Ijsrtm vol 2 (5) august september 2014

Vol 2 (5) August 2014

International Journal of Students’ Research in Technology & Management (IJSRTM)

Content 1. Effect of Fiber Length on the Short-Term Flexural Creep Behavior of Polypropylene C.Subramanian, Abdulrahman Khalfan Hassan Al Mamari and S.Senthilvelan 2. E-Waste: An Emerging Problem of Innovative Society Rahila N. Gadi and Nabeel Ahmed N.Gadi 3. Trend Analysis of Climate Variability in Salalah, Oman Mohammed Al-Habsi , Luminda Gunawardhana and Ghazi Al-Rawas 4. Using a New Programme to Predict Thermal Comfort as a Base to Design Energy Efficient Buildings Hanan Al-Khatri and Mohamed B. Gadi 5. Wadi Flow Simulation Using Tank Model in Muscat, Oman Mohammed Al-Housni, Luminda Gunawardhana and Ghazi Al-Rawas 6. Mobile Ad Hoc Networks

Parth Panchal and Meghana Shroff

International Journal of Students’ Research in Technology & Management Vol 2 (05), August-September 2014, ISSN 2321-2543, pg 157-162

Effect of Fiber Length on the Short-Term Flexural Creep Behavior of Polypropylene C.Subramanian*#1, Abdulrahman Khalfan Hassan Al Mamari #2, S.Senthilvelan#3 #1

Shinas College of Technology, Oman Petroleum Development Oman, Oman #3 Indian Institute of Technology Guwahati, India #2

1subra@shct.edu.om 2a.k.ha@hotmail.com 3ssvelan@iitg.ernet.in

Abstract—

Injection molded long fiber thermoplastic components are being used in recent days as a viable replacement for metals in many applications .Present work focus on the effect of fiber length on the short-term flexural creep performance of fiber reinforced thermoplastic polypropylene. Unreinforced polypropylene, 20 wt % short and 20 wt % long glass fiber reinforced polypropylene materials was injection-molded into flexural test specimens. Short-term flexural creep tests were performed for 2 h duration on molded specimen at various stress levels with the aid of in-house developed flexural creep fixture.

Experimental creep performance of polypropylene composites for 2 h is utilized to predict the creep performance with the aid of four parameter HRZ model and compared with 24 h experimental creep data. Creep strain was found to be increased with respect to time for all the test materials and found to be sensitive with respect to the stress level. Test results also revealed that long fiber reinforced thermoplastic material possessed enhanced creep resistance over their counter parts and HRZ model is sufficient enough to predict creep performance of polypropylene composites over wide range of stress.

Keywords- Injection molding, flexural creep, thermoplastic, creep, strain

I. INTRODUCTION Due to the mass production requirement in the automotive industries, discontinuous long fiber reinforced thermoplastics (LFRT) have shown significant role in replacing metals, short fiber reinforced thermoplastics, thermoset sheet molding and bulk molding composites [1]. The common problem associated with unreinforced thermoplastics is creep under moderate to severe stress at elevated temperature. Creep resistance of thermoplastic composites is significantly improved by increase in fiber loadings [2]. Dynamic mechanical analysis (DMA) was utilized to investigate the viscoelasticity of injection-molded nylon 6/6 material reinforced with short and long glass fibers by Sepe[3] and reported an increase in creep resistance for long glass fiber reinforced nylon composites. Challa and Progelhof [4] investigated the effect of temperature on the creep characteristics of polycarbonate and developed a relationship based on Arrhenius theory to develop creep master curves.

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Pegoretti and Ricco [5] studied the propagation of crack under creep for varying temperature conditions for polypropylene composites and observed that speed with which the crack progresses was dependent on the test temperature.

Krishnaswamy [6] performed extensive creep rupture testing on high density polyethylene pipes at various hoop stress levels and temperatures and observed the dependency of density and crystallinity towards failure. Houshyar [7] reported the improvement in creep properties with the addition of long polypropylene fibers in propylene-co-ethylene (PPE) matrix and visualized the improvement in interfacial properties. Trans-crystallization of the polypropylene matrix was observed in the PPE samples due to the thin layer of matrix on the reinforcement, which was attributed to good impregnation and wetting of the fibers. Greco et al. [8] investigated the flexural creep behavior for compression molded glass fiber reinforced polypropylene at various applied stress level. The effect of matrix crystallinity was highlighted for the improvement in creep properties for glass fiber reinforced polypropylene in their work. Acha et al. [9] studied the influence of interfacial adhesion in discontinuous jute fiber reinforced polypropylene. Relation between interfacial properties and creep deformation were investigated. Higher creep resistance was observed for polypropylene composites with good interfacial bonding which was confirmed by the observation of the composite fractured surfaces.

Findley and Khosla [10] conducted creep tests for unreinforced thermoplastics; polyethylene, polyvinyl chloride and polystyrene. Approximation was carried out for the linear viscoelastic region by power law and compared the creep performance by estimating the power law coefficient and power law exponent. Liou and Tseng [11] used Findley power law to estimate the creep compliance of carbon fiber nylon composites in hygrothermal condition. Power law model was modified by Hadid et al. [12] by incorporating the time and stress dependence during creep loading of polyamide specimens and estimated four parameters for describing the deformation occurring in the material and used stress–time superposition principle to predict long-term material creep behavior of injection molded fiber glass reinforced polyamide.

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Master curves were developed and a perfect superposition of the curves at various stress levels was visualized. Novak [13] used strain energy equivalence theory and developed a creep predictive model to predict the creep behavior of talc filled polypropylene. Banik et al. [14] reported the improvement in creep resistance due to unidirectional reinforcement for polypropylene-polypropylene composites. Burger and Findley power law model were used to predict the short term creep behavior and the underlying deformation mechanisms were also investigated. Liu et al.

[15] used multi-Kelvin element theory and power law functions to predict creep compliance in polyethylene material and compared with the tensile creep experiments.

Even though a lot of works were carried out in the past pertaining to the experimental creep behavior of plastics and composites, estimation and prediction of creep data using mathematical and numerical modeling is limited. Hence in this work the influence of reinforced fiber length on the creep performance of thermoplastic composite at various stress levels at room temperature condition was carried out. The results obtained through flexural creep test were analyzed using Findley power law model and empirical model proposed

by Hadid et al [12]. Short term experimental creep results were used to predict long term creep behavior of the molded specimen.

II. THEORECTICAL BACKGROUND A. Findley’s Power Law Model Mechanical behavior of polymeric material under constant stress was developed by Findley and Khosla [10]. The general form of the power law equation is given as

ε(t) = ε't t n

(1) is the time dependent strain, ε't is power law

where ε(t) coefficient which is stress and temperature dependent coefficient, n is the power law exponent and t is the time after loading.Power law model is simple in approach and successfully predicted nonlinear viscoelastic creep behavior of thermoplastic composites over large range of stress[1013]besides this model is also recommended by American Society of Civil Engineers (ASCE) for structural plastics design manual in the analysis of composite materials for long term structural behavior [16].

B. HRZ Model Findley’s power law was unsuccessful in accounting for the stress effect on the mechanical behavior of polymeric material. The two power law parameters in the Findley-Khosla

(n) were plotted with respect to stress level (ζ). The best fitting curve proposed the relation between

εt'

and ζ as

ε't = a ( ζ ) b

(2)

n=c exp ( e.ζ )

(3)

Similarly the best fitting curve proposed between n and ζ value takes the form Eqs. (2) and (3) are used in eq. (1) and strain at any particular time (t) can be calculated using the following HRZ equation

ε(t)= aζ bt cexp(e.ζ)

(4) where a, b ,c ,e are the curve fitting parameters obtained from the regression analysis. Chevali et al. [17] used the four parameter HRZ model to fit the experimental data obtained from flexural creep investigation for nylon 6/6, polypropylene and high-density polyethylene based long fiber thermoplastic composites.

III. EXPERIMENTAL CREEP PERFORMANCE OF POLYPROPYLENE COMPOSITES A. Specimen Fabrication In the current investigation, 20 wt % short glass fiber reinforced polypropylene (SFPP), 20 wt % long glass fiber reinforced polypropylene (LFPP) and unreinforced polypropylene (UFPP) obtained from Saint Gobain were used for injection molding the specimens. In general, lengths of the reinforced fibers in the short and long fiber reinforced pellets are 1 mm and 12.5 mm respectively [18]. Weight average fiber length of the reinforced fibers after injection molding for the chosen SFPP and LFPP materials are 0.440 mm and 1.251 mm respectively [19]. The base resin of LFPP and SFPP materials were having same molecular weight with a melt flow index of 40 g/10 min. According to the material supplier’s data, silane type coupling agent has been used for the manufacturing of SFPP and LFPP materials. Since both the investigated materials used the same type and amount of coupling agent, material behavior discussions were limited only to the reinforced fiber length. Developed injection molding dies and molded specimens are shown in Figs 1a and 1b. Raw materials were initially preheated for two hours at 353 K and during molding, screw speed of 50 rpm and a low back pressure of 0.25 MPa were kept to retain the residual fiber length. Process parameters used for injection molding are listed in Table I. Due to the presence of reinforced fibers in LFPP and SFPP materials, temperature in the three zones were kept higher than unreinforced material.

model ε't and n are significantly influenced by the applied stress level. Hadid et al. [12] modified the Findley’s power law to incorporate time and stress dependence in the model where the power law coefficient (ε't) and power law exponent

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recorded. Creep strain at instantaneous time ( ε(t)) is computed using the relation (5) [20].

ε(t) =

6δ(t).d l2

(5)

where, δ (t) is the deflection at instantaneous time , d is the thickness and l the test specimen length. The corresponding stress is calculated using the relation

Smax =

Fig 1a .Die for preparing specimens

3Pl 2 2wd

(6)

Where Smax is the stress and P is the load, l is the length and w is the width and d is the thickness of the specimen .The length, width and thickness of the specimen is 70mm, 13 and 3mm respectively.

Dial Gauge

Fixture

Steel Rod Fig 1b. Injection molded specimens for flexural creep testing

TABLE 1 INJECTION MOLDING PARAMETERS FOR THE SPECIMENS

Screw diameter L/D Screw speed Barrel temperature Zone 1 Zone 2 Zone 3

35 mm 20 50 rpm

Injection speed Mold temperature

50 mm/sec 40 ο C

255 ο C 250 ο C 240 ο C

IV. EXPERIMENTAL METHODOLOGY A fixture is developed in house to evaluate the creep performance of molded specimen according to ASTM D2990 standard. The specimen is kept in between the supports as shown in Fig 2a and the load is applied at the centre of the test specimen with the means of steel rod attached with dead load.

When the load is applied at the center the specimen is deflected and the deflection is recorded in the dial gauge as shown in Fig 2b. Test specimens were loaded with respect to various stress levels for 2 hrs. Constant load is maintained and test specimen deflection ( δ(t) ) is continuously measured and

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Dead Weight

Dial gauge Reading Specimen

Fixture

Fig 2(a-b). Assembled view of the flexural creep fixture

V. RESULTS AND DISCUSSIONS A. Creep Behavior of Polypropylene Thermoplastic Composites Creep performance evaluation was carried out at various loading levels ranging from 18.84 N/mm2 to 47.17 N/mm2 for all the materials. Fig 3 shows the 2h creep response of the chosen test specimens. A raise in creep strain was observed with the time period for all the specimens. Subsequent to the preliminary rapid increase in creep strain, the rate of creep

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strain decreases. Three trails were conducted for calculating creep strain for all the molded materials and the deviation for LFPP, SFPP and UFPP were found to be 2.5 %, 3.2 % and 1.5 % respectively Improved creep resistance behavior of long fiber reinforced polypropylene is observed is due to the improved load transfer from the matrix to the reinforced fibers and the matrix constriction to deformation.

Chevali et al. [17] also observed a similar behavior with the increase in loading of glass fiber reinforcement in the nylon

determined.

Fig 4b. Creep strain for SFPP

The correlation index, R2 indicates that power law function provides a good approximation to the visco elastic behavior at every stress levels. It is vivid from Figs (4a-4c) that the power law coefficient ( ε't ) and power law exponent (n) are dependent on the stress level and increases with the increase in stress level composites.

Since the power law coefficient ( ε't ) and power law exponent (n) are sensitive to the stress level, a methodology adopted by Hadid et al.[12] was used to establish the dependence of

Fig 3. Comparison of creep strain for three materials for a stress of 22.5N/mm2

Due to the increase in reinforced fiber length, stiffness retention is more pronounced in LFPP. Due to the substantial time requirement for the creep investigation, an empirical model is made use in the subsequent section to predict the creep strain for a specific period of time.

B. Empirical Model for Predicting Short Term Creep Behavior The creep performance of molded specimens was experimentally investigated for 2h duration for the stress range varying from 18.84, 22.25, 38.27 and 47.17 N//mm 2 and the test results are shown in Fig (4a-4c) .It is vivid from the results that for all the tested materials, creep strain increases with time and found to be increased with applied stress level. Power law function is fitted using eq. (1) for each and every stress levels thereby power law coefficient ( εt ), power law exponent (n) and correlation index (R2) are '

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power law coefficient ( ε't ) (Fig5a) and power law exponent (n) (Fig 5b) on applied stress level. Fig 5a shows the best fitting curve using eq. (2) and depicts the influence of applied stress (ζ) on power law coefficient ( ε't ) for the test specimen .

The constant curve fitting parameters (a, b from eq. 2) are also shown in Fig 5a. In general the constant parameters a and b are dependent on glass transition temperature, degree of crystallinity, and fiber orientation in the composite[20] . These parameters represent the instantaneous strain normally visualized during the initial period of load application. Fig 5b shows the best fitting curve using eq. (3) and elucidates the influence of applied stress (ζ) on power law exponent (n) for the test specimen. The constant curve fitting parameters (c, e from eq. 3) are also shown in Fig 5b. The constant parameters c and e are dependent on the time period of testing and relaxation mechanisms involved for the composite. These parameters represent the viscous response visualized during the secondary creep process. Eq. (4) is used to predict creep performance of molded specimen and compared with the 24 h experimental data as shown in Fig 6 (a-c). It is found that HRZ model predicted well with the experimental creep performance of the chosen thermoplastic composite specimen.

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Fig 4c. Creep strain for LFPP

Fig 6a Experimental and predicted creep performance of UFPP for 55MPa

Fig 5a. Variation of power law coefficients over stress Fig 6b Experimental and predicted creep performance of SFPP for 40MPa

Fig 5b. Variation of power law exponents over stress

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Fig 6c Experimental and predicted creep performance of LFPP for 20MPa

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VI. CONCLUSIONS Discontinuous fiber reinforced polypropylene composites were injection molded and its short term flexural creep performance is investigated. Due to the extensive time requirement for the creep performance evaluation, HRZ model was used in this work. Creep performance of the molded specimens was experimentally evaluated for 2 h and short term creep performance (24 h) was predicted with the aid of HRZ model over wide range of stress. The predicted performance was compared with 24 h experimental results and found to be satisfactory. From the present investigation, HRZ model was found to be useful in predicting the short-term creep performance of viscoelastic engineering material.

Experimental results confirmed that long fiber reinforced thermoplastics possessed enhanced creep retention characteristic. HRZ model parameters were also utilized to correlate investigated material characteristics.

REFERENCES [1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

[9]

J. Markarian, “Long fibre reinforcement drives automotive market forward”, Plastics, Additives and Compounding, Vol.7, pp.24-29, 2005.

B.V. Gupta and J. Lahiri, “Non-linear viscoelastic behavior of polypropylene and glass reinforced polypropylene in creep,” Journal of Composite Materials, Vol.14, pp.288-296, 1980.

Sepe, M.P. Use of advanced characterization techniques in evaluating the fitness-for-use of longglass fiber thermoplastics: San Francisco, 1994, pp.2029-2032.

S.R .Challa and R.C .Progelhof, “A study of creep and creep rupture of polycarbonate”, Polymer Engineering and Science, Vol.6, pp.546-554, 1995.

A. Pegoretti and T.Ricco, “Creep crack growth in a short glass fibres reinforced polypropylene composite”, Journal of Material Science, Vol.19, pp.4637-4641, 2001.

R.K. Krishnaswamy, “Analysis of ductile and brittle failures from creep rupture testing of high-density polyethylene (HDPE) pipes”, Polymer, Vol. 28, pp.11664 -11672, 2005.

S.Houshyar , R.A.Shanks and A. Hodzic, “Tensile creep behavior of polypropylene fibre reinforced polypropylene composites”, Polymer Testing,Vol. 24,pp. 257-264,2005.

A.Greco, Claudio Musardo and Alfonso Maffezzoli, “Flexural creep behaviour of PP matrix woven composite”, Composites Science and Technology, Vol.67, pp.1148-1158, 2007.

B.A. Acha M.M.Reboredo, and N.E.Marcovich, “Creep and dynamic mechanical behavior of PP–jute composites: Effect of the interfacial adhesion”, Composites Part A: Applied Science and Manufacturing, Vol.33, pp.1507-1516, 2007.

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[10] W.N. Findley and G. Khosla, “Application of the superposition principle and theories of mechanical equation of state, strain, and time hardening to creep of plastics under changing loads”, Journal of Applied Physics, Vol.26, pp.821–832,1955.

[11] W.J. Liou and C.I. Tseng, “Creep behavior of nylon6 thermoplastic composites”, Polymer Composites, Vol.18, pp.492-499, 1997.

[12] M.Hadid, S.Rechak and A.Tati, “Long-term bending creep behavior prediction of injection molded composite using stress-time correspondence principle”, Materials Science and Engineering A, Vol.385, pp.54-58, 2004.

[13] G.E. Novak, “Creep fracture of long fiber reinforced nylon 66”, Polymer Composites, Vol.16, pp.38-51, 1995.

[14] K.Banik, J.Karger-Kocsis and T. Abraham, “Flexural creep of all-polypropylene composites: Model analysis”, Polymer Engineering Science, Vol.48, pp.941-948, 2008.

[15] H.Liu, M.A.Polak and A.Penlidis, “A practical approach to modeling time-dependent nonlinear creep behavior of polyethylene for structural applications”, Polymer Engineering Science, Vol.48, pp.159-167, 2008.

[16] American Society of Civil Engineers, Structural Plastic Design Manual, 1986.

[17] V.S.Chevali, D.R. Dean, and G.M. Janowski, “Flexural creep behavior of discontinuous thermoplastic composites: Non-linear viscoelastic modeling and time–temperature-stress superposition”, Composites: Part A, Vol. 40, pp. 870877, 2009.

[18] “Twintex Product Data Sheet”, Long fiber thermoplastic pellets, 2005, USA. [19] C.Subramanian and S.Senthilvelan, “Development and preliminary performance evaluation of discontinuous fiber reinforced thermoplastic leaf spring”, Journal of Materials: Design and Applications, Proc. of Ins. Mech. E Part L,Vol. 223(3), pp.131-142, 2009.

[20] “ASTM D-2990 Standard test methods for tensile, compressive, and flexural creep and creep-rupture of plastics”, ASTM International, Philadelphia.

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E-Waste: An Emerging Problem of Innovative Society Rahila N. Gadi#1, Nabeel Ahmed N.Gadi*2 #

Dept of E&CE-Al-Musanna’s College of Technology, Oman

*

Dept of Community Medicine MM institute of Medical Science &Research Mullana, Haryana, India 1

rahila111@rediffmail.com

nabeel55@rediffmail.com

2

Abstract– In the past few years there is a revolution in electronic industry, which increases the volume and varieties of both solid and hazardous wastes. Urbanization Industrialization, fast changes in technologies leave a negative impact on health of human beings. Also increases the pollution in air, land and water. A growing municipal waste contains hazardous electrical and electronics products. When dumped in landfill will pollute the environment badly. This waste is usually named as E-waste (Electrical an Electronics Waste).In the absence of suitable techniques and protective measures, recycling e-waste can result in toxic emissions to the air, water and soil and pose a serious health and environmental hazard-waste is assuming serious proportions in developing countries and urgent steps need to be taken to mitigate this problem. This paper highlights the problem posed by e-waste and its hazards on environment and health Keywords– E-waste (Electrical &Electronic waste), carcinogen, landfills

I. INTRODUCTION During the last few years, there is an increasing acknowledgment of our impact on the environment due to our lifestyle, while the need to adopt a more sustainable approach concerning our consumption habits emerges as of particular significance. This trend regards industrial sector affecting the consumption habits and especially electronic industry where the short life cycles and the rapidly developing technology have led to increased E-waste volume [3] Electrical and Electronics waste, also known as Electronic waste or waste electrical & electronics equipment (WEEE), or in short called E-waste, is used to describe obsolete or end of life electrical & electronics equipment [4]. There is no generally accepted definition of E-waste around the world[2].According to the European Union directive WEEE means Electrical or Electronic Equipment which is waste within the meaning of article1(a) of directive75/442/EEC ,including all components, subassemblies and consumables which are part of the product at the time of discarding .However E-waste most often misunderstood as comprising only computers related IT equipment or email spam[5].It is universally understood as electronic waste disposed of by end users and a wide range of products, from simple devices to complex goods .Therefore E-waste comprises both white

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goods such as refrigerators ,washing machines and microwaves ,and brown goods which consists of TV ,Radios and Computers that have reached their ends for their current holder[6].

E-waste mainly comes from several sources: 

Residue or leftover materials from electronic products manufacturing process



.Leftover parts or materials or discarded EEE generated from a repair shop



Obsolete EEE coming from all sector of society like government offices, Companies, Education institutes, Household etc



Obsolete electrical or electronic products brought in by smuggling [7].

The production of electrical & electronic equipment (EEE) is one of the fastest growing global manufacturing activities.

Rapid economic growth, coupled with urbanization and a growing demand for consumer goods has greatly increased both the consumption and the production of EEE [8][9][10] II. MAGNITUDE OF PROBLEM The magnitude of the problem is really huge and scary.

According to UNEP, global E-waste generation is growing by about 40 million tons a year, and predicts that by 2020 in South Africa & china E-waste from old computers will jump by 200 to 400% from 2007 levels and by 500% in India [2].Developing countries are the major dumping grounds for E-waste. By 2020 there will be increase by 400 to 500%.The spectrum of hazardous E-waste Mountain looms large especially for developing countries with serious consequences for the environment and public health[11].The global E-waste production is accessed at 20-50 million ton/year, equal to 13% of the estimated global urban waste production. Personal computers, Cell phones and TV will contribute 5.5 Mt in 2010 and will increase to 9.8Mt in 2015.In developed countries Ewaste will stand for 8% of the urban waste volume[3].Each

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item‟s participation in the annual E-waste production(kg/year),depends on each electronics‟ item‟s mass M(Kg),its quantity (number) in the market and consumption(N) and its Average life cycle L (year).

Estimated Life E = MN/L For computers with an average 3 years life cycle contributes to a greater extent to the total E-waste flow compared to refrigerators and electric stoves, having an average of 10-12 years [12].Certain electrical & electronics equipment‟s which form the major part of the E-waste generation along with their mass and estimated life cycle are summarized in Table 1.

TABLE 1 ELECTRICAL & ELECTRONICS EQUIPMENTS & THEIR ESTIMATED LIFE

Items

Mass(Kg)

Estimated Life(Yrs)

Personal Computer

25

3

Cell Phones

0.1

2

Television

30

5

Fax Machines

3

5

AC

55

10

Photo copier

60

8

Washing Machine

65

8

Refrigerator

35

10

Microwave

15

7

Vacuum Cleaner

10

10

III. IMPACT ON HEALTH & ENVIRONMENT E-waste cannot be considered or treated like any kind of waste, because it contains hazardous and toxic substances such as heavy metals or others such as dioxins and furans (produced when E-waste is incinerated).For instance, lead represent 6% of the total weight of a computer monitor. It is been reported that nearly 36 chemical elements are incorporated in electronic equipment‟s [13].Electronic wastes can cause widespread environmental damage due to the use of toxic materials in the manufacture of electronics goods.

Hazardous metals such as lead (Pb) ,Mercury(Hg) and hexavalent chromium[Cr(VI)],in one form or the other are present in such wastes primarily consisting of cathode ray tubes(CRTs),PCB, capacitors, mercury switches ,relays

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.batteries etc. Liquid Cr tetardants on PCB, LCD, cartridges from photocopying machines, selenium drums etc. Land filling of E-waste can lead to the leaching of lead (Pb) into the groundwater and leads to un-portability of water. If the CRT is crushed and burned, it emits toxic fumes into the air cause air pollution, which are very hazardous to human being as well as animals. A rechargeable battery which contains toxic substances that can contaminate when burned in incinerators or disposed of in landfills .E-waste is much more hazardous than many other municipal wastes. Long term exposure to these substances damages the nervous system, kidney, reproductive system, endocrine system and bones. It also leads to carcinogen (cancer).Workers in E-waste recycling or disposal sector are poorly protected against the risk of it. They dismantle E-waste, often by hand in very unhealthy conditions. The hazardous substances found in the E-waste are considered dangerous to health. Inhaling or handling such substances and being in contact with them on a regular basis can damage the main organs of the human body. Working in poorly-ventilated enclosed areas without masks and technical expertise result in exposure to dangerous and slow poisoning chemicals. Due to lack of awareness, workers are risking their health [15][14].Scientist who examined Guiyu, China(one of the popular destinations of E-waste recycling activities) have determined that because of waste, the location has the highest level of cancer causing dioxins in the world. Pregnant women are six times more likely to suffer a miscarriage, and seven out of ten kids have too much lead (Pb) in their blood [17]. Ewaste is not alone factor in causation of environmental and health problems but its inadequate management which plays as a catalyst in the magnitude of the problem.

IV. STRATEGIES FOR REDUCTION OF E- WASTE The best option for dealing with E-waste is to reduce the volume. Designers should ensure that the product is built for re-use and/or upgradability. Stress should be laid on use of less toxic, easily recoverable and recyclable materials which can be taken back for refurbishment, remanufacturing, disassembly and reuse. Recycling and reuse of material are the next level of potential options to reduce E-waste.

Recovery of metals, plastic, glass and other materials reduces the magnitude of E-waste. These options have a potential to conserve the energy and keep the environment free of toxic materials that would otherwise have been released. It is high time the manufactures, consumers, regulators, municipal authorities and policy makers take up the matter seriously so that the different critical elements are addressed in an integrated manner. It is need of the hour to have an “E-waste policy “and national regulatory framework for promotion of such activities. An E-waste policy is best created but those who understand the issues. So it is best for industry to initiate policy formation collectively, but user involvement.

Sustainability of E-waste management system has to be ensured by improving the effectiveness of collection and recycling system (e.g: public-private partnership in setting up buy back or drop off center) and by designing in advance funding [1][15].The E-waste generated every year globally is

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40-50 million ton out of which 15 to 20 % is recycled and remaining is dumped in landfills/incinerators. If we have a good and effective recycling system and good policies to carry recycling process than we can sustain our natural resources which is depleting very fast V. E-WASTE MANAGEMENT To have a better management of E-waste the end user should be aware of the hazardous affects of E-waste. Proper awareness should be given and in turn survey should be conducted to find what people are doing with their E-waste. Is they are just dumping in the store room or selling to scrap people or they are giving back to the company .Find the amount of E-waste generated, by surveys from all sector of society, awareness program to educate the people how to reuse the existing Electrical & Electronics products. Next step will be the design of a proper E-waste management system to reduce and to recycle the E-waste generated. The first in the process is to collect the E-waste from all sector of the society i.e from companies, institution, residential, hospitals etc.

The second step involved to manage the E-waste is to apply the principle of three R i.e. Reduce, Reuse and Recycle.

As the duty of the user is that try to minimize the E-waste generation by up grading the system or repair it. If those things will not give the expected output then try to resale or recycle it. Many companies have take back schemes.

Segregation & dismantling of the various equipment or components is the third step where under proper environment this process is carried out. In the recycling process we can recovery many valuable materials and metals. Which can be reused? The last part is the hazardous materials disposal that has to be done with at most cares.[1][2][16] VI.NEED FOR E-WASTE POLICY AND REGULATION The policy should address all issues ranging from production and trade to final disposal, including technology transfer for the recycling of electronics waste. Clear regulatory instruments, adequate to control both legal or illegal exports and imports of E-waste and ensuring their environmentally sound management should be in place.

According to the EU the designers and the manufactures have to obey the RoHS directive which bans or restrict the use of certain hazardous substances like lead and its compound, Cadmium and ,its compound, Mercury, hexavalent chromium, polybrominated biphenyls[1].The regulations should prohibit the disposal of E-waste in municipal landfills and encourage owners and generators of E-waste to properly recycle the waste. Manufactures of products must be financially, physically and legally responsible for their products. Better management of hazardous substances may be implemented through measures such as 

Specific product take back obligations for industry.



Financial responsibility for actions and schemes



Greater attention to the role of new product design.

Follow RoHS directives.

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

Greater scrutiny of cross border movements of electrical & electronic products and E-waste



Increasing public awareness by labeling products as “Environmental Hazard”



Personal protection measures (masks, Gloves, shields, protective glasses etc) should be made available to all the workers who are engaged with Ewaste management.

The key questions about the effectiveness of legislation would includes 

What is to be covered by the Term Electronic Waste



Who pays for disposal is the producer responsibility the answer.



What would commitments



How can sufficient recovery of materials be achieved to guarantee recycling firms a reliable and adequate flow of secondary materials [18].

be

the

benefits

of

voluntary

A. Benefits of E-Waste 

Conservation of natural resources



Preventing soil, water and air contamination by toxic chemicals.



By back offers for consumers



Creates new jobs in the market



Creates new markets for secondary materials and components

B. Energy Efficiency [19][16] Reduction of energy requirement, cost involved in Ewaste recycling is comparatively less than the cost involved in mining and processing of new materials from scratch.

Recycling of Aluminum can save 95% of energy than production from basic ore. Recycling of plastic can save 70% of energy and glass up to 40%.Recovering of metals from recycling process generates only a fraction amount of co 2 emission compared from natural process. Innovation in Ewaste treatment should focus on the major needs to improve overall sustainability [1][18].Some of the policies in place globally for effectively managing E-waste are mention in table 2.

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REFERENCES [1]

Model

Current Examples

Likely Implications

Producers Responsibility Commonly known as EPR Manufacturers financially responsible beyond point of sale. Take back Schemes & recycle them up to a defined percentage by the manufacturers Funding model for this activity varies from company to company European Union Japan, South Korea, Taiwan Pressure on manufacturers to follow RoHS directive

Government Responsibility End consumer taxed a recycling fee on the purchased product.

This Tax/Fees is used to fund the Ewaste collection & recycling activity Government is responsible to monitor & collect the E-waste

[2]

[3]

[4] Switzerland California(USA) No incentives for manufacturer to create cleaner design.E-waste not likely to reduce as manufacturers do not have any liability

VII. CONCLUSION The Electronic market has revolutionized the whole world over last decades as Electrical & Electronics products increasingly capture the major part of our lifestyle. While no one can give the exact figures how much E-waste is presently generated or how much of this is hazardous, what is definite is that if we the people living in the innovative society don‟t try to manage the E-waste properly then E-waste have the potential of threatening human health and its environment.

Initiatives are been taken to reduce the volume of generation and to have an effective recycling techniques, which can sustain the natural resources as well as conserve the energy.

E-waste in developing countries is a menace. There is lack of awareness among the people about E-waste. This paper highlights some of the problems, their impact on human health and environment, briefly explains how to have an effective E-waste management system with examples

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[5]

[6]

[7]

[8]

Dejo Olowu Article „Menace of E-Wastes in Developing CountriesAn Agenda for Legal and Policy Responses‟, Lead Journal-ISS1746-58938/1 Law, Environment and Development Journal (2012), p.59, available at http://www.leadjournal.org/content/12059.pdf Sustainable Innovation & Technology Transfer Industrial Sector studies Recycling from E-waste to resources, July 200 UNEP-STEP G. Gaidajis*, k. Angelakoglou and d. Aktsoglou, ewaste: environmental problems and current management, journal of Engineering science and technology review 3 (1) (2010) 193- 199 Y. C. Jang and h. Yoon, 2006. The practice and challenges of electronic waste recycling in korea with emphasis on extended producer responsibility (EPR).

Anweshaborthaku, pardeepsingh international journal of environmental sciences volume 3 no.1, 2012 Deepalisinhakhetriwal, philippkraeuchi, rolfwidmer, 2007. Producer responsibility for ewaste management: key issues for consideration – learning from the swiss experience.Journal of environmental management, 2007. Xx: 1–1 Shah alam, selangor, electrical and electronic waste management practice by households in , malaysia,2010, international journal of environmental sciences volume 1, no 2 ,2010 Ramesh babu b, parandeak, ahmedbasha c. Electrical and electronic waste: a global environmental problem.

Waste manag res. 2007;25:307–18. [pubmed].

Sinha s. Downside of the digital revolution. Published in toxics link, 28/12/2007. Accessed 13 feb/96/ec . 2013.

Available: http://www.toxicslink.org/artview.php?id=124

[9]

V. O. Akinseye, electronic waste components in developing countries: harmless substances or potential carcinogen, 2013, annual review & research in biology, 3(3): 131-147 , 2013 [10] Bina rani et al, j advscient res, 2012, 3(1): 17-21 17 [11] K. Betts, producing usable materials from e-waste, environ sci technol. 42, pp. 6782–6783 (2008) [12] Musson se, jangnyc, townsendtg, chungih.

Characterization of lead leachability from cathode ray tubes using the toxicity characteristic leaching procedure. Environmental science & technology.

2000;34(20):4376-4381

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[13] Ajeetsaojie-waste management: an emerging environmental and health issue in india,national journal of medical research,volume 2 issue 1 jan – march 2012 issn 2249 4995 [14] India together: un report spotlights india‟s e-waste pile up – 31 march 2010.

Available from: http://www.indiatogether.org/2010/mar/envunewaste.htm [15] Electronic waste: where does it go and what happens to it? By michellecastillo: january 2011. Available from: http://techland.time.com.

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[16] Environment, energy and transportation program; electronic waste. National conference of state legislatures [cited june 10, 2006]; available from http://www.ncsl.org/programs/environ/cleanup/ elecwaste.

[17] Waste wise update: electronics reuse and recycling.

Environmental protection agency 2000 [cited july 14, 2006]; available from: http:// www.epa.gov/wastewise/wrr/updates.htm.

[18] Article on Benefits of E-waste Recycling by Drew Hendricks in Growing Green Jobs August 6, 2012 Available from www.ewaste.htm

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Trend Analysis of Climate Variability in Salalah, Oman Mohammed Al-Habsi #1, Luminda Gunawardhana #2, Ghazi Al-Rawas #3 #

Department of Civil and Architectural Engineering, Sultan Qaboos University P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman 1

u086829@student.squ.edu.om 2 luminda@squ.edu.om 3 ghazi@squ.edu.om

Abstract—The frequency and intensity of weather events are expected to change as climate change, which may result in more frequent and intensive disasters such as flash floods and persistent droughts. Subsequent impacts will affect regions in different ways, but projected to worsen conditions in water scares countries like Oman. In Oman, changes in precipitation and temperature have already begun to be detected, although a comprehensive analysis to determine long-term trends has yet to be conducted. We analyzed daily precipitation and temperature records in Salalah city of Oman, mainly focusing on extremes. A set of climate indices, defined in the RClimDex software package, were derived from the longest available daily series (precipitation over the period 1943-2011 and temperature over the period 19912011). Results showed significant changes in daily minimum and maximum temperatures associate with cooling as well as warming. The annual number of cold nights (percentage of days when daily minimum temperature (TN) less than 10th percentile of that during base period: 1991-2000) decreased by 8 days per decade (p-value = 0.3). On the other hand, the annual number of warm nights (percentage of days when daily minimum temperature (TN) larger than 90th percentile of that during base period) increased by 10 days per decade (p-value = 0.3). In contrast, the annual occurrence of cold days increased by 11 days per decade (p-value = 0.25), while the annual occurrence of warm days decreased by 4 days per decade (p-value = 0.62). The significant trends apparent in minimum temperatures reveal that Salalah area has become less cold rather than hotter. Moreover, contrary trends in minimum and maximum temperatures indicate that, in long-term, daily temperature range has decreased in this area.

Annual total precipitation averaged over the period 1943-2011 is 95 mm, which shows a statistically weak negative trend with a 2 mm/10 yr rate. There is also a tendency for precipitation extremes according to many indices. The contribution from very wet days to the annual precipitation totals steadily increases with significance at 87% level. The positive trend in simple daily intensity index is also clear and reasonably significant (p-value = 0.29). Results of all these indices lead us to conclude that precipitation intensity in Salalah has increased while mean precipitation changes are less marked.

I. INTRODUCTION Extreme weather events are causing extensive damage to economy, environment and human life. For example, the supper cyclone, hurricane gonu in 2007 caused extensive damage along coastline cities, with total rainfall reached 610

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mm near the coast. The cyclone caused about 4 billion in damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008).

Many studies show that these extreme events that used to be rare in more than 60 years before are becoming frequent in many parts of the world in recent decades. Alexander et al.

(2006) assessed changes in daily temperature and precipitation extremes. They found that the trends in minimum temperature are more significant, implying that many regions become less cold rather than hotter. Easterling et al. (2000) revealed the heavy precipitation change in Siberia and northern Japan while mean precipitation changes are less marked. Therefore, greater understanding of occurrence of past extremes is prime important to avoid or at least to reduce the damages such as catastrophic floods and prolonged period of droughts (Beniston et al. 2007; Fowler et al. 2005).

In Oman, changes in precipitation and temperature have already detected (Al Rawas and Valeo, 2010), although a comprehensive analysis to determine long-term trends has yet be conducted. With efforts to build a long-term database, the Sultan Qaboos University now possessed quality controlled records of daily temperature over the period 1991-2011 and daily precipitation over the period 1943-2011. The objective of this research is to use these data to evaluate the trends of extreme temperature and precipitation change in Salalah.

II. STUDY AREA Salalah, the second largest city in the Sultanate of Oman, located in southern of Oman and on the edge of the Indian Ocean (Fig. 1). Annual total precipitation averaged over the period 1943-2011 is 95 mm, which shows statistically weak negative trend of a 2 mm/10-years. Mean annual temperature during 1980-2008 warms at a rate of 0.12°C/10-years, which is relatively small compared to warmings recorded in northern cities such as Sur and Khasab (1.03 and 0.5°C per decade, respectively). Salalah costal plain serves one of the intense agricultural fields in the Sultanate of Oman. Consequently, over the time, saline water intrusion has become one of the major issues for the management of sustainable groundwater resource. By the end of 2003, a main project was operated to treat wastewater and re-inject 20000 m3 daily in the coastal wells in Salalah in order to stop seawater intrusion. In past, severe cyclones have occurred in Salalah area in 1959, 1963

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and 1966. In 2002, a tropical storm affected Salalah city which brought 58.6 mm rain in the city area and 250.6 mm rain in adjoining mountains.

We found no significant changes in most of precipitation indices (Table 1). However, consecutive wet days (CED) shows negative trend with a confidence 89% (Fig. 2). On the other hand, consecutive dry days (CDD) increases but exhibits only a statistically weak relationship with standard error larger than the slope of the fitted linear regression line. The simple TABLE I TEST STATISTICS OF PRECIPITATION INDICES

Index

Salalah

Slope

CDD 0.253 CWD -0.031 PRCPTOT -0.194 RX1day 0.018 RX5day -0.157 R95P 0.153 R95P/ 0.0027 PRCTOT SDII 0.015

Significant at

Standard error

P-value

0.38 0.020 0.535 0.211 0.284 0.466

0.507 0.113* 0.718 0.933 0.581 0.744

5% No No No No No No

10% No No No No Yes No

0.0017

0.130*

No

No

0.014

0.285

No

No

*Significance level < 25% Fig. 1. Study area in Oman

III. METHODOLOGY In this study, maximum and minimum temperatures, and precipitation trends were analysed using a selection of 27 indices. These indices were calculated using RClimDex software, which was developed by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) to analyse many aspects of a changing climate (Alexander et al. 2006). The quality control procedure in RClimDex was applied to identify errors in data processing.

Both minimum and maximum daily temperatures were considered as missing values if daily minimum temperature is greater than daily maximum temperature. Daily maximum and minimum temperature records were defined as outliers if they lye outside the range of four standard deviations (STDEV) from the mean of the records (Mean ± 4 × STDEV). Negative precipitation records were also considered as missing values.

Homogeneity test was conducted using RHtest software package to identify abrupt changes in data series. However, no artificial step changes were detected.

IV. RESULTS AND DISCUSSION The set of 27 indices used in this study includes 16 temperatures related and 11 precipitation related indices which describe changes in intensity, frequency and duration of temperature and precipitation events. For space reason, we present specific indices with significant impacts, together with combined indices, if the thresholds represent to values of hydrological significance. A trend is said to be detected when a test of the null hypothesis that no trend is present is rejected at a high significance level, such as 5% or 10%.

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Fig. 2. Trend of consecutive wet days (CWD)

Fig. 3. Trend of simple daily intensity index (SDII)

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Fig. 4. Contribution from very wet days to total precipitation

daily intensity index (SDII), which is the ratio of annual precipitation and number of wet days, shows a reasonably positive trend with a confidence of 71% (Fig. 3). Figure 4 depicts that the contribution from very wet days to the annual precipitation total steady increases with a reasonable high confidence of 87%. In other words, the probability of the null hypothesis (no contribution from extreme precipitation) becomes true is less than 0.13. These results lead us to conclude that precipitation intensity in Salalah has increased while the annual total precipitation slightly decreases.

Both absolute temperature indices: TNn (annual minimum value of daily minimum temperature) and TXx (annual maximum value of daily maximum temperature) in Table II exhibit no statistically significant change. However, the trends of TNx (annual maximum value of daily minimum temperature, Fig. 5) and TXn (annual minimum value of daily maximum temperature, Fig. 6) are relatively significant. The absolute magnitude of the gradients of two curves is higher than standard errors, even though none of them are statistically significant at 10% level. The extreme temperature range (ETR) index calculated from the difference between TXn and TNx indicates a reasonably strong upward trend (Fig. 7) with a confidence of 86%. In practical point of view, these changes indicate that the temperature of warmest nights increases while the temperature of coolest day times decreases.

When the percentile based indices were considered, the annual number of cold nights (percentage of days when daily minimum temperature (TN) less than 10th percentile of that during base period: 1991-2000) decreased by 8 days per decade (p-value = 0.3). On the other hand, the annual number of warm nights (percentage of days when daily minimum temperature (TN) larger than 90th percentile of that during base period) increased by 10 days per decade (p-value = 0.3).

In contrast, the annual occurrence of cold days increased by 11 days per decade (p-value = 0.25), while the annual occurrence of warm days decreased by 4 days per decade (pvalue = 0.62).

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V. CONCLUSIONS In this study, precipitation and temperature extremes in Salalah, Oman were investigated using a set of climate indices.

The significant trends apparent in minimum temperatures reveal that Salalah area has become less cold rather than hotter.

Moreover, contrary trends in minimum and maximum temperatures indicate that, in long-term, daily temperature range has decreased in this area.

Many precipitation indices show no statistically significant trend. However, there is a tendency for precipitation extremes according to some indices. The contribution from very wet days to the annual precipitation totals steadily increases with a confidence of 87%. The positive trend in simple daily intensity index is also clear and reasonably significant (pvalue = 0.29). However, the annual total precipitation averaged over the period 1943-2011 shows a weak negative trend with a -2 mm/10 yr rate. Results of all these indices lead us to conclude that precipitation intensity in Salalah has increased while mean precipitation changes are less marked TABLE III TEST STATISTICS OF TEMPERATURE INDICES

Index

Slope

Standard error

Pvalue

TNn TXx TNx TXn CSDI DTR TN10P TN90P TX10P TX90P ETR

-0.016 -0.077 0.024 -0.056 -0.353 -0.02 -0.217 0.282 0.313 -0.120 0.079

0.027 0.105 0.024 0.052 0.270 0.008 0.202 0.266 0.265 0.239 0.051

0.562 0.472 0.338 0.299 0.206* 0.025* 0.296 0.302 0.253 0.622 0.137*

Significant at 5% No No No No No No No No No No No

10% No No No No No No No No No No No

*Significance level < 25%

Fig. 5. Trend of annual maximum value of daily minimum temperature (TNx)

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International Journal of Students’ Research in Technology & Management Vol 2 (05), August-September 2014, ISSN 2321-2543, pg 168-171 REFERENCES

Fig. 6. Trend of annual minimum value of daily maximum temperature (TXn)

[1] M. E. Rafy, and Y. Hafez, ―Anomalies in meteorological fields over northern Asia and its impact on Hurricane Gonu,‖ 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[2] L. V. Alexander, et al., ―Global observed changes in daily extremes of temperature and precipitation,‖ Journal of Geophysical Research, 111, D05109, doi:10.1029/2005JD006290, 2006.

[3] D. R. Easterling, T. R. Karl, K. P. Gallo, D. A. Robinson, K. E. Trenberth and A. Dai, ―Observed climate variability and change of relevance to the biosphere,‖ Journal of Geophysical Researches vol. 105, pp. 101– 114, 2000.

[4] G. A. Al-Rawas and C. Valeo, ―Relation between Wadi drainage characteristics and peak flood flows in arid northern Oman,‖ Hydrological Sciences Journal,vol. 55, pp. 377-393, 2010.

[5] M. Beniston et al., ―Future extreme events in European climate: an exploration of regional climate model projections,‖ Climatic Change, vol. 81, pp. 71–95, 2007.

[6] H. J. Fowler, M. Ekstrom, C. G. Kilsby and P. D. Jones, ―New estimates of future changes in extreme rainfall across the UK using regional climate model integrations, 1. Assessment of control climate,‖ Journal of Hydrology, vol. 300, pp. 212–233, 2005.

Fig. 7. Trend of extreme temperature range index (ETR)

ACKNOWLEDGMENT Authors wishes to acknowledge Prof. Xuebin Zhang and Prof. Feng Yang at the Climate Research Branch of Meteorological Service of Canada for providing RClimDex.

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Using a New Programme to Predict Thermal Comfort as a Base to Design Energy Efficient Buildings Hanan Al-Khatri # ¹, Mohamed B. Gadi*² #

Civil and Architectural Engineering Department, Sultan Qaboos University, Oman

* Department of Architecture and Built Environment, University of Nottingham, UK ¹khatri@squ.edu.om ²Mohamed.gadi@nottingham.ac.uk

Abstract---- A strong relationship relates the thermal comfort and the consumption of energy, especially in the hot arid climate where the installation of HVAC systems is unavoidable. In fact, it has been reported that the HVAC systems are responsible for consuming huge amounts of the total energy used by the buildings that can globally reach up to 40% of the total primary energy requirement. The future estimations indicate that the energy consumption is likely to continue growing in the developed economies to exceed that of the developed countries in 2020. Under these situations, it seems that the shift towards more energy efficient buildings is not an option. Because part of any successful environmental design is to understand the potentials of the site, the proposed programme (THERCOM) assists in weighing the indoor and outdoor thermal comfort in different climates in order to provide better understanding of the site environment as well as testing the thermal comfort chances of the initial concepts.

Keywords---- energy efficient buildings, indoor thermal comfort, outdoor thermal comfort, passive design, arid climate, equatorial climate, warm temperate climate

I. INTRODUCTION The current records indicate that the buildings sector is responsible for consuming 40% approximately of the total primary energy requirements [1]. For any typical building, around 80% of this amount is consumed as an operational energy from which huge amounts are consumed for the HVAC systems alone [2]. This pattern of consumption is forecasted to grow as the future estimations predict that in 2020, the energy consumption of the developed economies are likely to exceed that of the developed countries [1].

The associated negative influences for these consumption patterns on the ecological systems of the planet impose their regulation. Hence, the concept of the energy efficient buildings is an attractive option. The energy efficient

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buildings can be characterised by their ability to satisfy both the proposed design requirements and the operational demands using the possible minimum energy compared with other buildings in the same design category [3]. This is mainly attained via applying the passive environmental design strategies in addition to utilising the renewable energy technologies.

In this regard, it may worth mentioning that the thermal comfort opportunities are defined to a large extent by the passive design strategies which in turn are mostly defined by the early design decisions. Thus, it is crucial to analyse and appreciate the thermal comfort demands in the early stages of the design in order to satisfy them passively as much as possible. Under the unavoidable conditions when the HVAC systems are required to modify the thermal conditions, the analysis of the thermal demands is still of benefit as it can be related to control the set points in order to achieve the optimal efficiency which will be reflected in potential savings.

However, in constructing such buildings, it is crucial to ensure that the proposed efficiency during the design stages is reflected in the operational stages as well. In fact, it has been reported that some of the energy efficient buildings tend to consume huge amounts of energy in order to keep them running properly, regardless of the apparent efficiency in the design stage [3].

The excess consumption of the operational energy may be partially due to the nature of the method by which the performance of these buildings is assessed. Frequently, a simulation approach is implemented to compare the intended scenario of the energy consumption with an ideal one.

Although the patterns of the occupants' behaviour are often included, it is difficult to predict the actual patterns.

Therefore, and taking into consideration that most of the operational energy is consumed to achieve the thermal comfort, it may be advantageous to view the thermal comfort demands from the approach of the adaptive models instead of

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applying the analytical ones. The former models are tailored towards specific groups of people in harmony with certain types of climates and they intensively consider the behavioural adaptations patterns [4]. As a result, most likely their predictions will resemble the actual patterns of consuming the energy in order to achieve the required thermal comfort.

Additionally and based on the characteristics of the energy efficient buildings, it can be understood that, at least in certain periods of the year, these buildings encompass the concept of the free running buildings that satisfy the heating and cooling demands passively. In a comparison with the buildings that depend on the HVAC systems, the free running buildings reduce the operational energy by around 50% [5]. However, in the attempt to use less energy, the risk of achieving poor quality of the indoor environment is obvious. This situation can partially be avoided by the comprehensive analysis of both the buildings thermal demands and the site potentials which leads to defining the periods at which the buildings can be operated on the free running mode. Inversely, in the situations of the uncomfortable conditions, the results of this analysis can be utilized to define adaptive set points that achieve the maximum potential savings.

II. THERCOM PROGRAMME Based on the Visual Basic programming language, the proposed programme (Thermal Comfort in Different Climates - THERCOM) has been developed to measure and predict the thermal comfort in the free running buildings (to download a trial version of the programme, kindly visit: http://www.nottingham.ac.uk/~lazmbg/MScREA/). It does so by means of measuring the wet bulb globe temperature index, the adaptive model for thermal comfort, and the tropical summer index. In addition, it assess the thermal comfort in the outdoor environments by means of measuring the wet bulb globe temperature index, the wind chill index, the discomfort index, and the heat index.

THERCOM can measure the thermal comfort in twelve different cities located in three climates based on the Koppen-Geiger climate classification. Based on the integrated data, the predictions can be calculated for 24 hours in each month for all the integrated indices, except those of the adaptive model for thermal comfort. This exception was due to the nature of the integrated formula which is based on the outdoor monthly mean temperature. The integrated climates are: the equatorial, arid, and warm temperate climates. The exclusion of the remaining two climates, i.e. snow and polar, was due to the relatively low populations in regions where these climates are dominant [6]. More details about the programme can be obtained from [7].

periods at which the interior thermal conditions are comfortable, the programme in fact defines the periods at which the HVAC system can be switched off in the examined building. On the other hand, predicting the outdoor thermal conditions is crucial in order to design the exterior environments properly as they affect the indoor environments [9].

III. METHODOLOGY The concept of the energy efficient buildings implies the good matching between the site environment and the used materials and equipment [3]. Based on this, and for the purpose of the study at hand, four mock-up models were constructed with different construction materials for the roof.

The thermal performance of these models was investigated based on the effectiveness of the roof materials in contributing towards providing the comfortable thermal conditions.

A. Constructional Details Despite the construction of the roof, the four models share identical dimensions, properties, and construction materials of the other parts of the models. They are basically a 3 m x 3 m x 3 m models with one 40 mm foam core plywood door (1 m x 2.2 m) located at the east facade and a single pane of glass with aluminium frame window (1.5 m x 1.5 m) located at the west facade. Brick concrete blocks with total thickness of 340 mm were used for the walls and a 100 mm concrete slab placed on the ground for the floor. The construction of these elements is detailed in Table 1.

For the roof, the investigated four construction systems are: - Cinder concrete with insulation - Hardboard slab with insulation - Timber slab without insulation - Concrete roof with asphalt cover The detailed components and their properties are displayed in Table 2.

The models are assumed to be located in Colombo city. It has been found that the west wind is dominant according to a previous analysis study of the city climate.

Therefore, the window was positioned on the west facade in order to encourage the natural ventilation. The wind velocity was modified based on the wind power low and based on Melaragno method to account for the changes in the wind velocity inside the buildings [10].

By predicting the interior thermal conditions, THERCOM assists in facilitating the selection of the most optimum design among the different design alternatives through comparing the thermal performance [5], [8]. In addition, by defining the

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TABLE 1 CONSTRUCTIONAL DETAILS OF THE MODELS ELEMENTS EXCEPT THE ROOF

Layer

Width (mm)

Density (kg/m³)

Specific heat (J/kg.ºC)

Conductivity (W/m.ºC)

Wall Brick Masonry Medium Concrete Cinder Plaster Building (Molded Dry) Concrete

110

2000

836.8

0.711

220

1600

656.9

0.335

10

1250

1088

0.431

656.9

0.837

1400

0.140

1130

0.008

100 3

Floor 3800 Door 530

Plywood Polystyrene Foam Plywood

34 3

530 Window

1400

0.140

Glass Standard

6

2300

836

1.046

46

B. Selected Thermal Index THERCOM programme was used to compute the thermal comfort for the explored models by means of calculating the Tropical Summer Index. This model was selected for the study at hand based on the coincidence of its climatic boundaries and the climatic conditions of the chosen city [7].

The investigated period includes 288 hours distributed as 24 hours from each month.

IV. RESULTS AND DISCUSSION A. Periods of Switching-off HVAC For each model, the dominant thermal conditions over the examined period are presented in their percentages of thermal sensation as depicted in Figure 1. As can be noted from the pie chart of the first model, a comfortable thermal sensation was dominant in 83% of the investigated hours followed by slightly warm sensation with a percentage of 16%. In 1% of the investigated hours, the dominant sensation was slightly cool.

For the second model, the pie chart indicates that in 78% of the examined hours, the thermal conditions were considered as comfortable. In 21% and 1% of the investigated hours, slightly warm and slightly cool sensations were presented respectively. For the third model, the thermal sensation of 76% of the tested hours was comfortable. In the remaining hours, a slightly cool sensation was present.

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Layer

Width (mm)

Density (kg/m³)

Specific Conductivit heat y (W/m.ºC) (J/kg.ºC) Case 1: Cinder concrete with insulation Aggregate 10 2240 840 1.8 Rubber natural 2 930 2092 0.138 Polystyrene 50 46 1130 0.008 foam Polyethylene 1 950 2301 0.502 Concrete cinder 100 1600 656.9 0.335 Plaster ceiling 10 1120 840 0.38 tiles Case 2: Hardboard slab with insulation Aggregate 10 2240 920 1.3 Rubber Polyurethane 2 1250 1674 0.293 elastomer Hardboard slab 10 1000 1680 0.29 Wool, fibrous 10 96 840 0.043 Board 10 160 1890 0.04 Coat 10 2300 1700 1.2 Case 3: Timber slab without insulation Sand 10 2240 840 1.74 Rubber 2 1100 2092 0.293 Slab 10 300 960 0.055 Plaster Board 10 1250 1088 0.431 Case 4: Concrete roof with asphalt cover Asphalt cover 6 900 1966 0.088 Concrete 150 950 656.9 0.209 lightweight Plaster 10 1250 1088 0.431

The fourth model has a different thermal scenario as demonstrated from the Figure. The comfortable conditions were dominant in only 52% of the examined hours, with the slightly warm and warm sensations forming the remaining percentages as 42% and 6% respectively.

Based on these percentages, it can be concluded that the longest period in which the mechanical ventilation systems can be switched off is of the first model followed by the second, third, and fourth with percentages of 83%, 78%, 76%, and 52% respectively.

For the rest of the investigated hours, it may be necessary to use the HVAC systems to achieve the required comfortable thermal conditions with an obvious need for cooling in the four cases.

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A detailed examination of the thermal conditions distributions as depicted in Figure 2 shows that for the first model, the mechanical ventilation can be switched off in about 14 hours from 20 to 10. Although an identical scenario is applicable for models 2 and 3 as can be noted from the Figure, the scope of switching off the HVAC systems in the hours from 10 to 20 is greater for the first model in comparison with the other models. In the fourth model, the hours at which the HVAC system can be switched off are limited to around 9 hours in each of January and February, 6 hours in each of May, June, November, and December, and the maximum is 13 hours in each of the months from July to October including both.

Nevertheless, it should not be forgotten that it is possible to expand the comfortable thermal conditions through the implementation of the passive design strategies. These strategies include the proper selection of the materials of the building envelope, the proper proportion of the openings to the solid area of the envelope, the orientation, the aspect ratio,

Fig. 1 Percentages of the thermal sensations of the examined models

Periods of Switching HVAC off

Fig. 2 Hours distribution of thermal sensations of the examined models

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the integration of the shading devices, etc.

Additionally, it should be mentioned that the use of the fans is permitted [12] as they consume negligible amount of energy compared with the HVAC systems to achieve an identical extension of the comfortable conditions.

B. Selecting the Optimum Roof System From other perspective, the statistical variance of the tropical summer index temperatures was calculated for the four models to show values of 1.92, 2.54, 3.11, and 3.89, where the means of the index temperatures were 28.59 ºC, 28.69 ºC, 28.91 ºC, and 30.29 ºC in sequence.

The narrowest spread of the index temperatures of the first model from its mean value, in addition to its longest comfortable period and consequently shortest uncomfortable periods especially those with slightly warm conditions in comparison with other models, indicate that the first model may be considered as the optimum option within the investigated alternatives.

Table 3 shows the thermal resistance of the four examined roofs. It is clear from the table that the first model has the best thermal performance as it has the highest thermal resistance.

A closer look clarifies that this resistance is mainly due to the presence of the thick insulation layer (layer 3: Polystyrene foam) which alone contributes of about 95% of the total roof resistance.

TABLE 3 DETAILS OF THE ROOF CONSTRUCTION

Resistance of Layer 1 Layer 2 Layer 3 Layer 4 Layer 5 Layer 6 Total

Model 1 0.006 0.014 6.250 0.002 0.299 0.026 6.597

Model 2 0.008 0.007 0.034 0.233 0.250 0.008 0.532

Model 3 0.006 0.007 0.182 0.023 0.218

Model 4 0.068 0.718 0.023 0.809

Nonetheless, the relatively good thermal performance of the first model may additionally be partially due to the combined effect of the high thermal mass of the concrete deck in addition to the position of the insulation layer where it was located above the structural deck close to the outer surface.

This according to [11] is the optimum position for the insulation to insure the most comfortable thermal conditions in the hot periods. For the first model, the order of the construction materials with the insulation closer to the outer surface insures that most of the heat is being prevented from passing through conduction to the interior layers of the roof.

The permitted amount is absorbed and stored in the thermal mass of the concrete and thus delayed from affecting the interior conditions.

Although a fibrous wool thermal insulation was used in the second model, its thinness and position towards the inner side of the roof, in addition to the low thermal mass of the

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hard board deck, might contributed towards the lower thermal performance of this model in comparison with the first model.

Moreover, the lack of the insulation layer had an influence on the much lower thermal performance of the remaining models. However, the lower thermal mass of the timber slab of the third model had a relatively positive impact on the interior thermal conditions as it has a shorter time lag. This insures that the indoor temperature follows the exterior temperature. On the other hand, the high thermal mass of the concrete deck had contributed in the continuous heat stress during the night period as it can be noted from Figure 2.

IV. CONCLUSION Under the current rates of energy consumption, it is important to consider the occupants' behaviour from the early stages of design as most of the operational energy is consumed to achieve the thermal comfort. This consideration is crucial for the energy efficient buildings as the risk of having poor quality of indoor environment is possible under the attempts to reduce the consumption of the operational energy.

Although calculating the thermal resistance may give an impression about the thermal performance of the examined roofs, the effect of the different construction systems and materials on the actual thermal conditions remains unclear.

Hence, it is important to consult tools such as THERCOM to understand the predicted thermal comfort experience of the users by means of computing the thermal comfort indices suitable for the cases under consideration.

THERCOM is of great importance as it helps in better understanding and good appreciation of the available thermal comfort opportunities and the deviation from the required conditions. This understanding helps in making decisions about selecting the appropriate equipment, materials, amenities and possibly adjusting the operating patterns which eventually will increase the efficiency of the buildings.

In the study at hand, four mock-up models were tested to explore the thermal performance of the roof construction system and materials. The thermal comfort conditions were investigated using the tropical summer index. The aim of this examination was to define the periods at which the HVAC systems can be switched off and to select the most optimum construction system among the explored roofs. The first model, cinder concrete with insulation, had the optimum thermal performance. Possible factors incorporated to achieve this performance include the position of the insulation layer, its high thermal resistance, and the high thermal mass of the concrete deck.

Furthermore, and in order to extent the comfortable conditions of the first model further, it is recommended to select the construction systems of the other parts of the building envelope based on their thermal properties, in particular the thermal mass. However, careful planning of the buildings layouts should be maintained to ensure the continuity of the natural ventilation.

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Finally, it is recommended to perform further investigations to explore the extent at which the comfortable thermal conditions may be extended by means of using fans as a step before the unavoidable use of the HVAC systems.

[6]

REFERENCES [1]

[2]

[3]

[4]

[5]

L. Yang, H. Yan, and J. C. Lam, “Thermal comfort and building energy consumption implications - A review,” Applied Energy, vol. 115, pp. 164-173, 2014.

M. K. Singh, S. Mahapatra, and S. K. Atreya, “Adaptive thermal comfort model for different climatic zones of North-East India,” Applied Energy, vol. 88, pp. 2420-2428, 2011.

A. Meier, T. Olofsson, and R. Lamberts, “What is an Energy-Efficient Building?,” in Proc. ENTAC, 2002, p.

3.

R. de Dear and G. S. Brager, “The adaptive model of thermal comfort and energy conservation in the built environment,” International Journal of Biometeorolgy, vol. 45, pp. 100-108, 2001.

M. A. Humphreys, H. B. Rijal, and J. F. Nicol, “Updating the adaptive relation between climate and

[7]

[8]

[9]

[10] [11]

[12]

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comfort indoors; new insights and an extended database,” Building and Environment, vol. 63, pp. 4055, 2013.

A. K. Mishra and M. Ramgopal, “Field studies on human thermal comfort - An overview,” Building and Environment, vol. 64, pp. 94-106, 2013.

H. Al-Khatri and M. B. Gadi, “Development of a new computer model for predicting thermal comfort in different climates using Visual Basic programming language,” in Proc. People and Buildings, 2013, paper MC2013-P24.

N. Djongyang, R. Tchinda, and D. Njomo, “Thermal comfort: A review paper,” Renewable and Sustainable Energy Reviews, vol. 14, pp. 2626-2640, 2010.

L. Shashua-Bar, I. X. Tsiros, and M. Hoffman, “Passive cooling design options to ameliorate thermal comfort in urban streets of a Mediterranean climate (Athens) under hot summer conditions,” Building and Environment, vol. 57, pp. 110-119, 2012.

F. Allard, Natural ventilation in buildings: a design handbook, Ed., London, UK: James & James, 1998.

I. C. d'Energia, Ed., Sustainable building: Design manual, New Delhi, India: The Energy and Resources Institute, 2004, vol. 2.

F. Nicol and M. Humphreys, “Derivation of the adaptive equations for thermal comfort in free-running buildings in European standard EN15251,” Building and Environment, vol. 45, no. 1, pp. 11 - 17, 2012.

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Wadi Flow Simulation Using Tank Model in Muscat, Oman Mohammed Al-Housni #1, Luminda Gunawardhana #2, Ghazi Al-Rawas #3 #

Department of Civil and Architectural Engineering, Sultan Qaboos University P.O. Box 33, Postal code 123, Al-Khoud, Sultanate of Oman 1

u089996@student.squ.edu.om 2

luminda@squ.edu.om 3

ghazi@squ.edu.om

Abstract— In Oman, changes in precipitation intensity and frequency have already begun to be detected, although the attributed impacts, such as, flash flooding is poorly understood.

For example, the supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths. The objective of this study is to develop a Wadi-flow simulation model to understand precipitation-river discharge relationship in Muscat. A lumped-parameter, non-linear, rainfall-runoff model was used. The Food and Agriculture Organization (FAO-56) modified Hargreaves equation was used for estimating reference evapotranspiration (ET0). Precipitation and temperature data during 1996-2003 were obtained from the Muscat-airport meteorological station. Observed river discharges during 26-30, March 1997 were used to calibrate the model and observations during 1997-2003 were used to verify our simulations. Simulated water discharges agreed with the corresponding observations, with the Nash–Sutcliffe model efficiency coefficient equals to 0.88. This developed model will later be used with a set of General Circulation Model scenarios (GCM) to understand the Wadi-flow variations under changing climate conditions.

I. INTRODUCTION Oman, located in south-Eastern corner of the Arabian Peninsula, encompasses a diverse range of topography, including mountain ranges, low land, coastal areas and arid deserts. The coastal line of Oman extends over 3165 km and experiences very severe tropical cyclones. The supper cyclonic storm, hurricane Gonu in 2007 led to the worst natural disaster on record in Oman, with total rainfall reached 610 mm near the cost. The cyclone and flash flood caused about $4 billion in damage (2007 USD) and 49 deaths (Rafy and Hafez, 2008). Recently changes in intensity and frequency of the weather events and subsequent impacts demand countermeasures to adopt with these changes in future.

Hydrological model is an effective tool that could provide river discharge response attributed to the changes in weather variables and can be used for planning countermeasures to cope with the potential impacts.

The tank model developed by Sugawara (1984) is a lumped parameter, non-linear rainfall- runoff model. The tank model is composed one, two, three or four tanks laid vertically in series. Various coefficients represent different hydrological

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processes such as surface and subsurface runoff and infiltration. The different in magnitude of these coefficients in different catchments reflects the geographical features of the watersheds. Gunawardhana and Kazama (2012) used the tank model to study water availability and low-flow analysis of the Tagliamento River discharge in Italy under changing climate conditions. Also, this tank model has been used for river discharge simulations in 12 catchment areas in Japan (Yokoo et al., 2001). Both studies were done in humid regions, but in this research, we test the performances of the tank model to simulate wadi flow in arid region in Oman.

The objective of this study is to develop a Wadi-flow simulation model to understand precipitation-river discharge relationship in Muscat (Al-Khoud catchment area). The developed model is expected to use for climate change scenarios in future studies to predict wadi flow variations under changing climate conditions.

II. STUDY AREA Wadi Al-Khoud in Oman is located in the northern part of Oman and at the western-north part of Muscat. The downstream of catchment area is towards northeast Gulf of Oman (Fig1). The total catchment area approximately is about 1740 km2. The elevation in the catchment area ranges from 41 m at the catchment outlet in Al-Khoud to 2339 m in the inland mountain area. The climate is arid and it is important for the water resources, especially for agriculture and domestic purposes. The annul precipitation occurs in November, December, March and April as observed from previous data.

The average annual rainfall in Muscat is around 63mm (AlKhoud station) to 210 mm (JabalBani Jabir). According to the meteorological records from 1984 to 2003, the annual average maximum and minimum temperatures near the catchment outlet were approximately 33 and 24C°, respectively. The geology of the catchment area mainly consists of 55% of igneous and volcanic rocks, whereas, 3% of metamorphic rocks, 16% of sedimentary rocks and 26% of recent deposits.

III. THEORY The tank model is a simple non-linear rainfall-runoff model composed of one or several tanks (Fig. 2). The

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coefficients represented for different hydrological processes (surface and subsurface runoff and infiltration) are generally obtained by matching observed and simulated data.

Magnitude differences of these coefficients in different catchments reflect the geographical features of the watersheds.

The rainfall summed to put into the first tank at the top.

Evapotranspiration is directly subtracted from the top tank.

Among the four tanks in the model, first tank at the top account for rapid runoff near the ground surface and second tank models the shallow subsurface runoff process. Other two tanks at the bottom delayed surplus water from the top two tanks.

delays (Todini, 2007). Representative mathematical model for the water exchange between tanks and daily runoff generation can be expressed as follows.

A(x)× [H(x,n)-Z(x)] 0

R(x,n) =

H(x,n) > Z(x) H(x,n) ≤ Z(x)

I(x,n) = B(x)× H(x,n)

(1) (2)

H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[T(n+1)×Δt] x=1 H(x,n+1)= H(x,n)-[R(x,n)×Δt]-[I(x,n)×Δt]+[I(x–1, n)×Δt] x≠1

(3)

T(n) = P(n)4– Evt(n) Q n   R x , n 

(4) (5)

 x 1

where x: n: Δt: A(x): B(x): H(x,n): Z(x): R(x,n): I(x,n): T(n): Evt(n): Q(n): P(n):

number of tanks counted from top number of days from the beginning (1/d) length of time step runoff coefficient of xth tank (1/d) infiltration coefficient of xth tank (1/d) water depth in xth tank at nth day (mm) height of runoff hole of xth tank (mm) runoff from xth tank at nth day (mm/d) infiltration in xth tank at nth day (mm/d) total input to first tank at nth day (mm/d) evapotranspiration at nth day (mm/d) total runoff at nth day (mm/d) precipitation at nth day (mm/d)

Fig. 1. Study area in Oman

This phenomenon represents hydrological role of the deep aquifers that accumulate the infiltrating water from the ground surface and released in to the downstream with certain time

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Fig. 2. Tank model structure for runoff generation

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Catchment area

A11 0.14 0.4 Z11 1 40

Al-Khoud Southern Japan* Al-Khoud Southern Japan*

A12 0.35 0.2 Z12 0.1 15

Model parameter A2 B2 0.05 0.05 0.1 0.05 Z3 H4 10 0 10 200

B1 0.37 0.15 Z2 5 20

A3 0.02 0.02 H3 0 40

B3 0.03 0.03 H2 0 2

A4 0.0003 0.003 H1 0 1

* based on 12 catchments in southern Japan from Yokoo et al.

The Food and Agriculture Organization (FAO-56) modified Hargreaves equation, one of the widely used temperature based method, was used for estimating reference evapotranspiration (ET0).

0.0023 Tmax  Tmin  ET0   17.8   Tmax  Tmin  Ra    2 

(6)

where Tmax(°C) is the maximum daily air temperature, Tmin(°C) is the minimum daily air temperature, Ra (MJ/m2/d) is the extra-terrestrial solar radiation and λ is the latent heat of vaporization (2.45 MJ/m2/d). Actual evapotranspiration was estimated by matching observed river discharge with simulations. Precipitation and temperature data during 19962003 were obtained from the Muscat-airport meteorological station. The Nash–Sutcliffe model efficiency coefficient is used to assess the predictive power of hydrological models. It is defined as:

 Q

 Qmt



 Q

 Qmt



T

E  1

t 1 T

t 1

t o

t o

2

(7)

2

where Qo is observed discharge, and Qm is modelled discharge. Qot is observed discharge at time t. The closer the model efficiency is to 1, the more accurate the model is. If the simulated discharges obtained from the tank model and historical discharges have a trend and significant correlations, the simulation is considered successful and the tank model can be used to evaluate the flow phenomena for the concerning watersheds.

IV. RESULTS AND DISCUSSIONS Model calibration was done by matching observed river discharges at gage station at the outlet of the catchment area in 1997 and the model verification was done according to data observed in 1997, 1999, 2000 and 2003 (Fig.3). Simulated wadi flow agreed with the corresponding observations, with Nash-Sutcliffe model efficiency coefficient of 0.88. Table 1 shows the calibrated model parameters in Al-Khoud

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catchment area. These model parameters in Al-Khoud were compared with the derived parameters in 12 catchment areas in Japan for understanding parameter dependency on different geographical and climatic settings.

The coefficients of the tank model represent different hydrological processes of the catchment. As example, larger A1 coefficient produces higher rapid surface runoff near the ground surface, while larger B1 coefficient stands for higher infiltration capacity. According to Table 1, A11 coefficient in Al-Khoud catchments is smaller than that in Japanese catchments. This is because top soil layer in Oman catchments generally has very low soil moisture content due to extreme dry condition in air and high evaporation throughout the year.

Therefore, infiltration potential is higher and runoff potential in very shallow subsurface layer is low in catchments in Oman than them in Japan. For this reason, Al-Khoud catchments generate smaller A11 coefficients for the tank models than in Japanese catchments. In contrast, A12 coefficient for AlKhoud catchment area is greater than Japanese catchment area. This can be attributed to the high representative gradient (RG) of the catchments in Oman than in Japan. Steep slope in Al-Khoud catchment area increases the runoff potential in the shallow subsurface layers. Therefore, infiltrated water from the top soil surface rapidly flows to downstream areas rather than recharging deep aquifers. For the same reason, Al-Khoud catchment area has small storage capacities (Z11, Z12 and Z2) than the Japanese catchments. Moreover the land-use types in the catchment area have a significant effect in retaining water in shallow subsurface layers. Absence of full grown trees with deep spread roots in Oman facilitates rapid subsurface flow which attenuates groundwater recharge and subsurface storage. This phenomenon replicate with small Z coefficients in Oman than in Japan. B1 coefficients between two catchments also depict significant differences. These variations indicate that the Al-Khoud catchment has higher infiltration capacity than the Japanese catchments, which may also be attributed to the low soil moisture content in Al-Khoud than in Japanese catchments.

V. CONCLUSIONS AND RECOMMENDATIONS The objective of this study was to develop a rainfall-runoff model to simulate Wadi flow in Muscat, Oman. Wadi AlKhoud catchment area was selected. Model calibration was

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carried out with observations in 1997. The simulated Wadi flow model was verified with observation in 1997, 1999, 2000 and 2004. The Nash–Sutcliffe model efficiency coefficient of 0.88 could be obtained. The calibrated tank model parameters in Wadi Al-koud catchment area were compared with the parameters calibrated in several catchments in Japan. Physical meaning of the tank model parameters in arid environment could be successfully interpreted. It was found that the differences of model parameters of two catchment areas depend on vegetation cover, topography (RG) and soil moisture content.

The tank model performance highly depends on input data quality. Lack of long-term quality controlled rainfall and river discharge records was a major constrain. Respective authorities are therefore encouraged to maintain a long-term data base to facilitate academic community.

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The results of this study showed the ability of the tank model to simulate Wadi flow with a reasonable accuracy and therefore will be applicable for climate impact predictions. In the next step of this study, downscaled GCMs scenarios from several models for different climate variables will be used with the developed tank model to simulate wadi flow variations in future.

REFERENCES [1] M. E. Rafy, and Y. Hafez, “Anomalies in meteorological fields over northern Asia and its impact on Hurricane Gonu,” 28th Conference on Hurricanes and Tropical Meteorology, pp. 1–12, 2008.

[2] M. Sugawara, “On the analysis of runoff structure about several Japanese River,” Japanese Journal of Geophysic, vol. 4, pp. 1-76, 1961.

[3] L. N. Gunawardhana and S. Kazama, “A water availability and lowflow analysis of the Tagliamento river discharge in Italy under changing climate conditions,” Hydrology and Earth System Sciences, vol. 16, pp. 1033-1045, 2012.

[4] Y. Yokoo, S. Kazama, M. Sawamoto and H. Nishimura, “Regionalization of lumped water balance model parameters based on multiple regression,” Journal of Hydrology, vol. 246, pp. 209-222, 2001.

[5] E. Todini, “Hydrologigal catchment modeling: past, present and future,” Hydrology and Earth System Sciences, vol. 11, pp. 468-482, 2007.

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Fig. 3. Observed and simulated wadi flows

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Mobile Ad Hoc Networks Parth Panchal1, Meghana Shroff2 Student, III year, Bachelor of Technology (Electronics) Mukesh Patel Institute of Technology Management and Engineering NMIMS, SVKM Mumbai 1panchal.parth@outlook.com 2meghanashroff@gmail.com Abstract— A mobile ad hoc network (MANET) is a selfconfiguring infrastructure-less network of mobile devices connected by wireless. The primary challenge in building a MANET is equipping each device to continuously maintain the information required to properly route traffic. AODV is a novel algorithm for the operation of such ad hoc networks. This routing algorithm is quite suitable for a dynamic self-starting network, as required by users wishing to utilize ad hoc networks. AODV provides loop free routes even while repairing broken links. We attempt to build such a network using AODV. Keywords— MANET, AODV, Ad hoc, network simulator NS

I. INTRODUCTION Laptop computers continue to show improvements in convenience mobility memory capacity and availability of disk storage. The smaller computers can be equipped with gigabytes of disk storage high resolution color displays pointing devices and wireless communications adapters.

Moreover because many of these small (in size only) computers operate with battery power users are free to move about at their convenience without being constrained by wires. More recently the interest in this subject has grown due to availability of license free wireless communication devices that users of laptop computers can use to communicate with each other. Several recent papers on this topic have focused on the algorithmic complexity of choosing the optimal set of ad hoc routers while others have proposed new routing solutions leveraging features from the existing Internet routing algorithms.

As mentioned earlier, each device in a MANET is free to move independently in any direction, and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use, and therefore be a router. Such networks may operate by themselves or may be connected to the larger Internet. MANETs are a kind of Wireless ad hoc network that usually has a routable networking environment on top of a Link Layer ad hoc network.

A. Destination-Sequenced Distance-Vector The Destination-Sequenced Distance-Vector (DSDV) Routing Algorithm is based on the idea of the classical Bellman-Ford Routing Algorithm with certain improvements. Every mobile station maintains a routing table that lists all available destinations, the number of hops to reach the destination and the sequence number assigned by the destination node. The sequence number is

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used to distinguish stale routes from new ones and thus avoid the formation of loops. The stations periodically transmit their routing tables to their immediate neighbors.

A station also transmits its routing table if a significant change has occurred in its table from the last update sent.

So, the update is both time-driven and event-driven.

The routing table updates can be sent in two ways: a “full dump” or an incremental update. A full dump sends the full routing table to the neighbors and could span many packets whereas in an incremental update only those entries from the routing table are sent that has a metric change since the last update and it must fit in a packet. If there is space in the incremental update packet then those entries may be included whose sequence number has changed.

When the network is relatively stable, incremental updates are sent to avoid extra traffic and full dump are relatively infrequent. In a fast-changing network, incremental packets can grow big so full dumps will be more frequent.

B. Dynamic State Routing (DSR) The key distinguishing feature of DSR is the use of link state routing. The sender/source knows the complete hopby-hop route. The routes are stored in route cache. A route discovery process is used to dynamically discover routes.

Route discovery works by flooding the network with RREQ packets. Each node receiving an RREQ rebroadcasts it, unless it is the destination or it has a route to the destination in its route cache. Such a node replies to the RREQ with a route reply (RREP) packet that is routed back to the original source. RREQ and RREP packets are also source routed. The RREQ builds up the path traversed across the network. The RREP routes itself back to the source by traversing this path backward. The route carried back by the RREP packet is cached at the source for future use. If any link on a source route is broken, the source node is notified using a route error (RERR) packet. The source removes any route using this link from its cache. A new route discovery process must be initiated by the source if this route is still needed. DSR makes very aggressive use of source routing and route caching.

C. Ad hoc On-Demand Distance Vector (AODV) AODV discovers routes on an as needed basis via a similar route discovery process. However, AODV adopts a very different mechanism to maintain routing information.

It uses traditional routing tables, one entry per destination.

It builds routes between nodes only when it is required by

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source nodes and also it maintains these routes as long as they are needed by these sources. AODV forms trees which connect multicast group members. The trees are composed of the group members and the nodes needed to connect the members. AODV uses sequence numbers to ensure the freshness of routes. It is loop-free, self-starting, and scales to large numbers of mobile nodes.

Although AODV does not depend specifically on particular aspects of the physical medium across which packets are disseminated, its development has been largely motivated by limited range broadcast media, such as those utilized by infrared or radio frequency wireless communications adapters. We do not make any attempt to use specific characteristics of the physical medium in our algorithm nor to handle the problems posed by channelization needs of radio frequency transmitters.

Nodes that need to operate over multiple channels are presumed to be able to do so. The algorithm works on wired media as well as wireless media as long as links along which packets may be transmitted are available. The only requirement placed on the broadcast medium is that neighboring nodes can detect each otherâ&#x20AC;&#x2122;s broadcasts.

AODV uses symmetric links between neighboring nodes. It does not attempt to follow paths between nodes when one of the nodes cannot hear the other one however we may include the use of such links in future enhancements.

II. AODV PROTOCOL AODV builds routes using a route request (RREQ) and route reply (RREP) message cycle. When a source node desires a route to a destination for which it does not already have a route, it broadcasts a RREQ packet to the network. Nodes receiving this packet update their information for the source node and set up backward pointers to the source node in the routing tables. In addition to the source node's IP address, current sequence number, and broadcast ID, the RREQ also contains the most recent sequence number for the destination of which the source node is aware.

with corresponding sequence number greater than or equal to that contained in the RREQ. If this is the case, it unicasts a RREP back to the source. Otherwise, it rebroadcasts the RREQ. Nodes keep track of the RREQ's source IP address and broadcast ID. If they receive a RREQ which they have already processed, they discard the RREQ and do not forward it.

Fig 3: Route reply

Figure 4: RREP Packet Format

As the RREP propagates back to the source, nodes set up forward pointers to the destination. Once the source node receives the RREP, it may begin to forward data packets to the destination. If the source later receives a RREP containing a greater sequence number or contains the same sequence number with a smaller hop count, it may update its routing information for that destination and begin using the better route.

Fig 5: AODV Algorithm Fig 1: Route discovery

Fig 2: RREQ Packet Format

A node receiving the RREQ may send a RREP if it is either the destination or if it has a route to the destination

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As long as the route remains active, it will continue to be maintained. Once the source stops sending data packets, the links will time out and eventually be deleted from the intermediate node routing tables. If a link break occurs while the route is active, the node upstream of the break propagates a route error (RERR) message to the source node to inform it. After receiving the RERR, if the source node still desires the route, it can restart route discovery.

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The algorithm’s primary objectives are: • •

To broadcast discovery packets only when necessary To distinguish between local connectivity management neighborhood detection and general topology maintenance • To disseminate information about changes in local connectivity to those neighboring mobile nodes that are likely to need the information Multicast routes are set up in a similar manner. A node wishing to join a multicast group broadcasts a RREQ with the destination IP address set to that of the multicast group and with the 'J'(join) flag set to indicate that it would like to join the group. Any node receiving this RREQ that is a member of the multicast tree that has a fresh enough sequence number for the multicast group may send a RREP. As the RREPs propagate back to the source, the nodes forwarding the message set up pointers in their multicast route tables. As the source node receives the RREPs, it keeps track of the route with the freshest sequence number, and beyond that the smallest hop count to the next multicast group member. After the specified period, the source node will unicast a Multicast Activation (MACT) message to its selected next hop. This message serves the purpose of activating the route. A node that does not receive this message that had set up a multicast route pointer will timeout and delete the pointer. If the node receiving the MACT was not already a part of the multicast tree, it will also have been keeping track of the best route from the RREPs it received. Hence it must also unicast a MACT to its next hop, and so on until a node that was previously a member of the multicast tree is reached.

AODV maintains routes for as long as the route is active. This includes maintaining a multicast tree for the life of the multicast group. Because the network nodes are mobile, it is likely that many link breakages along a route will occur during the lifetime of that route. The only other circumstance in which a node may change the destination sequence number in one of its route table entries is in response to a lost or expired link to the next hop towards that destination.

Once the next hop becomes unreachable, the node upstream of the break propagates an unsolicited RREP with a fresh sequence number i.e. a sequence number that is one greater than the previously known sequence number, and hop count of ∞ to all active upstream neighbors. Those nodes subsequently relay that message to their active neighbors and so on. This process continues until all active source nodes are notified. It terminates because AODV maintains only loop free routes and there are only a finite number of nodes in the ad hoc network. Consider node A wants to connect to node B, but the link is broken in between. This means that node A knows that the link to node B is down and increments the Sequence number and broadcast it.

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III. SIMULATION IN NS2 We have simulated AODV using an event simulator NS2. The main objective of our simulations is to show that on demand route establishment with AODV is both quick and accurate. Additional objectives include showing that AODV scales well to large networks and determining the optimal value for each of the necessary parameters.

A. Simulation environment The simulation experiment is carried out in LINUX (Ubuntu 12.04). The detailed simulation model is based on network simulator-2 (ver-2.36), is used in the evaluation.

The NS instructions can be used to define the topology structure of the network and the motion mode of the nodes, to configure the service source and the receiver, to create the statistical data track file and so on.

The following simulation results were obtained

Figure 6: Simulation scenario in the beginning

Figure 7: Simulation scenario

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Figure 8: Simulation scenario 2

Figure 11: Simulation scenario 5

Figure 9: Simulation scenario 3 Figure 12: Simulation scenario 6

Figure 10: Simulation scenario 4

B. Performance Analysis For AODV, packet delivery ratio is independent of offered traffic load, delivering between 85% and 100% of the packets in all cases. The lazy approach used by AODV to build the routing information as and when it is created makes it more adaptive and results in better performance (high packet delivery fraction and lower average end-toend packet delays). In the presence of high mobility, link failures can happen very frequently. Link failures trigger new route discoveries in AODV since it has at most one route per destination in its routing table. Thus, the frequency of route discoveries in AODV is directly proportional to the number of route breaks.

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Performance of AODV protocols in MANET can be realized by quantitative study of values of different metrics used to measure performance of routing protocols which are as follows: 1) Average End-to-End Delay: It is defined as average time taken by data packets to propagate from source to destination across a MANET. This includes all possible delays caused by buffering during routing discovery latency, queuing at the interface queue, and retransmission delays at the MAC, propagation and transfer times. The lower value of end to end delay means better performance of the protocol.

End to end delay = Σ (arrive time - send time) 2) Packet Delivery Ratio: It is a ratio of the number of packets received by the destination to the number of packets sent by the source. This illustrates the level of delivered data to the destination. The greater value of packet delivery ratio means better performance of the protocol.

PDR = Σ No. of packet received / Σ No. of packet sent

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3) Packet Loss: It is the measure of number of packets dropped by nodes due to various reasons. The lower value of the packet lost, the better performance of the protocol.

Packet lost = No of packet sent – No of packets received.

III. CONCLUSION In summary, we present a distance vector algorithm that is suitable for use with ad hoc networks. AODV has the following features: • • • • • •

Nodes store only the routes that are needed Need for broadcast is minimized Reduces memory requirements and needless duplications Quick response to link breakage in active routes Loop free routes maintained by use of destination Sequence numbers scalable to large populations of nodes Compared to DSDV and other algorithms which store continuously updated routes to all destinations in the ad hoc network our algorithm has longer latency for route establishment. But within the limits imposed by worst case route establishment latency, AODV is a sensible choice for ad hoc network establishment. We look forward to further development of the protocol for quality of service intermediate route rebuilding and various interconnection topologies with fixed networks and the Internet.

A. Future Scope We believe strongly in the scope of MANET, essentially in the form of Vehicular Ad hoc Network. Vehicular ad hoc network is a special form of MANET which is a vehicle to vehicle & vehicle to roadside wireless communication network. It has great scope in vehicle collision warning, security distance warning, driver

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assistance, cooperative driving, and cooperative cruise control, dissemination of road information, internet access, map location, automatic parking and driverless vehicles. It also has applications for emergency services, conferencing battlefield communications and community based networking.

ACKNOWLEDGMENT We would like to express our sincere gratitude towards Mr. Sharad Wagh, Assisstant Professor, NMIMS, for his technical guidance and constant encouragement throughout the project, and for his priceless inputs and patience to deal with our queries.

We would also like to thank the authority of SVKM’s NMIMS for providing us with a good environment and facilities to complete this project. Without help of the aforementioned, we would have faced many difficulties while doing this project.

[1]

[2]

[3] [4]

[5]

[6]

REFERENCES C. Perkins, E. Belding-Royer, and S. Das. Ad hoc On- Demand Distance Vector (AODV) Routing. RFC 3561 (Experimental), July 2003.

Y. C. Hu, D. Johnson, and A. Perrig. -SEAD: Secure efficient distance vector routing for mobile wireless ad hoc networks,‖ in Fourth IEEE Workshop on Mobile Computing Systems and Applications (WMCSA '02), 2002, p. 313.

Ashokan, Manel Guerrero Zapata. -Securing ad hoc routing protocols, 2002, ‖ in ACM workshop on Wireless security S. Kent, C. Lynn, J. Mikkelson, and K. Seo. Secure border gateway protocol (S-BGP) -real world performance and deployment issues, 2000.

A. Nagaraju, Dr S Ramachandram and Dr C. R. Rao. Applying heuristic technique to ad-hoc on demand distance vector routing to reduce broadcast, ‖ in the World Congress on Engineering Vol II, WCE 2007, London, U.K, 2007 NS-2, The ns Manual (formally known as NS Documentation) available at http: //www. isi.edu/nsnam/ ns/doc.

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Constraints Faced by Rural Women Members in Functioning of SHGs in Allahabad District of Uttar Pradesh Rukhsana*, Dipak Kumar Bose**, Priyanka Singh*** *Ph. D. Scholar, **Associate Professor Departmentt of Agriculture Extension & Communication, Allahabad School of Agriculture SHIATS, Allahabad ***Assistant Professor, Department of Arts for Women Chitamber School of Humanities Social Sciences, SHIATS, Allahabad Abstractâ&#x20AC;&#x201D; The present study was undertaken to study the constraints faced by rural women members in functioning of Self Help Groups. Hundred and fifty rural women members of SHGs from Allahabad district represented the sample for the study. A structured interview schedule was used for the collection of data. The findings revealed that the major constraints faced by the women members were lack of formal education, no freedom to take decisions, dominance of group leaders, decision made at administrative level, less cooperation of officials , less profit, travel expenses for disbursement of loan, poor monitoring and technical guidance, inadequate space for enterprise, high cost of raw materials, lack of storage facilities, non-cooperation between educated and uneducated people and non cooperation from family members. These constraints may be solved through extension strategies like adult education, vocational training of members, facilitating of bank officials and providing proper marketing facilities.

I. INTRODUCTION The SHG is a viable organized set up to disburse microcredit to the rural women for the purpose of making them enterprising and encouraging to enter into entrepreneurial activities. The formation of SHG is not ultimately a micro credit project but an empowering process. These SHG have common perception of need and an impulse towards collective action. Empowering women is not just for meeting their economic needs but also for more holistic social development. The SHGs empower women both socially and economically. They encourage women to participate in decision making in the households, community and local democratic sector and prepare women to take up leadership position. (Ramachandran and Balakrishnan 2008).

The SHG-Bank linkage model is the indigenous model of micro-credit evolved in India and has been widely acclaimed as a successful model. SHG-Bank linkage programme is considered a promising approach to reach the poor and has since its inception made rapid strides exhibiting considerable democratic functioning and group dynamism. The number of 500 Bank linked SHGs in 19911992 has gone up to more than 34 lakh by the end of March 2008. Cumulatively, these SHGs have accessed credit of Rs. 22,268 crore from banks during the period.

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About 4.1 crore poor households have gained access to the formal banking system through the programme. The faster growth in bank loans to SHGs has led to almost a four-fold increase in the average loans per SHG from Rs. 16,816 in 1999-2000 to Rs. 63,926 in 2007-08. These figures reflect the outstanding success of the programme. (Kumar and Golait, 2009).

On the other hand it has been revealed through various research studies that the real economic growth of the SHG beneficiaries has not been achieved. Despite policy initiatives, the extent of inclusion is very low in rural and semi - urban India. There are still 90 million people who are excluded from the formal banking system for various reasons like lack of knowledge in the rural poor related to banking and banking products, high transaction costs and illiteracy. In this scenario, microfinance, which is defined as the provision of financial services to the low income and vulnerable groups of the society is playing a challenging role in achieving twin goals of financial inclusion and poverty eradication in economically viable manner. (Rupa et al 2012) Mehta (2012) also reported some major issues and problems indicating SHG status. Most members of the SHG have no knowledge about the SHG and they do not have a principal occupation. Women member perform dual role in society relating to production and reproduction so they are over burdened and their contribution to the family economy and national economy remains largely invisible and undervalued. The existing communication channels are not adequate and do not reach to the BPL members of the society. There is unchecked exploitation of SHG women members in houses, at working place and public place.

Despite all the notable efforts on part of the government and non- government agencies, access to financial services for all at affordable rates remains a distant dream.

Remoteness of rural areas and poor infrastructure leads to market inefficiencies and a huge gap between demand and supply. Problem is compounded by the fact that rural population is still largely illiterate and not so technology driven. Kumar and Anand (2007). Critical gaps have been observed in the management of day to day activities of the

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Self Help Groups relating to different group dynamics, organizational management, financial management, arrangement of livelihood activities, internal monitoring, accountability etc. Intensive and extensive training programmes involving community resource persons, coordinators will have to be organized for existing as well as new Self-help Groups, so that village level organizations (Primary Federations) can be conveniently formed with the help of these groups. (Zakir et al 2011).

II. MATERIALS AND METHODS The present research study was conducted in three blocks of Allahabad District of UP viz; Chaka, Jasra and Handia. A list of SHGs operating in these three blocks was obtained from the block office. A proportionate random sample of 30 Self Help Group was selected from the three selected blocks. Five office bearers (women members) from each selected Self Help Group was taken as the sample of the study, thus a total of 150 respondents were selected for the present study. An interview schedule was constructed which consisted of list of statements related to personal constraints, organizational constraints, economic/financial constraints, managerial constraints, social constraints and marketing related constraints. The data was collected through personal interview method by using pretested structured interview schedule and the collected data were compiled, tabulated and analyzed.

III. RESULTS AND DISCUSSION After analyzing the data regarding socio-economic characteristics it was found that majority of the respondents were in the age group of 30-40 years (50.66%), married (85.33%), illiterate (48.67%), had nuclear family (62.67%) and were daily wage labours (48.67%).

A. Personal problems faced by the respondents The data with regard to personal problems faced by the respondents are presented in table 1. It is evident from the table that majority of the respondents i.e. 68.67 per cent faced the problem of lack of formal education and got ranked I. TABLE I DISTRIBUTION OF RESPONDENTS ACCORDING TO THE PERSONAL PROBLEMS FACED

N=150

Personal problems No freedom to take decisions Lack of motivation Lack of formal education

Frequency 42

Percentage 28.00

Rank II

26 103

17.33 68.67

III I

Rank) and 17.33 per cent of the respondents were those were having the problem of lack of motivation and placed at III rank.

B. Organisational Constraints Faced by the Respondents The table 2 reveals the data regarding the organisational constraints faced by the SHG members which clearly indicates that about half of the respondents reported that the decision related to group functioning and income generating activities were taken at higher level and the respondents were not involved into it. Near about 28.67 per cent of the respondent complain of conflicts among group members resulting in non cooperation among the group members.

TABLE II DISTRIBUTION OF RESPONDENTS ACCORDING TO THE ORGANIZATIONAL CONTRAINTS FACED

N=150

Organizational constraints Dominance of group leaders Conflicts in group Lack of participatory approach Irregular meetings Decision made at administrative level Poor record keeping Inadequate training

Frequency

Percentage

Rank

88

58.67

I

43 59

28.67 39.33

V III

21 74

14.00 49.33

VII II

37 44

24.00 29.33

VI IV

*multiple response The constraints of dominance of group leaders was reported by about 58.67 per cent of the respondents (Rank I) while 39.33 per cent were those who faced the problem of lack of participatory approach. The problem of irregular meeting was reported by about 14.00 per cent of the respondents (rank VII) followed by 24.00 per cent who complain that the records were not maintained properly (rank VI) and about 29.33 per cent complaint of inadequate training.

C. Economic/Financial constraints faced by the respondents The table 3 indicates the economic/financial constraints faced by the SHG members. It is revealed from the table that a large percentage of the respondents i.e. 62.67 per cent felt that the profit earned through the income generating activities are too little (rank I) followed by 54.67 per cent who reported that it was an extra burden for them to arrange for travel expenses to visit the bank often.

*multiple response Most of the SHGs members were illiterate, due to which they lack confidence and are unable to take decision at their own. In the study it was found that about 28 percent of the respondents had no freedom to take decisions (II

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International Journal of Studentsâ&#x20AC;&#x2122; Research in Technology & Management Vol 2 (05), August-September 2014, ISSN 2321-2543, pg 188-191 TABLE III DISTRIBUTION OF RESPONDENTS ACCORDING TO THE ECONOMIC/ FINANCIAL CONSTRAINTS FACED

N=150

Economic/ Financial constraints Inadequate loan transactions Exhaustive procedure in getting loan Travel expenses for disbursement of loan Irregular saving procedure and loan repayment of members Less cooperation of officials Less profit Short duration of repayment of loan

Frequency

Percentage

Rank

32

21.33

IV

28

18.67

VI

82

54.67

II

49

32.67

III

30

20.00

V

94 17

62.67 11.33

I VII

TABLE V DISTRIBUTION OF RESPONDENTS ACCORDING TO THE MARKETING RELATED CONSTRAINTS FACED

*multiple response About 21.33 per cent of the respondents reported that the loan amount disbursed to them is insufficient to start a profitable venture and got IV rank. The constraints at the III rank was reported by about 32.67 per cent of the respondents who complaint of irregular saving procedure of the members and some of the members of SHGs did not repay loan amount in time. About 18.67 per cent of the respondents faced the difficulties in disbursement of loan due to exhaustive procedure (VI rank) followed by 11.33 per cent who felt that the duration of repayment of loan is short and must be increased and this constraints was placed at VII rank.

D. Managerial constraints in functioning of SHGs The data enfolded in table 4 shows the managerial constraints faced by the respondents. It is clear from the table that about 45.33 per cent of the respondents faced the difficulties of poor monitoring and technical guidance (I rank) and about 28.67 per cent of the respondents had the constraints of lack of space for the enterprise which was ranked II. TABLE IV DISTRIBUTION OF RESPONDENTS ACCORDING TO MANAGERIAL CONSTRAINTS FACED

N=150

Managerial constraints No exposure in record maintenance Inadequate space for enterprise No permanency in getting materials Unskilled women group members Poor monitoring and technical guidance

cent who complaint of no exposure in record maintenance and were placed at V and III rank respectively. No permanency in getting the material was faced by about 21.33 per cent of the respondents and got IV rank.

E. Marketing Constraints Faced by the Respondents There were some marketing related constraints faced by the respondents which are presented in table 5. About 36 per cent of the respondents faced the problem of high market cost of raw material which got I rank. The raw material for the dairy, piggery and goat rearing is fodder and the medicines when their animals fell ill. The market cost of veterinary drugs was perceived as high by the respondents. SHG members engaged in namkeen making felt the market cost of besan, peanut etc was high.

Frequency 38

Percentage 25.33

Rank III

43

28.67

II

32

21.33

IV

10

6.67

V

68

45.33

I

N=150

Marketing related constraints

Frequency

Percentage

Rank

No market demand of the product

32

21.33

II

Lack of transportation

17

11.33

V

Lack of storage facilities

22

14.67

IV

Lack of market information

30

20.00

III

High cost of raw materials

54

36.00

I

*multiple response Lack of market demand of the product was faced by about 21.33 per cent of the SHG members (II rank) followed by 20.00 per cent who lack the information of market demand and placed at III rank. Near about 14.67 per cent of the respondents had no storage facilities due to lack of space while, problem of lack of transportation was faced by about 11.33 per cent of the SHG members and these problems got IV and V rank respectively.

F. Social Constraints Faced by the Respondents The data set in table 6 shows the social problems faced by the respondents. The data clearly indicates that the problem getting rank I was faced by about 25.33 per cent of the SHG members who reported the problem of conflict among educated and uneducated people due to differences in cognitive understanding. About 22.67 per cent of the respondents faced the problem of jealousness of friends and neighbor (rank II) while only about 7.33 per cent of the SHG members were those who faced the problem of caste system in the group/village.

*multiple response About 6.67 per cent of the respondents had unskilled women group members in their SHG followed by 25.33 per

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Table 6: Distribution of respondents according to the social constraints faced by them (N=150) Social constraints Non cooperation from family members Jealousness of friends and neighbor Cultural taboos not permitting Non-cooperation between educated and uneducated people

Frequency 17

Percentage 11.33

Rank IV

34

22.67

II

29

19.33

III

38

25.33

I

*multiple response About 11.33 per cent of the respondents faced the problem of non cooperation of family members followed by 19.33 per cent who faced the difficulty of cultural taboos.

IV. CONCLUSION The study therefore reflects that the major constraints faced were lack of formal education, no freedom to take decisions, dominance of group leaders, decision made at administrative level, less cooperation of officials, less profit, travel expenses for disbursement of loan, poor monitoring and technical guidance, inadequate space for enterprise, high cost of raw materials, lack of storage facilities, non-cooperation between educated and uneducated people and non cooperation from family members. These constraints may be solved through extension strategies like adult education, vocational training of members, facilitating of bank officials and

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providing proper marketing facilities.It is therefore suggested that the women members need to be sufficiently exposed to the objectives and functioning of the SHGs so that they could manage the group effectively. This also will develop their interest in undertaking various activities with credit facilities, need based training and generate income which will definitely make them empowered.

REFERENCES [1] T. Ramachandran and S. Balakrishnan, Impact of Self Help Groups on Women’s Empowerment- A Study in Kanyakumari District. Kurukshetra vol. 57(2), pp. 134, 2008.

[2] P. Kumar and R. Golait, Bank Penetration and SHGBank Linkage Programme: A Critique Reserve Bank of India Occasional Papers, vol. 29(3), pp. 119-138, 2009.

[3] J.S. Rupa, M. Majumdar, V. Ramanujam, Self Help Group (SHG) - Bank Linkage Model– A Viable Tool for Financial Inclusion. Journal of Economics and Sustainable Development vol. 3(10), pp. 134-142, 2012.

[4] M.C. Mehta, Self Help Groups – Its Rural Impediments. International Journal of Scientific and Research Publications, vol. 2(5), pp.1-3, 2012.

[5] S. Kumar and S. Anand, Journey of Rural Credit in India over the Past Sixty Years, Kurukshetra vol.

55(12), pp. 52-54, 2007.

[6] A.M.M. Zakir, N. Baruah, K. Kalita, Management of Self Help Groups, http://sirdassam.in/PDF/ SGSY/Publish_Books/Management_of_Self_Help_Gr oups.pdf, 2011.

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