Contemporary ENERGY Vol2 No2 (2016) by REMOO

International Journal of Contemporary ENERGY Peer-reviewed open-access E-journal

ISSN 2363-6440

Vol. 2, No. 2 (2016) November 2016 www.Contemporary-ENERGY.net

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Cover Illustration Gewerbegebiet Illustration; Source: http://de.123rf.com; Copyright: Ivan Smuk

Founding Editor & Editor-in-Chief Zoran V. Stosic

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editor@contemporary-energy.net

Director RENECON International, GERMANY; Former Vice President ICO South East Europe at AREVA, GERMANY

Editorial Board Prof. Jan Blomgren

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Uppsala University; CEO of INBEx, SWEDEN

Ass. Prof. Leon Cizelj

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University of Ljubljana; Head of Reactor Engineering Division at IJS, SLOVENIA

Ass. Prof. Davor Grgić

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Faculty of Electrical Engineering and Computing, University of Zagreb, CROATIA

Dr. Maximilian Emanuel Elspas

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Head of Energy Law and Lawyer Partner at Beiten Burkhardt Law Munich, GERMANY

Dr. Dietmar O. Reich

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Co-Head of Competition Practice Group and Lawyer Partner at Beiten Burkhardt Law Brussels, BELGIUM

Dr. Miodrag Mesarović

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Secretary General of the SerbianWEC Member Committee; Senior Advisor to Energoprojekt-ENTEL, Belgrade, SERBIA

Prof. Ana M. Lazarevska

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Faculty of Mechanical Engineering, University of Skopje, MACEDONIA

Prof. Li Ran

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School of Engineering, University of Warwick, UNITED KINGDOM; Deputy Director of China State Key Lab in Power Transmission Apparatus Security, Chongqin University, CHINA

Dr. Changxin Liu

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Deputy Director General of China National Nuclear Corporation – CNNC, Beijing CHINA

Prof. Xu Cheng

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Institute of Fusion and Nuclear Technology, Karlsruhe Institute of Technology – KIT, GERMANY; School of Nuclear Sciences and Engineering, Shanghai, Jiao Tong University, CHINA

Prof. Josua P. Meyer

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Department of Mechanical and Aeronautical Engineering, University of Pretoria, SOUTH AFRICA

Prof. Zhao Yang Dong

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Chair Professor and Head of School of Electrical and Information Engineering, University of Sidney, AUSTRALIA

M.Sci.Engng. Jukka Tapani Laaksonen

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Vice President ROSATOM Overseas, Moscow, RUSSIA; Former Director General of the STUK, FINLAND

M.Sci.Engng. Jože Špiler

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Head of TechnicalServices and Investments at GEN-energija, Krško, SLOVENIA

Prof. Michael Narodoslawsky

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Institute for Process and Particle Engineering, Technical University of Graz, AUSTRIA

Dr. Raffaella Gerboni

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Post-Doc Fellow Researcher, Energy Department, Politecnico di Torino, ITALY

Prof. Henryk Anglart

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Deputy Head of Physics Department, KTH Royal Institute of Technology, Stockholm, SWEDEN

Dr. Suna Bolat

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Assistant Professor, Eastern Mediterranean University – EMU, Famagusta, North Cyprus, TURKEY

Prof. Nikola Popov

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Faculty of Engineering Physics, McMaster University, Hamilton; President DENIPO Consulting Ltd., Toronto, Ontarion, CANADA

Prof. Milovan Perić

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Managing Director of CoMeT Continuum Mechanics Technologies GmbH, GERMANY; Senior Corporate Consultant CD-adapco, UNITED KINGDOM

Prof. Umberto Desideri

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Department of Energy Engineering, University of Pisa, ITALY

Prof. Shpetim Lajqi

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Faculty of Mechanical Engineering, University of Prishtina, KOSOVO

Dr. Camila Braga Viera

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Post-Doc Researcher, SCK-CEN Belgian Nuclear Research Center, Boeretang, BELGIUM

Ass. Prof. Manuel Ruiz de Adana Santiago

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Department of Applied Thermodynamics, University of Cordoba, SPAIN

Dr. Naseem Udin

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Principal Lecturer, Institute Teknology Brunei, BRUNEI

Prof. Gordana Laštovička -Medin

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Faculty of Science and Mathematics, University of Montenegro, Podgorica, MONTENEGRO

Prof. Serkan Dag

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Department of Mechanical Engineering, Middle East Technical University – METU, Ankara, TURKEY

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___________________________________________________________________________________________________________ A Word from the Editor–in–Chief

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

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A WORD FROM THE EDITOR-IN-CHIEF “Although most people adjust in a day or two, it can take some people up to a week to get used to the time change” says Dr. Plante, an assistant professor of psychiatry at the School of Medicine and Public Health of Wisconsin University. A study conducted at Stanford University indicates an increase in traffic accidents on the Monday following the spring time shift change, and a small increase in car crashes on days following the fall time change as well. In the week after Daylight Saving Time there was a 7% increase in car crashes, according to the Texas A&M University study. The boost in morning traffic accidents was even greater – it was 14%. A 2008 Swedish study showed an increase of about 5% in heart attacks on the three weekdays following the spring time shift. In the 2014 Texas A&M University study of 42,060 people, researchers found a 21% decrease in heart attacks following the fall time change. By contrast, they noticed a 24% increase in heart attacks on the Monday after the clock springs forward. Founding Editor & Editor–In–Chief Zoran V. Stosic

On last Sunday of October, at 3 am, we set the clocks back, gaining an extra hour of sleep as Daylight Savings Time ends. The idea was first suggested by Benjamin Franklin in 1784 and was originally established in the U.S. during both World Wars in order to take advantage of longer daylight hours and save energy for the war production. Defenders of Daylight Saving Time suggest that extended daylight hours improve energy conservation by allowing people to use less energy to light their businesses and homes. Opponents argue that the energy saved during Daylight Saving Time is offset by greater energy use during the darker autumn and winter months. But, does the spring and fall time change affect our health? Or, does the extra 60 minutes we scored last weekend in October gave our health a boost, or hurt it?

A 2009 study headed by Dr. Barnes, an assistant professor at the U.S. Military Academy at West Point, analysed the severity of workplace accidents in miners on the Monday following the time change. The researchers found a 5.7% increase in injuries and a 67.6% increase in work days lost to injuries. Dr. Barnes said the results were likely to be similar in other workplaces with similar hazards. The 2008 Australian study found an increase in suicides among men following the start of Day Light Saving Time – an increase of roughly 0.44 per day. The researchers suggested the clock shift leaves many without morning sunlight, which perhaps promotes winter depression, which might lead to suicide. However, they haven’t verified the link between these two. A betterestablished finding is that spring is the peak time of the year for suicides. So, what is the bottom line? Is the energy saving caused by time changes twice a year real or fictive, and could we reliable quantify it? Are these time changes boosting or hurting our health? Could we quantify time change effects on our health and corresponding financial loss and compare it with energy savings? Are we interested in such analysis?

___________________________________________________________________________________________________________ A Word from the Editor–in–Chief

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Living in a Complex World – The many Faces of Energy Issues REMOO–2016: The 6th International Conference & Workshop

by Jan Blomgren

Eduard Schnessl, Andreas Wimmer Trends in the Development of Large Gas Engines for Power Generation

Michel Joel Tchatchueng Kammegne, Ruxandra Mihaela Botez, Teodor Lucian Grigorie, Mahmoud Mamou, Youssef Mebarki A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology – A New Multidisciplinary Experimental Model

Ivana Ivanović, Aleksandar Sedmak, Miloš Milošević The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming Reactor

Gordana Laštovička-Medin Thermal Imaging and Uncertainties in the Interpretation: Case Study

Ionut Purica Hazard Risks and their Impact on Critical Infrastructures (Case Analysis – Natural Gas Networks of Italy and Romania)

Gazmend Pula, Kadri Kadriu, Gazmend Kabashi, Valon Sadiku Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the Deterministic Methodology

Simon Pezzutto, Reza Fazeli, Matteo De Felice Smart City Projects Implementation in Europe: Assessment of Barriers and Drivers

About the Journal

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The Journal

Editorial

CONTENT

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Editorial

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Living in a Complex World —The many Faces of Energy Issues REMOO–2016: The 6th International Conference & Workshop by Jan Blomgren

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LIVING IN A COMPLEX WORLD — THE MANY FACES OF ENERGY ISSUES REMOO–2016: THE 6TH INTERNATIONAL CONFERENCE & WORKSHOP Many different persons have been attributed as the origin of this quote. No matter who it was, it makes a great summary of the notoriously difficult challenge to look into the crystal sphere and to give credible outlooks for the future in the energy sector of society. Yes, society, not just industry. Often we talk about the energy or power industry, but this limitation is rarely useful when we want to understand the big picture. Energy production and use is a cornerstone of society, and has been so since the first civilizations emerged some 5000 years ago or so. Energy does not only shape the entire society, our understanding of energy also affects the eternal questions about purpose and goal, in short our thinking about who we are. Let me present just one historic example (I happen to love history of science!): the concept of evolution. Often we write the history very binary, presenting the proponents of the ideas that prevailed in the end as geniuses (well, sometimes they were indeed so, but sometimes they just happened to be more lucky in their guessing…) and their counterparts are often depicted as stupid. This is indeed true when it comes to evolution, but what we often forget is that the sceptics at that time had some powerful arguments. When the idea of biologic evolution was launched it was quickly concluded that enormous time spans were required for evolution to be able to create the large diversity we can observe. However, lord Kelvin pointed out that if we supposed that sun was utilizing the most efficient energy source known at the time, hard coal, it would last only about 75 000 years in total. Darwin was painstakingly aware of this weak spot in his theory, and this dilemma was not solved until after his death with the discovery of nuclear energy in the early twentieth century. It was, however, not until slightly more than a century after the publication of About the origin of species that we had a reasonably convincing theory for the energy production in our Sun. Advances in energy research do not only develop society; they also develop our fundamental conception of the World. If we read newspapers or watch news on TV, it is easy to get the impression that thighs just get worse in the World. When we have realized that spectacular bad news sell more newspapers than slowly progressing good news, we can turn to statistics and realize that the standard of living in the World has improved dramatically during the last decades. The poverty has been reduced at an unprecedented rate, and so has the population increase as well as the violence, both in wars and in smaller-scale human violence like murders. Energy has been pivotal in all these developments. Increased energy production has allowed billions of human beings on this planet to swing themselves out of poverty, with all the other improvements mentioned above as consequences. This has been achieved thanks to a steady gradual development rather than revolutions. Improving things one percent per year for a long time can in the end make large differences, with no media coverage. I can take my own field, nuclear power, as example. We have managed to increase the energy output from nuclear fuel one or a few percent per year, and now we extract twice as much energy from each fuel bundle than what we did in 1980. Nothing of this spectacular success has been a revolution – it is all thanks to relentless incremental improvement in science and technology. ___________________________________________________________________________________________________________ “Living in a complex world – The many Faces of Energy Issues”

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

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Photographer: Curt-Robert Lindqvist. Reprinted with permission from SKB

The role of science and technology as drivers in developing more efficient energy exploitation and thereby functioning as engine in global development was a common underlying theme in the recent REMOO conference held May 18-19 2016 in Budva, Montenegro. Although the conference title was ”Science and Engineering for Reliable Energy”, the conference attracted an even wider scope of contributions, not limiting to science and engineering in themselves, but also to their utilization in society. In fact, the scope was even wider: some contributions studied implications in the opposite direction, i.e., how societal factors affect energy technology. Some of the contributions are presented in the present issue of the International Journal of Contemporary Energy. Schnessl and Wimmer describe trends in the development of large gas engines for power generation. Gas has increased its share of the global power production significantly in the last two decades, and most predictions point to a further increase. This paper concerns primarily energy production, whereas our next contribution concerns conservation of energy. Tchatchueng Kammegne, Botez, Grigorie, Mamou and Mebarki presents results on research on how to reduce energy consumption in aviation. Ivanovic, Sedmak and Milosevic have performed work relevant for optimization of fuel cells. Hence these three technical works treat aspects of production, conservation and storage of energy, showing the breadth of the conference. Another aspect of energy conservation is how to detect inefficiencies. Thermal imaging is a well-established technique to study heat transfer and dissipation in general, and maybe most importantly to identify heat leaks and other inefficient uses of energy. Lastovicka-Medin claims that in spite of its widespread use (or possibly because of it?), there are many more users than persons able to correctly interpret the images. We move on to distribution of energy from producer to end user. Purica has studied hazard risks on critical infrastructure, exemplified with a case study of natural gas networks of Italy and Romania. Pula, Kadriu, Kabashi and Sadiku have studied the reliability of electricity transfer to consumers in a case study of the grid in Kosovo. Finally, we have papers on how society affects energy technology. Pezzutto, Fazeli and De Felice make a classical SWOT analysis (Stength, Weaknesses, Opportunities, Threats) on smart cities in Europe. What are the most important factors that prevent widespread introduction of these technologies? Which are the factors with most potential to support such an introduction? Read the paper and find out. ___________________________________________________________________________________________________________ “Living in a complex world – The many Faces of Energy Issues”

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This sums up the contributions in this issue of the International Journal of Contemporary Energy. You can look forward to most interesting reading. Last but not least, reserve May 10-12, 2017 in Venice, Italy, for the next conference in this series.

Jan Blomgren Associate Editor

Jan Blomgren is CEO and founder of INBEx (Institute of Nuclear Business Excellence), providing independent nuclear executive advice and business leadership training globally. The INBEx team comprises over 20 former CEOs, Director Generals and similar. He was the youngest professor ever in Sweden in nuclear physics, holding the chair in applied nuclear physics at Uppsala University. His research was focused on neutron-induced nuclear reactions, an area in which he has published over 200 papers in refereed international journals and conference proceedings. When plans to build new nuclear power in Sweden were initiated, he was recruited to Vattenfall, one of the largest nuclear power operators in Europe. At Vattenfall, he was responsible for planning the competence development needed for nuclear new-build, as well as coordinating training for nuclear power plant personnel. In addition, he was Director of the Swedish Nuclear Technology Centre, which is the coordination organization for nuclear research and education involving universities, industry and the regulator. He was involved in the creation of ENEN, the European Nuclear Education Network, in which essentially all European universities in nuclear engineering collaborate. Moreover, he has recently established a large collaboration with France on research and education. Finally, he is the father of several industry-sponsored university programs, as well as having started a number of nuclear business training programs in industry. Jan Blomgren is alone in Europe to have upheld high-ranked positions both at university and nuclear industry. He is frequently invited speaker at conferences, and was recently invited as expert advisor to the French Senate.

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Authors’ Papers 1

Eduard Schnessl, Andreas Wimmer

Trends in the Development of Large Gas Engines for Power Generation 11

Michel Joel Tchatchueng Kammegne, Ruxandra Mihaela Botez, Teodor Lucian Grigorie, Mahmoud Mamou, Youssef Mebarki

A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology – A New Multidisciplinary Experimental Model 22

Ivana Ivanović, Aleksandar Sedmak, Miloš Milošević

The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming Reactor 29

Gordana Laštovička-Medin

Thermal Imaging and Uncertainties in the Interpretation: Case Study 42

Ionut Purica

Hazard Risks and their Impact on Critical Infrastructures (Case Analysis – Natural Gas Networks of Italy and Romania) 47

Gazmend Pula, Kadri Kadriu, Gazmend Kabashi, Valon Sadiku

Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the Deterministic Methodology 56

Simon Pezzutto, Reza Fazeli, Matteo De Felice

Smart City Projects Implementation in Europe: Assessment of Barriers and Drivers

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DOI: 10.14621/ce.20160201

Trends in the Development of Large Gas Engines for Power Generation Eduard Schnessl1*, Andreas Wimmer1,2 1

LEC GmbH – Large Engines Competence Center Inffeldgasse 19, 8010 Graz, Austria; Eduard.Schnessl@lec.tugraz.at 2 Institute of Internal Combustion Engines and Thermodynamics Graz University of Technology, Austria

Abstract

1. Introduction

Numerous studies verify that the global significance of natural gas for combined heat and power generation (CHP) and mobility will greatly increase in the future. In its World Energy Outlook (WEO) 2012, the IEA (International Energy Agency) predicts that the use of natural gas for power generation will double in the next 20 years. Due to great improvements in efficiency and power output in recent years, large gas engines for stationary power generation have registered significant growth. To make gas engines more competitive in areas currently dominated by diesel engines, intensive research is required to overcome the disadvantages that still exist. This primarily entails improving dynamic behaviour and robustness. Further challenges will result from the great fluctuations in gas quality to be expected of grid gas and LNG. The trend to use special gas engines which make use of many gases that would otherwise not be exploited will continue to increase. The previous research focus of the LEC was on thermodynamically oriented optimization of combustion concepts for large engines. Developed at the LEC over the course of many years, LEC Development Methodology (LDM) is based on the intensive interaction between simulation of the engine cycle and experimental investigations of single cylinder research engines. LDM has been applied successfully to a wide variety of combustion concepts. A methodology which allows optimization of the overall system has also been created: LDM Advanced. Using a multidisciplinary approach which includes mechanics, material sciences, chemistry, and tribology in addition to thermodynamics, its main focus is on extensive physical modeling of all combustion related subsystems and effects. This paper indicates future trends in engine performance and describes the LEC development methodology.

Numerous studies verify that the global significance of natural gas for power generation and mobility will greatly increase. Figure 1 presents a prognosis made by the International Energy Agency (IEA) about the development of global power generation as divided into shares of the individual areas (World Energy Outlook 2012) [1]. According to this prognosis, the share of natural gas will increase significantly in the next 20 years and even double.

Keywords:

Internal combustion engines; Development methodology; Single cylinder research engines; Gas engine; Power generation

Article history:

Received: 23 April 2016 Revised: Accepted: 18 October 2016

The main impetus for this development comes from the large natural gas resources in conventional and unconventional deposits (shale gas, tight gas and CBM), the trend in the price of natural gas (especially in the U.S.), the discussion about how to stop using nuclear energy in various countries (e.g., Germany and Japan) and the fact that natural gas technology can be used to bridge the gap between carbon-based and "carbonfree" energy supply and mobility since natural gas has less carbon than other fossil fuels. Currently, one of the most important areas of gas engine application is in combined heat and power plants (CHPP), where engines are used to produce electricity and heat. Gas engines are also used to produce power independent of the grid in generator sets (gen-sets) and in mechanical drive applications for pumps and compressors (e.g., petrochemistry, oil and gas production, wastewater treatment). As future emission regulations for marine applications are becoming more stringent, manufacturers and shipping companies are increasingly interested in using gas and dual fuel (DF) engines for ship propulsion. In addition, the use of gas engines for the exploitation of special gases such as landfill gas, waste gas from industry, and flare gas is also gaining in importance [2], [3]. On the whole, there is a clear trend toward increased use of gaseous fuels for engine operation. Figure 2

___________________________________________________________________________________________________________ E. Schnessl, A. Wimmer: “Trends in the Development of Large Gas Engines for Power Generation”, pp. 1–10

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Figure 1. Development of resources for global power generation [1]

Figure 2. Orders received worldwide for large engines > 1 MW/engine

shows global development of orders for large engines for power generation with an output greater than 1 MW. It can be seen that the share of gas and DF engines nearly doubled from 2002 to 2012, achieving a share of almost 25%. Since it offers advantages in certain situations, however, the diesel engine still dominates. Any significant gains by gas engines will thus require further improvements in gas engine technology.

2. State of the art performance of Large Gas and DF Engines To describe state-of-the-art technology for large engines and to identify potential areas in gas and DF engines that require development, it is first necessary to determine the evaluation criteria. Figure 3 shows selected features in the areas of performance and robustness.

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Performance is characterized by load response, power output, emissions and efficiency while robustness consists of long-term stability, fuel flexibility and maintenance. The current state of diesel, gas and dual fuel engines have been evaluated according to these criteria. As shown in Figure 3, the diesel engine has more shortcomings than a modern gas engine with regard to PM, NOx and CO2 emissions (the over 30% advantage in CO2 of the gas engine is mainly due to the higher energy content in terms of mass and the lower carbon content of natural gas). In contrast, the Otto gas engine shows inherent advantages in emissions except for methane slip due to incomplete combustion and the loss of unburned gas during the scavenging phase. In recent years, the efficiency of the gas engine has improved significantly, and in this respect it has outperformed the diesel engine. To confirm this statement, Figure 4 presents the efficiencies that can be obtained with modern highspeed and medium-speed large gas and diesel engines in relation to NOX emissions. The limit of TA Luft is given in g/kWh to allow comparison with diesel engines. Typical emission limits for large diesel engines are the 7.4 g/kWh limit for locomotive engines corresponding to U.S. EPA Tier 2 and the 9.0 g/kWh limit for marine engines (calculated for an engine speed of 1000 rpm)

corresponding to IMO Tier 2. The disadvantage of the diesel engine arises in particular from the considerably higher NOX emissions from the diesel process caused by the high temperatures in the burned zone of nonpremixed combustion that proceeds near the stoichiometric air/fuel ratio. However, the diesel engine exhibits higher losses not only from losses from incomplete combustion but also from increased wall heat transfer due to the higher compression ratio as well as higher mechanical losses. Since measures such as EGR, increased injection pressure and post-injection have a negative effect on efficiency, improvements in emissions are presumably possible only on account of fuel efficiency, see [4]. The specific power output of the modern gas engine is nearly that of a diesel engine. However, there are still significant disadvantages in the areas of load response and robustness. A compromise between a diesel engine and a gas engine, the dual fuel engine has drawbacks mainly in diesel mode. As compared to the Otto gas engine, it has disadvantages in terms of particulate emission and fuel efficiency. On the other hand, load response behaviour is superior because during load changes, the gas mode is switched to pure diesel mode while accepting the Diesel specific disadvantages during these short periods of time (e.g. smoke).

Figure 3. Evaluating engine technologies ___________________________________________________________________________________________________________ E. Schnessl, A. Wimmer: â&#x20AC;&#x153;Trends in the Development of Large Gas Engines for Power Generationâ&#x20AC;?, pp. 1â&#x20AC;&#x201C;10

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Figure 4. Efficiencies of current high-speed and medium-speed large gas and diesel engines

3. Main challenges in the future development of Gas Engines Due to great increases in efficiency and power output in recent years, large gas engines for stationary power generation have registered significant growth, thereby obtaining a considerable boost. Figure 5 provides one example of such a gain, charting the development of the GE type 6 engine over the years. Starting with a value of 38% (1994), efficiency increased to over 47% (2013). Over the same time period, BMEP increased from 12 to 24 bar.

Figure 5. Increase in output and efficiency of the type 6 engine (GE Jenbacher)

In addition, low emission gas engines are favoured to solve the problem of how to meet the very stringent emission requirements for marine applications. Along with pure SI operation, dual fuel (DF) technology (from gas operation with diesel pilot injection to pure diesel operation) is a promising approach. In the meantime, DF technology is being intensively discussed for many other applications (such as locomotives). All in all, the inference is that gas and DF engines have great potential. To promote the use of environmentally sound gas and DF engine technology, the following challenges must be met:

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3.1. Dynamic behaviour

3.2. Robustness

Significant improvements in transient behaviour are necessary for gas engines to be used in areas currently dominated by diesel engines (e.g., mobile applications) and increasingly strict future requirements for stationary operation (island mode, grid parallel operation). The dynamic behaviour of the gas engine is inferior to that of a conventional diesel engine because the load acceptance of the gas engine is greatly limited by the knock limit, cf. [5]. This is especially true for high performance gas engines, which achieve a high level of efficiency and BMEP when operated with a very high compression ratio, extreme Miller valve timing and thus a high level of boost pressure as well as low turbocharger reserve. Dynamic behaviour can be improved through more robust engine design (e.g., lower BMEP, moderate Miller valve timing, lower boost pressure). However, this results in poorer efficiency and emission values. Thus one major goal must be to provide high performance gas engines with sufficiently transient behaviour. Dual fuel engines exploit the advantages of the diesel mode for transient operation. However, here too new strategies for more favourable transient behaviour must be developed in parallel to desired improvements in efficiency and emissions. The considerably higher number of degrees of freedom that resulting from operation with two fuels also represents a great challenge.

Along with worse dynamic behaviour, the gas engine also has the disadvantage that engine behaviour changes over runtime. This change is mainly caused by the formation of deposits on the combustion chamber walls and wear on the components involved in combustion. The limited service life of the spark plug shortens the maintenance interval for gas engines and represents a further drawback. Higher demands are also placed on high performance engines. Thus it is critical to design robust combustion concepts, and this design should be based on a profound understanding of wear mechanisms so that components can be optimized when appropriate.

3.3. Fuel sources Gas and dual fuel concepts face the additional challenge of great fluctuations in the quality of grid gas and liquefied natural gas (LNG). The quality of grid gas will fluctuate in the future because of the diversification of its sources and more importantly the more extensive feeding of biogas and hydrogen as well as synthetic natural gas (SNG) from power to gas facilities, cf. Figure 6. Current regulations make reference to either the calorific value or the Wobbe Index, each of which must be maintained within a narrow range. No specific requirements exist for the change in knock resistance (methane number), which is a deciding factor for gas engines. Currently the lowest methane number being discussed is 65 (+/-2), cf. [6].

Figure 6. Causes of fluctuating quality of grid gas ___________________________________________________________________________________________________________ E. Schnessl, A. Wimmer: â&#x20AC;&#x153;Trends in the Development of Large Gas Engines for Power Generationâ&#x20AC;?, pp. 1â&#x20AC;&#x201C;10

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Table 1: LNG composition with geographic variation [Mole Percent]

Figure 7. Flare gas

The composition and thus the quality of LNG are by nature highly dependent on the source, cf. Table 1. The different fractions of methane have a great impact on knock resistance. However, methane number is influenced not only by its source but also by the liquefaction process and the storage system, which can lead to different shares in heavier hydrocarbons. More and more large engines are being run on biogas and special gases. Special gas engines permit environmentally sound and energy efficient use of gases which would otherwise not be exploited, for example landfill gas, industrial waste gas and flare gas. There is clearly great potential for using flare gas to power engines. According to one estimate by GE, around 5% of global flare gas production is wasted annually, cf. Figure 7. Furthermore, gases with a very low calorific value (for example gases from steel production processes) are interesting as a future source of fuel for engines. In this context, dual fuel technology could be advantageous. However, gas composition has an impact on the different engine components, which must be designed accordingly.

3.4. Future emission limits Research and development expenditure is very heavily influenced by the development of the emission limits.

Very different emission regulations for large engines exist around the globe. These regulations define limits depending on the region and the application. Due to this variety, this paper will not described this legislation in detail. Since the permissible level of NOx emissions has a great influence on achievable efficiency and engine technology, Figure 8 provides an example of the future development of NOx limits in the EU for stationary lean burn gas, diesel and dual fuel engines. It shows the development of limits in the Gothenburg Protocol [7] and EU directive 2010/75/EU [8] in comparison to TA Luft. With the exception of a few regions, the EU limit of 200 mg/mn³ (with a 5% O2 concentration in the exhaust gas) is the strictest limit for lean burn gas engines. This limit can be considered to be the basic goal for stationary applications, yet it is imperative to achieve this limit without losses in efficiency. Gas engines are faced with yet another series of challenges due to the recent discussion of formaldehyde emissions. According to TA Luft, the emission of formaldehyde is limited to 60 mg/mn³. As soon as a substance is proven to be a carcinogen, TA Luft stipulates that its emissions must be reduced. In theory, formaldehyde emissions should be limited to 1 mg/mn³. Gas engines regularly emit significantly higher amounts of formaldehyde. This is true in particular of biogas engines, which can only be used after the gas has undergone an extensive purification procedure to

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Figure 8. Limits for stationary gas engines proposed by the EU

Figure 9. State-of-the-art development methodology (LDM) ___________________________________________________________________________________________________________ E. Schnessl, A. Wimmer: “Trends in the Development of Large Gas Engines for Power Generation”, pp. 1–10

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remove catalyst poisons. In the future, it will become increasingly important to avoid the formation of this pollutant within the engine. Like formaldehyde, the topic of methane slip has also stimulated much discussion in recent years in terms of its environmental impact [9]. The main component of natural gas, methane makes up the largest amount of THC emissions and has an impact on the greenhouse effect around 25 times greater than that of CO2. Greater legal regulation can be expected in this area. From the standpoint of total greenhouse gas emissions as well as efficiency, it is essential to reduce the level of THC emissions from the engine to a minimum; this reduction is thus an important research objective.

3.5. Increased output and efficiency Gas engines have already achieved a very high state of development in terms of efficiency and power. From a thermodynamic perspective, it is possible to improve the efficiency of gas engines by increasing the compression ratio even more. Dual fuel engines represent a compromise between gas engine and diesel engine technology. Introduced relatively recently, they are still in the initial stages of development. Further improvements in efficiency can be achieved in both modes of operation (gas mode and diesel mode) through intelligent combustion concept design. In general, any further increase in performance will be heavily influenced not only by thermodynamics but also by wear and durability, areas of particular importance. To sum up, the main challenges for the future development of gas engines are to improve robustness (higher fuel flexibility, long-term stability and maintenance), dynamic behaviour and methane slip. Fuel efficiency remains an issue in both operating modes of the dual fuel engine but is particularly challenging in diesel mode due to PM and NOx emissions; as with the conventional gas engine, robustness is one of the main issues in gas mode.

4. Development methodology

investigations on single-cylinder research engines (SCE), see Figure 9. The methodology makes use of threedimensional CFD simulation as well as zero- and onedimensional engine cycle simulation. While 3D CFD simulation is employed above all to optimize the details of relevant processes (e.g., mixture formation and combustion in the pre-chamber and main combustion chamber, determination of the location of knock), 0D/1D engine cycle simulation is applied to pre-optimize significant engine parameters (e.g., compression ratio, valve timing). Statistical methods such as the DoE method are used in both simulation and experiments, see [11], [12]. For this methodology to be applied, it must be guaranteed that the results from single cylinder tests can be transferred to the multicylinder engine (MCE). To this end, it is necessary to achieve boundary conditions comparable to those of the multicylinder engine, not only the thermal boundary conditions but also the conditions at the beginning of the intake stroke (temperature, pressure, and working gas composition). These conditions are determined in an iterative process based on 1D engine cycle simulation of the multicylinder engine and the single cylinder set-up. Simulation is conducted using commercially available tools (e.g., AVL FIRE, Converge, GT Power, AVL Boost). Research institutions and OEMs also develop and use simulation tools of their own. The LEC has developed its own software suite to describe relevant procedures. All in all, LDM is excellently suited to steady state combustion concept development (CCD) and has already been implemented to accomplish a variety of research and development tasks. New challenges have arisen from the transition to transient CCD and the expansion of a thermodynamically oriented approach to a multidisciplinary and much more comprehensive approach. In analysis and simulation, it is not yet possible to describe the highly complex processes in dual fuel combustion with sufficient precision; the general validity of the models is not fully known. In the experimental evaluation of combustion concepts on the single cylinder research engine, the limits of measuring techniques have been reached since the changes possible when developing new concepts have become extremely small.

4.1. State-of-the-Art-Methodology LEC Development Methodology (LDM) can be regarded as the state-of-the-art in development methodology [10], [11], [12]. Since its creation, many manufacturers and research institutions have come to rely on this method, which has established itself as the standard in the area of large engines (albeit under different names) [13], [14], [15]. LDM is used to develop and optimize combustion concepts and is based on the intensive interaction between simulation and experimental

4.2. Advanced Methodology New paths must be taken to improve applied technologies and development methodology for gas and dual fuel engines. This will require a transition to holistic treatment of all combustion-related processes. While LDM is currently focused on stationary development of combustion concepts, a significantly more comprehensive approach will be required in the future.

___________________________________________________________________________________________________________ E. Schnessl, A. Wimmer: â&#x20AC;&#x153;Trends in the Development of Large Gas Engines for Power Generationâ&#x20AC;?, pp. 1â&#x20AC;&#x201C;10

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Figure 10. Transition from LDM to LDM Advanced

As indicated in Figure 10, LDM Advanced, the latest version of LDM currently in use at the LEC, incorporates combustion-related aspects such as durability, wear, ignition, and fuel supply into the transient development of combustion concepts and controls. This necessitates detailed physical modelling of all effects and their suitable connection to the appropriate models. In the area of spark plug wear, for example, detailed models to describe spark initiation and removal of material along with parameters derived from thermodynamic simulation (e.g., heat transfer, gas composition, velocity, turbulence) must be made available and linked to an overall model. To accomplish this, integration of expertise from a variety of disciplines will be required. This comprehensive approach is used for all systems under consideration. Further examples of systems are controls (from the control concept itself to the optimal integration of the sensor into the cylinder head to durability and the algorithms for recognizing sensor errors) and ignition (from ignition initiation to flame kernel propagation and subsequent combustion).

development work will focus on measures to improve the robustness, dynamic behavior and fuel flexibility. The consideration and optimization of the entire system will become more and more important, thereby making the use of a comprehensive development methodology absolutely essential.

5. Conclusions

[1]

Warnecke, W., Karanikas, J., Levell, B., Mesters, C., Schreckenberg, J., Adolf, J., "Gas – Eine Brückentechnologie für zukünftige Mobilität?", 34 Internationales Wiener Motorensymposium, 25–26 April 2013.

[2]

Zauner, S., Arnold, G., Kopecek, H., Kumar, C.,Spreitzer, C., Trapp, C., Schneßl, E., Wimmer, A., „Nutzung von Gichtgas im Großgasmotor mit

An increase in achievable efficiency will not be the sole target of future development of gas engines. Further reduction of NOx emissions will be a considerable challenge. Very strict legislation is expected that will limit NOx and HC and make the use of exhaust gas after treatment imperative in many cases. In addition,

Acknowledgements The authors would like to acknowledge the financial support of the "COMET - Competence Centres for Excellent Technologies Programme" of the Austrian Federal Ministry for Transport, Innovation and Technology (BMVIT), the Austrian Federal Ministry of Science, Research and Economy (BMWFW) and the Provinces of Styria, Tyrol and Vienna for the K1-Centre LEC EvoLET. The COMET Programme is managed by the Austrian Research Promotion Agency (FFG).

References

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Hilfe zylinderdruckbasierter Motorregelung und Zweigasbetrieb“, 3 Rostocker Großmotorentagung „Die Zukunft der Großmotoren III – Großmotoren im Spannungsfeld von Emissionen, Kraftstoffen und Kosten“ 18–19 September 2014. [3]

Wimmer, A., Schneßl, E., Simon N., “HyWood – Nachhaltige Strom- und Wärmeerzeugung mit wasserstoffreichem Synthesegas aus Biomasse“, Submission and nomination for the Energy Globe Styria Award, Graz 2016.

[4]

Wimmer, A., Pirker, G., Engelmayer, M., Schnessl, E., “Gas Engine Versus Diesel Engine: A Comparison of Efficiency”, MTZ Industrial 11:2-6, 2011.

[5]

CIMAC Working Group "Gas Engines": Position Paper "Transient Response Behaviour of Gas Engines", Conseil International des Machines a Combustion, April 2011.

[6]

EUROMOT 2013: "Gas Quality Harmonisation", The European Association of Internal Combustion Engine Manufacturers – EUROMOT, 18 September 2013.

[7]

Gothenburg Protocol 2010: "Protocol to the 1979 convention on long-range transboundary air pollution to abate acidification, eutrophication and ground-level ozone", Gothenburg, 1999, available in the internet, URL: http://www.unece.org/env/lrtap/multi_h1.htm, Status: 30.07.2010.

[8]

Council of the European Union: Interinstitutional File: 2007/0286 (COD), Brussels, 2009, Annex V S. 14.

[9]

EUROMOT 2012: Euromot Position "Methane Slip from Internal Combustion Gas Engines", The European Association of Internal Combustion Engine Manufacturers – EUROMOT, 27. April 2012.

[10]

Kogler, G., Wimmer, A., Eichlseder, H., Schnessl, E., Winter, H., "Methodology in the Development Process of Large Gaseous Fuelled Engines". – ICE 2003-0575 (2003), S. 547 – 557. Spring Technical Conference of the ASME Internal Combustion Engine Division; 2003.

[11]

Wimmer, A., Winter, H., Schnessl, E., Pirker, G., Dimitrov, D., “Brennverfahrensentwicklung für die nächste Gasmotorengeneration von GE Jenbacher,” 7th Dessau Gas Engine Conference, Dessau, Germany, March 24–25, 2011.

[12]

Wimmer, A., Pirker, G., Schnessl, E., Trapp, C., Schaumberger, H., Klinkner, M., “Bewertung von Simulationsmodellen zur Brennverfahrensauslegung für die neue Generation von Großgasmotoren,” 10th International Symposium on Combustion Diagnostics, BadenBaden, Germany, May 22–23, 2012.

[13]

Auer, M., Friedrich, C., Waldenmaier, U., Knafl, A., Stiesch, G., "Combustion Development Methodology for MAN Diesel & Turbo Large Bore Gas Engines", 14th Conference "The Working Cycle of the Internal Combustion Engine", Graz 2013.

[14]

Schlemmer-Kelling, U., Hamm, T., Reichert, E., Struckmeier, D., "FEV Single Cylinder Engine Family for large engine applications of MAN", 22nd Aachen Colloquium Automobile and Engine Technology 2013.

[15]

Trapp, Ch., „The Future of Gas Engines – A Technology Comparison with Diesel Engines in the Light of Legislation and Market“, 14th Conference "The Working Cycle of the Internal Combustion Engine", Graz, 2013.

[16]

Krenn, M., Pirker, G., Mühlberger, M., Wimmer, A., “Einsatz der DoE-Methode zur simulationsbasierten Optimierung von Großgasmotoren,” 14th Working Process of the Internal Combustion Engine Conference, Graz, 2013.

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DOI: 10.14621/ce.20160202

A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology – A New Multidisciplinary Experimental Model Michel Joel Tchatchueng Kammegne1, Ruxandra Mihaela Botez1*, Teodor Lucian Grigorie1, Mahmoud Mamou2, Youssef Mebarki2 1

École de Technologie Supérieure 1100 Notre Dame West, H3C 1K3, Montreal, Quebec, Canada; ruxandra.botez@etsmtl.ca 2 National Research Council Canada 1200 Montréal Road, K1A 0R6, Ottawa, Ontario, Canada

Abstract

1. Introduction

The research presented in this present paper was done within the framework of the international CRIAQ MDO505 Morphing Wing project, developed as a collaborative research project between academia, research centres and industry partners. The work exposed in the paper is related to the development of an experimental morphing wing model and its performance evaluation by using some wind tunnel tests. This collaborative research aimed at the drag reduction over a wing by morphing it, conducting in this way at fuel savings and low emissions. The association between the drag reduction and wing morphing comes from the fact that if the wing airfoil shape is changed in a specific way then the laminar to turbulent flow transition point position can be moved toward its trailing edge. The model designed, fabricated and tested during our project is based on the dimensions of a full scale wing tip structure, equipped with a morphable flexible upper surface made from composite materials and deformed by using four miniature electrical actuators, with an array of 32 Kulite pressure sensors to monitor the air flow behaviour over the upper surface, and with an aileron also electrical actuated. The first specific objective for our research team in this project was to develop a new morphing mechanism for the wing by using miniature electrical actuators; these actuators should deform the upper wing surface, so that the laminar-to-turbulent transition point moves closer to the wing trailing edge reducing in this way the drag force as a function of flow condition by changing the wing shape. The flow conditions were univocally defined by mean of Mach numbers, airspeeds, angles of attack and aileron deflection angles. The second specific objective was to develop a control system for the morphing actuators to obtain the desired morphed shape of the wing for each studied flow case, while the third specific objective was to develop a monitoring system able to detect and visualize the airflow characteristics using pressure sensors installed on the upper surface of the morphing wing, evaluating in this way the gains brought by the proposed architecture. During the paper sections are successively exposed the project description, the morphing wing model instrumentation and the mechanisms used to control it. Finally, a wind tunnel aerodynamic results analysis is performed, discussing the extension of the laminar region of the flow over the wing by using the morphing wing technology.

Regarded as one of the promising technologies in terms of saving fuel and limit emissions in the aerospace industry, the morphing technology has undergone various ways of implementation, among which highlights the morphing wing. The advantages of this technology have been proven by developing and testing numerous experimental models both in Industrial laboratories and in the laboratories of universities and research institutes. The researches were carried out both by local projects involving a single institution, and through collaborative projects with large industrial impact, involving entities from all sectors of aerospace field, and integrating human resources and expertise from academia, research and testing, and industry. The mechanism that has been identified morphing wing technology impact on fuel consumption was to improve the aerodynamic performance of the vehicle by reducing the drag. Therefore, technical solutions were sought to change the wing shape as a function of the flight conditions so as to obtain an extension of the laminar flow on its surface, extension equivalent with a decrease in drag force [1]-[20].

Keywords:

Energy save; Drag reduction; Morphing wing; Experimental testing; Wind tunnel; IR analysis

Article history:

Received: 09 April 2016 Revised: 30 October 2016 Accepted: 03 November 2016

A research team from the Royal Melbourne Institute of Technology, Australia, developed and tested in the wind tunnel a wing model morphed by using SMA actuators; a significant change in the lift to drag ratio was detected when the wing was morphed [1]. In another study was performed the aerodynamic design optimisation of a micro air vehicle wing to obtain the optimal antisymmetric wing twist distribution, with the aims to produce minimum induced drag and to achieve a better roll response [2]. A multiloop controller for the aeroelastic morphing unmanned aerial vehicle concept was formulated by a collaborative research team from USA and Spain; the approach successfully enabled inflight transformation between vehicle states in less than

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one minute, while maintaining the overall vehicle stability and control [3]. At Virginia Tech, USA, the using of macro fiber composite actuators in morphing unmanned vehicles was tested; an important improvement of the lift to drag ratio was experimented as a consequence of wing morphing [4]-[6]. A concept of hexagonal chiral honeycomb structure for adaptive wing box configurations was proposed at University of Sheffield, UK [7]. A collaborative research between Portugal and Canada used a multidisciplinary design optimization tool, coupling an aerodynamic shape optimization code with a structural morphing model to obtain a set of optimal wing shapes for minimum drag at different flight speeds [8]. The optimum drag reduction as a consequence of the airfoil morphing was also investigated at University of Tokyo, Japan [9]. From another perspective of the morphing technologies, a topology optimization approach for determining the distribution of structural properties and actuators to design a morphing wing that is capable of achieving multiple target shapes was realized at University of Ohio, USA [10]. Several experiments on flow control using an adaptive circular arc airfoil were also performed at University ok Kentuky, USA [11]. At RTM Nagpur University, India, a variable camber wing model using multi section ribs was designed and tested [12]. From the aerodynamic optimization perspective, a very interesting study has been realised at Purdue University, USA, where the energy was used as objective in the optimization process of a morphing airfoil [13]. Based on the fact that dynamic loads are essential for the design of any morphing-wing aircraft, several studies were conducted at University of Texas at Arlington, USA, to develop methodologies suitable for numerical calculation of the dynamic loads for morphing wing aircraft [14], [15]. At Cranfield University, UK, has been realised an investigation into the concept and optimal design of a lightweight seamless aeroelastic wing (SAW) structure for small air vehicles; two innovative design features have been created in the SAW trailing edge

section: an open sliding trailing edge and a curved beam and disc actuation mechanism [16]. A collaborative research team realized an experimental analysis of low speed flow over an adaptive airfoil with oscillating camber; the experimental results were compared to a series of CFD simulations in order to evaluate, among others, the effectiveness of the oscillating camber as a flow control mechanism [17]. At Middle East Technical University, Ankara, Turkey, was performed the modelling and aeroelastic analysis of an adaptive camber wing subjected to low-speed subsonic flow; the camber variation was controlled at six spanwise stations, the actuation force magnitudes being determined iteratively using linearized influence coefficients [18]. Researchers from University of Toronto, Canada, developed an aerodynamic optimization algorithm and used it to assess an adaptive airfoil concept for drag reduction at transonic speeds [19]. A review of the morphing aircraft, with specific focus on modelling and flight control of large-scale planform altering flight vehicles, proceeded to demonstrate in a fundamental manner that, although design methods for rigid aircraft have become highly developed, the consideration of morphing necessitates further investigation into the typically disparate fields of dynamic modelling, aerodynamic theory, and flight control theory [20]. In order to develop such green aircraft technologies, our research team from Research Laboratory in Active Controls, Avionics and AeroServoElasticity (LARCASE) at École de Technologie Supérieure in Montréal, Canada, developed some morphing wing projects. In a first project, called CRIAQ 7.1 (Consortium for Research and Innovation in Aerospace in Quebec), a morphing wing experimental model was realized at LARCASE laboratory (Figure 1). During this project, new methodologies to morph a wing by using smart actuators and various control techniques, starting from open loop control architectures to closed loop real time optimization of

Figure 1. Wind tunnel experimental model for CRIAQ 7.1 project ___________________________________________________________________________________________________________ M. J. Tchatchueng Kammegne et al: “A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology …”, pp. 11–21

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Test chamber

Figure 2. Morphing wing model in Price- Païdoussis subsonic wind tunnel

the morphing wing controller, were developed and experimentally validated [21]-[40]. In the open loop architecture, the research team proposed and validated few control techniques for the morphing wing actuation system, based on classical or intelligent methodologies. On the other way, simulations and experimental methods pertinent to transition location detection has been presented [35], [36], [40]. In another morphing wing project developed by our team, a wing prototype with an integrated actuation mechanism was fabricated and tested at Ecole de Technologie Superieure in Montreal (Figure 2). In this project instead of using adaptive materials such as SMA and piezoceramic actuators, a new approach using electrical actuators coupled to two actuation lines was tested. A control system was designed for the actuation system to obtain the optimized profile for each considered flight case. The actuator position was controlled using a cascade control algorithm. The aerodynamic results obtained in our Price-Paidoussis wind tunnel were compared with the numerical results predicted by XFoil software in the optimization phase [41]-[44]. The here exposed work refers to the morphing wing studies of the LARCASE team related to a new CRIAQ project, Multi-Disciplinary Optimization 505 (MDO 505), aiming at fuel consumption optimization by applying morphing wing technology to a real aircraft wing. The project, realized at École de Technologie Supérieure in Montréal, Canada, is the result of a collaborative multidisciplinary research team, integrating human resource coming from partners in Canada and Europe. The industrial partners in Canada are Bombardier Aerospace and Thales, while in Europe is Alenia Aerospace. The universities and research institutes participating in Canada are École de Technologie Supérieure (ETS), École Polytechnique and Institute of Aerospace research at National Research Council of

Canada (IAR-NRC). Universities and research centres participating from Europe are Frederico II Naples University and Italian Aerospace Research Center (CIRA) [45]-[46].

2. Morphing wing project In this research project, a wing-aileron prototype was designed, tested and validated using win tunnel tests at National Research Council Canada (IAR-NRC). The multidisciplinary research team of the project was divided into three sub-teams covering aerodynamic, structural, and control fields. The main aims of the project were to reduce the operating costs for the new generation of aircraft through in-flight fuel economy, and also to improve aircraft performances, expand its flight envelope, replace conventional control surfaces, reduce drag to improve range and reduce vibrations and flutter risk [47]. The first specific objective for our research team in this project was to develop a new morphing mechanism using miniature electrical actuators for a full-scaled portion of the wing of a real aircraft equipped with an aileron. The actuators deform the upper wing surface, made of a flexible skin, so that the laminar-to-turbulent transition point moves closer to the wing trailing edge reducing in this way the drag force as a function of flow condition by changing the wing shape. The flow conditions were univocally defined by mean of Mach numbers, airspeeds, angles of attack and aileron deflection angles. The second specific objective was to develop a control system for the morphing actuators to obtain the desired morphed shape of the wing for each studied flow case, while the third specific objective was to develop a monitoring system able to detect and visualize the airflow characteristics using pressure sensors installed on the upper surface of the morphing wing.

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Figure 3. Wing structure and actuations lines positions

Figure 4. 3D view of the morphing wing structure ___________________________________________________________________________________________________________ M. J. Tchatchueng Kammegne et al: “A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology …”, pp. 11–21

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The used experimental wing segment was with a maximum chord of 1.5 m, and a minimum one of 1.08 m, and has three distinct parts: 1) a metal part, which has the structure as in the original aircraft wing; 2) a morphing part, consisting of a flexible skin installed on the upper surface of the wing; and 3) an actuated aileron (Figure 3 [47], [48]. The first part structure includes four ribs, two at the ends (Rib 1 and Rib 4), and two inside (Rib 2 and Rib 3) having also the role to support the actuators. The morphing skin, made from composite materials, allowing the wing shape changing, was positioned on the upper side of the wing between 20% and 65% of the wing chord (Figure 4). To morph the flexible skin were used four similar actuators disposed on two actuation lines positioned at 37% and 75% of the wing’s span. The actuators were positioned at 32% and 48% of the local wing chord on each of the two actuation lines. The actuators were fixed on the wing ribs and the top were attached to the flexible skin with screws. The actuation mechanism architecture supposed the direct actuation of the flexible skin by the four actuators. This architecture, with estimated forces of over 1300 N per actuator, correlated with the small space inside the morphed wing (the wing thickness varies between 10 cm and 20 cm), and with small maximum displacement (maximum 5 mm) imposed serious size/power constraints to the actuators. To meet both the requirements of size and power, the actuator was designed in-house by using some components acquired on the market such as the miniature brushless direct current (BLDC) motor [47]. To establish the optimum shape of the wing for a specific flow condition an optimization phase was performed by the aerodynamic team of the project. The optimization procedure was applied for several combinations of Mach numbers (M), angles of attack (α) and aileron deflection angles (δ). An in-house developed genetic algorithm was used in the iterative optimization process, with the objective to search the optimum shapes for an airfoil through local thickness changes to improve the upper surface flow. The optimization started from a reference airfoil shape, and was a complex one, needing several interactions between the genetic algorithm parameters, objective function, aerodynamic solver and shape reconstruction using spline interpolation [48]. For each optimized airfoil resulted four vertical displacements corresponding to the positions of the four actuators. Actually, the optimization gave the displacement values for one pair of actuators situated at 37% of the wing span, while the displacements for the second pair of actuators were calculated as a linear dependence [48]. All optimization results were stored in a database in order to be used as reference vertical displacements for the control system. The aerodynamic performance of the morphing wing model was tested in wind tunnel at Institute for

Aerospace Research at the National Research Council Canada (IAR-NRC) in Ottawa for ninety seven flow cases. The tested flow cases were obtained as combinations of nineteen values for the angle of attack (varied from -3 degree to +3 degree), three values for the Mach number (0.15, 0.2, 0.25) and thirteen values for the aileron deflection angle (varied between -6 degrees an +6 degrees). For each case, the flexible upper surface of the wing was actuated in order to obtain the four optimized values of the vertical displacements corresponding to the four actuation points and stored in the aerodynamic database. The evaluation of the laminar-to-turbulent transition location was performed by using the pressure data obtained from 32 high precision Kulite piezoelectric-type sensors placed on the flexible skin on two closes chord lines [46]-[48].

3. Instrumentation of the experimental model For the four morphing actuators was developed a control system able to control theirs linear positions. Actually, the control system included four similar controllers software implemented, able to modify the actuators linear positions until the real displacements of the morphing skin in the four actuation points equalled the desired displacements of the optimized airfoil resulted for a flow case. The feedback signals containing the actuators positions are provided by four Linear Variable Differential Transformers (LVDT). From the point of view of the control system were developed and tested various controllers, based on classical or intelligent techniques. The controllers were preliminary tested in the lab conditions, in the absence of the airflow, together with the associated software and hardware components included in the experimental model (Figure 5) [47]. The experimental model instrumentation was developed around a National Instrument equipment and included a NI PXIe-1078, 9-Slot 3U PXI Express Chassis, a NI PXIe-8135 embedded controller, four NI PXIe-4330 Data Acquisition Cards with Integrated Signal Conditioning for Bridge-Based Measurements, a NI PXI8531, 1-Port CANopen Interface, a NI PXIe-6356 Simultaneous X Series Data Acquisition Card, a SCXI1000 rugged, low-noise chassis that can hold up to four SCXI modules, a NI SCXI-1540 8-Channel LVDT Input Module, a NI SCXI-1315, and two Programmable power supplies Aim-TTi CPX400DP. The next test of the experimental model was in the wind tunnel (Figure 6), the pressure signals being logged in parallel while the shape of the airfoil changed. A Graphical User Interface (GUI) was developed for the control system and for the data acquisition system. Simultaneously with the control system characteristics monitoring, the user visualized on a parallel screen the real time Fast Fourier Transforms (FFT) associated to the

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Figure 5. Bench test at École de Technologie Supérieure in Montréal

Figure 6. Wind tunnel testing of the experimental model

32 Kulite pressure sensors equipping the upper surface flexible skin. As a secondary method to evaluate the transition point position over the entire wing model surface for each tested flow case the infra-red (IR) thermography was used. In this way, visualizations with a Jenoptik Variocam camera were performed to measure the surface temperatures [49].

4. Wind tunnel experimental results To evaluate the aerodynamic gain of the morphing wing technology on the experimental model, the recorded pressure data during the wind tunnel tests were post processed in order to obtain the pressure coefficient distribution curve and the spectral repartition of the pressure. The transition region determined by the flow separation and characterized by the amplification of the

Tollmien-Schlichting waves was captured by the Kulite pressure sensors. The same aerodynamic gain was also evaluated by using the infra-red thermography technique. The pressure data were recorded at 20 kHz rate, for both un-morphed and morphed airfoils in ninety-seven flow cases, and were analysed using Fast Fourier Transforms (FFT) decomposition to detect the magnitude of the noise in the surface air flow. Subsequently, the data were high pass filtered at 1 kHz and processed by calculating the standard deviation (STD) of the signal to obtain a plot diagram of the pressure fluctuations in the flow boundary layer. Ninety seven flight cases were tested in the wind tunnel, obtained as combinations between nineteen values for the angles of attack (between - 3deg. and +3 deg.), three values for the Mach numbers (between 0.15 and 0.25), and thirteen for the aileron deflection angles (between - 6deg. and +6 deg.).

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Figure 7. STD of the pressure data acquired for Mach=0.15, α=-2˚, δ=-2˚ flow case

Figure 8. FFT of the pressure data acquired for Mach=0.15, α=-2˚, δ=-2˚ flow case ___________________________________________________________________________________________________________ M. J. Tchatchueng Kammegne et al: “A Fuel Saving Way in Aerospace Engineering based on Morphing Wing Technology …”, pp. 11–21

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Figure 9. IR visualisation for Mach=0.15, α=-2˚, δ=-2˚ flow case

For the flow case associated to Mach=0.15, α=-2˚, δ=-2˚, Figure 7 presents the STDs of the acquired pressure data both for un-morphed and morphed airfoils. It results that the transition for un-morphed airfoil begins on the pressure sensor #16 (placed at 50.79% of the wing chord), while for morphed airfoil it begins on the sensor #19 (placed at 53.45% of the chord). On the other way, the maximum value of the STD for un-morphed airfoil was associated with the sensor #20 (placed at 54.60% of the chord), while for morphed airfoil was associated with the sensor #22 (placed at 56.87% of the chord). In the same flow case, the FFT plots for the two airfoils (unmorphed and morphed) are shown in Figure 8. The FFT associated to the un-morphed airfoil shows that the curve corresponding to the sensor #17 is easiest detached indicating the transition beginning. A more visible detachment appears at the level of the sensors #18 and #19, producing the transition to the upper FFT curves package. For the morphed airfoil, the FFT characteristics show that the transition begin on the sensor #20, the maximum influenced FFT curves corresponding to the sensors #21 to #23. As a consequence, the FFT and STD based conclusions are similar for this flow case, the laminar region being extended with over 3% of the chord in the Kulite sensors section. The infra-red thermography visualizations (from 0% to 70% of the chord) of the extrados for this flow case with and without any morphing applied are shown in Figure 9. The wind blow from the left to the right, the blue

region indicates the low-temperature area associated with the laminar flow, while the yellow region indicates the high temperature area associated with the turbulent flow. The transition area of the 3D-wing was averagely represented by the black line and delimited by the two white lines along the wing span. The IR average transition in this flow case was 53.18% of the chord for the un-morphed airfoil and 56.89% of the chord for the morphed airfoil. Therefore, according to the IR analysis, for this flow case the laminar region was extended with an average value of 3.71% of the chord by using the morphing wing technology.

5. Conclusions The paper presented the morphing wing technology benefits on a wing-aileron prototype designed, developed and experimentally tested in wind tunnel during a collaborative research project between industry and academia. The main objective of the research was to control the morphing of the wing for various flow conditions, defined by mean of Mach numbers, airspeeds, angles of attack and aileron deflection angles, in order to obtain the displacement of the laminar-to-turbulent transition point closer to the wing trailing edge, and to produce in this way a higher laminar flow region on the airfoil which generates a decrease of the drag force. To evaluate the aerodynamic gain of the morphing wing technology on our experimental model, the recorded pressure data during

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the wind tunnel tests were post processed in order to obtain the pressure coefficient distribution curve and the spectral repartition of the pressure. The data were analysed using Fast Fourier Transforms (FFT) decomposition to detect the magnitude of the noise in the surface air flow. Subsequently, the data were high pass filtered at 1 kHz and processed by calculating the standard deviation (STD) of the signal to obtain a plot diagram of the pressure fluctuations in the flow boundary layer. As a secondary method to evaluate the transition point position over the entire wing model surface for each tested flow case the infra-red (IR) thermography was used. The wind tunnel testing results exposed in the paper, and obtained with the FFT, STD and IR evaluations for the flow case associated to Mach=0.15, α=-2˚, δ=-2˚, have shown that the transition was delayed by about 3%. From the STD analysis resulted that the transition for un-morphed airfoil started on the pressure sensor #16 (placed at 50.79% of the wing chord), while for morphed airfoil it started on the sensor #19 (placed at 53.45% of the chord). On the other way, the maximum value of the STD for unmorphed airfoil was associated with the sensor #20 (placed at 54.60% of the chord), while for morphed airfoil was associated with the sensor #22 (placed at 56.87% of the chord). Similar results, based also on the pressure sensors data, were obtained from the FFT analysis. On the other way, the infra-red thermography visualizations (from 0% to 70% of the chord) of the extrados shown that the IR average transition in this flow case was 53.18% of the chord for the un-morphed airfoil and 56.89% of the chord for the morphed airfoil. The experimentally obtained results were promising for all flow cased tested in the wind tunnel during our project, proving the fulfilment of the project main objective. Generated as combinations between nineteen values for the angles of attack (between - 3deg. and +3 deg.), three values for the Mach numbers (between 0.15 and 0.25), and thirteen for the aileron deflection angles (between - 6deg. and +6 deg.), the ninety seven tested flow cases provided ninety seven desired optimized airfoils, obtained by changing the upper surface of the wing in the vertical direction. The testing results for all of these cases confirmed the feasibility of the morphing wing technology, and, having in mind that our project used a real wing structure, create the premises for a future application of this technology on real aircrafts.

thank the Consortium for Research and Innovation in Aerospace in Quebec (CRIAQ) and the National Sciences and Engineering Research Council (NSERC) for their funding of the CRIAQ MDO 505 project. Thanks are also due to Master student Yvan Tondji for his help in the data post-processing.

References [1]

Abdullah, E. J., Bil C.,Watkins, S., Numerical Simulation of an Adaptive Airfoil System using SMA Actuators, 48th AIAA Aerospace Sciences Meeting Including The New Horizons Forum and Aerospace Exposition, Orlando, Florida, US, 2010.

[2]

Ahmed, M.R., Abdelrahman, M.M., ElBayoumi, G. M., and ElNomrossy, M.M., Optimal wing twist distribution for roll control of MAVs, The Aeronautical Journal, Royal Aeronautical Society, 115, 641-649, 2011.

[3]

Baldelli, D.H., Lee, D.H., Sanchez Pena R.S., and Cannon, B., Modeling and Control of an Aeroelastic Morphing Vehicle, Journal of Guidance, Control, and Dynamics, 31(6), 16871699, 2008.

[4]

Bilgen, O., Kochersberger, K.B., and Inman, D.J., Macro-Fiber Composite Actuators for a Swept Wing Unmanned Aircraft, The Aeronautical Journal, Royal Aeronautical Society, 113, 385395, 2009.

[5]

Bilgen,O., Kochersberger, K.B., Inman, D.J., and Ohanian, O.J., Novel, Bidirectional, VariableCamber Airfoil via Macro-Fiber Composite Actuators, Journal of Aircraft, 47(1), 303-314, 2010.

[6]

Bilgen, O., Kochersberger, K.B., Inman, D.J., Ohanian, O.J. Macro-fiber composite actuated simply supported thin airfoils, Smart Materials and Structures, Vol. 19, No. 5, 2010, pp. 055010.

[7]

Bornengo, D., Scarpa, F., and Remillat, C., Evaluation of hexagonal chiral structure for morphing airfoil concept, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 219(3), 185192, 2005.

[8]

Gamboa, P., Vale, J., Lau, F. J. P., and Suleman, A., Optimization of a Morphing Wing Based on Coupled Aerodynamic and Structural Constraints, AIAA Journal, 47(9), 2009.

[9]

Hiroharu, S., Kenichi R., Asei T., Laminar airfoil modification attaining optimum drag reduction by use of airfoil morphing, Journal of Aircraft, 47 (4), pp. 1126-1132, 2010.

Acknowledgemts The authors would like to thank the Thales Avionics team for their support - especially Mr. Philippe Molaret, Mr. Bernard Bloiuin, and Mr. Xavier Louis, as well as the Bombardier Aerospace team, Mr. Patrick Germain and Mr. Fassi Kafyeke in particular. We would also like to

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

ISSN 2363-6440

___________________________________________________________________________________________________________

[10]

Inoyama, D., Sanders, B.P., and Joo, J.J., Topology Optimization Approach for the Determination of the Multiple-Configuration Morphing Wing Structure, Journal of Aircraft, 45(6), 1853-1863, 2008.

[11]

Jacob, J.D., Aerodynamic Flow Control Using Shape Adaptive Surfaces, Paper No. DETC99/VIB8323, ASME Conference, 1999.

[12]

Nadar, A. et al, Design and Analysis of MultiSection Variable Camber Wing, International Journal on Mechanical Engineering and Robotics, 1(1), pp. 122-128, 2013.

[13]

Namgoong, H., Crossley, W.A., and Lyrintzis, A.S., Aerodynamic Optimization of a Morphing Airfoil Using Energy as an Objective, AIAA Journal, 45(9), 2113-2124, 2007.

[14]

Obradovic, B., and Subbarao, K., Modeling of Dynamic Loading of Morphing-Wing Aircraft, Journal of Aircraft, 48(2), 424-435, 2011.

[15]

Obradovic, B., and Subbarao, K., Modeling of Flight Dynamics of Morphing-Wing Aircraft, Journal of Aircraft, 48(2), 391-402, 2011.

[16]

Perera, M., and Guo, S., Optimal design of an aeroelastic wing structure with seamless control surfaces, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 223(8), 1141-1151, 2009.

[17]

Raymond P. Le Beau, Jr., Anthony K., Nan-Jou P., Jacob J., Analysis of Low Speed Flow over an Adaptive Airfoil with Oscillating Camber, 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, AIAA Paper No.2010-93, Florida, 2010.

[18]

Seber, G., and Sakarya, E., Nonlinear Modeling and Aeroelastic Analysis of an Adaptive Camber Wing, Journal of Aircraft, 47(6), 2067-2074, 2010.

[19]

Zingg, David W., Diosady, L., Billing, L., Adaptive airfoils for drag reduction at transonic speeds, AIAA Journal, Vol. 3656, 2006.

[20]

Seigler, T.M., Neal, D.A., Bae, J.S., and Inman, D.J., Modeling and Flight Control of Large-Scale Morphing Aircraft, Journal of Aircraft, 44(4), 1077-1087, 2007.

[21]

Botez, R.M., Grigorie, T.L., Popov, A-V., Mamou, M., and Mébarki, Y., A New Morphing Wing Mechanism Using Smart Actuators Controlled by a Self-Tuning Fuzzy Logic Controller, AIAA Centennial of Naval Aviation Forum “100 Years of Achievement and Progress”, 2011.

[22]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., On-off and proportional-integral

controller for a morphing wing. Part 1: Actuation mechanism and control design, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 226/2, 2012, pp. 131-145. [23]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., On-off and proportional-integral controller for a morphing wing. Part 2: Control validation–numerical simulations and experimental tests, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 226/2, 2012, pp. 146-162.

[24]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., A hybrid fuzzy logic proportionalintegral-derivative and conven-tional on-off controller for morphing wing actuation using shape memory alloy. Part 1: Morphing system mechanisms and controller architecture design, Aeronautical Journal, 116 (1179), 2012, pp. 433449.

[25]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., A hybrid fuzzy logic proportionalintegral-derivative and conven-tional on-off controller for morphing wing actuation using shape memory alloy. Part 2: Controller implementation and validation, Aeronautical Journal, Vol. 116, No. 1179, 2012, pp. 451-465.

[26]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., Controller and Aeroelasticity Analysis for a Morphing Wing, AIAA Atmospheric Flight Mechanics (AFM) Conference, Aug. 8-11, Portland, Oregon, SUA, 2011.

[27]

Grigorie, T.L., Botez, R.M., Adaptive Neuro-Fuzzy Inference Controllers for Smart Material Actuators, 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 12-15 April, Orlando, Florida, USA, 2010.

[28]

Grigorie, T.L., Botez, R.M., Neuro-Fuzzy Controller for SMAs for a Morphing Wing Application, 51st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 12-15 April, Orlando, Florida, USA, 2010.

[29]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., An Intelligent Controller Based Fuzzy Logic Techniques for a Morphing Wing Actuation System Using Shape Memory Alloy, 52nd AIAA/ ASME/ ASCE/ AHS/ ASC Structures, Structural Dynamics and Materials Conference, Denver, CO, USA, 4-7 April 2011.

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

ISSN 2363-6440

___________________________________________________________________________________________________________

[30]

Grigorie, T.L., Popov, A.V., Botez, R.M., Control of Actuation System Based Smart Material Actuators in a Morphing Wing Experimental Model, AIAA Atmospheric Flight Mechanics (AFM) Conference, Boston, MA, USA, 19-22 August, 2013.

[31]

Grigorie, T.L., Popov, A.V., Botez, R.M., Control Strategies for an Experimental Morphing Wing Model, AIAA Aviation 2014, AIAA Atmospheric Flight Mechanics (AFM) Conference, Atlanta, GA, 16-18 June, 2014.

[32]

Grigorie, T.L., Popov, A.V., Botez, R.M., Mamou, M., Mébarki, Y., A New Morphing Wing Mechanism Using Smart Actuators Controlled by a Self-Tuning Fuzzy Logic Controller, 11th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, 20-22 Sept., Virginia Beach, VA, SUA, 2011.

[33]

Grigorie, T.L., Popov, A.V., and Botez, R.M. Design and Experimental Validation of a Control System for a Morphing Wing, AIAA Atmospheric Flight Mechanics Conference, 2012.

[34]

Popov, A.V., Botez, R.M., Labib, M., Transition point detection from the surface pressure distribution for controller design, Journal of Aircraft, 45 (1), 2008, pp. 23-28.

[35]

[36]

Labib, M., Popov, A., Fays, J., and Botez, R.M. “Transition Point Displacement Control on a Wing Equipped with Actuators”, AIAA Guidance, Navigation and Control Conference, 2008. Popov, A.V., Botez, R.M., Mamou, M., Grigorie, T.L., Variations in Optical Sensor Pressure Measurements due to Temperature in Wind Tunnel Testing, Journal of Aircraft, 46, 1314-18, 2009.

[37]

Popov, A.V., Grigorie, T.L., Botez, R.M., Mamou, M., Mébarki, Y., Real time morphing wing optimization validation using wind-tunnel tests, Journal of Aircraft, Vol. 47, No. 4, 2010, pp. 13461355.

[38]

Popov, A.V., Grigorie, T.L., Botez, R.M., Mamou, M., Mébarki, Y., Closed-loop control validation of a morphing wing using wind tunnel tests, Journal of Aircraft, Vol. 47, No. 4, 2010, pp. 1309-1317.

[39]

Popov, A.V., Grigorie, T.L., Botez, R.M., Mamou, M., Mébarki, Y., Modeling and Testing of a Morphing Wing in Open-Loop Architecture, Journal of Aircraft, 47, 917-23, 2010.

[40]

Silisteanu, P-D, and Botez, R-M. Transition-FlowOccurrence Estimation: A New Method, Journal of Aircraft, 47, 703-08, 2010.

[41]

Gabor, O.S., Koreanschi, A., Botez, R.M., Lowspeed aerodynamic characteristics improvement of ATR 42 airfoil using a morphing wing approach, IECON 38th Annual Conference on IEEE Industrial Electronics Society, Montreal, Canada, 2012.

[42]

Kammegne, M.J.T., Grigorie, T.L., Botez, R.M., Koreanschi, A., Design and Validation of a Position Controller in the Price-Paidoussis Wind Tunnel, Proceedings of Modelling, Simulation and Control Conference, Innsbruck, 17-19, Feb. 2014.

[43]

Kammegne, M.J.T., Grigorie, T.L., Botez, R.M., Koreanschi, A., Design and wind tunnel experimental validation of a controlled new rotary actuation system for a morphing wing application, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, January 2016, vol. 230, no. 1/2016, pp. 132-145.

[44]

Mosbah, B.A., Flores Salinas, M., Botez, R.M., Dao, T., New methodology for wind tunnel calibration Using Neural Networks, SAE International Journal of Aerospace, Vol. 6, No. 2, pp.761-766, 2013.

[45]

Khan, S., Botez, R.M., Grigorie, T.L., A New Method for Tuning PI Gains for Position Control of BLDC Motor Based Wing Morphing Actuators, AIAA Modeling and Simulation Technologies Conference, Dallas, TX, 22-26 June, 2015.

[46]

Kammegne, M.J.T., Nguyen, D.H., Botez, R.M., Grigorie, T.L., Control validation of a morphing wing in an open loop architecture, AIAA Modeling and Simulation Technologies Conference, Dallas, TX, 22-26 June, 2015.

[47]

Kammegne, M.J.T., Grigorie, T.L., Botez, R.M., Design, numerical simulation and experimental testing of a controlled electrical actuation system in a real aircraft morphing wing model, The Aeronautical Journal of the Royal Aeronautical Society, Volume: 119, No. 1219, pp. 1047-1072, September 2015.

[48]

Kammegne, M.J.T., Botez, R.M., Mamou, M., Mebarki, Y., Koreanschi, A., Sugar Gabor, O., Grigorie, T.L., Experimental wind tunnel testing of a new multidisciplinary morphing wing model. 18th International Conference on mathematical methods, computational techniques and intelligent systems (MAMECTIS '16), Venice, Italy, January 29-31, 2016

[49]

Mebarki, Y., Mamou, M., Genest, M. Infrared Measurements of the Transition Detection on the CRIAQ Project Morphing Wing Model, NRC LTR AL-2009-0075, 2009.

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DOI: 10.14621/ce.20160203

The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming Reactor Ivana Ivanović1*, Aleksandar Sedmak2, Miloš Milošević1 1

Innovation Center, Faculty of Mechanical Engineering, University of Belgrade Kraljice Marije 16, 11120 Belgrade 35, Serbia; ivanovicivana@hotmail.com 2 Faculty of Mechanical Engineering, University of Belgrade Kraljice Marije 16, 11120 Belgrade 35, Serbia

Abstract

1. Introduction

This study deals with geometry of the inlet part of a packed bed methanol steam reforming reactor, which is a component of the specific high temperature indirect internal reforming polymer electrolyte membrane fuel cell stack. Important elements of the reactor geometry are predefined as well as the inlet and the outlet boundary conditions, the catalyst volume and properties; it remains to be examined how the rest of geometry, a geometry that could be changed, should be modelled to achieve desired efficiency. In this initial stage of analysis, the flow was treated as steady, laminar, incompressible, with inserted porous media, with constant temperature and without chemical reaction. It was concluded that applied changes of the inlet channel and the inlet chamber geometry have no significant influence on pressure drop trough the reactor. Possible corrections of the inlet geometry, which result in more favourable flow distribution, were proposed.

The research in the field of polymer electrolyte membrane fuel cell (PEMFC) is intensifying in recent years. According to results so far it seems that PEMFCs are efficient clean portable energy source if continuous supply of hydrogen as fuel is ensured. The supply of hydrogen must be resolved in such a way to produce minimum carbon monoxide as a pollutant by-product. It is evident that necessity of supplying PEM fuel cells with hydrogen lunched a number of parallel series of studies related to methanol steam reforming in micro reactors, as methanol is known to be a good source of hydrogen.

Keywords:

Methanol steam reforming reactor; Heterogeneous catalyst bed; Laminar flow; Computational fluid dynamics

Article history:

Received: 15 April 2016 Revised: 31 October 2016 Accepted: 04 November 2016

The main differences in the approach to methanol steam reforming is where the process take place. It can be external, in the reformer which is independent of the fuel cell, or, it can be internal, direct or indirect. In the internal reforming fuel cell, heat of the system is used for reforming process which is endothermic. In the direct internal reforming fuel cell methanol, or other fuel, is supplied directly to the anode where the catalyst is placed. In the indirect internal reforming fuel cell, which is the subject of this study, the reformer exists, and it is placed in the fuel cell stack as well as other devices necessary for the reforming process. Upon review [1], the first study analyzing reforming in indirect internal reforming high temperature fuel cell was an experimental study published in 2005 in Ref. [2]. The stack in Ref. [2] was composed of reformer, made of aluminum and packed with CuO/ZnO/Al2O3 catalyst, and two high temperature PEMFCs. Methanol water mixture was supplied from evaporator which was placed externally, outside of fuel cell stack. The reforming temperature was between 180-200℃. Resulting performance was lower than in the case of the same fuel cell stack directly supplied with the mixture of H2 and CO2.

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The way in which packed bed micro methanol steam reformers developed during last decade can be seen from experimental and numerical studies given in Refs. [3] – [7]. In the work of Pattekar and Kothare from 2005 (Ref. [3]) the radial micro rector with integrated vaporizer was presented. The reactor was packed with commercial Cu/ZnO/Al2O3 catalyst as in Ref. [2]. Experimental study and numerical study, which used inhouse FORTRAN code, were performed. It was demonstrated that that reformer produced hydrogen for up to 20W of power. The same type of the reformer was studied in Ref. [4]. Kinetics of the model and pressure drop are calculated using in-house Matlab code. The goal was to produce hydrogen for 24W and 72W of power which was achieved. The analysis of carbon monoxide as by-product was also presented in Ref. [4]. Design, extensive experimental analysis, and 3D thermal analysis of real micro reactor are presented in Ref. [5]. Copper based catalyst was again used in the form of packed bed. Special attention was paid to heat transfer and insulation of the reforming system. The study presented in Ref. [6] from 2015 is noteworthy since it gives an extensive experimental and CFD analysis of three packed bed reformers with different geometry: multi-channel, radial, and tubular. Full 3D CFD analysis with power low kinetic model was performed and results were compared to experimental results. Another comprehensive experimental and complete 3D CFD analysis of plate-type micro methanol steam reforming reactor is given in Ref. [7]. In this study the 3D CFD analysis was performed in order to determine the influence of free flow area geometry of the micro methanol steam reforming reactor on velocity distribution and pressure drop in packed bed reaction chamber of the reactor.

2. Model description The external dimensions and shape of the reformer stack correspond to the dimensions of the fuel cell stack. It is composed of three plates, illustrated in Figure 1a. A middle plate, with a thickness of 4 mm, contains a reaction volume and inlet and outlet channels. The initial geometry of the reaction volume with channels is presented in Figure 1b. The dimension of the reaction volume is 34×37.4×4 mm. The catalyst bed in the reaction volume is expected to be separated from the channels with stainless steel mesh. Diameters of the inlet and the outlet are 3 mm. In the changeable part, there is 3.5 mm in length between the center of the inlet and the steel mesh, and 5.5 mm between the steel mesh and the center of the outlet. The inlet channel, or the outlet channel, consists of vertical pipe like geometry that leads to, or from, small chamber. The reforming reactor is placed between fuel cell stack and the thick insulation wall. It is expected that it will be heated by the fuel cell and that the temperature of the top surface of the upper plate of the reactor will be between 180 and 240 ℃. When the heat transfer is included into calculations, with the constant temperature at the top boundary surface, insulation at the bottom boundary surface, and the flux to the surroundings at side boundary surfaces, temperature differences are very small, approximately 0.5 ℃, mostly at edges and corners of the plates. According to this results, heat transfer was excluded from calculations, temperature of the system is treated as constant with the value of 180 ℃. The methanol-water mixture ratio 1:1.3, and flow rate at the inlet is from 2.923⋅10-6 m3/s and below. The catalyst particle diameter is 300 μm, bulk density is around 1.1 g/mL, and catalyst density is around 4.7 g/mL.

Figure 1. Methanol steam reformer stack (a.) and the initial geometry of the reaction volume with inlet and outlet channels (b.) ___________________________________________________________________________________________________________ I. Ivanović, A. Sedmak, M. Milošević: “The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming …”, pp. 22–28

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3. Numerical modelling In this first series of calculations chemical reaction have not been taken into consideration. Stainless steel mesh, which holds catalyst in place, was also excluded from geometry. The flow was modeled as steady, laminar, viscous, with inserted porous media. Free flow in the inlet and the outlet channel is given by incompressible continuity equation ∇ =0

(1)

and steady incompressible Navier-Stokes equations

∇ =∇− +

∇ + ∇

(2)

Flow in reaction volume, i.e. in the inserted packed bed catalyst porous media, is given by Brinkman equation ∇ =∇ − +

∇ + ∇

(3)

where ε and k are porosity and permeability respectively. When heat transfer is included into calculations Temperature of the fluid was set to constant value of 180 ℃. The density of the methanol-water mixture was calculated from the ideal gas low relation

= RT

(4)

Molar mass of ideal gas mixture is given as sum of molar masses of its components =∑

(5)

where xi are mole fractions of methanol and water. Flow rate was imposed as laminar inlet boundary condition, and zero gage pressure was imposed at the outlet.

4. Results and discussions Simulations were carried out on desktop PC with Intel Core i5-2300 CPU on 2.8 GHz and 16 GB RAM memory. Since the heat transfer of the system has not been taken into consideration only the inner volume geometry of the reformer was used.

4.1. Results for initial geometry The first set of calculations for the initial geometry were executed for inlet flow rates of 2.923 10-6 m3/s,

1.949⋅10-6 m3/s, and 0.974⋅10-6 m3/s. To get the feel of the flow, the streamlines of the flow field for the highest inlet flow rate are illustrated in Figure 2. The fully developed laminar flow enters through a vertical pipe to a reformer chamber very close to a packed bed catalyst, continues through the catalyst porous media, end exits through an elbow of a horizontal channel, through the channel, and through vertical pipe. The dominate feature of the central part of the inlet chamber flow is recirculation (see Figure 2). Recirculation is present in the case of all inlet flow rates as illustrated in Figure 3, and, as expected, weakens with decreasing of flow rate intensity. There will be more discussion about velocity field further in the text; important for this group of simulations is influence of inlet flow rate on pressure drop, which develops mainly in the porous media. It can be seen from Figure 4 that difference in pressure at the exit from the porous media is negligible compared to the difference at the entrance. As expected, higher inlet flow rate produces higher pressure in the inlet channel and consequently larger pressure drop in porous media. The flow rate difference of approximately 1⋅10-6 m3/s results in a pressure difference of approximately 40 Pa. The gage pressures in the inlet and the outlet channel are illustrated in Figure 5 to demonstrate that the pressure differences in these parts of reformer are negligible compared to pressure difference in porous media. It can be seen from Figure 5 that the order of magnitude of these pressure drops is 10-2 Pa.

4.2. Potential corrections in inlet geometry The fact is that structure of the flow field in the inlet and the outlet channel must depend, among other, on their geometry. Previously, it was demonstrated that the geometry of the inlet channel results in recirculation, and, that the pressure drop in two channels is negligible compared to the pressure drop in the porous media. Some changes of the inlet channel are introduced and their influence on the flow field were examined. These changes were mostly focused on the recirculation. First, the sidewalls of the inlet channel are rotated to tangent the inlet pipe. Thickness of the initial inlet channel is 4mm, and it has been narrowed so that the whole bottom surface was raised 2 mm, (b, Figure 6). The simulations were executed only for the highest inlet flow rate. The recirculation was still present in the flow of the inlet channel. As illustrated in Figure 7, pressure closest to the top of the chamber in the entrance region of the porous media is insignificantly higher than the pressure in the case of basic geometry. The pressure at the other levels is now

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Figure 2. Streamline presentation of the velocity field for the inlet flow rate of 2.923⋅10-6 m3/s

Figure 3. Streamlines in the inlet channel and at the entrance to a porous media for inlet flow rates 2.923⋅10-6 m3/s (left), 1.949⋅10-6 m3/s (center), and 0.974⋅10-6 m3/s (right) at cross section y = 0

Figure 4. Values of velocity (left) and gage pressure (right) for three different inlet flow rates along the porous media in the cross-section y = 0 at z = 0.002 m ___________________________________________________________________________________________________________ I. Ivanović, A. Sedmak, M. Milošević: “The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming …”, pp. 22–28

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Figure 5. Gage pressure in the inlet channel (left) and in the outlet channel (right) for the highest inlet flow rate in the cross-section y = 0 at z = 0.002 m

Figure 6. Initial inlet geometry (a) compared with a change in the form of step (b), and a step combined with curved bottom surface (c)

Figure 7. Pressure for the step change in the entrance region of the porous media at different levels in cross section y = 0 compared with the pressure for the highest flow rate of the initial geometry at level z = 0.002 mm ___________________________________________________________________________________________________________ I. Ivanović, A. Sedmak, M. Milošević: “The Influence of Inlet Geometry on the Performance of a Methanol Steam Reforming …”, pp. 22–28

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Figure 8. Streamline presentation of the velocity field in the case of inclined step surface for the inlet flow rate of 2.923⋅10-6m3/s

Figure 9. Velocity magnitude values in z cross sections of the inlet channel for initial geometry (a) and for the step geometry (b) in the case of the highest inlet flow rate

influenced by the presence of the step. This influence is obvious in first few millimeters of the length where the pressure rapidly approaches the pressure of the initial geometry. In further attempt to improve geometry of the inlet channel, the inclined wide cylindrical form has been cut from the step geometry (see c, Figure 6). As illustrated in Figure 8, the result was flow liberated from recirculation. In addition, the influence of the step that was illustrated in Figure 7 was less apparent, but the pressure was insignificantly lower than the pressure in the case of original geometry. The impression is that the geometry of the inlet channel has to be somewhere in between changed geometries

and the initial geometry. From Figure 9 left, it is obvious that the flow in the case of initial geometry is not evenly distributed at all levels of the inlet chamber. The best distribution is in the vicinity of the cross-section z = 1.5 mm, almost at the bottom of the reformer. There is a large gap caused by recirculation at z = 2.5 mm, near the entrance to a chamber, and the gap near the top wall is even larger (bottom left, Figure 9). Step geometry is illustrated in Figure 9 right. As mentioned step starts at z = 2 mm. Velocity magnitude is higher according to shallower space of the chamber. There is the space with very high velocity near the entrance at level z = 2.5 mm but the flow in whole inlet chamber is better distributed than in the case of initial geometry.

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Sustainable Energy Reviews, vol. 29, p. 355–368, 2014.

5. Conclusions In this work, only flow field in the reformer was analyzed, heat transfer and chemical reaction were excluded from calculations. The flow field was examined for three different inlet flow rates and two changes in the inlet chamber geometry. It was demonstrated in which way changes in geometry of the inlet chambers influence flow field distribution and pressure drop. Presented study is less then initial for this type of problems. In further studies heat transfer and chemical reaction must be introduced in the calculations. This includes numerous parameters with uncertain values which indicates that sensitivity analysis must be performed.

Acknowledgements This research was carried out under the NATO Science for Peace Project EAP.SFPP 984738, and the Ministry of Education and Science of the Republic of Serbia project III 43007 The authors gratefully acknowledge colleagues from Slovenian National Institute of Chemistry for help in resources as well as in suggestions and comments.

[2]

C. Pan, R. He, Q. Li, J. O. Jensen, N. J. Bjerrum, H. A. Hjulmand and A. B. Jensen, "Integration of high temperature PEM fuel cells with a methanol reformer," Journal of Power Sources, vol. 145, p. 392–398, 2005.

[3]

A. V. Pattekar and M. V. Kothare, "A radial microfluidic fuel processor," Journal of Power Sources, vol. 147, p. 116–127, 2005.

[4]

J. C. Telotte, J. Kern and S. Palanki, "Miniaturized Methanol Reformer for Fuel Cell Powered Mobile Applications," International journal of chemical reactor engineering, vol. 6, no. 1, pp. 1542-6580, 2008.

[5]

K. Shah and R. Besser, "Understanding thermal integration issues and heat loss pathways in a planar microscale fuel processor: Demonstration of an integrated silicon microreactor-based methanol steam reformer," Chemical Engineering Journal, vol. 135S, p. S46–S56, 2008.

[6]

P. Ribeirinha, M. Boaventura, J. C. B. Lopes, J. M. Sousa and A. Mendes, "Study of different designs of methanol steam reformers: Experiment and modeling," International journal of hydrogen energy, vol. 39, pp. 19970-19981, 2014.

[7]

A. Pohar, D. Belavič, G. Dolanc and S. Hočevar, "Modeling of methanol decomposition on Pt/CeO2/ZrO2 catalyst in a packed bed microreactor," Journal of Power Sources, vol. 256, pp. 80-87, 2014.

References [1]

A. Iulianellia, P. Ribeirinhab, A. Mendesb and A. Basilea, "Methanol steam reforming for hydrogen generation via conventional and membrane reactors: A review," Renewable and

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DOI: 10.14621/ce.20160204

Thermal Imaging and Uncertainties in the Interpretation: Case Study Gordana Laštovička-Medin Faculty of Sciences and Mathematics, University of Montenegro Džodrdža Vašingtona bb, 20000 Podgorica, Montenegro

Abstract

1. Introduction

This paper presents a case study of thermal imaging. It explores the challenges in the interpretation of thermal imaging. In particular, it analyses the uncertainties and the sources of inaccuracies. The rapid technological development leads to the paradoxical situation where there is a higher amount of users of thermal imaging than the amount of those who understand the physics behind it and know how to interpret the colourful images of the false colour displays since it is sometimes very difficult to quantitatively describe observations due to background interfering conditions such as thermal reflection, shadow effects of nearby objects etc. This paper tackles this problem. It focuses on the identification and qualitative interpretation of source uncertainties. It is not intended to be an exhaustive list of all possible uncertainties but rather shows many qualitative examples. Images shown here were taken as part of the Low Carbon Household Thermal Image Survey. The given information might be beneficial for those who want to make their own household energy loss investigations and for those who want to use thermal imaging in as an educational tool for the visualizations of phenomena in physics and chemistry related to energy transfer. In particular this paper can be beneficial for those who want to study the cross-correlation effect amongst independent and uncorrelated uncertainty sources as well as to link the investigations of accuracy in measurement interpretations to the investigations of ambient features and distant dependant measurements.

Thermal imaging technology has become increasingly popular at colleges and universities in both the classrooms and the labs. It can help to visualize and thereby enhance the understanding of physical phenomena from mechanics, thermal physics, electromagnetism, optics and radiation physics, qualitatively as well as quantitatively, in an interactive and engaging way [1], [2], [3]. A few concepts that can be easily visualized with a thermal imaging camera include: the thermal properties of materials and objects, heat conduction, convection, radiation, heat insulation and friction.

Keywords:

Thermal imaging; Uncertainties; Interpretation; Emissivity; Reflection; Infrared radiation

Article history:

Received: 26 April 2016 Revised: 30 October 2016 Accepted: 03 November 2016

This paper explores the applications of thermal imaging for enegy loss visualisations. The work was done by the supportive and informal Low Community Carbon Group [4]. The aim was to find out how to reduce carbon footprint substantially and to raise awareness of climate change locally and at the same time promoting a more sustainable lifestyle through redusing the energy consumption and increasing the energy efficiency. The qualitative analyses were only done without providing a metrological evaluation of the commercially available infrared camera, since only one camera type had been used. The camera type was Flir. For methodology research we refer to [3], where the author suggests how to best estimate the accuracy of thermal imaging instruments, whilst considering the level of accuracy attributed to measurements from these thermal imagers. The paper is structured as follows. It begins with an introduction to the infrared thermography applications. Then the terminology and concepts are explained and followed by a description of the property of measurement and uncertainty sources. The uncertainty issues such as emissivity and reflectivity were explored in Chapter 7, whilst Chapter 8 presents the interpretation of images. The measurement error analyses of a thermal imaging were only considered

___________________________________________________________________________________________________________ G. Laštovička-Medin: “Thermal Imaging and Uncertainties in the Interpretation: Case Study”, pp. 29–41

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qualitatively since for the quantitative analyses we would need a more accurate knowledge of a materials’ emmisivity to what we didn’t have reliable access. While it is reasonable to interpret uncertainties qualitatively, the quantitative interpretation of the measured temperatures can only be undertaken once they have been converted into meaningful temperatures.

2. Infrared thermograph application Thermal imaging can be helpful in quantifying heat losses and for condition monitoring. It can also be used effectively to identify changes in the condition of an object over time by spotting a trend of changing temperatures. Most frequently, thermal imaging is used to find abnormalities or unusual patterns of radiated heat which are indicative of a fault or excessive heat loss.

The use of thermal imaging technology in industries and in science is illustrated in Figure 1 [5]. Additionally there is a growing field of medical diagnostic thermography (breast abnormalities, thyroid abnormalities, musculoscelatal, peripheral vascular, cerebral vascular, inflammatory and neoplastic conditions). The reason to use thermal imaging technology in medical diagnostics because temperature is a very good indicator of health, as changes of just a few degrees on the skin (cutaneous or superficial) can be used as an indicator of possible illnesses [6]. For example, IRT is used to detect superficial body tumors, such as breast cancer [7]. Tumors generally have an increased blood supply that increases the skin temperature over them [8]. Therefore, IRT can be used as an effective early indicator of breast cancer [9], which results in a much higher chance of survival [10]. In these applications, IRT is a complementary diagnostic tool with high efficiency only in the detection of early warning signals. This early

Figure 1. Different aspect of thermal imaging applicatios [5] ___________________________________________________________________________________________________________ G. Laštovička-Medin: “Thermal Imaging and Uncertainties in the Interpretation: Case Study”, pp. 29–41

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Figure 2. Medical diagnostic thermography [16]

Figure 3. Medical diagnostic thermography [18]

detection is the main advantage of IRT compared with other methods. IRT is used in many other medical applications, such as the diagnosing of diabetic neuropathy or vascular disorders [11], fever screening [12], skin diseases [13], dentistry and dermatology [14] and heart operations [15]. Moreover, functional infrared thermal imaging (fITI) is considered as an upcoming, promising methodology in psychophysiology (Figure 2) [16]. Furthemore, functional infrared imaging was also used to study the facial thermal signatures of three fundamental emotional conditions: stress, fear and pleasure arousal [17]. Neurodevelopmental disorder

characterized by impaired social interaction, verbal and non-verbal communication, and restricted and repetitive behaviour such as autism can be monitored using the thermal imaging technology as well. Figure 3 [18] shows images captured during the treatment of autistic children. It clearly idicates behavioural change in body temperature emissions before and after treatment. For more details in medical Infrared Imaging we refer to [19]. To conclude, number of applications for thermal imaging is rapidly growing because IRT has many advantages over other technologies [20]. In general, the

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main advantages of IRT are the following: IRT is a noncontact technology: the devices used are not in contact with the source of heat, i.e., they are non-contact thermometers; IRT provides two-dimensional thermal images, which make a comparison between areas of the target possible, IRT is in real time, which enables not only high-speed scanning of stationary targets, but also acquisition from fast-moving targets and from fastchanging thermal patterns; IRT has none of the harmful radiation effects of technologies, such as X-ray imaging and thus, it is suitable for prolonged and repeated use; IRT is a non-invasive technique, thus, it does not intrude upon the target or affect it in any way and it can also be easily incorporated into neurological and psychological studies or work with children with behaviour disorders and neurological diversity [21]. However, IRT is not without its drawbacks. Fast and affordable hardware has recently become available, but an infrared camera is still an expensive device. Other, inexpensive models with high spatial resolution provide lower accuracy, which makes them unusable for some applications. Infrared images can also be difficult to interpret; in general, specific training is required. IRT is also highly dependent on working conditions, such as the surrounding temperature, airflow or humidity. Thus, progress on accuracy of image interpretation in needed.

3. Physics laws of infrared radiation In order to acquire good knowledge of image interpretation it is important to firstly understand the important terms and concepts behind them as well as the procedure of converting thermal (infrared radiation) into electric signal which visualizes the invisible (to

human eye – infrared) energy to a visible image on the camera’s screen. Infrared measuring devices acquire infrared radiation emitted by an object and transform it into an electronic signal [22]. Thermal radiation is electromagnetic radiation emitted over a range of wavelengths by an object related to the object’s temperature. The infrared ray is part of electromagnetic radiation covering the “band” of wavelength between 0.78 m to 1000 m as shown in Figure 4 [23]. The temperature of the object, along with other factors, determines the intensity at each wavelength. Radiation thermography is the use of a sensor to measure the thermal radiation emitted by an object, generally with the intent to determine the object’s temperature [24]. Sensors often contain only a single sensing element and yield a single measurement value. By contrast, a thermal camera uses a focal plane array (FPA), which is an array of sensors. By displaying the array of measured values, an image is formed which is a representation of the temperature distribution on the surface of the object. Each element of the array is a pixel. Each pixel corresponds to a location in space of the scene being imaged, this is called a scene. True temperature refers to the actual temperature of an object. Apparent temperature refers to the temperature reported by a ‘perfect’ camera, and includes properties of the scene being imaged such as emissivity and reflections [24]. Note that this is not necessarily the same as the imaged temperature, which is the temperature reported by the actual camera, and also includes properties of the image acquisition process such as scattering in the camera optics. It is important to remember that thermal cameras do not actually measure temperature. They

Figure 4. The electromagnetic spectrum [23] ___________________________________________________________________________________________________________ G. Laštovička-Medin: “Thermal Imaging and Uncertainties in the Interpretation: Case Study”, pp. 29–41

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measure intensity of electromagnetic radiation within a range of wavelengths during a period of time (the integration time of the camera). The difference between a visible image and an infrared image is that the visible image is a representation of the reflected light on the scene, whereas in the infrared image, the scene is the source and can be observed by an infrared camera without light. Images acquired using infrared cameras are converted into visible images by assigning a colour to each infrared energy level. The result is a false-colour image called a thermogram [25]. The calibration of the camera allows the user to convert these measured intensities to imaged temperatures. Imaged temperatures may be converted to apparent temperatures, and apparent temperatures may then be converted to true temperatures, if one has a qualitative and quantitative understanding of the physical properties of the objects, the characteristics of the camera, as well as the conditions encountered while acquiring the images. Attaining accurate true temperatures is generally the goal when using thermal cameras. The wavelengths of light being detected depend on the spectral response of the camera and any filters used [24] In order to understand the difference between apparent temperature and true temperature, it is important firstly to understand four basic laws of infrared (IR) radiation: Kirchhoff's law of thermal radiation, Stefan-Boltzmann law, Planck’s law, and Wien’s displacement law. The characteristics of thermal radiation depend on various properties of the surface it is emanating from, including its temperature, its spectral absorptivity and spectral emissive power, as expressed by Kirchhoff's law of thermal radiation which states that: “For a body of any arbitrary material emitting and absorbing thermal electromagnetic radiation at every wavelength in thermodynamic equilibrium, the ratio of its emissive power to its dimensionless coefficient of absorption is equal to a universal function only of radiative wavelength and temperature. That universal function describes the perfect black-body emissive power”. [26]. It is important to note that the thermal radiation is not monochromatic, i.e., it does not consist of just a single frequency, but comprises a continuous dispersion of photon energies, its characteristic spectrum. If the radiating body and its surface are in thermodynamic equilibrium and the surface has perfect absorptivity at all wavelengths, it is characterized as a black body. A black body is also a perfect emitter. The radiation of such perfect emitters is called black-body radiation. Planck's law describes the spectrum of blackbody radiation, which depends only on the object's temperature. The temperature determines the wavelength distribution of the electromagnetic radiation. Thus, the distribution of power that a black

body emits with varying frequency is described by Planck's law. At any given temperature, there is a frequency fmax at which the power emitted is a maximum. Wien's displacement law, and the fact that the frequency is inversely proportional to the wavelength, indicates that the peak frequency fmax is proportional to the absolute temperature T of the black body. Wien's displacement law determines the most likely frequency of the emitted radiation, and the Stefan–Boltzmann law gives the radiant intensity [27]. The intensity of the radiation depends on the temperature and nature of the materials’ surface. At lower temperatures, the majority of this thermal radiation is at longer wavelengths. As the object becomes hotter, the radiation intensity rapidly increases and the peak of the radiation shifts towards shorter wavelengths. The relationship between the total radiation intensity (all wavelengths) and temperature is defined by the Stefan- Boltzmann law which reflect relationship between the power radiated by a dense hot body and the temperature (P = e A σ T4 (W) where the variable T represents the absolute temperature, A is the surface area of the radiator, and e is the emissivity, a function of emitted wave length; for a perfect black body e = 1 and the Stefan Boltzmann Constant, σ, is equal to 5.67 x 10-8 W/(m2 K4). The Plank and the Stefan- Boltzmann laws are linked as follows. Energy radiated from the blackbody is described by Planck’s Law but in order to obtain total radiant emittance of the blackbody, the equation describing Plank's law has to be integrated over all wavelengths (0 to infinity). The result is the Stefan- Boltzmann equation. In order to find out the wavelength on the maximum spectral radiant emittance, differentiate Planck’s law and take the value to 0.

4. The concept of working the thermal imaging camera The concept of working the thermal imaging camera (See Figure 5 [23]) is as follows: Infrared energy (A) coming from an object is focused by the optics (B) onto an infrared detector (C). The detector sends the information to the sensor elecronics (D) for image processing. The electronics translate the data coming from the detector into an image (E) that can be viewed on the viewfinder or on a standard video monitor or LCD screen [23]. Infrared thermography is the art of transforming an infrared image into a radiometric one, which allows temperature values to be read from the image. So every pixel in the radiometric image is in fact a temperatue measurement. In order to do this, complex algorithm are incrporated into thermal image camera.

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5. Infrared thermometer vs. imaging camera

Figure 5. Thermal imaging camera [23]

It is important to distinguish IR thermometer from the thermal imaging camera. Infrared (IR) thermometer are reliable and very useful for single spot temperature reading, but when scanning large areas, it is easy to miss critical parts like the air leakages [23]. A comparison between the images captured by infrared thermometer and those captured by a thermal imaging camera is displayed in Figure 6 [23]. With an infrared thermometer one is able to measure the temperature at one single spot. FLIR thermal imaging cameras can measure temperature on the entire images. For example FLIR (Forward Looking InfraRed) i3 has an image resolution of 60 x 60 pixels. This means tha it is equal to using 3600 IR thermomeers at the same time.

6. Properties of measurement and nature of uncertainty sources

Figure 6. The comparison between the visualization of what a IR thermometer and a thermal camera see [23]

Thermal imaging cameras detect and measure the sum of infrared energy over a range of wavelengths determined by the sensitivity of the camera’s detector. Thermal imagers cannot discriminate energy at 7µm from energy at 14µm the way the human eye can distinguish various wavelengths of light as colour. They calculate the temperature objects by detecting and quantifying the emitted energy over the operational wavelength range of the detector. The temperature is then calculated by relating the measured energy to the temperature of a blackbody radiating an equivalent amount of energy according to Planck’s Blackbody Law.

Identification, characterization and verification of uncertainties when detecting the loss of heat due to faulty insulation are complex procedures. The possible errors assigned to a measurement system itself is the following: calibration of camera sensitivity and systematic offsets in sensor, conversion of apparent to true temperature, camera optics, electronic effects, instrument error from instrument noise, integrated averaging of radiance over increasing pixel area due to increased viewing distance (decreased resolution) etc. Other uncertainty sources are linked to ambient conditions such as weather humidity, atmospheric pressure and ambient temperature. For example infrared sensed data can be subjected to errors greatly due to atmospheric attenuation by atmospheric scattering caused by particulate material in the atmosphere and absorption by gases. The errors arising from viewing the surface at an oblique angle can significantly affect the measurement accuracy and thus the validity of data/image interpretation. The uncertainty in calibration of camera, sensitivity and offset may be linked to incorrect adjustment of camera to emissivity of inspected object. Furthermore, the dependency of camera sensitivity towards polarization of the measured thermal radiation brings uncertainty as well. So to improve accuracy the camera system must vary as a function of polarization angle. Also an incomplete understanding of resolution (the smallest possible distance between two values of measurement) and repeatability (the range of values attained by repeated measurements under the same conditionals) may be a significant source of uncertainty. For instance, since the response of camera is a linear function of intensity but it is not a linear function of temperature, as a consequence resolution of the temperature

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measurement depends on the temperature being measured and not on true temperature. In some cases the effect of non-uniform emissivity can be avoid using long integration time. Moreover one of the essential issues is to apply the suitable form of Plank equation in order to convert apparent true temperature. As clearly explained in [28] there are multiple modification of Plank’s equation in the literature. As many parameters (reflectivity, transmittance, atmospheric absorption, changes in emissivity as a function of temperature) are taken into account, the more realistic description of energy loss can be achieved. However, there are many issues unique to a measurement procedure and each source of uncertainty may be of greater or lesser importance depending on the specific quantity measured. For example, in certain cases camera sensitivity and pixel cross talk are of major concern. By contrast, when measuring a peak temperature motion blue effects are likely to be more important. So it is important to understand how those error sources affect the measurement uncertainty and to link the investigation of errors to the investigation of uncertainties because they do not exclude each other. In some cases the investigation of components of the combined standard uncertainty requires the conducting the study for uncorrelated input variables of the measurement model because estimation of the influence of cross-correlations among the variables on measurement accuracy is an important issue. The influence of correlations depends on measurement conditions and these may differ significantly. For example, the combined standard uncertainty may depend strongly on the correlation between variables representing the object emissivity and the ambient temperature. Additionally, variables representing the ambient and atmospheric temperature may affect the temperature measurement uncertainty to some extent as well. To determine which uncertainty sources are of most concern it is crucial to consider which are important to the question being asked. As with any measurement system there are sources of uncertainty that must be understood to fully assess the quality of the measurement result. It is also useful to remember that any temperature measurement is valid only at some location during some time interval. This leads to characterisation of uncertainties such as amplitude, temporal and special [28]. For instance if temperature a short distance away have very different amplitudes due to large thermal gradients in the image, even a modest spatial uncertainty can cause a large amplitude uncertainty regardless of how well the sensitivity of the camera is known. There are many other issues involved with uncertain analysis which are described elsewhere [29].

7. Uncertainty sources: Emissivity and reflectivity Interpreting a thermal image takes a degree of skill and understanding. Different materials and surfaces emit heat at different rates, so some allowance must be made for the construction of each different object inspected. Additionally, thermal imaging cameras cannot distinguish between emitted and reflected infrared energy so the user must be aware of any other sources of infrared energy that may cause reflection and must be able to recognise these in thermograms. Angular variation in emissivity may also bring uncertainty in data interpretaton so analysis with increased viewing distances as they vary both along the view path (atmospheric effects) and across the image (viewing distance and atmospheric effects) especially if viewing obliquely would increase image interpretation accuracy. Thus in order to get the correct interpretation of thermal images it is important to put the object of inspection into the environmental context, taking into account the texture and interaction of materials with radiation as well. An assessment of how accurately the attenuation and distance measurements need to be made in order to obtain useful temperature measurements is essential. It is important to look at all the possible interferences between object and surrounding that may affect the way object's features appear in a camera's display. For instance wind, humidity or pressure can mislead the meaning of image captured by camera. Further, since materials have different thermal conductivity, the difference in thermal conductivity of materials can lead to large temperature variations in certain situations. Reflection and emission are other issues which have to be carefully taken into consideration. Those issues will be discussed later. The ambient temperature may also affect the result and alter the accuracy significantly. For instance, high ambient temperature can mask hot spots by heating the entire object while a low ambient temperature might cool down the hot spots to a temperature below a previously determined threshold. However, not only weather conditions, but also indoor and outdoor temperature can alter the accuracy of interpretations and mislead the conclusion. The nature of ventilation and heating system in the household may bring additional uncertainty in measurement interpretation. Among the issues previously mentioned, the emissivity is one of the key unfamiliar concepts causing the inaccurate interpretation. The reason is explained as follows. Emissivity is defined [30] as the ratio of the radiance emitted by a surface to the radiation emitted by blackbody at the same temperature. The spectraldirectional emissivity of a surface at a given temperature is the ratio of the radiance of the radiation emitted at a particular wavelength in a particular direction to the

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radiance of the radiation emitted by blackbody at the same temperature. Thus, the emissivity is a dimensionless number between 0 (for a perfect reflector) and 1 (for a perfect emitter). The physical interaction of material and matter is here seen as follows. The emissivity of a surface depends not only on the material but also on the nature of the surface. Additionally, it is important to clarify the emissivity variation with variation of angle viewing. For instance, authors in articles [31, 32] showed experimentally that the emissivity of a surface may change as a function of the viewing angle to that surface, with maximum emissivity at normal viewing angles to the emitting surface[33]. Authors in article [32] measured the apparent temperature of various samples (soils and sand) at a fixed temperature using a spectro-radiometer over a range of viewing angles. The spectro-radiometer measured the IR radiation reflected from a series of mirrors one of which was attached to a goniometer. This mirror could be rotated about all angles (00–900) from the horizontal and reflects the IR radiation from the target sample. Moreover, the texture of surface and the emissivity variation with angle viewing are correlated to a certain extension. For instance, if a surface is a diffuse then there will be no change in emissivity with angle. Thus, knowledge of the surface is essential both for accurate non-contact temperature measurement and for heat transfer calculations. When viewing ‘real’ more reflective surfaces, with a lower emissivity, less radiation will be received by the thermometer than from a blackbody at the same temperature and so the surface will appear colder than it is unless the thermometer reading is adjusted to take into account the material surface emissivity. To summarize, given two objects with the same true temperature but different emissivity, a higher apparent temperature will be calculated for the object with higher emissivity. Given two objects with the same emissivity but different true temperature, a higher apparent temperature will be calculated for the object with higher true temperature. The apparent temperature of an object may be substantially different from its true temperature. Only when the emissivity of objects is known can thermal imagers compensate for emissivity and calculate true temperature. Another adjustment which has to be carefully considered is reflectivity. Objects with high reflectivity can reflect energy radiated by other objects. For example, polished aluminium reflects about 90% of the energy incident upon its surface. Just as thermal imagers cannot detect the emissivity of objects in order to calculate their true temperature, they also can’t detect the reflectivity of objects. Therefore, when calculating the apparent temperature of an object, thermal imagers detect and quantify energy emitted from the object, as well as the energy reflected from the surface of the

object. If an object reflects energy from another radiating source with a higher temperature, the apparent temperature that is calculated for the object will be higher than its true temperature. Likewise, if an object reflects energy from another radiating source with a lower temperature, the apparent temperature that is calculated for the object will be lower than its true temperature.

8. Analysis of images It is important to note that our thermal imaging applications were only qualitative in nature. As starting point, to conduct a thermographic inspection of a building, it was needed to reach a minimum temperature difference of 10 C° between the interior and the exterior for several hours before the inspection begins. The measurements were both done in the evening and also in the early morning. The early morning inspections have an obvious advantage because the sunlight tends to warm exterior walls and roofs, complicating thermographic inspections. Ideally, the perfect measurement would be under conditions where sun is not shining on the building for at least three hours before the inspection begins. If the house has brick or stone veneer, the sun-free interval should be at least eight hours long. For this reason a few measurements were conducted on the same object and repeated twice, early in the morning and in the evening but keeping the same temperature difference. To ensure fairness the influence of the surrounding was considered (reflection of light, pressure difference, humidity, position and brightness of street lamps). We also found that very windy days are not good because they affect the true temperature of scanned objects. Furthermore, interior heating has to be performed enough long in order to achieve the consistency of requested temperature difference of 10 degrees Celsius between interior (indoor) and exterior (outdoor) temperature. Keeping changes to a minimal level has enabled to achieve more accurate understanding of images. In particular we tried to ensure that any known air leakage is restricted. Before doing inspection of household we intentionally produced conditions for air-leakage in order to reproduce irregular shapes with uneven boundaries mages which enable us to recognize it accurately and identify it when occurs during inspection. According to “Guidelines for Thermographic Inspections of Buildings,” a standard produced by RESNET, “The thermal image for air leakage will appear as ‘fingers’ or ‘streaking’ showing as dark when cold air is observed and lighter colors when warm air is viewed. The thermal images will produce irregular shapes with uneven boundaries and large temperature variations. These air leakage sites are often at joints, junctions or penetrations in the enclosure. There is often a temperature gradient within a finger or streaking area”.

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Another important knowledge we gained was the understanding how to distinguish thermal bridging sites from thermal bypass or air leakage sites. Thermal bridging sites will not change size or shape during an inspection. We also learn that leaks in a low-slope roof can be well identified through thermal imaging. Importantly, for a useful thermographic inspection, the roof must be dry, otherwise the imaging is biased. When the sun shines on a low-slope roof, it heats up the roofing and the top of the insulation below. Once the sun sets, the insulation begins to cool; however, damp insulation cools at a much slower rate than dry insulation. That’s why leaky areas of the roof show up as warm spots when viewed at night. In what follows, thermal Images that correspond to three household’s outdoor inspections are interpreted. The images in Figures 7, 8 and 9 correspond to the first

inspected object, images in Figures 10 and 11 correspond to the second inspected object and the images in Figure 12 correspond to the third household. Figure 7a corresponds to the front elevation. Despite the poor resolution we were able to interpret the images. At the very initial step we thought that the horizontal cool band label as A represents the concrete floor slab which appears cooler than the rooms above and below. That this slab (and the cooler end wall on the left above A) can be ‘seen’ thermally through the outer wall, suggests that the walls are poorly insulated and that heat is escaping from the rooms through the wall fabric. If the cavity in the wall had been insulated (it should be in such a modern building), the image suggests that the insulation has been poorly fitted. This might explain the diagonal grading in wall colours from yellow (~2.5˚C) bottom left to white (5˚ C) top right. There was a

Figure 7. a) Front elevation; b) Rear elevation (east side) [4]

Figure 8. Thermal images: a) rear elevation (west end window, outdoor view); b) lounge window (interior view) [4] ___________________________________________________________________________________________________________ G. Laštovička-Medin: “Thermal Imaging and Uncertainties in the Interpretation: Case Study”, pp. 29–41

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Figure 9. Bedroom window (interior view) [4]

Figure 10. Images of second inspected household: Front elevation (ground and first floor) [4]

Figure 11. Rear elevation; the second inspected object [4]. ___________________________________________________________________________________________________________ G. Laštovička-Medin: “Thermal Imaging and Uncertainties in the Interpretation: Case Study”, pp. 29–41

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Figure 12. Rear elevation, third inspected object [4]

suggestion that the window frames (B) are conducting more heat out than the glass panes. The wall temperature reaches a maximum (i) above the window and (b) in the corner where the gable end juts out (C). This may be a corner effect (perpendicular walls reinforcing emission) or may represent a thermal gradient in front room of inspected flat. However, a closer inspection into the building showed that there was an error introduced in our initial understanding of the thermal image. The previous interpretation of the front elevation image assumed that the wall is brickfaced from top to bottom, concealing an internal concrete floor slab what was shown as wrong assumption. However, the floor of the considered flat corresponds with an external concrete feature on the outside of the inspected building. Thus the horizontal green band labelled on the image as A (in Figure 7a) could represent the concrete facing here. Nevertheless, our further investigation brought another difficulty in interpretation of image. Namely, the emissivity tables show that concrete and red brick have similar emissivity (0.94 and 0.93 respectively) so the previous arguments may still apply, though things are not quite as simple as we thought at the beginning. Figure 7b corresponds to rear elevation and shows an image of window on the east end side of household. It is obvious that thermal

emission is most intense at the top of the window (D). Another closer inspection has shown that there were trickle vents that could be closed to retain more heat. Additionally the frame was poorly fitted. As in the front, the frame conducts more heat than the glass panes. Figure 8a (left) corresponds to rear elevation and shows the side of flat with west end window. One side of the window is emitting more heat at the top (E) than the other. No sign of the floor effect was found in this picture. Figure 8b corresponds to the lounge window (interior view). The cool frame was suggesting heat loss. However, glass may be reflecting warm temperatures from wall or curtain. When scanning target in order to minimize the reflection we did a few control tests changing the angle direction towards the inspected target. This way we have developed a useful methodology for reducing the possible systematic errors. Figure 9 (interior view) reflects the heat escaping from a bedroom. With a poorly insulated wall, heat loss will be maximised at the crossing point where two walls (or wall and poorly insulated ceiling) meet. This fact is well seen here. There seems to be a 2˚C difference in interior wall temperature between centre and edge of wall. These cool corners could attract condensation and

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possible mould. Furthermore, wherever two or more of the surfaces of a structure come together, such as at the top of the foundation, band joists between floors (as applicable), interior and exterior wall intersections, walls and ceilings, walls and floors, there are gaps which act as thermal bypasses. Finally, we present images of other two households (Figures 10–12) that have been captured outside during winter night.

References

9. Conclusions The analyses presented in this paper were carried out and interpreted by Low Carbon Community group members who despite being trained in thermal imaging are not professional experts. Whilst participating in the community project the author of this paper found thermal imaging a very powerful educational tool for teaching the concepts such as thermal conductivity, reflection and emission of infrared radiation. Furthermore it can efficiently help visualisation of all learning steps involved in the student’s process of constructing the knowledge. It also fosters selfreflected and self-directed learning and the knowledge crafting with artefacts. In particular, it helps resolving the misconception and understanding how inaccurate the representation of the image is driven by lack of knowledge (interaction of radiation with matter and interfering effects from surrounding environment). The method of problem solving used for identifying the root causes of faults or problems associated to uncertainties is investigated. A certain set of artificial interferences of inspected object to its surrounding was artificially created or existed modified. Some items were located close to the inspected object and their impact on energy loss interpretation (reflectivity, ambient temperature) was explored. Furthermore, air flow and changes in the ambient temperature and the humidity were artificially created in order to examine the uncertainties and errors in image interpretations. Thus an impressive amount of thermal images corresponding to simulated surrounding effects were stored in a data pool (data base) for further development of pattern recognition and neural network. The modelling simulations can be an important tool for optimizing the energy loss.

[1]

Klaus-Peter Möllmann and Michael Vollmer, Infrared thermal imaging as a tool in university physics education, European Journal of Physics, Volume 28, 2007.

[2]

Mary Diakides, Joseph D. Bronzino, Medical Infrared Imaging: Principles and Practices, Taylor & Francis Group, 2013.

[3]

Waldemar Minkina and Sebastian Dudzik, Infrared Thermography: Errors and Uncertainties, ISBN: 978-0-470-74718-6, September 2009.

[4]

Private communication: Low Carbon Headington (The Community Action Group (CAG) Project consists of over 60 groups across Oxfordshire, at the forefront of community led climate change action, organising events and projects to take action on issues including waste, transport, food, energy, biodiversity and social justice).

[5]

FLIR Brochure “Thermal imaging for R&D/Science applications, available online: http://flirmedia.com/MMC/THG/Brochures/RN D_004/RND_004_EN.pdf.

[6]

B.F. Jones, A reappraisal of the use of infrared thermal image analysis in medicine. IEEE Trans. Med. Imaging. 1998; 17:1019–1027.

[7]

W.C. Amalu, A Review of Breast Thermography, available online: http://www.iact-org.org/downloads/a-reviewof-bc.pdf.8

[8]

D.A. Kennedy, T. Lee, D. Seely, A comparative review of thermography as a breast cancer screening technique, Integr. Cancer Ther. 2009; 8: 9–16.

[9]

N. Arora, D. Martins, D. Ruggerio, E. Tousimis, A.J. Swistel, M.P. Osborne, R.M. Simmons, Effectiveness of a noninvasive digital infrared thermal imaging system in the detection of breast cancer. Am. J. Surg. 2008; 196: 523–526.

[10]

E.K. Ng, A review of thermography as promising non-invasive detection modality for breast tumour, Int. J. Therm. Sci. 2009; 48: 849–859.

[11]

F. Ring, Thermal imaging today and its relevance to diabetes. J. Diabetes Sci. Technol. 2010; 4: 857–862.

[12]

A.V. Nguyen, N.J. Cohen, H. Lipman, C.M. Brown, N.A. Molinari, W.L. Jackson, H. Kirking, P. Szymanowski, T.W. Wilson, B.A. Salhi et al, Comparison of 3 infrared thermal detection

Acknowledgements The author whishes to acknowledge R. Gill and Low Carbon Headington whose engagement and interest in conducing the thermal imaging household’s survey made results presented in this paper possible.

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systems and self-report for mass fever screening. Emerg. Infect. Dis. 2010; 16: 1710–1717. [13]

[14]

J. Vargas, M. Brioschi, F. Dias, M. Parolin, F. Mulinari-Brenner, J. Ordonez, D. Colman, Normalized methodology for medical infrared imaging. Infrared Phys. Technol. 2009; 52: 42–47. H. Fikackova, E. Ekberg. Can infrared thermography be a diagnostic tool for arthralgia of the temporomandibular joint? Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endodontology. 2004; 98: 643–650.

[15]

A. Manginas, E. Andreanides, V. Leontiadis, P. Sfyrakis, T. Maounis, D. Degiannis, P.A. Alivizatos, D.V. Cokkinos, Right ventricular endocardial thermography in transplanted and coronary artery disease patients: First human application. J. Invasive Cardiol. 2010; 22: 400–404.

[16]

Stephanos Ioannou, Vittorio Gallese and Arcangelo Merla, Thermal infrared imaging in psychophysiology: Potentialitie and limits, Psychophysiology, 51 (2014), 951–963. Wiley Periodicals, Inc. Printed in the USA.

[17]

A. Merla, GL. Romani, hermal signatures of emotional arousal: a functional infrared imaging study, Conf Proc IEEE Eng Med Biol Soc, 2007, 247-9.

[18]

http://doublehelixwater.com/preliminaryautism-research-results/

[19]

Nicholas A. Diakides, Joseph D. Bronzino Medical Infrared Imaging, CRC Press; 2007, Michael Vollmer, Klaus-Peter Möllmann, Infrared Thermal Imaging: Fundamentals, Research and Applications, John Wiley & Sons.

[20]

R. Gade, T.B. Moeslund, Thermal cameras and applications: A survey. Mach. Vision Appl. 2014; 25: 245–262.

[21]

Rubèn Usamentiaga, Pablo Venegas, Jon Guerediaga, Laura Vega, Julio Molleda and Francisco G. Bulnes, Infrared thermography for temperature measurement and non-destructive testing, Sensors (Basel). 2014 Jul; 14(7): 12305– 12348, Published online 2014 Jul 10. doi: 10.3390/s140712305.

[22]

G.J. Zissis and W.L. Wolfe, The Infrared Handbook, Technical report, DTIC document. 1978.

[23]

FLIR Brochures:Thermal Imaging GuideBook for Insustrial Applications; available online on www.flir.com.

[24]

Eric P. Whitenton, An introduction for machining researchers to measurement uncertainty sources in thermal images of metal cutting, International Journal of Machining and Machinability of Materials 2012 Vol. 12 No. 3DOI: 10.1504/IJMMM.2012.049255, 2012.

[25]

G. Gaussorgues, Infrared Thermography. Springer; Berlin/Heidelberg, Germany: 1994.

[26]

G. Kirchhoff, “Ueber das Verhältnis zwischen den Emissionsvermögen und dem Absorptionsvemögen der Körper die Wärme und Licht“, Annalen der Physik und Chemie 109 (2):275-301; Translated by Guthrie, F. as Kirchhoff, G. (1860). "On the relation between the radiating and absorbing powers of different bodies for light and heat", Philosophical Magazine. Series 4. 20: 1–21.

[27]

K. Huang, Statistical Mechanics (2003), p. 280.

[28]

Eric P. Whitenton, Characterization of Uncertainties when measuring metal cutting temperatures using infrared radiation thermography, Proc. SPIE 7299, Thermosense XXXI, 72990G (April 22, 2009); doi: 10.1117/12.818799.

[29]

B. Taylor, C. Kuyatt, Guidelines for evaluating and expressing the uncertainty of NIST measurement results, NIST Technical note 129, 1994 Edition.

[30]

F.P. Incropera and D. P. De Witt (1985), Introduction to Heat Transfer, pp. 654– 746, John Wiley, Hoboken, N. J.

[31]

J.A. Sobrino and J. Cuenca, Angular variation of thermal infrared emissivity for some natural surfaces from experimental measurements, Appl. Opt., 38, 3931–3936, 1999.

[32]

J. Labed and M. P. Stoll, Angular variation of land surface spectral emissivity in the thermal infrared: Laboratory investigations on bare soils, Int. J. Remote Sens., 12, 2299– 2310, 1991.

[33]

M. Ball and H. Pinkerton, Factors affecting the accuracy of thermal imaging cameras in volcanology, Journal of geophysical research, Vol. 111, B11203, doi:10.1029/2005JB003829, 2006.

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DOI: 10.14621/ce.20160205

Hazard Risks and their Impact on Critical Infrastructures (Case Analysis – Natural Gas Networks of Italy and Romania) Ionut Purica Romanian Academy and AOSR Calea 13 Septembrie Nr. 13, sector 5, 050711 Bucharest, Romania; puricai@yahoo.com

Abstract

1. Quantification of risk

Interconnection of critical infrastructures represent one of the pillars of the EU Energy and climate change strategy at the horizon of 2030. The risks associated with these networks should be analysed based on the geographical distribution of each network by contrast to local objectives such as nuclear power plants or dams. Based on distributed hazard risks evaluation done for Italy’ regions in case of seismic and landslide and for Romania’s counties in case of flood, draught, snow and freeze and on the risks of mechanical failure with gas escape and ignition, the risk map is determined for each country measured in probable deaths per million inhabitants. These results may provide the needed information for optimizing the allocation of mitigation means and for implementing efficient insurance policies.

The quantification of risk has always been an intensely debated subject. Early reports such as WASH-1400, 'The Canvey Island Reports' have tried to assess valid scenarios on which to base the various physical and statistical analysis heading to determine frequencies of accidents and intensities of their consequences. Since there is no general method by means of which to establish all the consequences to be considered as negative and which of them, if not all, should be analyzed, then, there is no way to be certain that a complete analysis has been done. Moreover, when such an analysis is done on a complex system, such as the Natural Gas system in Italy and Romania an embedded structure is encountered having various levels of complexity at different scales. When considering the data, one has to disaggregate at various scales and to identify the inter-correlations both horizontally and vertically within the structure. Inevitably the uncertainty is rather high in relation to some data, the time horizons of different papers and statistics do not completely overlap, and there is not a consistent way of reporting the data (see e.g. Pollner 2010, ISTAT and INS).

2. Data preparation When considering the data to quantify risk at the level of the Italian and the Romanian natural gas system we are faced with a time evolution and space distribution. Keywords:

Hazard risk; Modelling energy system; Gas grid; Mapping risk

Article history:

Received: 12 February 2016 Revised: 30 October 2016 Accepted: 03 November 2016

The space disaggregation of data is decided by the intersection of the sets of available consistent data, which, for the whole countries are given by the regional distribution. From this point of view we distinguish among three types of data: (i) data reported on a regional distribution

___________________________________________________________________________________________________________ I. Purica “Hazard Risks and their Impact on Critical Infrastructures (Case Analysis – Natural Gas Networks of Italy and Romania)”, pp. 42–46

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basis, which give total certitude at this level (e.g. population, surface, natural gas consumption); (ii) data reported in absolute values aggregated over the whole country which we had to consider as uniformly distributed (like the probability of gas ignition); and (iii) data reported in specific values in correlation with other data whose distribution we know. Based on the known distribution we may generate a distribution of the unknown data (with a certain level of incertitude, though) e.g. the frequency of gas pipe rupture may be generated for each region based on the number of pipe kilometers in each region and the frequency of rupture per kilometer which is reported in various papers. The data storage and manipulation has been done in the 'Excel' computer program environment.

3. Logical model From a risk point of view we may distinguish between two types of risk leading to potential deaths and disabilities. The first type stems from the fact that methane is mainly distributed through a network of pipes which have practically a uniform distribution over the total surface of each of Italy's regions and Romania’s counties. Of course we stick to the regional disaggregation; going bellow that introduces totally different distributions of data which have to take into account the big cities, the industrial platforms, the power plants, and so on. If an assessment is done for a specific area the distributions mentioned above must be considered, but the methodology presented bellow will be the same. On the average, over the hole country, in 1986 Italy had in each square kilometer of surface served by the gas network (i.e. Sardegna excluded) a length of 76.2m of principal transport pipe and 334.4m of distribution pipes; or we may say that for each kilometer of pipe there corresponds a surface of 2.4 square kilometers. In other words there is one kilometer of methane pipe in every square of 1.56 km side. Taking the population density of 190 inhabitants/sqkm we have that in 2.4 sqkm there are 463 inhabitants. We did all this averaging just to point out that a gas escape has a sensible probability of ignition and that people may be affected. Based on the data described previously we may consider that the surface of every region has a percentage which shows ground movements either as ground instabilities or as seismic movements. Both the ground instabilities and the seismic movements are characterized by a surface affected in every region and by an intensity of the movements expressed by the number of

movements recorded per region per year respectively as a seismic intensity on the Mercali scale. In the case of the ground instability we have expressed both the number of areas per 100 sqkm and the intensity of movements as regional percentages from a country total. Considering the seismic case, there are three levels of seismic intensity surfaces, so we summed the surfaces and expressed them for each region as a percentage and we also calculated an intensity as a surface pondered regional index expressed also as a percentage from a country total. After this normalization, considering the ground movements, we may distinguish among four types of surfaces: (i) having both ground instability and seismic movements; (ii) with only ground instability; (iii) with only seismic movements; and (iv) without instabilities. If we express this in a Boolean logic, putting g-ground and s-seismic percent of unstable surfaces, we have that, for each region, r, of surface, Sr, the instable surface is given by: Sr (g s+g (1-s)+(1-g) s); while the stable surface is: Sr (1-g) (1-s). Considering there is a certain number of km of methane pipes distributed on the surface of each region, we may assess that some of these pipes will pass through ground movement affected surfaces. So the distribution of the frequency of ground movement caused accidents is not the same for all the pipe length in a given region and, since we assumed a uniform distribution of pipes over each region, the length of pipe will be pondered by the same ground movement coefficients as the surfaces of those regions. If we look now at the frequencies of gas escape incidents we see that there is a rather sharp behavior limit given by the 16" pipe diameter. Bellow 16" diameter there is a higher frequency of incident but a lower probability of ignition while for diameters over 16" the incident frequency is small but the ignition probability is high due to the large gas masses involved. Based on the above comments we may separate several categories of causes, which have specific incident frequencies: (i) causes which are not sensitive to diameter or ground movement like construction/ materials; corrosion; other causes; (ii) causes which are sensitive to ground movement. They increase the frequency of accident for the pipe length affected by ground movement; (iii) causes which are sensitive to diameter variation as hot tapping and external interference, which apply respectively to pipe lengths having diameters lower and/or greater than 16". Representing the above into a logical tree for each type of pipe damage: pinhole (p)- diameter of defect smaller or equal to 20 mm; hole (h)- diameter of defect greater than 20 mm; rupture (r)- diameter of defect greater than pipe radius; we obtain Figure 1.

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Figure 1. Event tree for risk evaluation

Table 1: Defect types

__________________________________________________________ Defect type Formula (L-pipe length) __________________________________________________________ p

(L) ((gs+g(1-s)+(1-g)s)*0.24E-3+(1-g)(1-s)*0.23E-3) (d*0.5E-3+D*0.02E-3)*1.6E-2

(L) ((gs+g(1-s)+(1-g)s)*0.062E-3+(1-g)(1-s)*0.043E-3) (d*0.97E-3+D*0.05E-3)*2.7E-2

(L) ((gs+g(1-s)+(1-g)s)*0.014E-3+(1-g)(1-s)*0.012E-3)

(d*0.47E-3*4.9E-2+D*0.07E-3*35.3E-2) __________________________________________________________ Calculating the branches of the tree and summing for each defect type we obtain parameters presented in Table 1.

(L) ((gs+g(1-s)+(1-g)s)(dm+Dn)+(1-g)(1-s)(du+Dv))

Summing on all defect types to obtain the total ignition accident probability we have:

m=3.78E-9 ; n=5.06E-10

(1)

where

u=3.24E-9 ; v=4.28E-10

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and d=69.6% ; D=30.4% only for transport pipes d=94.02% ; D= 5.98% for transport and distribution pipes. Up till now we have been calculating the values of the frequency of gas releases and release followed by ignition. Since risk is defined as the frequency of an adverse event multiplied by its consequences we shall now take a look at the consequences of the type of incidents our analysis was involved with. The evaluation of consequences in terms of accidents from the use of the Natural Gas network are analyzed in Purica (1991) and we do not repeat them here.

4. Results The calculations of risk expressed as probable deaths from the use of network gas in every region of Italy, taking into account the specific data for each of them, are presented in Figure 2. We must finally mention, for comparison, that the mortality index for the Italian electrical grid distribution system is of approx. 4 (deaths/E6.inhabitants) in 1983. This indicates that the Natural Gas network is as safe as the electric grid if compared with a total Italian all energy sources incident mortality index of 13 (deaths/E6.inhabitants) in 1983. Another risk assessment case mapped for this study relates to the influence of the climate change events

Figure 2. Natural gas risk in Italy [probable deaths / million inhabitants]

mentioned above on critical infrastructure in particular the gas network of Romania. The assessment is actually done as an example for critical infrastructure that is responding to the directive 2008/114/CE. The analysis is similar to the one done for Italy replacing the values of the 4 combined seismic and franuosity risks with the four types of hazard risks (flood, drought, snow, freeze) as evaluated in a previous paper (Purica ESPERA 2014). The assessment starts with the probabilities determined for each event and for each county. Then it considers the number of km of gas network in each county (given by the National Institute of Statistic of Romania). The event probabilities are combined with the mechanical failure probabilities of gas pipelines, based on a more elaborate event tree (see Purica 1991 and 2010) and the above calculation for Italy. The combination of these two types of probabilities results in the gas escape probability due to CC events followed by mechanical failure. Considering the population at risk as the one supplied by the gas network and the impact, in probable deaths per gas escape event, from gas grid accidents’ estimations, the risk is determined as measured in potential deaths per thousand inhabitants, from gas escape events, in each county. The resulting map of this type of risk is presented below. The map shows the areas where the gas grid is more developed having a higher risk. The probabilities of mechanical failure are based on estimations done for similar material pipelines in Italy – Romania does not have at present a consistent activity of determining and reporting these values.

Figure 3. Romania gas grid CC and mechanical risk [probable deaths/1000 cap]

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5. Conclusions The methodology developed in the paper for the mapping of network distributed risks allows among other to introduce a policy of optimal allocation of mittigation means among the regions/counties of each country in order to minimize the intervention time in case of accident and also to devise insurance policies better addapted to this type of risks coverage.

[3]

Purica, I., Climate Change events induced risk assessment and mapping as a basis for an insurance policy, 2nd International Conference ‘Economic Scientific Research - Theoretical, Empirical and Practical Approaches’, ESPERA 2014, 13-14 November 2014, Bucharest, Romania, Procedia Economics and Finance 22 ( 2015 ) 495 – 501 doi: 10.1016/S22125671(15)00245-2.

[4]

IPCC (2013). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change, Cambridge University Press. http://www.ipcc.ch/pdf/specialreports/srex/SREX_Full_Report.pdf

[5]

John Pollner, Jolanda Kryspin-Watson, Sonja Niewwejaar, (2010) Disaster Risk Management and Climate Change Adaptation in Europe and Central Asia, The World Bank, http://www.preventionweb.net/files/15518_gfd rrdrmandccaeca1.pdf.

[6]

ISTAT - Italy, and INS – Romania, (sources of data at national and regional level).

Moreover, with appropiate data, the method may be extended to other type of critical infrastructure risk mapping giving the possibility to better face the requirements of the EU energy and climate change 2030 strategy.

References [1]

Purica, I., La dinamica dei rischi nel sistema gas naturale in Italia, Report ENEA, 1990 (award ISPESL in 1992).

[2]

Purica, I., Risc dynamics in the Italian gas system, FOREN 2010, WEC regional conference Neptun.

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DOI: 10.14621/ce.20160206

Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the Deterministic Methodology Gazmend Pula, Kadri Kadriu, Gazmend Kabashi, Valon Sadiku Faculty of Electrical and Computer Engineering, University of Prishtina 10000 Prishtina, Kosovo; fiek@uni-pr.edu

Abstract

1. Introduction

This paper presents the application of the N-1 criterion in critical sections of the system as the deterministic approach in the planning methodology for the enhancement of its operational security. The deterministic approach is applied in order to establish the planning base that will provide for a secure, continuous and quality supply of power system consumers. The security of supply is determined by the Network Code also for havaric conditions respectively in cases of outages or loss of any of the essential elements of the full system configuration, transmission lines or substations/transformers. Irrespectively of whether occurring conditioned by faults, overloads, operator interventions or due to imposed changes of the system configurations. This analysis and planning methodology for the enhancement of the operational security of the system by applying the deterministic approach respectively the N-1 respectively N-k approach is used in the Kosovo Power System (KPS) and its transmission system operator (TSO). It is widely applied also in the regional ones depending on the level of accuracy and reliability demanded by the respective analysis. It can and usually is augmented and complemented with state-of-theart probabilistic-stochastic approaches few basic premises and practices of which are presented also in this paper.

The intense development of the contemporary electric energy market in the region and in Kosovo, imposes permanent new challenges to power system operators. Hence they are consequentially obliged to provide a much higher degree of security, quality, reliability and availability of supply and operation compatible with the conditions and provisions defined in respective Network Codes. The increasingly competitive environment of power system operators demands an increasingly efficient and flexible system operation, primarily from the point of view of security and availability of supply, both in quantitative or quality terms. Operational security and availability of supply capacities with the demanded quality of supply are determined meritorily by the operational system stability within the required framework of Network Codes. One of the principal methods for achieving these objectives in the KPS consists in the application of the deterministic planning methodology respectively in the application of the N-1 respectively N-k criterion.

Keywords:

Power system planning methodology; Power system operational security; Deterministic approach; N-1 criterion

Article history:

Received: 28 January 2016 Revised: 04 November 2016 Accepted: 08 November 2016

The principal objective for the planning methodologies is the determination of the maximal levels of power flows through the elements of the power system. In view of this, the N-1 criterion is an essential technical criterion on basis of which the power system is to operate in such a flexible mode as to be able to withstand outages or unanticipated system interventions in any elements of the system such as transmission line, generator or power transformer. However, this should hold true with none of the power system elements being affected unacceptably negatively by overstepping as a consequence the Network Codes requirements. The application of this criterion has proved to provide fully solid indicators for the reliable assessment of the power system security of operation. It should be mentioned also that it does not, nor does it need to include in this the context of the

___________________________________________________________________________________________________________ G. Pula et al: “Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the …”, pp. 47–55

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technical i.e. emergency operation of the system the economic aspects of its operation. In the recent period there has been a permanently increasing interest for the application of deterministic methodology by applying the n-1 criterion due to the credible and reliable results that the methodology provides in enhancing the security of operation of the system. As in the case of most regional system operators, the Kosovo TSO (KOSST- Kosovo Electricity Transmission, System and Market Operator) applies consistently the (N-1) criterion for the assessment and long-term enhancement of its system operation. In this paper the deterministic methodology is elaborated by applying appropriate simulations of the system operation in relevant operational configurations. The program software applied for this purpose was the industrial/commercial scale power system software PSS/E. The objective of the analysis was to provide relevant, reliable and credible data for determining the optimal transmission system configuration that would provide for a high degree of system operational security, reliability and availability. In other words, to be able to provide continuous supply also in the cases of outages of its critical sections and/or elements that has a high probability of occurrence. The relevant data obtained from the software simulation of the system consists of power system flows, levels of relative percentage load or overload levels of each element of the system, as well as voltage profile of the system. These data provide a solid base for the assessment and consequential planning methodology for the long-term enhancement of security, reliability and availability of the system operation as well as its further expansion.

2. The deterministic methodology and the application of the N-1 criterion The security and reliability of power system operation is of essential importance for upholding the objective of continuous and quality supply of power system consumers. The operational security and reliability of the system is assessed on basis of the capability of the system to enable the continuous supply of all its consumers in within the quantitative and quality requirements as determined by the Network Code, in conditions of outages of any elements of the system, even in most critical ones. Enhancement of the operational security and reliability of the power systems can be determined in a very efficient manner by applying the deterministic methodology respectively by applying the N-1 criterion [1]. This criterion determines that the operational power transmission system security and reliability is provided for if the system is capable of withstanding in a safe,

stable and flexible manner unexpected faults and outages or consequential major changes in the system configurations resulting from such disruptions. These faults and outages could affect any of its respective elements such as transmission lines or power transformers. But the system nevertheless must continue with the required quantitative and quality indicators of supply of its consumers compatible with the Network Code. It should be mentioned in this context that the deterministic methodology does not account for the quantitative aspect of probability of incidence of such faults and/or outages that can endanger the normal and reliable system operation. This means that the deterministic methodology is applied and considered practically in critical high loaded conditions of the system operation, which in the elaborated case of the KPS means operational conditions with maximal i.e. peak anticipated load. In principle, the planning methodology of the Kosovo TSO /KOSST/ is such that the system should be upheld within the Network Code requirements during its entire operation for any given anticipated N-1 configuration .i.e. for any outage of any system element. Within this framework the outage of any of the comprising elements of the power transmission system that might occur for whatever reason, may not cause: • Overload of transmission lines/cables beyond their thermal limits; • Overload of power transformers; • Reduction of power supply capacity; • Overstepping of the voltage profile requirements including their respective rate of change; • Endangering transient and/or dynamic stability; The deterministic planning methodology is applied by the Kosovo TSO as in many other countries worldwide. The deterministic planning criteria uses N, (N-k) terminologies to describe the system configuration for which a system is planned , where ‘k’ is the number of elements out of the N-normal system configuration at any given time for the analyzed contingency due to the respective outage of its elements. These terms are defined as follows: • (N) criterion denotes the Normal system configuration planned with all transmission power system elements in a satisfactory mode of operation. • (N-k) criterion denotes the system configuration planned with all but k transmission system elements in a satisfactory mode of operation for any ‘k’ credible contingency resulting with outage of k number of system elements [2].

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Gathering of input data and creation of system model in PSS/E Creation of actual system model Technical analysis of system performance (power flow, N-1 criterion )

Assessment of equipment condition and live cicle Revitalisation plan of transmission network

Identification of needs for system reinforcement

. Evaluation of new connection application to the TN

Connection aproved

Creation of different scenarios of system reinforcement Technical analysis of system performance ( power flow, short circuits, dynamics) Selection of optimal scenario and determining a final list of the reinforcement projects

Figure 1. Algorithm of transmission planning methodology

The algorithm on Figure 1 shows a summarized schematic presentation of the transmission network planning methodology.

• Definition of the possibilities of network strengthening the network based on N-1 contingencies; • Analysis of voltage profiles and system losses;

3. The planning methodology for the deterministic approach The approach of the transmission network planning methodology consists of the following steps: • Collection of input data (creation of the data base for network modeling network); • Definition of different scenarios taking into account factors strengthening the development of generation, load, balanced power system exchanges, etc.; • Creation of computer models of the network transmission compatible with PSS/E; • Determination of plans for revitalizing existing system facilities and equipment as based on their anticipated life cycles; • Identification of network constraints (N-1 simulations);

• Defining system reinforcement and expansion plans. The basic principle upholding the security and reliability of the transmission power systems respectively their planning and development methodology consists of the necessity of fulfilling the system technical criteria as required by the Network Code for the Normal system configuration, but also for the N-1 system configuration. Furthermore these conditions have to be fulfilled even foremost demanding respectively most critical conditions of system operation. For the N-1 criterion i.e. the single contingency criterion, the transmission system shall be designed to maintain operational reliability within the Network Code requirements for the N-1 configuration meaning the Normal configuration minus the loss/outage of any of its elements such as power line or transformer. N-1 is a common security standard in ENTSO/E. The single contingencies to be considered under an N-1 criterion are:

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• Loss of a single transmission circuit • Loss of a single generator • Loss of a single bus section • Loss of an interconnecting transformer The loss of a system element could be either planned (as part of scheduled maintenance) or unplanned (as an unanticipated disruption fault event or intervention), either by inadvertent disconnection or as a consequence of the incidence of fault occurrence. In other words, for an N-1 contingency that the system must maintain: – TSO elements must operate within acceptable short term ratings during contingencies; – - No load curtailment required to maintain N-1 security level for any operating condition; – - Voltage quality provided within the Network Code requirements; – - Cascading outages do not occur.

4. Application of the deterministic methodology for the elaborated case study In this paper the case study subjected to the application of the deterministic methodology refers to the KPS operational security and reliability in its full transmission

configuration as presented in Figure 2 more specifically in one of its critical sections as shown in Figure 3 below. Simulation and the technical analysis of the performance of the system for a sequence of different cases in different time periods have been carried out with the respective software package programs of the PSS/E. The programming iterative package FNR (Fast Newton Raphson) Load Flow is applied for calculating the power flows and voltage profiles in the system, whereas for the calculation of the network reliability criterion the ACA-AC Contingency Solution integrated in the PSS/E is applied. The deterministic methodology for the analysis of the operational security and reliability of the system respectively the application of the N-1 criterion consists in the necessity of the systems upholding its normal operating mode as required by the Network Code. This pertains to all times, in any given case of contingencies resulting in an outage of any of the elements of the system, power line or transformer, irrespective of the cause of the outage [3].

4.1. Case study N normal configuration operation The results obtained from the system operation simulation for the case N i.e. for the Normal full

Figure 2. Actual single line representation of the Kosovo Power System ___________________________________________________________________________________________________________ G. Pula et al: “Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the …”, pp. 47–55

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Figure 3. Case study section of the Kosovo Power System

Figure 4. Case study N – Power flows, voltage profiles, relative system element loads

configuration of the system, provide the data for power flows and voltage profiles for each of the system buses as well as the relative percentage loads of each of the system elements for the entire system and for its peak load of 1.126 /MW/. The results have been graphically and numerically presented in Figure 4 for the analyzed

critical section of the analyzed system focusing on its eastern section between the busbars of Peja-GjakovaPrizren as shown in Figure 3. The relative percentage loads of each element of the system i.e. in every line and transformer are presented in graphical and numerical form in Figure 4.

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Table 1: Case Study N – Percentage load of system elements/lines 110 kV lines Peja3-Peja1 Peja3-Klina Peja3-Skenderaj Peja1-Peja2

Itherm (%) 72 67 52 49

It can be seen from Figure 4 that the relative percentage loads for the N-normal configuration case considered are well within the r Network Code requirements and not even remotely close to their respective thermal limits. Furthermore, the majority of the system elements stand amply in the safe domain of relatively lightly loaded levels. However, in this context, it can be seen from the results shown in Table 1 that relatively high percentage load flow for the analyzed N case configuration have the line element Peja 1–Peja 3, as well as the transformer connected to buses Peja 3 – Peja 1 with 72% and 84% respectively. Consequentially the two referred elements are thus indicated to be potentially of critical importance for the system operational security. Hence between the two the critical element is to be found that has to be switched off for the purpose of simulating the element outage for the application of the deterministic methodology i.e. the N-1 criterion.

4.2. Case study N–1 configuration operation From the results obtained from the analysis of the case study N, it can be concluded that the element that is clearly indicated to be considered and verified by applying the deterministic method respectively the N-1 criterion, is the outage of the power line Peja 1 – Peja 3. Therefore the system is re-configured with the outage of this line, respectively without this critical line and the simulation of the system operation is carried out. The results for the power flows, voltage profiles and the relative percentage loads of each elements of the system are then presented graphically and numerically as shown in Figure 5. It is obvious from the results presented in the figure that four lines of the N-1 system configuration exceed their respective relative load limits ie are overloaded beyond their thermal power limits. Clearly this comes about due to the outage of the referred line and consequential collapse of the two-way power supply caused by the outage. It can be easily concluded from what is presented in this figure that line Gjakova 1 – Deçan exceeds its thermal limit with its 109% of the relative percentage load, while lines overloaded beyond or close to their respective

thermal limits result to be also the lines Peja 3 – Klina with 101%, the line Klina – Gjakova 1 with 100% and the line Deçan – Peja 2 with 98%, which also stands above the thermal limit of 95% of the continuous power rating. In Table 2 are shown the relative overloads of these critical lines resulting from the power flows of the N-1 system configuration. From what has been presented above, it can be concluded that the application of the N1 criterion with the outage of the referred line does not fulfill and uphold the security criteria as required by the Network Code. Hence the evident conclusion is that the line would need to be electrically reinforced Furthermore not by enhancing its transmission capacity with increased conductor cross sections respectively their thermal power limits, but instead, with the construction of a parallel line Peja 1 – Peja 3. Preferably, providing for maximal power transmission capacity for the given voltage level. It can also be concluded from the above analysis that the outage of this line results with a seriously worsened voltage profile in this section of the system that is not compatible with the Network Code requirements. Furthermore, the voltage in the Peja 1 bus collapses to a value of 84.1 /kV/, followed closely with the voltage drop of the Peja 2 substation at only 89.8 /kV/. From what has been said above in the beginning of this analysis, it can be concluded that a relative (over)load of 109.2% occurs in the given N-1 system configuration in the line Gjakova 1 – Deqan. This situation can cause a trip cascading effect, respectively local black out when the relay protection trips the overloaded line Gjakova 1- Deqan. Hence, of it can also be concluded that the application of the N-1 criterion in this configuration, that the outage of this line is also highly relevant for the upholding of the N-1 criterion i.e. for the operational security of the system. This is clearly the one case, alongside the case of potential contingency caused by the outage of the power transformer on the busbar Peja 3. Namely, from the analysis of the considered case N /normal configuration/ that has been already been indicated to be a potentially even more critical contingency. It has been concluded also that network transformer voltage regulation would be insufficient to positively enough address and affect the network contingency resulting from an N–1 element outage. Otherwise should such alternative options of power generation adjustment and/or voltage control in the form of transformer tap changes, referred to frequently as optimizing measures, be sufficiently effective to correct the effects of the N–1 contingency, it would have presented a much more cost-effective solution to this type of contingencies. But such major N-1 configuration changes are normally addressed with power system

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Figure 5. Case N-1 – Power flows, voltage profiles, relative system element loads

Table 2: Case N-1 – Percentage load of system elements/lines Critical outage 110 kV line Peja3-Peja1

Overloaded 110 kV lines Deçani-Gjakova1 Peja3-Klina Klina –Gjakova 1 Peja2- Deçan

construction measures, such as adding or enhancing system elements i.e. lines and/or substations as is presented in the next section. In this context it should be said that the analysis carried out with the application of this method results in the conclusion that the N-1 criterion would not be fulfilled in either of these two cases considered. Therefore, both of these two elements i.e. the respective section of the transmission system should be electrically reinforced appropriately with additional power transmission capacity. It would be redundant and indeed superfluous to conclude additionally that N-k criterion with k>1 would be indicated for the further assessment of the system operation security and reliability [4-5].

4.3. Case study N+1 configuration operation In the above presented analysis of the application of the deterministic approach it has been concluded that for the outage of the line Peja 1 – Peja3 the N-1 criterion cannot uphold the operational security of the system.

Ithrm (%) 109 101 100 98

Voltage (kV) Peja1 84.1 Peja2 84.8 Deqan 89.8 Gjakova 1 97.5

Hence the referred line should be reinforced with a parallel line between the respective buses. Therefore in order to substantiate the conclusion of the necessity of line reinforcement in order to increase the transmission capacity with concrete operational simulation results, the case study has been analyzed in which the construction of a second i.e. of a parallel line between Peja1 and Peja 3 substations has been simulated. For the purposes of this analysis, the case has been labeled as Case N+1 Configuration and the results of the respective power flows, relative percentage loads of the system elements and the overall voltage profile of the system obtained by the simulation has been presented graphically and numerically as given below in Figure 6. It can be concluded from the figure above that the transmission capacity reinforcement of this segment of the considered system with an additional parallel line to the existing one, which as a single line has proved to be critical and not being able to uphold the N-1 criterion, has proved to be efficient from the point of view of the system operational performance and security as it has enhanced its indicators well within the Network Code

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required ranges. More specifically, the resulting optimized power flows in the elements of the system have therefore resulted in a maximal percentage relative load which is low and does not exceed 59% of nominal load of the line Peja 2 – Peja 1. Whilst the other line relative percentage loads are still lower and stand in the range of relatively lightly loaded lines. Thus they provide for a high margin of security and an increased availability of the transmission capacities of this part of the system. From the figure it can be seen that the voltage profile in the referred section of the system in this case is practically an optimal one with voltage deviation of 34% of Un and with a voltage that drops only 106 kV. Voltage increases in this case do not rise above 112.8 kV. A chronological enhancement of the transmission capacities of the KPS for the N case and for the N-1 case as determined by the application of the deterministic methodology referring to the N-1 criterion for the forthcoming period, are within the framework of the respective long-term planning period KOSTT [3]. The

respective anticipated transmission development is presented in Figure 7.

capacity

Hence, based on the application of the N-1 criterion it can be concluded that the operational system security can be near-optimally enhanced with such an intervention of power network reinforcement by addition of a parallel line. This is consistent with longterm KPS development system planning [3]. This can be contested in somewhat relative terms, but not in essential ones, nor with any high probability of occurrence only from probabilistic and stochastic aspects of various comprising elements of the system and their component parts. Such effects that could potentially occur depending on respective component/equipment quality and duration of operation, conditions of system operation, meteorological conditions and other for which it should be mentioned that they have a limited incidence, frequency and gravity of occurrence. However, in certain sets of circumstances they might additionally negatively affect the system operational security.

Figure 6. Case N+1 – Power flows, voltage profiles, relative system element loads ___________________________________________________________________________________________________________ G. Pula et al: “Enhancement of the Operational Security of the Kosovo Power System by applying N-1 Criterion of the …”, pp. 47–55

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Figure 7. Chronological development of the KPS transmission capacities for N and N-1 configurations

5. Conclusions Transmission power system operational security is an important study topic that has been researched widely and intensely in the recent years. Within this framework the deterministic methodology, the application and the observation of the N-1 criterion has proven to have decisive and meritory significance. The upholding of this criterion demands that the system be capable to flexibly withstand the outage or loss of any of its elements due to whatever cause of occurrence and to maintain its normal operational performance indicators within the Network Code requirements. In other words, the system should be able to accommodate its consequential mode of operation in a flexible manner, meaning by fulfilling all Network Code requirements. This should hold true for any arbitrary system configuration changes caused by the loss or outage of any of its elements, at any given time or in any operational conditions, including critically high load conditions. It should be mentioned in this context that the application of the deterministic methodology in the form of the N-1 criterion does not take into account the probabilistic and stochastic aspects of the incidence of occurrence. With the application of the deterministic methodology respectively of the N-1 criterion for the considered case of the KPS, it has been provided for a near-optimal ie a very reliable system configuration within the framework of the long-term planning methodology of KOSST. Thus a solid operational performance is provided well within Network Code requirements. From what has been elaborated above, it can be concluded that the

application of the deterministic methodology i.e. the N1 criterion provides for a highly reliable long-term enhancement of the operational security of the system. Namely it provides for normal operational performance indicators also in the case of outage or loss of any element of the system, even of the critical ones. This includes power system operation even under critical load conditions accommodating in a flexible manner an outage or loss of any of its elements with an alternative power flow and operational reliability. Hence it can preclude bottle-neck critical phenomena in issues of transmission capacities/capabilities. Furthermore, without overloading system elements and risking operational security even in conditions of grave faults.

References [1]

Dong Z, Zhang P, Emerging Techniques in Power System Analysis, Springer Verlag, Berlin, 2010.

[2]

Seifi H, Sadegh M, Electric Power System Planning, Springer Verlag, Berlin, 2011.

[3]

KOSTT, Transmission Development Plan 20142023, www.kostt.com

[4]

G. B. Shrestha, P. J. Fonseka, “Congestion-driven Transmission Expansion in Competitive Power Market,” IEEE Trans.PowerSyst., vol. 19, no. 3, August 2004.

[5]

K. Uhlen, On-Line Security Assessment and Control – Probabilistic versus Deterministic Operational Criteria, Proc. ESREL’98, Trondheim, Norway, 16-19 June, 1998.

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DOI: 10.14621/ce.20160207

Smart City Projects Implementation in Europe: Assessment of Barriers and Drivers Simon Pezzutto1*, Reza Fazeli2, Matteo De Felice3 1

Institute for Renewable Energy, EURAC research Viale Druso 1, 39100 Bolzano, Italy; simon.pezzutto@eurac.edu 2 Faculty School of Engineering and Natural Sciences, University of Iceland Sæmundargötu 2, 101 Reykjavík, Iceland; rfazeli@hi.is 3 Department of Sustainability, ENEA Lungotevere Thaon di Revel 76, I-00123 Rome, Italy; matteo.defelice@enea.it

Abstract

1. Introduction

This investigation has the aim to provide advice and support on the implementation of smart city projects at European Union level. A quantitative feasibility study - strengths, weaknesses, opportunities and threats analysis - based on more than one hundred previous experiences of smart city projects in Europe, indicates a certain difficulty in carrying out the investigated efforts. Results show that the main obstacle is the environment external to the analysed activities (opportunities and threats), while issues internal (strengths and weaknesses) to the investigated projects appear to facilitate their execution. The following were identified as main barriers (weaknesses and threats): i.) subsidies, ii.) communication between project participants and the public, and iii.) expertise in designing new technologies and solutions. In contrast, the most effective drivers (strengths and opportunities) are i.) public participation, ii.) cooperation between different stakeholders, and iii.) political commitment over the long term. Public participation is not only the most powerful driver, but also the most utilized factor to overcome the detected barriers.

The European Union (EU) is facing unprecedented challenges related to climate, energy, social and economic aspects, with specific goals to be achieved by 2020, 2030 and 2050 [1-3]. Europe has both an ecological footprint twice as large as its area and a dependence on imported energy (primarily in the form of fossil fuels) coming mainly from Africa, Russia, and the Organization of Petroleum Exporting Countries (OPEC) - all of which have current conflicts causing them to be fragile markets [4]. Less than half of the gross energy consumption of Europe is domestically produced [5]. The International Energy Agency (IEA) has predicted that, specifically for fossil fuels, Europe’s energy dependence will continue to increase, potentially reaching 90% in 2030 [6]. Transitioning to a low-carbon economy is currently a major European goal. Key aspects of a low-carbon economy include: support for smart energy management, reductions in emissions and higher levels of energy efficiency. A low-carbon economy will place much higher value compared to a modern day economy on energy efficient building materials, renewable energy sources (RES), hybrid and electric cars, low-carbon power generation, smart grid equipment, smart cities (SCs), and carbon capture & storage [3].

Keywords:

Smart cities; Projects; Implementation; Europe; Barriers and drivers

Article history:

Received: 06 April 2016 Revised: 26 October 2016 Accepted: 04 November 2016

The primary energy utilization in Europe in 2010 was approximately 1,800 Mtoe [7]. Currently cities consume 40% of the energy and studies have predicted that the percentage will increase to 75% by 2030 [8-9]. Smart cities represent a method of creating urban areas, which are both sustainable and efficient. Currently, SC projects primarily focus on energy efficiency measures, adding RES, and offsetting emissions [10]. As noted in the literature, most renewable energy technologies are economically competitive compared to

___________________________________________________________________________________________________________ S. Pezzutto, R. Fazeli, M. De Felice: “Smart City Projects Implementation in Europe: Assessment of Barriers and Drivers”, pp. 56–65

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traditional energy sources; however, due to a wide range of technical, market-related and institutional barriers, the implementation of such technologies has not reached yet its full potential [11-14]. Considering the limited evidence in the literature concerning the performance of SC projects at EU level, the main purpose of this study is to grant deep understanding on the development of previously-completed and current SC projects in Europe. Thus, a quantitative feasibility assessment framework consisting of four elements (strengths, weaknesses, opportunities, and threats SWOT) has been applied to assess more than one hundred previous experiences in SC projects. The paper is structured as follows: developed framework - section 2; results obtained from the survey on the main barriers and drivers for European SC projects - section 3; conclusions are drawn in the final section.

2. Methodology This work consists primarily of a SWOT analysis supporting decision makers who are transforming European urban environments into SCs. Analysing experiences from previously-completed and current SC projects helps to provide a more effective implementation of future ones. The analysis includes understanding possible difficulties (weaknesses and threats) and the factors, which will lead to a successful project implementation (strengths and opportunities). The highest number of ongoing and completed SC projects in Europe were identified using an extensive investigation. Available documentation on SC projects analysed in the present work was provided especially by: • The European Commission (EC - financed within the Sixth and Seventh Framework Programme “CONCERTO initiative”, the “Smart cities and communities initiative” - Seventh Framework Programme, and Horizon 2020 “Smart Cities & Communities” activities) [15-19]; • “Amsterdam smart city” [20]; and • Individual EU member states programmes (e.g. Austria´s “Climate and Energy Fund”) [21].

Throughout the analysis, it was assumed that strengths and weaknesses are “internal factors”, or characteristics of a SC project itself. The opportunities and threats for a given project are considered to be “external factors”, or factors describing the environment surrounding a SC project [22]. An exploratory study was used to identify the factors, both barriers and drivers, for each project. A literature review was used to identify those encountered during project implementation, and then the most common factors were selected from the list. After the list was created, experts were asked to quantitatively describe the effectiveness of each factor for the SC project(s) they work(ed) on. Out of 124 smart city projects, a new sample size (new ss) deriving from 94 questionnaire responses (randomly selected) was used to identify the quantified effectiveness for each factor. This value was calculated using equation (1), which identifies the required sample size to perform an accurate quantitative statistical elaboration [23]:

new ss = ss / [1 + ( ss − 1 / population )]

(1)

where

ss = Z 2 * p * (1 − p ) / c 2 Z (constant) = 1.96 for 95% confidence level p (level of significance) = 50% c (confidence interval) = 4.84% The factors were rated on a Likert scale, with a possible range of -5 to 5, including 0 (see Table 2, Appendix). The values have the following significance: • Negative values represent barriers, with -1 indicating a minor barrier and -5 a major barrier • 0 indicates neutrality • Positive values represent drivers, with +5 representing a very effective driver and +1 a less effective driver

The investigation revealed 124 SC projects and identified a list of barriers and drivers for those. The analysis was performed in two ways: studying the freely available documentation, and performing direct interviews with SC experts.

The use of average absolute values of expert responses allowed to define the effectiveness of each factor by focusing the analysis on its relevance, while neglecting whether it was a driver or barrier [24].

The expert interviews only considered empirical information. In the case of current projects, the interviews only covered barriers and drivers that had occurred previously in the project. The experts were specifically asked to provide only that information.

To determine the uniformity of expert responses, a consistency analysis was performed. The level of agreement of the experts was quantified using the interquartile range (IQR) of the weights distribution [2527]. A higher IQR indicates a low level of agreement [28].

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Figure 1. Quantitative approach of the utilized SWOT matrix

Each factor´s impact was defined as the product of the number of times it appeared and its effectiveness value (see Table 1). Allocating a factor within the four aspects of the SWOT matrix is difficult if the limits of an item are floating. When the appropriate section was uncertain, the choice of where to allocate the factor was made by analysing how closely it fit one side compared to another one. Next, the quantitative result was derived from the developed SWOT matrix. In order to achieve this, a more detailed evaluation methodology was developed in substitution of the traditional one. After assigning the impact value for each factor in the SWOT matrix, the values are summed for each section and the total sum is identified for internal and external factors. The final result is the combined sum of internal and external factors. The result is the final output of the SWOT matrix, which provides an estimate of how challenging the implementation of SC projects has historically been in Europe. The complete procedure is shown in Figure 1. For the final step, the experts were surveyed to identify the best strengths and opportunities to use for overcoming the observed weaknesses and threats. This step is indicated in Figure 1 by the crossed arrows. The reason for choosing an applied methodology in contrast to a fundamental research approach is that findings can be applied to related issues. The SWOT

analysis provides stakeholders with a broader understanding of SC projects management and it helps them to enhance the implementation of energy efficiency and energy saving initiatives in cities.

3. Results A survey was used to understand the most frequently encountered barriers and drivers in European SC projects. There were an extraordinarily high number of barriers (over 500) and drivers (nearly 400) covering administration, policy, technique, legislation, operativity, economy, and behaviour fields. This section describes the significance of the most important factors and specifies their classification (strength, weakness, opportunity, or threat). – Public participation (strengths) This factor refers to cases in which all necessary attention is dedicated to the involvement of key players in SC projects during the whole life cycle of the project. This factor usually results in higher adoption rates for project decisions and both acceptance and support for project activities [29-31]. –

Cooperation among stakeholders (strengths)

This strength drives effective coordination and increases trust between collaborators, which helps when

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implementing steps toward reaching the goals of the project [32], [33-35]. –

Marketing application for awareness and involvement (strengths)

This factor describes the communication of activities and values of each SC project. It mainly increases awareness and involvement of the public in SC activities using radio, television, internet communication strategies, and newspapers [3], [36-37]. –

Communication between project participants and the public to increase awareness (weakness)

A lack of adequate information concerning SC projects on the side of utilizers and inhabitants can lead to aversion and resistance to the project. Two types of project information obstacles are unavailability, and asymmetric access [16], [38]. –

Expertise in designing new technologies and solutions (weakness)

This factor quantifies the available experience in technologies used within a given SC project (e.g. solar thermal systems, photovoltaics, district heating systems etc.). Inadequate expertise can cause unsuccessful installations, delays, and/or operation problems [39-41]. –

Inertia (weakness)

–

This term describes the consistency of political support, mainly given by stability of the local government, which can lead to a significant support for a project, facilitating implementation [37], [39], [42-43]. –

Environmental awareness (opportunity)

This factor is based on the understanding that a given project experiences higher public acceptance when it addresses publicly appreciable issues such as air pollution, climate change, and reductions in CO2 emissions. –

Affordable and mature technologies suitable for local conditions (opportunity)

Smart city projects depend on the availability of economically affordable technologies, which are both sufficiently developed, and appropriate for the present local conditions (e.g. a wind turbine project requires an adequate local wind resource) [26], [41], [44]. –

Subsidies (threat)

Subsidies provide financial support for SC activities [45]. Examples of different kinds of subsidies include: interest-free loans, tax breaks, cash grants etc. [46]. A lack of subsidies can cause barriers to implementation of and investment in SC projects [26], [42], [47]. –

Inertia describes the challenges associated with changing behaviour, and also refers to resistance to technology and developing new habits. Inertia can occur in both organizations and individuals, and can cause delays in project implementation [34-35].

Political commitment over the long term (opportunity)

Requirements from the EC concerning reporting and accountancy (threat)

According to several of the interviewed experts, EC reporting and accountancy requests can be excessively strict and require a large time investment. This factor describes how this threat affects a given project.

Table 1: Effectiveness of factors (barriers and drivers)

Effectiveness

IQR

Appearances

Impact

• Public participation • Cooperation among stakeholders

FACTORS

2.07 3.80

2.3 1.2

52 19

107.64 72.20

• Marketing application for awareness and involvement

3.71

1.7

51.94

3.79

2.2

75.80

3.99 2.55 4.12 4.51

0.2 2.5 2.2 1.5

18 28 17 15

71.82 71.40 70.04 67.65

1.48

1.3

44.4

2.31

2.3

76.23

4.80

2.1

62.40

4.60

2.4

59.80

• Communication between project participants and the public to increase awareness • Expertise in designing new technologies and solutions • Inertia • Political commitment over the long term • Environmental awareness • Affordable and mature technologies suitable for local conditions • Subsidies • Requirements from the European Commission concerning reporting and accountancy • Ownership structure of realities

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Figure 2. Main SWOT analysis results

–

Ownership structure of realities (threat)

The ownership structure of real estate can have a significant impact on the success of a SC project. Target properties with fragmented ownership models (e.g. high-rise office buildings, or multi-family houses) might cause disagreement among property owners, and raise significant challenges for the project. Table 1 provides the effectiveness value calculated for each factor, IQR calculations, and the impact numbers for each addressed issue. To quantify the level of agreement among the experts, a consistency analysis was also implemented. The agreement was quantified using the IQR of the weights’ distribution. The interquartile range does not exceed 2.5 for any single factor, indicating a high level of agreement among the experts. As exhibited in Figure 2, the highest total impact sum (about -650) is given within the threats section of the SWOT matrix. Strengths, at around +400, have the second highest impact value. The third highest impact value of -300 corresponds to the weaknesses. Opportunities received the lowest total impact value, at +250. Counterpositioning the impact values sum of the internal factors (strengths and weaknesses) a positive value of approximately +150 is obtained. The impact value for strengths exceeds that of the weaknesses by

about one third. The opposite trend is observed for the external factors (opportunities and threats). The difference between these two values is nearly -400. The impact value of the threats category is nearly double that of the opportunities category. The overall result of the SWOT matrix is approximately 250. This negative value implies that completing SC projects within Europe is highly difficult. This is largely a result of the external factors in the SWOT matrix. The internal factors from the SC projects analysed (amounting to about +150) facilitate project implementation. The external factors (about -350) in the SC projects investigated significantly hinder completion. The driver used to overcome the barriers most frequently mentioned by experts is public participation. As shown in Table 1, this factor appeared 52 times. Since this factor is characterised also by the highest impact value (+107), it is safe to conclude that public participation is the key driver of the SWOT analysis.

4. Conclusions The quantitative results of the strengths, weaknesses, opportunities and threats analysis show that it is currently difficult to implement smart city projects in Europe. The challenge derives primarily from the external factors (opportunities and threats) in the studied smart city projects.

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Contrarily, the internal factors in smart city projects support project success. As shown in the strengths, weaknesses, opportunities and threats matrix, the negative result of the external factors is nearly three times higher than the positive result of the internal factors. This means that the result of the matrix is a negative outcome. It should be noted that this result comes from the perception of experts who estimated the impact of various factors on projects they have/are working on. The most impactful factors appear to be public participation, subsidies, and communication between project participants and the public to increase awareness. Thus, any measure that improves public participation or involvement in the project will likely facilitate project implementation. The impact number comparing internal and external factors affecting the implementation of ongoing or previous projects indicates that the most impactful strengths are cooperation among stakeholders, public participation, and marketing applications for awareness and involvement. This information leads to conclude that information exchange is highly important to smart city projects. In the analysed projects, the most impactful weaknesses were expertise in designing new technologies and solutions, inertia, and communication between project participants and the public. Thus, behavioural issues were more relevant than technical concerns in the studied projects. Among the opportunities, the strongest impact was identified for environmental awareness, the presence of affordable and mature technologies suitable for local conditions and long-term political commitment. Similarly, to the weaknesses, technical issues are surpassed by other factors – this time environmental and political issues. Finally, the biggest threats are ownership structure of realities, requirements from the European Commission concerning reporting and accountancy, and subsidies. All of these threats are based on legislation. The final threats matrix includes a factor, requirements from the European Commission concerning reporting and accountancy, which has not been discussed in previous studies. This barrier makes it very important to track and document the activities of collaborators throughout the entirety of smart city projects. Public participation is the driver most commonly utilized to overcome barriers. As this factor also has the highest impact value of all elements in the strengths, weaknesses, opportunities and threats matrix, it is the most important driver of the analysis.

This investigation provided an understanding of the most relevant drivers, external barriers, and internal barriers of smart city projects in Europe. It can assist in future smart city projects by indicating possible risks and opportunities that may arise in any given project. These barriers and drivers refer also to a number of important considerations for decision makers when initiating and evaluating smart city projects. One possibility for future work includes the development of an open source strengths, weaknesses, opportunities and threats tool. The tool could include a web interface, and make use of the knowledge discussed in this investigation. It might further facilitate the decision making process, and assist in future smart city projects.

Acknowledgements We are grateful to the Seventh Framework Programme for research, technological development and demonstration, which partially sponsored this investigation under the SINFONIA Project (Grant Agreement Number 609019).

List of abbreviations, acronyms and symbols CO2

Carbon dioxide

Confidence interval

European Comission

European Union

IEA

International Energy Agengy

IQR

Interquartile range

Overall

Opportunities

OPEC

Organization of Petroleum Exporting Countries

Level of significance

RES

Renewable energy sources

Strenghts

SCs

Smart cities

SWOT

Strengths, Weaknesses, Opportunities, Threats

Sample size

Threats

Weaknesses

Constant

References [1]

EC, 2020 climate & energy package, http://ec.europa.eu/clima/policies/strategies/2 020/documentation_en.htm (last accessed 18.10.2016)

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

ISSN 2363-6440

___________________________________________________________________________________________________________

[2]

EC, 2030 Energy Strategy, http://ec.europa.eu/clima/policies/2030/index_ en.htm (last accessed 18.10.2016)

[3]

EC, 2050 Energy Strategy, https://ec.europa.eu/energy/en/topics/energystrategy/2050-energy-strategy (last accessed 18.10.2016)

[4]

WWF, Living Planet Report 2014, WWF, 2014.

[5]

EUROSTAT, Energy production and imports, http://ec.europa.eu/eurostat/statisticsexplained/index.php/Energy_production_and_i mports (last accessed 19.10.2016)

[6] [7]

[8]

[9]

[10]

IEA, WORLD ENERGY OUTLOOK, Publishing, Paris, France, 2015.

22, Number 10, pp. 811-818, doi:10.1016/03014215(94)90139-2. [15]

EC, Smart cities and communities, http://ec.europa.eu/research/participants/porta l/desktop/en/opportunities/fp7/calls/fp7energy-smartcities-2012.html (last accessed 19.10.2016)

[16]

EC, CONCERTO projects, http://concerto.eu/concerto/concerto-sites-aprojects/sites-con-projects.html (last accessed 19.10.2016)

[17]

EC, Smart Cities & Communities, https://ec.europa.eu/inea/en/horizon2020/smart-cities-communities (last accessed 19.10.2016)

[18]

EC, The CONCERTO initiative, http://concerto.eu/concerto/aboutconcerto.html (last accessed 19.10.2016)

[19]

EC, SMART CITIES AND COMMUNITIES, http://ec.europa.eu/eip/smartcities/ (last accessed 19.10.2016)

[20]

Amsterdam city, Amsterdam smart city, http://amsterdamsmartcity.com/ (last accessed 20.10.2016)

[21]

Climate and Energy Fund, Austria's Smart Cities and Smart Urban Regions, http://www.smartcities.at/cityprojects/austrias-smart-cities-and-smart-urbanregions/ (last accessed 20.10.2016)

[22]

Pahl Nadine, Richter Anne, SWOT Analysis - Idea, Methodology And A Practical Approach, Grin Publisher, Berlin, Germany, 2009

[23]

Creative Research Systems, Sample Size Formulas for our Sample Size Calculator, http://www.surveysystem.com/sample-sizeformula.htm (last accessed 21.10.2016)

[24]

Clapham Christopher, Nicholson James, The Concise Oxford Dictionary of Mathematics, OXFORD University Press, Oxford, United Kingdom, 2009.

OECD

EUROSTAT, Consumption of energy, http://ec.europa.eu/eurostat/statisticsexplained/index.php/Consumption_of_energy (last accessed 19.10.2016) EIFER, ENERGY, CITIES AND TERRITORIES, https://www.eifer.kit.edu/-energy-cities-andterritories(last accessed 19.10.2016) Bourgeais Vincent, Just over 40% of the EU population lives in cities Urban population in the Nordic Member States most satisfied with public space, EUROSTAT, 2015. Pezzutto Simon, Vaccaro Roberto, Zambelli Pietro, Mosannenzadeh Farnaz, Bisello Adriano, Vettorato Daniele, FP7 SINFONIA project, Deliverable 2.1 SWOT analysis report of the refined concept/baseline, EURAC, Bolzano, Italy, 2014.

[11]

Painuly Jyoti Prasad, Barriers to renewable energy penetration; a framework for analysis, Renewable Energy, Volume 24, 2001, Issue 1, pp. 73–89.

[12]

Goh Choo Hong Telvin, Hooper Val, Knowledge and information sharing in a closed information environment, Journal of Knowledge Management, Volume 13, Number 2, 1997, Issue 2, pp. 21-34, doi: 10.1108/13673270910942673.

[13]

Giffinger Rudolf, Fertner Christian, Kramer Hans, Kalasek Robert, Pichler-Milanconvic Natasa, Meijers Evert, Smart cities Ranking of European medium-sized cities, Vienna University of Technology, Vienna, Austria, 2007.

[25]

Schenler Warren, Hirschberg Stefan, Burgherr Peter, Makowski Marek, Granat Janusz, Deliverable D10.2 - RS2b Final report on sustainability assessment of advanced electricity supply options, PSI, 2009.

[14]

Sandstad Alan H., Howarth Richard, Normal’ markets, market imperfections and energy efficiency, Energy Policy, 1994, Issue 4, Volume

[26]

Stevenson Vicki, Some initial methodological considerations in the development and design of Delphi surveys, LCRI, 2010.

International Journal of Contemporary ENERGY, Vol. 2, No. 2 (2016)

ISSN 2363-6440

___________________________________________________________________________________________________________

[27]

Malczweski Jacek, GIS and Multicriteria Decision Analysis, JOHN WILEY & SONS, New York, USA, 1999.

[28]

Lane David, Percentiles, http://cnx.org/content/m10805/latest/ (last accessed 20.10.2016)

[29]

IEA. Energy Efficiency Governance, Publishing, Paris, France, 2010.

[30]

WEC, Smart grids: best practice fundamentals for a modern energy system, 2012.

[31]

Mosannenzadeh Farnaz, Vettorato Daniele, Defining Smart City: a conceptual framework based on keyword analysis, Tema Journal of Land Use, Mobility and Environment, 2014, Special Issue, SMART CITY - PLANNING FOR ENERGY, TRANSPORTATION AND SUSTAINABILITY OF THE URBAN SYSTEM, pp. 683-694.

[32]

[33]

[36]

Howarth Richard B., Andersson Bo, Market barriers to energy efficiency, Energy Economics, Volume 15, Number 4, 1993, pp. 262-272, doi:10.1016/0140-9883(93)90016-K.

[37]

EU Smart Cities Information System, CONCERTO archive, http://smartcitiesinfosystem.eu/concerto/concerto-archive (last accessed 21.10.2016)

[38]

EC, Market Place of the European Innovation Partnership on Smart Cities and Communities, https://eu-smartcities.eu/ (last accessed 21.10.2016)

[39]

Pîrlogea Corina, Barriers to Investment in Energy from Renewable Sources, Economia Seria Management, Volume 14, Number 1, 2011, Issue 1, pp. 133-140.

OECD

[40]

Golev Artem, Corder Glen D., Giurco Damien P., Barriers to Industrial Symbiosis, Journal of Industrial Ecology, Volume 19, Number 1, 2014, Issue 1, pp. 141-152, doi: 10.1111/jiec.12159.

Elzinga David, Energy Technology Perspectives 2012, IEA, Paris, France, 2013.

[41]

Cagno Enrico, Worrell Ernst, Trianni Andrea, Pugliese Giacomo, A novel approach for barriers to industrial energy efficiency, Renewable and Sustainable Energy Reviews, Volume 19, 2013, pp. 290-308, doi: 10.1016/j.rser.2012.11.007.

Lee Gyu M., Benefits and barriers to the smart grid, the Korean example, http://www.oecd.org/sti/ieconomy/46137179.p df (last accessed 22.10.2016)

[42]

Kaminker Christopher, Stewart Fiona, THE ROLE OF INSTITUTIONAL INVESTORS IN FINANCING CLEAN ENERGY, OECD Publishing, OECD, 2012

[43]

UITP, Planning tomorrow’s smart city: Turning plans into reality, http://www.uitp.org/news/planningtomorrow%E2%80%99s-smart-city-turningplans-reality (last accessed 23.10.2016)

[44]

Gann David, SMART LONDON PLAN, Smart London Board, London, United Kingdom, 2012.

[34]

Bent Elliott, Crowley Michael, Nutter Melanie, Wheel Claire, GETTING SMART ABOUT SMART CITIES, 2012

[35]

Sorrell Steve, Schleich Joachim, Scott Sue, O'Malley Eoin, Trace Fergal, Boede Ulla, Ostertag Katrin, Radgen Peter, Reducing Barriers to Energy Efficiency in Public and Private Organizations, Project JOS3CT970022, SPRU, 2000.

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Appendix Table 2: Barriers and drivers of smart city projects, respective weighing possibilities and assessed effectiveness [10] Effectiveness

POLICY National roadmaps, strategies, and policies for energy goals

-5

-4

-3

-2

-1

2.67

Political commitment over the long term

-5

-4

-3

-2

-1

4.12

Cooperation among stakeholders

-5

-4

-3

-2

-1

2.90

Communication between project participants and the public to increase awareness

-5

-4

-3

-2

-1

3.79

-5

-4

-3

-2

-1

1.57

-5

-4

-3

-2

-1

2.27

Existence of public-private engagement models

-5

-4

-3

-2

-1

1.80

Existence of financing models suitable for the innovation to address stakeholder involvement

-5

-4

-3

-2

-1

1.27

Public procurement

-5

-4

-3

-2

-1

2.30

Coordination of a large number of tenants

-5

-4

-3

-2

-1

1.30

Marketing application for awareness and involvement

-5

-4

-3

-2

-1

3.71

Set up of institutions to support the projects

-5

-4

-3

-2

-1

0.67

Obligations given to project participants

-5

-4

-3

-2

-1

0.53

Public participation

-5

-4

-3

-2

-1

2.07

Transparency of legislation

-5

-4

-3

-2

-1

2.13

Consistency of implementation and interpretation of law

-5

-4

-3

-2

-1

1.20

Existence of regulatory stability

-5

-4

-3

-2

-1

1.37

Procedures for authorization of technologies

-5

-4

-3

-2

-1

1.60

Existence of data security and privacy

-5

-4

-3

-2

-1

1.13

Tax pressure

-5

-4

-3

-2

-1

0.73

Transparency of taxation system

-5

-4

-3

-2

-1

0.83

Subsidies

-5

-4

-3

-2

-1

2.31

Existence of regulatory incentives for implementation of smart city projects

-5

-4

-3

-2

-1

1.42

Tariffs regulations

-5

-4

-3

-2

-1

1.33

-5

-4

-3

-2

-1

1.48

-5

-4

-3

-2

-1

3.99

Existence of training material

-5

-4

-3

-2

-1

1.63

Monitoring

-5

-4

-3

-2

-1

1.59

ADMINISTRATION

Existence of multi-actor/multi-sectorial planning tools Share of valuable data between different departments

LEGISLATION

TECHNIQUE Affordable and mature technologies suitable for local conditions Expertise in designing new technologies and solutions

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ECONOMY Adverse selection

-5

-4

-3

-2

-1

1.57

Principal-agent relationship

-5

-4

-3

-2

-1

0.70

Split incentives

-5

-4

-3

-2

-1

0.80

Hidden costs

-5

-4

-3

-2

-1

0.80

Accessibility to capital

-5

-4

-3

-2

-1

0.83

Risk and uncertainty

-5

-4

-3

-2

-1

1.07

Up-front costs

-5

-4

-3

-2

-1

1.03

Costs of material, construction, and installation

-5

-4

-3

-2

-1

2.37

Economic crisis

-5

-4

-3

-2

-1

2.40

Existence of financial schemes

-5

-4

-3

-2

-1

2.80

Combining of different financial schemes

-5

-4

-3

-2

-1

0.30

Stability of costs during project life cycle

-5

-4

-3

-2

-1

0.93

Payback time

-5

-4

-3

-2

-1

0.97

Existence of tried and tested solutions and proven on the ground examples

-5

-4

-3

-2

-1

2.03

Complexity of applying solutions with regard to local conditions

-5

-4

-3

-2

-1

1.13

Interoperability between systems

-5

-4

-3

-2

-1

1.37

Supporting hard infrastructure

-5

-4

-3

-2

-1

1.70

Well-defined or documented in detail processes

-5

-4

-3

-2

-1

1.93

Existence of performance indicators for technologies implementation

-5

-4

-3

-2

-1

1.13

Form of information

-5

-4

-3

-2

-1

1.67

Credibility and trust

-5

-4

-3

-2

-1

1.77

Values related to energy efficiency, which may inhibit measures from being undertaken

-5

-4

-3

-2

-1

0.67

Inertia

-5

-4

-3

-2

-1

2.55

Bounded rationality

-5

-4

-3

-2

-1

2.03

Public acceptance of technologies

-5

-4

-3

-2

-1

1.77

Environmental awareness

-5

-4

-3

-2

-1

4.51

Requirements from the European Commission concerning reporting and accountancy

-5

-4

-3

-2

-1

4.80

Ownership structure of realities

-5

-4

-3

-2

-1

4.60

FINANCE

OPERATIVITY

BEHAVIOUR

ADDITIONAL FACTORS

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About the Journal

.e5

Instructions for Authors

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