alexander (Pty) Ltd G H H Mining Machines (Pty) Ltd Geobrugg Southern Africa (Pty) Ltd Glencore Gravitas Minerals (Pty) Ltd Hall Core Drilling (Pty) Ltd Hatch (Pty) Ltd Herrenknecht AG HPE Hydro Power Equipment (Pty) Ltd Huawei Technologies Africa (Pty) Ltd Immersive Technologies IMS Engineering (Pty) Ltd Ingwenya Mineral Processing (Pty) Ltd Ivanhoe Mines SA Joy Global Inc.(Africa) Kudumane Manganese Resources Leica Geosystems (Pty) Ltd Loesche South Africa (Pty) Ltd Longyear South Africa (Pty) Ltd Lull Storm Trading (Pty) Ltd Maccaferri SA (Pty) Ltd Magnetech (Pty) Ltd Magotteaux (Pty) Ltd Malvern Panalytical (Pty) Ltd Maptek (Pty) Ltd Maxam Dantex (Pty) Ltd MBE Minerals SA Pty Ltd MCC Contracts (Pty) Ltd MD Mineral Technologies SA (Pty) Ltd MDM Technical Africa (Pty) Ltd Metalock Engineering RSA (Pty) Ltd Metorex Limited Metso Minerals (South Africa) Pty Ltd Micromine Africa (Pty) Ltd MineARC South Africa (Pty) Ltd Minerals Council of South Africa Minerals Operations Executive (Pty) Ltd MineRP Holding (Pty) Ltd Mining Projections Concepts Mintek VOLUME 122

MIP Process Technologies (Pty) Limited MLB Investment CC Modular Mining Systems Africa (Pty) Ltd MSA Group (Pty) Ltd Multotec (Pty) Ltd Murray and Roberts Cementation Nalco Africa (Pty) Ltd Namakwa Sands (Pty) Ltd Ncamiso Trading (Pty) Ltd Northam Platinum Ltd - Zondereinde Opermin Operational Excellence OPTRON (Pty) Ltd Paterson & Cooke Consulting Engineers (Pty) Ltd Perkinelmer Polysius A Division of Thyssenkrupp Industrial Sol Precious Metals Refiners Rams Mining Technologies Rand Refinery Limited Redpath Mining (South Africa) (Pty) Ltd Rocbolt Technologies Rosond (Pty) Ltd Royal Bafokeng Platinum Roytec Global (Pty) Ltd RungePincockMinarco Limited Rustenburg Platinum Mines Limited Salene Mining (Pty) Ltd Sandvik Mining and Construction Delmas (Pty) Ltd Sandvik Mining and Construction RSA(Pty) Ltd SANIRE Schauenburg (Pty) Ltd Sebilo Resources (Pty) Ltd SENET (Pty) Ltd Senmin International (Pty) Ltd SISA Inspection (Pty) Ltd Smec South Africa Sound Mining Solution (Pty) Ltd SRK Consulting SA (Pty) Ltd Time Mining and Processing (Pty) Ltd Timrite Pty Ltd Tomra (Pty) Ltd Traka Africa (Pty) Ltd Ukwazi Mining Solutions (Pty) Ltd Umgeni Water Webber Wentzel Weir Minerals Africa Welding Alloys South Africa Worley

The Journal of the Southern African Institute of Mining and Metallurgy

INVITATION FROM THE ORGANIZING COMMITTEE

sustainability and accountability is a great honour, that I hereby to local communities is more extend this invitation to you, dear pronounced, as voice continues esteemed members, to the 32nd Society of Mining Professors Annual to be added to expectation, with Meeting and Conference to be hosted unparalleled clarity. Our contribution by the Namibian University of Science to the mining industry discourse, in and Technology and at the Windhoek the form of relevant research and Country Club and Resort, Windhoek, well-trained graduates, remains a Namibia, from 8–14 September 2022. top priority. I wish to extend my fraternal greetings Namibia is richly endowed with to the delegates, SOMP members, Prof. Harmony Kuitakwashe mineral resources, and the mining spouses and partners who will travel Musiyarira industry significantly contributes to from around the globe to be part of this the national economy. Namibia also landmark conference. From my end, I revere this boasts a strategic geographical location, making it opportunity; and as we collectively put shoulder to a major economic gateway to the southern Africa wheel to achieve a successful conference, I wish to region. With a stable political climate, diverse call upon your continued and generous cooperation cultural heritage, sound infrastructure, and a as we prepare for this conference. beautiful climate, this country is a shining jewel on Namibia University of Science and Technology the African continent. I can express it with certainty (NUST) is honored to collaborate with Southern and confidence, that the warmth of the Namibian African Institute of Mining and Metallurgy (SAIMM) people can only be ideal for our delegates and the and Society of Mining Professors (SOMP) to host country has a lot to offer to the delegates, prethe conference and annual meeting. Our thrust conference and post-conference itinerary. to push the frontiers of innovation in minerals The program of our Annual Meeting and engineering is amply demonstrated in our great Conference Meeting will follow a participatory and plans for a Centre for Minerals Resources interdisciplinary approach through the following Engineering that will serve the entire sub-Saharan activities; conference presentations, workshops, region as the Centre of Excellence in Minerals panels, parallel sessions, poster presentations and Research and Development. As a university, we open discussions. It will also include a spouses and have been at the forefront of fostering major global partners programme, pre-conference and post [1] collaborations and we are hopeful that we will conferences technical tours. The accompanying continue to harness the strengths that derive from persons program includes tours to the Museum, continued collaboration, premised on our quest for Windhoek City tour Windhoek, Game Drive and quality and excellence. lunch as well as community tours. Once again, the conference comes at a time, I look forward to a great conference and meeting. when the mining industry is grappling with I also wish to urge you to explore the unique multiple challenges. As a global academic body opportunity to experience our wonderful Namibian of respected character, we continue to foster hospitality and country during your stay. valuable relations with an industry that faces an We invite you to register from now on for the urgent need to transform its approach to business. conference as well as to the technical visits The business, stakeholder and technological and the accompanying persons program. We landscapes are fast evolving, faster than at any recommend that you book your accommodation juncture in modern history. Therefore, of particular – in Windhoek –in advance; the demand for importance, is our ability to define with accuracy, hotel rooms inthe summer season is very high. the prevailing global context, as we face a possibly However, thehotels will have a special rate for the exciting future, while drawing useful lessons from conferenceattendees. https://www.saimm.co.za/ the past as well as a fast dying present. Indeed, saimm-events/upcoming-events/32nd-sompthe race for ownership of the future is aggressive annual-meeting-and-conference#accommodation and acrimonious. At the same time, the call for

THE 8th INTERNATIONAL CONFERENCE 2-3 NOVEMBER 2022 - CONFERENCE 4 NOVEMBER 2022 - TECHNICAL VISIT VENUE - SUN CITY, RUSTENBURG, SOUTH AFRICA

The Platinum conference series has covered a range of themes since its inception in 2004, and traditionally addresses the opportunities and challenges facing the platinum industry. This prestigious event attracts key role players and industry leaders through: • High quality technical papers and presentations • Facilitating industry networking • Having large, knowledgeable audiences • Global participation, and • Comprehensive support from industry role players.

WHO SHOULD ATTEND • • • • • • • • • • • • • • • • •

Academics Business development managers Concentrator managers Consultants Engineers Exploration managers Explosives engineers Fund managers Geologists Hydrogeologists Innovation managers Investment managers Market researchers and surveyors Marketing managers Mechanical engineers Metallurgical consultants Metallurgical managers

• • • • • • • • • • • • • • •

Metallurgists Mine managers Mining engineers New business development managers Planning managers Process engineers Product developers Production managers Project managers Pyrometallurgists Researchers Rock engineers Scientists Strategy analysts Ventilation managers

The 8th International PGM Conference will, under the guidance of the organising committee, structure a programme which covers critical aspects of this continually evolving and exciting industry. The success and relevance of this event to the industry really depends on your participation and support. You can participate in this event as an organising committee member, author/ presenter, delegate or sponsor.

COVID-19 Protocols

The SAIMM is committed to the safety and wellbeing of our members and the industry. We will take all necessary precautions to ensure that we adhere to protocols and guidelines. Sun International has strict COVID-19 protocols in place to ensure the safety of guests at all their facilities. Social functions will be arranged in open spacious venues. The vast open spaces and outdoor activities like golf, swimming pools and game drives all make for a top class and safe conference venue.

ABOUT THE VENUE The Sun City resort lies in a tranquil basin of an extinct volcano in the Pilanesberg adjacent to South Africa's rich platinum belt. It boasts four hotels, an award-winning golf course and many other attractions. Nestled in the rolling hills of the Pilanesberg, one of South Africa’s most scenic locations, Sun City is a world unto itself and has earned its reputation as Africa’s Kingdom of Pleasure. Finally re-discovered and now part of Sun City, the Lost City and the Valley of Waves, fabled to be the ruins of a glorious ancient civilisation, celebrate and bring to life the legends of this mystical city.

FOR FURTHER INFORMATION, CONTACT: Camielah Jardine, Head of Conferencing

E-mail: camielah@saimm.co.za Web: www.saimm.co.za

Saimm 202205 may

Articles inside

by J.L. Porathur, S. Sekhar, A.K. Godugu, and S. Bhargava

by M. Onifade, B. Genc, K.O. Said, M. Fourie, and P.O. Akinseye