Ijre published paper 7(3), 2017

1. InvertisJournalofRenewableEnergyVol.7,No.3(115-172)July-September2017 ISSN 2231-3419 ISSN 2454-7611 (Online) (Printed) Volume 7, No. 3, July-September 2017 Available at : www.indianjournals.com Abstracted/Indexed by Index Copernicus International (ICV-77.28), MIAR (ICDS-3.7), Google Scholar, CNKI Scholar, ISA(CSIR), INSPEC, EBSCO Discovery, Summon(ProQuest), Primo & Primo Central, J-Gate, Indian Science, OAJI, Cite Factor, DRJI, ISRA-JIF, ICMJE, DOAJ{Under Process with - Indian Citation Index, Thomson Reuters, SCOPUS, EMBASE, CABI, SJIF, Jour-Informatics, GIF, EZB, ScholarSteer,IIJIF}

2. INTERNATIONALADVISORY BOARD Shyam Singh Chauhan Ex. Director R.R. Institute of Modern Technology Bakshi Ka Talab, Sitapur Road Lucknow, U.P., India R.K. Sharma Infra red Division SSPL Lucknow Road, Timarpur Delhi - 110 054, India P.J. George Kurukshetra Institute of Technology and Management (KITM) Pehwa Road, Bhorasida, Kurukshetra - 136 119, Haryana, India Nawal Kishore Department of Applied Physics Guru Jambheshwar University Hisar - 125 001, Haryana, India I.P. Jain Director Centre for Non-conventional Energy Sources 14, Vigyan Bhavan University of Rajasthan, Jaipur - 302 004 Rajasthan, India Naresh Padha Department of Physics & Electronics University of Jammu, Jammu - 180 006 India Bhaskar Bhattacharya Director School of Engineering and Technology Sharda University, Knowledge Park 3 Greater Noida - 201 306, U.P., India Kishan Pal Singh Principal University Polytechnic Mangalayatan University Aligarh Mathura Highway Aligarh - 202145, India Avinashi Kapoor Department of Electronic Science University of Delhi, South Campus New Delhi - 110 021 India Amitava Majumdar Sr. General Manager-Technical & Corp. R&D Moser Baer India (MBI) 66, Udyog Vihar, G B Nagar Greater Noida - 201 306, U.P, India C A N Fernando Department of Electronics Wayamba University of Sri Lanka, Kuliyapitiya Sri Lanka R.C. Maheshwari Advisor, Hindustan College of Science & Technology Agra - 211 011, U.P. India G.D. Sharma Physics Department, JNV University Jodhpur - 342 005 Rajasthan, India Z.H. Zaidi Chief Editor Invertis Journal of Science & Technology New Delhi - 110 060 India Abdol Rahim Baharvand Researcher and University Teacher Lorestan University, Khorramabad Iran

3. INVERTIS JOURNAL OF RENEWABLE ENERGY Volume 7 July-September 2017 No. 3 Owned, Published and Printed by Sanjeev Gautam, 60/10, Old Rajinder Nagar, New Delhi - 110 060 Printed at Alpha Printers, WZ-35/C, Naraina Ring Road, New Delhi - 110 028. Ph : 9810804196 Chief Editor : Prof. Z.H. Zaidi, Ph. : 09213888999, E-mail : ijre2011@gmail.com CONTENTS The energy transfer/flow management algorithm 115 for a photovoltaic solar home Osama Shaukat Numerical analysis of friction factors in smooth and rough 123 microchannels Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz Effect of operating conditions on the performance of vapor 131 absorption refrigeration system Md. Meraj, Rashid Imam and Md. Ashfaque Alam Study and analysis of plate type heat exchanger 137 Numan Ansari, Mohd. Islam and Sayyed Haider Study of CFD approach to discretise first derivative 142 of partial differential equation Hasan Shamim, Shadab Ahmad and Shah Alam Thermal design of liquid cooled charge air cooler: 147 A computational approach Tribhuwan Chandra Joshi and Yogendra Singh Kushwah Utilisation of exhaust gases of automobile 158 Jitendra Singh and Shahbaz Mozammil Life cycle analysis of multi-split Variable Refrigerant 165 Flow (VRF) system : case study Md. Khurshid Alam and Shah Alam Patron Umesh Gautam R.M. Mehra Sharda University Mohd Parvez Al-Falah University Assistant Editor Sumit Kumar Gautam Editors Chief Editor Z.H. Zaidi

4. Ranjana Jha N S I T, Delhi University

5. The energy transfer/flow management algorithm for a photovoltaic solar home 115 The energy transfer/flow management algorithm for a photovoltaic solar home OSAMA SHAUKAT Departmentof Mechanical Engineering Al-Falah University, Faridabad, Haryana *E-mail: osama_shaukat@yahoo.com Abstract In this research paper, an energy flow management algorithm for a grid-connected-photovoltaic system with battery storage devoted to supply a home is presented. Modeling of photovoltaic (PV) and wind farms (WF) stations to take into account these renewable energies into the power flow formulation are summarized. This algorithm favors the fulfillment of the home energy demand by the energy produced by the photovoltaic generator or stored in the batteries than that got from the grid. This algorithm manages the flow of energy in the house through the combination of four switches. It was applied to the case of a home installed in a coastal region of Bou-Ismaïl (Algeria).The efficiency of the algorithm was tested for two weeks, a favorable week in summer and an unfavorable week in winter regarding the weather conditions. The simulation of the on grid PV system was done using real data of the irradiation and the temperature acquired by the meteorological station of the Bou-Ismaïl site and a home load profile for each season. The results obtained revealed that the energy demand satisfaction for the house is high in the favorable summer week and is only 33% in the winter unfavorable week. To meet a high rate of self- consumption a Home Energy Management is required. Key words : Photovoltaic (PV); solar home; energy management; consumption profiles. 1. Introduction Solar energy is radiant light and heat from the Sun that is harnessed using a range of ever-evolving technologies such as solar heating, photovoltaic, solar thermal energy, solar architecture, molten salt power plants and artificial photosynthesis. It is an important source of renewable energy and its technologies are broadly characterized as either passive solar or active solar depending on how they capture and distribute solar energy or convert it into solar power. In 2011, the International Energy Agency said that "the development of affordable, inexhaustible and clean solar energy technologies will have huge longer-term benefits. It will increase countries' energy security through reliance on an indigenous, inexhaustible and mostly importindependent resource, enhance sustainability, reduce pollution, Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 115-122 lower the costs of mitigating global warming, and keep fossil fuel prices lower than otherwise. In 2000, the United Nations Development Program me, UN Department of Economic and Social Affairs, and World Energy Council published an estimate of the potential solar energy that could be used by humans each year that took into account factors such as insolation, cloud cover, and the land that is usable by humans. These renewable energy sources are a very good solution in the global energy problem. The energy generated by the photovoltaic systems constitutes a large part of the total amount of energy produced by renewable energy sources. Photo voltaic cells belong to the group of distributed generations. These cells produce power by utilizing the sunlight. There have been many research efforts to improve the efficiency of photovoltaic systems. In this context, photovoltaic (PV) generation appears as the most promising DOI No. : 10.5958/2454-7611.2017.00016.9

6. 116 Osama Shaukat alternative thanks to its maturity, its environmentally friendly characteristics, low maintenance and the fact that the sun is everywhere. The residential and building sector is in many countries the first energy consumer, about 40% of the global energy consumption[1], therefore efficient utilization and control of energy consumption at household level is crucial[2]. The challenge resides in the matching of the intermittent energy production with the dynamic power demand[3]. This needs to design an energy management strategy in order to optimize the use of PV source and storage and to match the local production with local consumption. In the literature, several works are particularly focused on optimizing the energy. Consequently, studies have been directed to "smart homes"[4-7]. In this paper the case of a home powered by on grid photovoltaic system with storage is investigated. An energy flow management algorithm was developed. It manages the energy flow available in the home through a combination of switches to meet the energy demand optimally using the energy produced by the photovoltaic generator and/or the energy stored in the batteries and/or the energy drawn from the grid. The purpose is to minimize this last and ultimately reach the self- consumption mode. Two particular weeks have been chosen, one in summer and one in winter, in order to tests the algorithm. The paper is organized as follows. In Section 2, the chosen photovoltaic system which feeds the home to satisfy the energy demand profile is presented. The models used to simulate the PV system are given in section 3. The proposed energy flow management algorithm and the operating mode of the system are presented in section 4, while in Section 5, the obtained simulation results, using the MATLAB-SIMULINK are given and interpreted. 2. PV System description and energy demand of the home 2.1 Description of the proposed PV system In order to study how to meet the energy needs of a family by using mainly the energy produced by a photovoltaic installation, the sizing of the PV system has been done by using PVSST 1.0 locally developed software[8]. The optimal PV system configuration obtained is an array of 3.2kWp and a battery bank of 12kWh. To feed the loads of the house, 4kW DC/AC converter has been chosen. In order to prevent the batteries from a total discharge, the lowest level of the State Of Charge (SOC) was set to 25%. This SOC corresponds to a capacity of 3kWh. The SOCmax was set to 85% which corresponds to 10 kWh. As shown on figure 1, the PV system operation depends on the combination status of four switches (K1, K2, K3, K4) which is related to the energy demand, the energy Fig. 1. Grid-connected PV system with storage for the solar home

7. The energy transfer/flow management algorithm for a photovoltaic solar home 117 available from the PV generator, the SOC of the battery bank and the energy taken off from the grid. In order to meet optimally the energy needs of the home, an energy flow management algorithm has been developed. 2.2 Solar home energy demand The case treated in this paper is a house of 57 m2 area situated in the coastal region of Bou-Ismaîl (Latitude: 36° 38' 33'' North and Longitude: 36° 38' 33'' North) occupied by a family of three members. The energy demand of a home depends on many factors such as the number of appliances, the electrical power used by each appliance and the amount of use of appliances determined by the behavior of the occupants in the home. Solar cell : A solar cell (also called photovoltaic cell or photoelectric cell) is a solid state electrical device that converts the energy of light directly into electricity by the photovoltaic effect. The following are the different types of solar cells.  Amorphous Silicon solar cell (a-Si)  Bio hybrid solar cell  Buried contact solar cell  Cadmium telluride solar cell (CdTe)  Concentrated PV cell (CVP and HCVP) 2.3 Home energy demand To design the most efficient PV power system for supplying the dwelling, the solar energy resources of a site and the energy consumption of the household should be known. Unfortunately, the electricity demand is rarely available, so the daily load profile must be generated. A home energy management (HEM) system is an integral part of a smart grid that can potentially enable demand response applications for residential customers. This paper presents an intelligent HEM algorithm for managing high power consumption household appliances with simulation for demand response (DR) analysis. The proposed algorithm manages household loads according to their preset priority and guarantees the total household power consumption below certain levels. A simulation tool is developed to showcase the applicability of the proposed algorithm in performing DR at an appliance level. This paper demonstrates that the tool can be used to analyze DR potentials for residential customers. Given the lack of understanding about DR potentials in this market, this work serves as an essential stepping-stone toward providing an insight into how much DR can be performed for residential customers. In the studied case, the home load profile has been determined by considering the daily load profile of each appliance, their power ratings and their estimated operating time per day, then their summation leads to the daily consumption home profile. For the summer, the daily energy demand varies between 13.87 kWh and 16.27 kWh. For the winter, the energy demand varies between 12.03 kWh and 18.30 kWh. For these two seasons, the high energy demand is explained by the use of energy intensive equipment for heating and air conditioning. 3. PV system modeling In this section, the modeling of the PV generator, the batteries and the power converter will be presented. For PV system modeling, a one diode model for the PV generator has been used[10]. For the batteries, the Copetti's model has been chosen as it is well suited for lead acid batteries allowing the simulation of the whole operating process charge- discharge-overcharge while considering the temperature change of the battery[11, 12]. For the DC/ DC converter, a boost converter controlled by a MPPT Fuzzy logic Controller has been used[13, 14] and the DC/AC converter has been modeled by its yield curve. Solar energy : Solar is scaling up rapidly, with capacity more than trebling over the past four years. New installations totaling more than 50 GW in 2015 took global solar PV power generating capacity to 231 GW by year end, a 28.1% increase versus the end of 2014. Capacity has more than trebled in the past four years. The largest increments in 2015 were recorded in the Asia Pacific region; China added 15.2 GW, just ahead of Japan with 12 GW, together accounting for more than half of the growth in global solar capacity. The US provided the third largest addition (7.3 GW). China's cumulative installed capacity (43.5 GW) moved it ahead of Germany (39.7 GW), with Japan (35.4 GW) in third place, and the US (25.6 GW) overtaking Italy (18.9 GW) to take fourth place. Solar power generation enjoyed another year of very rapid growth in 2015, with a 33%

8. 118 Osama Shaukat increase. Its overall share of global power generation remains low (1.1%), but that share has almost doubled in just two years. Solar is starting to have a noticeable impact in terms of sources of power generation growth, contributing more than 30% of the growth of global power in 2015. Energy plays a pivotal role in our daily activities. The degree of development and civilization of a country is measured by the amount of utilization of energy by human beings. Energy demand is increasing day by day due to increase in population, urbanization and industrialization. The world's fossil fuel supply viz. coal, petroleum and natural gas will thus be depleted in a few hundred years. The rate of energy consumption increasing, supply is depleting resulting in inflation and energy shortage. This is called energy crisis. Hence alternative or renewable sources of energy have to be developed to meet future energy requirement. 4. Energy Classification Energy can be classified into several types: 4.1 Primary and Secondary Energy Primary energy sources are those that are either found or stored in nature. Common primary energy sources are coal, oil, natural gas, and biomass (such as wood). Other primary energy sources available include nuclear energy from radioactive substances, thermal energy stored in earth's interior, and potential energy due to earth's gravity. The major primary and secondary energy sources are Coal, hydro power, natural gas, petroleum etc. Primary energy sources are mostly converted in industrial utilities into secondary energy sources; for example coal, oil or gas converted into steam and electricity. Primary energy can also be used directly. 4.2 Commercial Energy and Non Commercial Energy The energy sources that are available in the market for a definite price are known as commercial energy. By far the most important forms of commercial energy are electricity, coal and refined petroleum products. Commercial energy forms the basis of industrial, agricultural, transport and commercial development in the modern world. The energy sources that are not available in the commercial market for a price are classified as non- commercial energy. Non-commercial energy sources include fuels such as firewood, cattle dung and agricultural wastes, which are traditionally gathered, and not bought at a price used especially in rural households. These are also called traditional fuels. Non-commercial energy is often ignored in energy accounting. Fig. 2. Solar PV generation capacity

9. The energy transfer/flow management algorithm for a photovoltaic solar home 119 "energizes" our computers, lights, refrigerators, washing machines, and air conditioners, to name only a few uses[1]. We use energy to run our cars and trucks. Both the gasoline used in our cars, and the diesel fuel used in our trucks are made from oil. The propane that fuels our outdoor grills and makes hot air balloons soar is made from oil and natural gas. 4.4 Renewable Energy and Trends in Solar Photovoltaic Energy Production 4.4.1 Energy Scenario The present energy scenario is discussed under categorical division of World, Bangladesh. 4.4.2 World Energy Scenario Global economic recession drove energy consumption lower in 2009 - the first decline since 1982. World primary energy consumption - including oil, natural gas, coal, nuclear and hydro power - fell by 1.1% in 2009. The issues at hand are numerous and include increasing atmospheric carbon dioxide concentrations from greenhouse gas emissions, environmental safety of energy production techniques, volatile energy prices, and depleting carbon based fuel reserves to name a few (Nguyen and Pearce 2010; Choi et al. 2011)[5]. As a result, countries are facing an increasing challenge to diversify energy sources and bringing renewable generation to the forefront of policy discussion. 4.3 Renewable and Non-Renewable Energy All forms of energy are stored in different ways, in the energy sources that we use every day. These sources are divided into two groups --renewable (an energy source that we can use over and over again) and nonrenewable (an energy source that we are using up and cannot recreate in a short period of time). [2] Figure Renewable and nonrenewable energy sources can be used to produce secondary energy sources including electricity and hydrogen. Renewable energy sources include solar energy, which comes from the sun and can be turned into electricity and heat. Wind, geothermal energy from inside the earth, biomass from plants, and hydropower and ocean energy from water are also renewable energy sources. However, we get most of our energy from nonrenewable energy sources, which include the fossil fuels --oil, natural gas, and coal[2]. They're called fossil fuels because they were formed over millions and millions of years by the action of heat from the Earth's core and pressure from rock and soil on the remains (or "fossils") of dead plants and animals. Another nonrenewable energy source is the element. Uranium, whose atoms we split (through a process called nuclear fission) to create heat and ultimately electricity. We use all these energy sources to generate the electricity we need for our homes, businesses, schools, and factories. Electricity Fig. 1.1. Renewable Energy Sources and Non-Renewable Energy Sources

10. 120 Osama Shaukat In the United States, a rise in renewable energy generation has been supported by the availability of federal tax credits and programs in individual states (U.S. Energy Information Administration 2013a)[3]. Many states are implementing renewable portfolio standards, or renewable energy standards, that outline goals to increase electricity generation from renewable resources (U.S. Energy Information Administration 2013a). These policies seek to remove barriers to install renewable generation and can include grant programs, loan programs, and state renewable electricity tax credits. The Database of State Incentives for Renewables & Efficiency (DSIRE) provides an outline of state renewable portfolio standards available throughout the nation (NorthGraph 1.1 : Power generation capacity in world by source, 2008

11. The energy transfer/flow management algorithm for a photovoltaic solar home 121 Carolina State University 2013)[8]. In 2012, about 12 percent of U.S. electricity was generated from renewable sources (U.S. Energy Information Administration 2013b). The United States Energy Information Administration states that the five renewable sources most often utilized include biomass, water, geothermal, wind and solar (U.S. Energy Information &!! 4.5 Energy transfer/flow management algorithm The figure 3 depicts the detailed flowchart of the flow energy management algorithm. The main idea is that the photovoltaic production should be utilized as much as possible to reach the self-consumption. The priority is given to the supply of the loads, then the charge of the batteries and at last, the excess energy is fed into the grid. The algorithm operation is based mainly on the PV production, the SOC of the battery and the Ibat which indicates if the battery is in charge or discharge and if it is able to feed the loads or not. Depending on the state of theses parameters one of the modes indicated in the previous paragraph is used. 5. Simulation Results and Discussion In order to test the efficiency of the flow energy management algorithm the satisfaction of the energy demand of the solar home by the photovoltaic system, has been evaluated for two chosen cases. The first one is 'a favorable week' for the PV production relatively to weather conditions in summer and the second one is 'an unfavorable week' in the winter. For each case, depending on the PV produced and the load energy profile a combination of the switches, directs the energy flow to the given target. The simulations were done using the irradiation and the temperature data acquired by the meteorological station of the site of Bou-Ismaïl. The PV electrical production was calculated using the PV system model presented briefly in paragraph 3. The algorithm was performed using the appropriate load profile of each season. The figures 4 and 5 show the states of the K1, K2, K3 and K4 switches and the variation of the photovoltaic production, the energy demand (load profile), the energy battery storage and the grid energy for the summer and winter week respectively. From the results presented in figure 4 and 5, the excess energy produced in the favorable week in summer is 8.5%, this percentage corresponds to an energy of 9kWh which is injected to the grid. On the other hand, in winter, 67% of the energy demand of the unfavorable week is satisfied by the grid (65kWh) this is due to the low photovoltaic energy production during this season. To better explain the energy flow in the studied PV system, two particular cases will be discussed. The first one corresponds to a favorable day in summer (25/08/2015), and the second corresponds to an unfavorable day in winner (03/ 02/2015). As it can be seen on figure 6, between midnight and 5am there is no PV production and the energy demand is very low, the battery is at its low level (25%). Between 5 am and 5 pm, the PV array produces 2kWh. After 5 pm, as the PV production is low, the batteries supply a part of the demand. Between 7 pm and 9 pm all the energy needed is taken from the batteries. After 9 pm the batteries continues to discharge in the loads but the demand is so high that the rest of the energy needed was withdrawn from the grid. Indicates that, for the chosen day it can be noticed that the irradiation is at low level all the day and this conducts to a low PV production. In this case, the energy demand is exclusively satisfied by the grid. The battery bank is all day long near its lowest level (25%). The highest energy demand is situated between 5 pm and 9 pm. 6. Conclusion Thanks to the decreasing of the cost of PV installations, the grid parity comes a reality. Nowadays, it is not profitable as before to sale the produced photovoltaic electricity. It is more interesting for the PV owners to use it for their own needs and try to reach their self-consumption. In this article, as a first step an energy flow management algorithm which directs the energy flow according to priorities set was presented. It appears that even if the energy flow algorithm is necessary it is not sufficient. To go further and to use the PV electricity produced as much as possible, a Home Energy Management (HEM) is needed. This last will allow the balancing between the demand and the generation, by controlling the deferrable loads, reduces the energy consumption for example by using

12. 122 Osama Shaukat natural light as long as possible, exchanging excess energy produced between neighbors instead of drawing off energy from the grid. 7. Acknowledgements We would like to thank Dr Shahzad Ahmad Siddiqui, for his valuable advices on the writing of this research paper. References [1] OECD/IEA, 2013. Transition to sustainable buildings. Strategies and opportunities to 2050. [2] Asare-Bediako B., Ramirez Elizondo L.M, Ribeiro P.F. and Kling W.L., Consideration of Electricity and Heat Load Profiles for Intelligent Energy Management Systems. UPEC 2011. 46th International Universities' Power Engineering Conference. Soest. Germany; 5-8th September 2011. [3] Riffonneau Y., Bacha S., Barruel F. and Ploix S., Optimal Power Flow Management for Grid Connected PV Systems with Batteries. IEEE Trans. Sustain. Energy. 2(3), (2011). [4] Gudi N., Wang L. and Devabhaktuni V., A demand side management based simulation platform incorporating heuristic optimization for management of household appliances. Int J Elec Power, 43(1), (2012) 185-193. [5] Di Giorgio A. and Pimpinella L., An event driven smart home controller enabling consumer economic saving and automated demand side management. Appl Energ, 96, (2012) 92-103. [6] Chen X., Wei T. and Hu S., Uncertainty-aware household appliance scheduling considering dynamic electricity pricing in smart home.IEEE Trans. Smart Grid, 2, (2013) 932-941. [7] Tascikaraoglu A., Boynuegri A.R. and Uzunoglu M., A demand side management strategy based on forecasting of residential renewable sources: A smart home system in Turkey. Energ Buildings, 80, (2014) 309-320. [8] Chikh M., Mahrane A.and Bouachri F., PVSST 1.0 sizing and simulation tool for PV systems. Energy Procedia, 6, (2011) 75-84. [9] Al-Alawi A. and Islam S.M., Demand side management for remote area power supply systems incorporating solar irradiance model, Renew. Energ., 29, (2004) 2027-2036. [10] Sera D., Teodorescu R. and Rodriguez P., PV panel model based on datasheet values. Proc. IEEE Int. Symp. Ind. Electron. http:// dx.doi.org/10.1109/ISIE.2007.4374981 (2007) 2392-2396. [11] Copetti J.B. and Chenlo F., Internal resistance characterization of lead acid battery for PV rates. Proceedings of the 11th European PV Solar Energy. Conference, Monteux, (1992) 1116-1119. [12] Copetti J.B. and Chenlo F., A general battery model for PV system simulation. Prog Photovoltaic Res. Appl. (1993) 283-292. [13] Chekired F., Mellit A., Kalogirou S.A. and Larbes C., Intelligent maximum power point trackers for photovoltaic applications using FPGA chip: A comparative study. Elsevier, Sol. Energy, 101, (2014) 83-99. [14] Chekired F., Larbes C., Rekioua D. and Haddad F., Implementation of a MPPT fuzzy controller for photovoltaic systems on FPGA circuit. Elsevier, Energy Procedia. 6, (2011) 541- 549.

13. Numerical analysis of friction factors in smooth and rough microchannels 123 Numerical analysis of friction factors in smooth and rough microchannels MOHD OWAIS QIDWAI1, M.M. HASAN1 and MOHD ARIZ2 1Department of Mechanical Engineering, F/o Engineering and Technology, Jamia Millia Islamia, New Delhi, India 2Global Evolutionary Energy Design, New Delhi, India *E-mail: owais00738@gmail.com Abstract Based on the available literature, the researchers are divided that transition in smooth channel occurs in low Reynolds region or not, and various experimental results contradicts each other. Also, the effect of surface roughness has any considerable effects on early transition behavior or not. The numerical procedures are used these days and various researches are ongoing with the help of numerical methods on studying the flow characteristics. The author aims in understanding the flow behavior in low Reynolds regime between 100 - 1400 for smooth and rough channel with roughness to hydraulic diameter ratio of 0.264. The flow remains in laminar regime for smooth channel and rough channel, and no significant effect of roughness obtains in both the cases. The early transition effects are not seen in the analysis. The friction factor decreases with increase in Reynolds number. Key words : CFD, Friction Factor, Laminar, Reynolds Number, Single phase, Transition, Turbulent, Velocity profile. 1. Introduction For successful operation of electronic devices, the microchannel heat sink is best available option for decades. As per Garimella et al.[1] liquid cooling has lot of potential as discussed in the TCO decision criterion for high density and high computing electronic devices. In the development of liquid cooling microchannel heat sink various researches regarding friction factor[2,3], pressure drop[4] and thermal resistance[5] has been published in recent years. Most of the investigation performed in earlier phase were experimental, but recent development in mathematical models open ways for numerical studies and consistent results were obtained by various researchers[6,7,8], proving the validity of the numerical simulations. Mala and Li[9] performed experimental studies on circular cross sectional microchannel of stainless steel, with one channel with hydraulic diameter in Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 123-130 the range of 50-254. The ratio of surface roughness to the hydraulic diameter in the channel varies from 0.69-3.5. They found that for Reynolds number 80 - 2500, the critical Reynolds number obtained was in the range of 300-900. As per their observation early transition is obtained with increase in friction factor. Brackbill and Kandlikar[10] also obtained early transition from laminar to turbulent regime in the range of 572-2367, for introducing saw tooth profile roughness in the microchannel. Many authors published results with higher range of critical Reynolds number. Tam et al.[11,12] obtained critical Reynolds number in the range of 2100-2700. Baviere et al.[13] found critical Reynolds number in the range of 2417- 2822. Based on the literature review, and applicability of numerical procedures to the study of microchannel flow characteristics, the authors aims at finding out the region of transition in the microchannel with the help of friction factor obtained theoretically and DOI No. : 10.5958/2454-7611.2017.00017.0

14. 124 Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz through numerical procedures for Reynolds number varying from 100-1400, for single phase water flow in the microchannel with constant thermos-physical properties. Classical conventional theory from open literature consists of relations of friction factor (Darcy and Fanning) with the pressure drop. The fanning friction is defined as 21 2   = w Ff u (1) Darcy friction factor and fanning friction factor are related as 4=D Ff f (2) And Darcy friction factor in terms of pressure drop is given by 2 2   = H D P D f L u (3) Where P is the pressure drop across the length of microchannel. The Poiseuille number (Po) is defined as the product of Darcy friction factor and Reynolds number (Re), where Reynolds number is defined as,  Re = HuD (4) The friction factor obtained in the above relation is evaluated based on assumption that Steady, laminar, incompressible flow takes place. The Poiseuille number on the other hand is obtained for the same assumption along with fully developed flow between two parallel infinite plates. For a finite dimension rectangular cross sectional microchannel, Poiseuille number is defined based on the aspect ratio  by Shah and London[14].      2 3 4 5 = 96(1 – 1.3553 + 1.9647 – 1.7012 + 0.09564 – 0.2537 ) Po (5) Various experimental investigations have confirmed that microscale friction factor can be obtained by macroscale theories. Therefore Navier- Stokes equation can be used to study incompressible, Newtonian liquids in laminar regime[15]. Several numerical studies have been performed earlier which confirm the applicability of numerical schemes available for thorough analysis Xu et al.[16], Lee et al.[17], Jones et al.[18]. The present paper aims at investigating the effect of laminar to turbulent transition with the increase in Reynolds number for smooth and rough channel with roughness to hydraulic diameter ratio of 0.264. The numerical scheme is validated with the experimental work of Hao et al.[19]. 2. Mathematical Model Figure 1 Shows the schematic diagram of smooth channel with the dimensions as used in Hao et al.[19]. The average surface roughness in the experimentation was obtained 0.032 micron, on the inside surface of the channel. To study the entire domain is computationally expensive process and hence single channel with exact dimensions are considered for the analysis. For the rough channel as shown in Figure 2, the ribs are introduced only on one side of the channel to analyse its effect on the friction factor and transition regime. The first roughness element is introduced at x= L1=6.8 mm from the inlet boundary and thereafter a pitch value of 2.95 mm is chosen to place the ribs, so that L2= L3= L4= L5= L6= 2.95 mm. Length L1 is selected with a higher value so that fully developed flow is obtained in the region. The ribs have cross- sectional dimension of hr = wr = 50 ?m are introduced Fig. 1. Schematic Diagram of Smooth Microchannel Fig. 2. Ribs of square cross section with hr = wr are introduces in the smooth channel as roughness element

15. Numerical analysis of friction factors in smooth and rough microchannels 125 in the smooth channel as roughness element as shown as shown in Figure 3. Three-dimensional geometry of the model for smooth and rough channelis shown in Figure 4&Figure 5 respectively. Assumption 1. The flow takes place under steady state conditions. 2. No phase change during the flow. 3. No slip boundary condition. 4. Viscous dissipation, flow mal distribution and external heat transfer are neglected. 5. Thermophysical properties of the fluid remain constants. 6. Developing flow at inlet boundary. The governing equation is along with the boundary conditions for 3D, laminar incompressible flow in cartesian coordinates are: Continuity equation       + + = 0 u w x y z (6) The boundary conditions are 2 2 2 2 2 2 1                       + + w = – + + + u u u P u x y z x u u u x y z (7) 2 2 2 2 2 2 1                           + + w = – + + + u P u x y z z x y z (8) 2 2 2 2 2 2 1                       + + w = – + + + w w w P u x y z z w w w x y z (9) The boundary conditions are At z = 0 At z = L w = Uin, u=v=0   = u = v = 0 w x At x = 0 At x = w u=v=w=0 u=v=w=0 At y = 0 At y = h u=v=w=0 u=v=w=0 The above equation is solved using CFD software CFX., the pressure and velocity distribution are identified in the fluid domain for smooth and rough channels. Fig. 3. Schematic diagram of channel with roughness element Fig. 4. Smooth channel Fig. 5. Rough channel

16. 126 Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz 3. Numerical Solution Ansys CFX is used to solve the continuity and momentum equation using Finite volume method (FVM). A mesh of fluid domain is generated for the channel with dimension of length L = 23 mm; height h = 0.146 mm andwidth w = 0.027 mm. The dimensions considered are same as that of Hao et al.[19] for the smooth channel with no ribs. The numerical solution also involves surface roughness effect of 0.032 micron as mentioned by Hao et al.[19]. For a flow of Re = 100 three mesh sizes were used as shown in Table 1. The number of nodes are increased for each solution and the resultant pressure drop from inlet to outlet boundary is mentioned along with the central velocity in fully developed region about 18 mm down the inlet boundary. The convergence criterion adopted for the solution of momentum and continuity equations is to be less than 10-6. 4. Result and Discussion From Fig. 6, it is observed that frictional factor decreases with increase in Reynolds number for both smooth and rough microchannel. There is no significant deviation from Darcy friction factor and numerical frictional factor for both smooth and rough microchannels. However, the slight deviation starts taking place at Re=600 for friction factor in rough microchannel, which is not so significant for which early transition effect in rough channel can be concluded. Though a higher value of friction factor is obtained for Re > 900 in case of rough channel. But, it can be said that there is no effect of surface roughness on transition for flow with low Reynolds number. From Fig. 7 it appears that the velocity profile is parabolic for low Reynolds number, and as the Reynolds number is increased the parabolic velocity Table 1. Grid independence study Mesh Number of Pressure Drop Fully developed Configuration Nodes P (Pa) central velocity (m s–1 ) 1 429229 8482.00 0.955027 2 576000 8478.65 0.950493 3 792000 8474.30 0.948219 Fig. 6. Comparison of Friction Factor obtained using pressure drop for smooth and rough microchannel from numerical solution and C/Re., where C is obtained from equation 5 for smooth channel

17. Numerical analysis of friction factors in smooth and rough microchannels 127 Fig. 7. Fully developed velocity profile across the channel at 18 mm down the inlet boundary in smooth channel distribution tends to become blunter, which suggest early transition from laminar to turbulent regime. Fig. 6 shows the shift from Darcy friction profile is started early around Re=600. and considerable shift takes between the Darcy friction factor and numerical friction factor around Re=1000. The flow is still in the laminar regime, but this could be the understanding of earlier authors that some of them may concluded this as the early shift in transition. The velocity profile at Re=900 and Re=1000 are presented in Fig. 9 for comparison. Based on the profile obtained it may be said that it marks the beginning of transition but does Fig. 8. Fully developed velocity profile across the channel at 18 mm down the inlet boundary in rough channel not reach critical Reynolds value in smooth channel. Fig. 8 shows almost parabolic velocity profile except the slight deviation is due to the presence of roughness element in the microchannel. The deviation from parabolic velocity profile increases with the increase in Reynolds number. As shown in Fig. 10, the velocity profile for rough channel at Re = 500 have a sharp parabolic peak, while the profile for Re = 600 is considerably blunter. Both the profiles are deviated from central mean position because of the presence of roughness element. As

18. 128 Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz Fig. 9. Comparison of fully developed velocity profile in smooth channel (a) Fig. 10. Comparison of fully developed Velocity profile in rough channel (b) (a) (b) shown in Fig. 11 and Fig. 12, the flow recirculation increases with increase in Reynolds number. Since the flow is not shifted into transition or turbulent phase either, otherwise due to stronger transverse momentum exchange in turbulent regime, the case would have obtained wise versa, with length of flow recirculation zone smaller and blunter profile at Re=1300.

19. Numerical analysis of friction factors in smooth and rough microchannels 129 Fig. 11. Flow Recirculation in rough channel for Re=600 Fig. 12. Flow Recirculation in rough channel for Re=1300 5. Conclusion Based on the above discussion, following points may be concluded: 1. Roughness to hydraulic diameter ratio of 0.264 has no significant effect in early transition from laminar to turbulent regime in the range of Re = 100 to 1400. 2. The friction factor has higher value for Re>900 for both the channels, but based on streamwise velocity, it cannot be asserted that profile obtained in Fig. 9 & Fig. 10, is not parabolic in nature. 3. Conventional theories are in good agreement with experimental results mostly. Only in the studies where entrance loss, exit loss and developing flow are not considered, reports deviation from it [2]. Nomenclature Subscript  Shear Stress w wall  Fluid Density F Fanning Factor ¯u Average flow velocity D Darcy Factor f Friction Factor H Hydraulic  Difference P Pressure D Diameter L Length  Viscosity  aspect ratio (h/w) h Height of Channel w Width of channel References [1] Garimella S.V., Persoons T., Weibel J.and Yeh L.T., "Technological drivers in data centers and telecom systems: Multiscale thermal, electrical, and energy management," Appl. Energy, 107, (2013) 66-80.

20. 130 Mohd Owais Qidwai, M.M. Hasan and Mohd Ariz [2] Dai B., Li M. and Ma Y., "Effect of surface roughness on liquid friction and transition characteristics in micro- and mini-channels," Appl. Therm. Eng., 67(1-2), (2014) 283-293. [3] Steinke M.E. and Kandlikar S.G., "Single- phase liquid friction factors in microchannels," Int. J. Therm. Sci., 45(11), (2006) 1073-1083. [4] Gunnasegaran P., Mohammed H. and Shuaib N.H., "Pressure Drop and Friction Factor for Different Shapes of Microchannels," 7-8, (2009). [5] Qu W. and Mudawar I., "Experimental and numerical study of pressure drop and heat transfer in a single-phase micro-channel heat sink," Int. J. Heat Mass Transf., 45(12), (2002) 2549-2565. [6] Lee P.S. and Garimella S.V., "Thermally developing flow and heat transfer in rectangular microchannels of different aspect ratios," Int. J. Heat Mass Transf., 49(17-18), (2006) 3060-3067. [7] Li J. and Peterson G.P., "3-Dimensional numerical optimization of silicon-based high performance parallel microchannel heat sink with liquid flow,"Int. J. Heat Mass Transf.,50(15- 16), (2007) 2895-2904. [8] Sahar A.M., Özdemir M.R., Fayyadh E.M., Wissink J., Mahmoud M.M. and Karayiannis T.G., "Single phase flow pressure drop and heat transfer in rectangular metallic microchannels," Appl. Therm. Eng., 93, (2015) 1324-1336. [9] Mohiuddin Mala G. and Li D., "Flow characteristics of water in microtubes," Int. J. Heat Fluid Flow, 20(2), (1999) 142-148. [10] Brackbill T.P. and Kandlikar S.G., "Effect of Sawtooth Roughness on Pressure Drop and Turbulent Transition in Microchannels," Heat Transf. Eng., 28(8-9), (2007) 662-669. [11] Tam L.M. et al., "The Effect of Inner Surface Roughness and Heating on Friction Factor in Horizontal Micro-Tubes," 44403, (2011) 2971- 2978. [12] Tam L.M., Tam H.K. and Ghajar A.J., "Simultaneous Heat Transfer and Pressure Drop Measurements for a Horizontal Micro- Tube," 38921, (2011) T10122-T10122-8. [13] Conference I., June M. and York N., "ICMM2004-2338," 0, (2016) 1-8. [14] Shah R.K. and London A.L., Laminar Flow Forced Convection in Ducts: A Source Book for Compact Heat Exchanger Analytical Data. (1978). [15] Xu B., Ooti K.T., Wong N.T. and Choi W.K., "Experimental investigation of flow friction for liquid flow in microchannels," Int. Commun. Heat Mass Transf., 27(8), (2000) 1165-1176. [16] Lee P.S., Garimella S.V. and Liu D., "Investigation of heat transfer in rectangular microchannels," Int. J. Heat Mass Transf., 48(9), (2005) 1688-1704. [17] He Y., Shao B.D., Cheng H.M. and Tang Y.J., "Numerical Simulation and Size Optimization of the Flow Channel of Rectangular Micro- Channel Heat Sink," Appl. Mech. Mater., 444- 445, (2013) 568-573. [18] Jones B.J., Lee P.-S. and Garimella S.V., "Infrared micro-particle image velocimetry measurements and predictions of flow distribution in a microchannel heat sink," Int. J. Heat Mass Transf., 51, (2008) 1877-1887. [19] Hao P.-F., Yao Z.-H., He F. and Zhu K.-Q., "Experimental investigation of water flow in smooth and rough silicon microchannels," J. Micromech. Microeng, 16, (2006) 1397-1402.

21. Effect of operating conditions on the performance of vapor absorption refrigeration system 131 Effect of operating conditions on the performance of vapor absorption refrigeration system MD. MERAJ1, RASHID IMAM2 and MD. ASHFAQUE ALAM3 1 Engineering & Technology, Department of Mechanical Engineering, JMI, New Delhi-110025, India 2 Department of Mechanical Engineering, Vishveshwarya Group of Institution, Noida, UP-203207, India 3 Department of Mechanical Engineering, NIT, Jamshedpur, Jharkhand-831014, India *E-mail: md.meraj1221@gmail.com Abstract In this paper, a thermodynamic analysis of single effect vapor absorption refrigeration system (VARS) is carried out. LiBr-Water is used as working fluid during the analysis. This analysis is carried out to study the effect of operating conditions on the performance of vapour absorption refrigeration system. The generator temperature, the condenser temperature and the evaporator temperature are taken as operating conditions for the analysis. From the result and discussion, it is found that the coefficient of performance (COP) of the system increases with increasing the generator and evaporator temperature up to a certain limit but decreases with increasing the condenser temperature. Key words : VARS, LiBr-Water, COP, generator temperature, condenser temperature, and evaporator temperature. 1. Introduction Present day, the rate at which the non-renewable energy sources are being utilized has become a major concern for the world. The future prospect of nonrenewable sources of energy like coal, natural gases and petroleum products are going to be scarce. To preserve these energy sources for our future generation, we have to reduce its consumption by using alternative sources of energy like solar energy, geothermal energy, waste heat, hydro-energy etc. There are many ideas has been developed to utilized these alternative sources of energy and researches has also been under the processes to improve the systems which utilize these sources. In this regard vapor absorption refrigeration systems are the best alternative system to reduce the rate of consumption of non-renewable energy sources. Vapor absorption refrigeration system (VARS) invented much earlier than vapor compression refrigeration system (VCRS) but due to law coefficient of performance and inven-tion of high performance Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 131-136 refrigerant for VCRS during Second World War, the popularity of VARS decreases. But, in present scenario of energy crisis has forced the world to use vapor absorption refrigeration system in place of vapor compression system to reduce the rate of consumption of non-renewable energy sources. VARS is one of the best replacement for the VCRS, from the energy point of view as well as environmental,because this system works on law grade of energy such as solar energy, geothermal-energy, waste-heat from industries, cheap available energy etc., and VARS uses such type of refrigerant-absorbent combination which do not contributes in global warming and ozone depletion like LiBr2-H2O, H2O -NH3, LiNO3-NH3, NaSCN-NH3 etc. From construction point of view absorption system and compression system are similar but only the differenceis that the compressor in case of compression system is replaced by the generator- solution heatexchanger-pump-absorber assembly which is used to circulate the working fluid entire the system by creating pressure differ-ences[8-9]. DOI No. : 10.5958/2454-7611.2017.00018.2

22. 132 Md. Meraj, Rashid Imam and Md. Ashfaque Alam Aphornratna. S and Sriveerakul. T[1] performed an experimental investigation of single-effect absorption. They have usedaqueous lithium-bromide as working fluid. They have done their analysis on 2 kW cooling capacity experimental refrigerators which was tested with various operating temperatures. From results, it was found that the system performance is strongly dependent on thesolution circulation ratio (SCR)and also on solution heat exchanger. They have resulted that energy input to the generator is reduced to 60% by usingsolution heat exchanger. Darwish A. N. et. al.[2] presented the performance analysis and evaluation of the roburabsorption-refrigeration water-ammonia (ARWA) system.The system is analysed by using aspen plus flowsheet simulator.They analysed COP, heat duties of the evaporator, absorber, and the condenser and the flow rate of refrigerant passing through the evaporator.The results obtained by them is compared with some manufacturer data and experimental data reported in the journal literature. Saghiruddin and Siddiqui[3] perfor-medthe economic analysis of ordinary and evacuated tubular type flat- plate collectors for operating absorption cycles with and without heat recovery absorber. Water- Ammonia, NaSCN3 and LiNO3-NH3 mixtures has been selected as the working fluids in the cycles. Use of heat recovery absorber, in addition to the primary absorber in the conventional absorption cycles lead to the improvement in COP by 20-30 % in Water- Ammonia and 33-36% in NaSCN-NH3 and LiNO3- NH3 mixtures. Kaushik and Kumar[4] performed thermodynamic analysisof two-stage vapour absorption refrigeration system using ammonia- water (NH3-H2O) and ammonia-lithium nitrate (NH3-LiNO3) as working fluid. They havefound that minimum evaporator temperature is achieved in NH3-LiNO3 combination, and COP of the NH3- LiNO3 is higher than the NH3-H2O. Marcos et al.[5] performed optimization of COP in single and double effect LiBr-H2O absorption chillers. They analyzed water cooling system and air cooling system and found that solution concentration is an important parameter to improve COP. With this, they also found the crystallization limit. Their study showed that COP of single effect becomes 0.85 to 0.74 in water cooled and 0.72 to 0.65 in air cooled system. Similarly, in double effect cycle it was 1.18-1.2 in the water cooled and 1.15-1.07 in the air cooled system. Talbi M. M. and AgnewB.[6] presented an exergy analysis on a single effect absorption refrigeration cycle with lithium-bromide-water as the working fluid pair. They calculated the loads on each component of absorption system, exergy of each components and total exergy of system. However, some of the research has been done on the energy and exergy analysis of the double effect absorption refrigeration system[10, 11,12]. From literature survey it is absorbed that there is no work has been done on the effect of operating condition on the performance of vapour absorption refrigeration system. Therefore this paper present a thermodynamic analysis which shows variation of performance of VARS with the operating conditions like the generator temperature, the condenser temperature and the evaporator temperature in the presented analysis. 2. System Description A schematic diagram of vapour absorption refrigeration system is shown in Fig. 1. on which analysis has beendone. This system consists of an Evaporator (E), Absorber (A), Generator (G), Condenser(C), Throttle valve (TV), Pre-cooler (PC), Fig. 1. Schematic diagram of single effect vapour absorption refrigeration system.

23. Effect of operating conditions on the performance of vapor absorption refrigeration system 133 Preheater (PH) and Pump.The operating temperature of generator, condenser, evaporator and absorber is shown byTg, Tc, Te and Ta respectively in figure 1. There are two pressure levels in this system; the generator and condenser operate at high pressure level while evaporator and absorber operate at low pressure level. LiBr-H2O mixture is used as working fluid in the system in which LiBr works as an absorbent and H2O works as refrigerant. LiBr-H2O mixture circulate in the generator-solution heat exchanger-pump-throttle valve-absorber assembly, generating the water vapor in the generator which flows through condenser, throttle valve, solution heat exchanger and evaporator. The working fluid having the different state condition while circulating inthe system is shown in figure by different state point. 3. Thermodynamic Analysis The thermodynamic analysis of single effect vapour absorption refrigeration system is based on the application of mass, concentration and energy conservations. For performing these applications, there are some assumptions are made to simplify the analysis, these are as follows :  The systems are in steady state.  The refrigerant (water) at the outlet of the condenser is saturated liquid.  The refrigerant (water) at the outlet of the evaporator is saturated vapour.  Temperature of absorber and condenser are same.  Expansion process in throttle valve is isenthalpic.  Heat loss to environment and pressure drop in the systems are negligible.  No leakage of air in the system. Mass, concentration and energy conservation equation of generator are respectively expressed by: 5 6 10 m m m (1) 5 5 6 6 10 10 m X m X m X (2) 6 6 10 10 5 5= –EQ m h m h m h (3) Mass, concentration and energy conservation equation of absorber are respectively expressed by: 3 2 12m m m  (4) 3 3 2 2 12 12m X m X m X  (5) 2 2 12 12 3 3= –aQ m h m h m h (6) Energy consumption of solution pump can be defined as: 4 4 3 3= –pW m h m h (7) Energy conservation of condenser and evaporator is given by : 6 6 7 7= –cQ m h m h (8) 1 1 9 9= –eQ m h m h (9) The coefficient of performance of the system can be expressed as follows : /( )e E DCOP Q Q W  (10) A computer program has been developed using FORTRAN language to carry out the system simulation of the single effect vapour absorption refrigeration system. The analysis has been done for 1 Ton of refrigeration. Properties of LiBr-water have been evaluated by the correlation from[7]. The calculation parameters for the simulation are summarized in table 1. Table 1 Calculation Parameters Evaporator temperature (Te in °C) 5-(2.5)-12.5 Absorber temperature (Ta in °C) 30-(5)-40 Condenser Temperature (Tc in °C) 30-(5)-40 Effectiveness of pre-heater (%) 75 Effectiveness of pre-cooler (%) 75 Cooling load (kJ/h) 12600 4. Results and Discussion Figure 2 shows the variation of coefficient of performance (COP) of single effect vapour absorption system with genera-tor temperature at which heat is supplied at different values of evaporator temperature (i.e. Te = 5.0, 7.5, 10.0 and 12.5 °C), the condenser temperature and absorber temperature at which heat is rejected to the surroundings are equal and kept constant i.e. Ta = Tc = 30 °C. From this graph, it is seen that the coefficient of performance of single effect increases drastically from low values at low generator temperature, reach to maximum value and

24. 134 Md. Meraj, Rashid Imam and Md. Ashfaque Alam Fig. 3. Variation of coefficient of performance (COP) with condenser temperature (Tc) for different evaporator temperature (Te). Fig. 2. Variation of coefficient of performance (COP) with generator temperature (Tg) for different evaporator temperature (Te).

25. Effect of operating conditions on the performance of vapor absorption refrigeration system 135 then with further increase in the increase in the generator temperature slightly decreases i.e. the results show an optima. From this result it is also observed that with increasing the evaporator temperature for a particular generator coefficient of performance increases. Figure 3 shows the variation of coefficient of performance (COP) of single effect vapour absorption system with con-denser temperature at which heat is rejected to surrounding at different values of evaporator temperature (i.e. Te = 5.0, 7.5, 10.0 and 12.5 °C). From this graph, it is seen that the coefficient of performance decreases gradually with increases in condenser temperature for a particular evaporator temperature. From this result it is also observed that with decreasing the evaporator temperature for a particular condenser temperature coefficient of performance decreases. Figure 4 shows the variation of coefficient of performance of single effect absorption system with evaporator temperature at which the refrigerated space should be maintained at different values of condenser temperature (Tc = 30, 35, 40 & 45 °C). From the graph, it is observed that the coefficient of performance increases gradually with increase in evaporator temperature for a particular condenser temperature. From this result it is also observed that with increasing condenser temperature for a particular evaporator temperature coefficient of performance increases. 5. Conclusions From the above result and discussion it is concluded that coefficient of performance system has strong effect on the operation condition. The performance of system is dependent on generator temperature, evaporator temperature and condenser temperature simultaneously. It is found that the coefficient of performance of presented single effect vapour absorption refrigeration system increases with increasing the generator and evaporator temperature up to a certain limit but decreases with increasing the condenser temperature. Therefore, to obtain efficient performance of single effect vapour absorption refrigeration system, it should be operated at moderate generator, evaporator and condenser temperature of vapour absorption refrigeration. Fig. 4. Variation of coefficient of performance (COP) with evaporator temperature (Te) for different condenser temperature (Tc).

26. 136 Md. Meraj, Rashid Imam and Md. Ashfaque Alam References [1] Aphornratana S. and Sriveerakul T., "Experimental studies of a single-effect absorption refrigerator using aqueous lithium- bromide: Effect of operating condition to system performance", Experimental thermal and fluid science, 32, (2007) 658-669. [2] Darwish N.A., Al-Hashimi S.H. and Al- Mansoori A.S., "Performance analysis and evaluation of a commercial absorption- refrigeration water-ammonia (ARWA) system", International Journal of Refrigeration, 31, (2008) 1214-1223. [3] Saghiruddin and Siddiqui M.A., "Economic analysis and performance study of three ammonia-absorption cycles using heat recovery absorber", Energy Conversion and Management, 37, (1996) 421-432. [4] Kaushik S.C. and Kumar R., "Thermodynamic study of two stage vapour absorption refrigeration system using NH3 refrigerant with liquid solid absorbents", Energy Conversion and Management, 4, (1985) 427-431. [5] Marcos J.D., Izquierdo M. and Palacios E., "New method for COP optimization in water- and air-cooled single and double effect LiBr- water absorption machines", International Journal of Refrigeration, 34, (2011) 1348-1359. [6] Talbi M.M. and Agnew B.,"Exergy analysis: an absorption refrigerator using lithium bromide and water as working fluid", Applied Thermal Engineering, 20, (2011) 619-630. [7] Kaita Y., "Thermodynamics properties of lithium bromide-water solutions at high temperatures", International Journal of Refrigeration, 24, (2001) 374-390. [8] Cengel Y.A. and Boles M.A., "Thermo- dynamics an engineering approach", Tata McGraw Hill Education Private Limited New Delhi, (2008). [9] Arora C.P., "Refrigeration and Air Conditioning", McGraw Hill Education Private Limited New Delhi, (2009). [10] Kaushik S.C. and Arora A., "Energy and exergy analysis of single effect and series flow double effect water-lithium bromide absorption refrigeration systems", International Journal of Refrigeration, 32, (2009) 1247- 1258. [11] Mairaj M., Siddiqui S.A. and Hafiz A., "Energetic and exergetic analysis of some models of vapour absorption chillers using lithium bromide and water", Journal of Basic and Applied Engineering Research, 2(4), (2015) 326- 329. [12] Meraj M., Hafiz A. and Ahmad M.J., "Second Law Analysis of Series and Parallel Flow Double Effect Vapor Absorption Chiller", IOSR Journal of Me-chanical and Civil Engineering, 13(3), (2016) 104-110.

27. Study and analysis of plate type heat exchanger 137 Study and analysis of plate type heat exchanger NUMAN ANSARI1, MOHD. ISLAM1 and SAYYED HAIDER2 1 Department of Mechanical Engg. Faculty of Engg.& Technology, Jamia Millia Islamia,New Delhi-110025,India 2 Department of Mechanical Engg., Al-Falah School of Engineering & Technology, Haryana-121004, India *E-mail: numan.ansari5@gmail.com Abstract With the emerging trend in technology heat transfer dissipation from those device which required certain temperature for their efficient operation in the major problem. In this regards high technology is required to cool such devices. As far as heat exchanger is the major solution of such problem. Plate heat exchanger are the exchangers having a number of plates combined together having different corrugation for transfer the heat between the two fluid. An experimental investigation are done on the plate type heat exchanger to estimate the value of heat transfer characteristics by changing the mass flow rate and study the pressure drop. And from the experiment estimate the value of heat transfer characteristics for hot and cold fluid, nusselt number, pressure drop and effectiveness. It is shown that Nusselt number, pressure drop and effectiveness are depends on the mass flow rate. This paper is concerned with the plate type heat exchanger and investigation is carried out by considering the different works published in the field of heat exchangers. Key words : Plate heat exchanger (PHX), heat exchanger (HXCH), chevron angle, gaskets, plate, flow arrangement, domestic hot water (DHW). 1. Introduction Plate heat exchanger (PHE) are the exchangers having a number of plates combined together having different corrugation for transfer the heat between the two fluid. Plate heat exchanger are widely used in the industry and are commonly designed with the corrugated channel surface resulting in the enhanced heat transfer performance by increasing the area over which heat transfer take place and generating a vigorous mixing of effect within the working fluid. Component of plate type heat exchanger are shown in figure. As shown in Figure 1, the plate heat exchanger is basically a series of individual plates pressed between two heavy end covers. These plates are gasketed, welded or brazed together depending on the application of the heat exchanger. The basic geometry of plates used in plate heat exchanger is shown in figure 2. Stainless steel is a commonly used metal for the plates because of its ability to withstand Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 137-141 high temperatures, its strength, and its corrosion resistance[1]. The entire assembly is held together by the tie bolts. This has a major advantage over a conventional heat exchanger in that the fluids are exposed to a much larger surface area because the fluids spread out over the plates. This facilitates the transfer of heat, and greatly increases the speed of the temperature change. The concept behind a heat exchanger is the use of pipes or other containment vessels to heat or cool one fluid by transferring heat between it and another fluid. In most cases, the exchanger consists of a coiled pipe containing one fluid that passes through a chamber containing another fluid. The walls of the pipe are usually made of metal or another substance with a high thermal conductivity to facilitate the interchange, whereas the outer casing of the larger chamber is made of a plastic or coated with thermal insulation, to discourage heat from escaping from the exchanger. DOI No. : 10.5958/2454-7611.2017.00019.4

28. 138 Numan Ansari, Mohd. Islam and Sayyed Haider Chevron Angle , Typically varying from 20° to 65°,  is the measure of softness (small , low thermal efficiencyand pressure drop) and hardness (large , high thermal efficiency and pressure drop) of thermal and hydraulic characteristics of plates. Some authors define "/2- " as the chevron angle[1]. Pressure drop (p) is in direct relationship to the size of the plate heat exchanger. If it is possible to increase the allowable pressure drop, and incidentally accept higher pumping costs, then the heat exchanger will be smaller and less expensive. As a guide, allowable pressure drops between 20 and 100 kPa are accepted as normal for water/water duties. 2. PHE Parts and their function Plate with gaskets Plate heat exchangers consist of pressed plates; the separating gaskets between each plate; the end plates used to clamp the plate stack together and the frame to hold the plate stack in place. The plate is pressed metal. A wide range of metals and corrugation shapes can be used that suit the chemical, flow and corrosive properties of the media passing across the plates[4]. Plates for an exchanger have indentations and corruga-tions to encourage more turbulent flow across them and to make thinner films of media to promote better heat transfer. The headers to feed and remove the fluids pass through all plates. Unwanted headers are blocked off on a plate. Gaskets, each plate have a gasket that produces a sealing and channel system through the entire plate pack in which the two heats exchanging media flow in a counter-current direction. The circular portion of a gasket stops the fluid from going across the heat transfer plate and sends it to next open channel. The remaining portion or field gaskets directs the opposing fluid across the heat transfer surface. The gaskets separate the plates and create the thin chamber through which the fluid film swirls and flows. They also serve the purpose of directing the media from the entry port to the exit port. The frame is made up of thick steel pressure retaining parts, the fixed cover and the movable cover that when pulled together with the tightening bolts from the pres-sure retaining structure for the plates. The carrying bar and guide bar act as a carrier and guide both the plates and movable cover. The heat exchangers plates, which make up the heat transfer surface, are clamped between two plates of steel with the use of the tightening bolts. The heat exchanger construction allows a plate heat exchanger to be easily opened for inspection and cleaning. In a plate heat exchanger corrugated plate like this one are used between the barrier of hot fluid and cold fluid. The corrugated plate increases the area of heat transfer. PHE plate usually made of advance material like titanium which makes plate stronger and durable. The thickness of plate is 0.5 mm to 0.6 mm. Fig. 1. Various parts of PHE Fig. 2. Geometry of plate [1]

29. Study and analysis of plate type heat exchanger 139 Flow arrangement, Plate heat exchangers are very easy counter flow where hot and cold fluid flow in opposite direction as shown in figure. The plate is placed in such a way that the flow bond by each successive plate alter-nates the hot fluid and cold fluid. The heat exchangers plates with gaskets are arranged in an alternating pattern of left hand flow and right hand flow to direct the fluids in an opposing direction within the heat exchanger. The complete assembly of all the plates and gaskets is called the "Plate Pack". 3. Modelling of PHX and analysis of heat transfer performance The experimental set up presents the principal geometry parameters and illustrates the experimental setup established to investigate the heat transfer characteristics in the corrugated channel for different flow conditions. The basic components of the experimental apparatus include a water loop, an air loop, and a measurement system. The water loop comprises a water tank containing a heater, a pump, a flow meter, and a temperature controller. Fig. 5. Flow arrangement of PHE Fig. 3. Plate with gaskets [4] port ring gasket Flow ports Fig. 4. Gaskets [4] Fig. 6. Experimental set up of PHE Importantly, all of the components in the water system are thermally insulated such that wall temperature of the corrugated channel can be maintained at a nearly constant temperature. The air loop consists of the test section containing the corrugated channel, a blower, an air flow meter, and a number of valves which enable the flow rate to be adjusted. Additionally, a flow straightner can be installed at the entrance of the test section to maintain a uniform inlet flow. The test section is constructed from Galvanized Iron (GI) sheets, each with corrugated surface on both the sides. The two cases are clipped between two corrugated plates, metal plates to form the corrugated channel through which the working fluid is passed. During experiments, hot water was flowed through the two hollow cases to maintain the channel surfaces at an approximately constant temperature and thermocouples wrapped

30. 140 Numan Ansari, Mohd. Islam and Sayyed Haider in copper tubes and inserted in upper metal plates were used to record the corresponding air temperature. The side effect was avoided by specifying a small aspect ratio for the channel such that variations in the channel height could be neglected. In the experiments, the temperature distribution in the horizontal, middle plane of the channel was monitored using thermocouples positioned at different locations along the length of the channel in the water loop and in air loop.The temperature of the inlet and outlet water is measured using mercury thermometers. The pressure of the air at the inlet and outlet of the test section is measured using the pressure gauges. 4. Results and Discussion The experiments described herein represent the study of fully developed heat transfer for water flowing in a cor-rugated duct. The duct had a corrugation angle of 29 degree and interval spacing equal to the corrugation height. The Reynolds number based on hydraulic diameter was varied from 1500 to 25,000, and the prandtl number was varied from 4 to 8. Table 2. Counter Flow Condition (Air) Air Position Distance Xm TX Tb hx Nux × 103 channel of X (cm) ºC ºC (KW/m2k) Ma thermocouple (cm) 2.0×10–3 kg/s 1 9.7 29.1 42 43.75 7.13 45.43 2 48.5 66.5 45.5 47.25 9.43 66.93 3 84.5 49 hxm=8.28 Nux=56.18 Table 1. Counter Flow Condition (Water) Surface temperature for 100 LPM Water Position Distance Xm TX Tb hx Nux × 103 channel of X (cm) ºC ºC (KW/m2k) Mw thermocouple (cm) 0.133 kg/s 6 12 11.25 70 67.5 88.30 8.79 5 10.5 29.25 65 66.5 38.25 12.73 4 48 46.75 68 66 85.43 8.43 3 45.5 66.25 64 65 18.57 6.01 2 87 86.20 66 64.75 81.93 7.34 1 85.5 63.5 hxm=62.49 Nux=8.66 Experimental investigation are done by changing the mass flow rate in the experimental setup and study the pressure drop and heat transfer characteristics in the corrugated channel of the plate heat exchanger. The experimental data are substituted into the correlations to identify the characteristics and effect on the Nusselt number by changing the mass flow rate. The analytical results show that local Nu and effectiveness are affected by the change into the flow condition for a given set. 5. Conclusions Although a conclusion may review the main points of the paper, do not replicate the abstract as the conclusion. A conclusion might elaborate on the importance of the work or suggest applications and extensions. Authors are strongly encouraged not to call out multiple figures or tables in the conclusion- these should be referenced in the body of the paper. 6. Conclusions The authors wish to thank A, B, C. This work was supported in part by a lished manuscript).

31. Study and analysis of plate type heat exchanger 141 References [1] Bridle J.S., "Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition," Neurocomputing-Algorithms, Architectures and Applications, Fogelman- Soulie F. and Herault J., eds., NATO ASI Series F68, Berlin: Springer-Verlag, (1989) 227-236. (Book style with paper title and editor). [2] Chen W.-K., Linear Networks and Systems. Belmont, Calif.: Wads-worth, (1993) 123-135. [3] Poor H., "A Hypertext History of Multiuser Dimensions," MUD History, http://www.ccs. neu.edu/home/pb/mud-history.html. 1986. (URL link *include year). [4] Elissa K., "An Overview of Decision Theory," unpublished. (Unplublished manuscript). [5] Nicole R., "The Last Word on Decision Theory," J. Computer Vision, submitted for publication. (Pending publication). [6] Kaufman C.J., Rocky Mountain Research Laboratories, Boulder, Colo., personal communication, (1992). (Personal communication). [7] Coming D.S. and Staadt O.G., "Velocity- Aligned Discrete Oriented Polytopes for Dynamic Collision Detection," IEEE Trans. Visualization and Computer Graphics, 14(1), (2008) 1-12, doi:10.1109/TVCG.2007.70405. (IEEE Transactions ) [8] Bingulac S.P., "On the Compatibility of Adaptive Controllers," Proc. Fourth Ann. Allerton Conf. Circuits and Systems Theory, (1994) 8-16. (Conference proceedings). [9] Goto H., Hasegawa Y. and Tanaka M., "Efficient Scheduling Focusing on the Duality of MPL Representation," Proc. IEEE Symp. Computational Intelligence in Scheduling (SCIS '07), (2007) 57-64, doi:10.1109/SCIS.2007. 367670. (Conference proceedings). [10] Williams J., "Narrow-Band Analyzer," PhD dissertation, Dept. of Electrical Eng., Harvard Univ., Cambridge, Mass., (1993). (Thesis or dissertation). [11] Reber E.E., Michell R.L. and Carter C.J., "Oxygen Absorption in the Earth's Atmosphere," Technical Report TR-0200 (420- 46)-3, Aerospace Corp., Los Angeles, Calif., Nov. (1988). (Technical report with report number) [12] Hubert L. and Arabie P., "Comparing Partitions," J. Classification, 2(4), (1985) 193-218. (Journal or magazine citation). [13] Vidmar R.J., "On the Use of Atmospheric Plasmas as Electromagnetic Reflectors," IEEE Trans. Plasma Science, 21(3), (1992) 876-880, available at http://www.halcyon.com/pub/ journals/21ps03-vidmar, (URL for Transaction, journal, or magzine). [14] Martinez J.M.P., Llavori R.B., Cabo M.J.A.and Pedersen T.B., "Integrating Data Warehouses with Web Data: A Survey," IEEE Trans. Knowledge and Data Eng., preprint, 21 Dec. 2007, doi:10.1109/TKDE.2007.190746.(PrePrint).

32. 142 Hasan Shamim, Shadab Ahmad and Shah Alam Study of CFD approach to discretise first derivative of partial differential equation HASAN SHAMIM, SHADAB AHMAD and SHAH ALAM Jamia Millia Islamia, New Delhi *E-mail: hasanshmm@gmail.com Abstract The process of converting governing partial differential equations into algebraic equation is known as discretisation. The finite difference method is one of the most powerful and simple method to convert partial differential equation (PDE) into algebraic equation. The accuracy of finite difference method increases with refining grid size. In this present study the finite difference method (FDM) is used to determine the shear stress over a flat plate. This shear stress is function of velocity gradient as given by Newton's Law of viscosity. The first derivative of velocity gradient is replaced by forward difference, Reward difference and the central difference approaches. The exact solution of equation is compared with approximate solution and the errors are determined for different values of grid points spacing. It is found that central approach is more accurate than forward and reward approaches. The effect of order of accuracy such as O(y), O(y)2, O(y)3 has been also studied. It shows as order of accuracy increases, computational errors decreases. Key words : Discretisation, PDE, Finite difference method, Forward difference, Reward difference, Central difference, Order of accuracy, Mesh spacing, 1. Introduction Computational Fluid Dynamics (CFD) provides a qualitative (sometimes even quantitative) prediction of fluid flows by means of mathematical modelling, Numerical methods and software tools[1]. These advantages of CFD over experiment based approach are given as :  Substantial reduction of lead time and cost of new designs.  Ability to study systems where controlled experiments are difficult or impossible to perform.  Ability to study systems under hazardous conditions. The main problem with CFD is that code user must have high skilled position. The assumptions, made regarding type of flow e.g. two dimensional, three dimensional, Compressible, Non compressible, Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 142-146 Viscous, Non viscous. Laminar, Turbulent should be realistic and must also be able to handle convergence, consistent, stability associated problems in the solution[2]. However there are several applications of CFD in different fields of daily life and engineering. While analysing problems with CFD approach, we get PDE[3]. These equations are first converted into algebraic equations;only then solution of PDE is possible. This process is known as Discretisation. There are three different methods to discretise the PDEs into algebraic equations. These methods are finite difference method (FDM), Finite element method (FEM) and Finite volume method (FVM)[4]. In this present analysis we are using FDM to discretise PDE and observe the accuracy of solution. 2. Statement of Problem In this we want to determine shear stress over a flat plate, when air is flowing over it. The velocity profile is vertical direction is assumed as : DOI No. : 10.5958/2454-7611.2017.00020.0

33. Study of CFD approach to discretise first derivative of partial differential equation 143        = 1 – y L u c e Where c = 480 L is the length of plate (Let L = 3 cm) We determine shear stress at a distance of 0.35 cm with step size of 0.10 cm, 0.15 cm, 0.20 cm, 0.25 cm, 0.30 cm, 0.35 cm, 0.40 cm. Dynamic viscosity of air at 15°C, µ = 1.81×10–5 Pa-s 3. Methodology i. On the basis of above parameters, We want to find out shear stress near wall by using Newton's law of viscosity, Given as : wall =        du dy wall ii. The velocity gradient which is first order differential equation is discretised by using Finite difference approach. iii FDM for 1st order accuracy i.e. forward, reward and central difference approaches are used to discretise the equation. The expressions are as given below[1,5]: 1    , i, j– + O( y) i ju uu dy y Forward     , i, j – 1– + O( y) i ju uu dy y Reward 1 2     , i, j – 1– + O( y) * i ju uu dy y Central iv FDM for 2nd order accuracy i.e. forward, reward/backward & central difference approaches are used to discretise the equation[6]. The expressions are as given below:- 2 3 2     , i, j + 1 , 2 + 4* – * + O( y ) * i j i ju u uu dy y Forward 23 2     , i, j – 1 , 2 * – 4* + O( y ) * i j i ju u uu dy y Reward 2 1 24 4       , i, j + 1 , , – 2 – + 4* – * + O( y ) * i j i j i ju u u uu dy y Central v. FDM for 3rd order accuracy i.e. forward, reward/backward & central difference approaches are used to discretise the equation[7, 8]. The expressions are as given below : 3 13 18 11 6      , i, j + 2 , , 3 * + 9* * – * + ( y ) * i j i j i ju u u uu dy y Forward 2 311 9 2 6     , i, j –1 , – , – 3 * – 18* * – * + ( y ) * i j i j i ju u u uu dy y Reward 3 1 1 2 32 18 18 9 2 12         , i, j +2 , , , , – 3 * – 9* * – * * – * + O( y ) * i j i j i j i j i ju u u u u uu dy y Central vi The approximate solution of equation is compared with exact solution at (y=.35) for different step sizes (y) i.e. 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40. vii The effect of order of accuracy on solution has been also observed. The order of accuracy is taken as O(y), O(y)2, O(y)3 for FORWARD, BACKWARD/REWARD & CENTRAL difference method. viii The errors are also represented in graph for different step sizes and order of accuracy.

34. 144 Hasan Shamim, Shadab Ahmad and Shah Alam 4. Result Table 1. Errors in forward difference approach for 1st, 2nd & 3rd order of accuracy S.l. No. Step size Error (%) Error (%) Error (%) O(Y) O(Y)2 O(Y)3 1 0.1 1.65 0.04 0.001 2 0.15 2.46 0.08 0.003 3 0.2 3.26 0.14 0.007 4 0.25 4.05 0.22 0.013 5 0.3 4.84 0.31 0.022 6 0.35 5.61 0.42 0.035 7 0.4 6.38 0.54 0.051 Table 2. Errors in reward difference approach for 1st, 2nd & 3rd order of accuracy S.l. No. Step size Error (%) Error (%) Error (%) O(Y) O(Y)2 O(Y)3 1 0.1 -1.69 0.04 -0.001 2 0.15 -2.54 0.09 -0.003 3 0.2 -3.41 0.16 -0.008 4 0.25 -4.28 0.25 -0.016 5 0.3 -5.17 0.36 -0.028 6 0.35 -6.07 0.50 -0.046 7 0.4 -6.97 0.66 -0.070 Table 3. Errors in central difference approach for 1st, 2nd & 3rd order of accuracy S.l. No. Step size Error (%) Error (%) Error (%) O(Y) O(Y)2 O(Y)3 1 0.1 -0.02 0.04 -3.70E-05 2 0.15 -0.04 0.08 -1.88E-04 3 0.2 -0.07 0.15 -5.94E-04 4 0.25 -0.12 0.23 -1.45E-03 5 0.3 -0.17 0.33 -3.01E-03 6 0.35 -0.23 0.46 -5.58E-03 7 0.4 -0.30 0.60 -9.54E-03 Table 1. 1st order accuracy for forward, reward and central difference accuracy S.l. No. Step size Error (%) Error (%) Error (%) forward reward central 1 0.1 1.65 -1.69 -0.02 2 0.15 2.46 -2.54 -0.04 3 0.2 3.26 -3.41 -0.07 4 0.25 4.05 -4.28 -0.12 5 0.3 4.84 -5.17 -0.17 6 0.35 5.61 -6.07 -0.23 7 0.4 6.38 -6.97 -0.30

35. Study of CFD approach to discretise first derivative of partial differential equation 145 Fig. 2. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y)2 Table 2. 2nd order accuracy for forward, reward and central difference approach S.l. No. Step size Error (%) Error (%) Error (%) forward reward central 1 0.1 0.04 0.04 0.04 2 0.15 0.08 0.09 0.08 3 0.2 0.14 0.16 0.15 4 0.25 0.22 0.25 0.23 5 0.3 0.31 0.36 0.33 6 0.35 0.42 0.50 0.46 7 0.4 0.54 0.66 0.60 Fig. 1. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y) ERROR(%)ERROR(%)

36. 146 Hasan Shamim, Shadab Ahmad and Shah Alam Table 3. 3rd order accuracy for forward, reward and central difference approach S.l. No. Step size Error (%) Error (%) Error (%) forward reward central 1 0.1 0.001 -0.001 -3.70E-05 2 0.15 0.003 -0.003 -1.88E-04 3 0.2 0.007 -0.008 -5.94E-04 4 0.25 0.013 -0.016 -1.45E-03 5 0.3 0.022 -0.028 -3.01E-03 6 0.35 0.035 -0.046 -5.58E-03 7 0.4 0.051 -0.070 -9.54E-03 Fig. 3. Errors in forward (series 1), reward (series 2) and central (series3) approach using O( y)3 ERROR(%) 5. Conclusion  The effect of grid spacing and order of accuracy has been observed by calculating shear stress.  It is found the central difference approach has least error for fix step size compare to forward and backward difference approach.  Higher order of accuracy has least error in each approach. References [1] Anderson D. John, "Computational Fluid Dynamics: Basic with applications" Tata McGraw Hill, (2012). [2] Versteeg H. K. and Weeratunge Malalasekera, "An Introduction to Computational Fluid Dynamics" (2007). [3] Ferziger J.H. and Peric M., Computational Methods for Fluid Dynamics. Springer, (1996). [4] Hirsch C., Numerical Computation of Internal and External Flows. John Wiley & Sons, Chichester, I & II, (1990). [5] Wesseling P., Principles of Computational Fluid Dynamics. Springer, (2001). [6] Donea J. and Huerta A., Finite Element Methods for Flow Problems. John Wiley & Sons, (2003). [7] Ohner R.L., Applied CFD Techniques: An Introduction Based on Finite Element Methods. John Wiley & Sons, (2001). [8] Cuvelier C., Segal A. and Van Steenhoven A.A., Finite Element Methods and Navier- Stokes Equations. Kluwer, (1986). [9] CFD-Wiki http://www.cfd-online.com/Wiki/ Main Page.

37. Thermal design of liquid cooled charge air cooler: A computational approach 147 Thermal design of liquid cooled charge air cooler: A computational approach TRIBHUWAN CHANDRA JOSHI* and YOGENDRA SINGH KUSHWAH Subros Technical Centre, India *E-mail: tribhuwan.joshi@subros.com Abstract Successive advent of vehicle emissions norms & strong emphasis on fuel efficiency have enforced vehicle manufactures to deploy turbo charging of intake air prior to intake manifold. However introduction of turbochargers also signify need of a heat exchanger called charge air cooler or intercooler to reduce the temperature of turbocharged air to optimum limit prior to intake manifold of engine. The major limitation of conventional air to air charge air coolers is that they yield low heat transfer rate to weight ratio & low heat transfer rate to frontal area ratio characteristics. Beside this at higher boost pressure and higher temperature conditions there are metallurgical challenges for conventional air to air charge air coolers. Therefore; design optimization aimed at improved heat transfer from charge air is the need of strict environmental norms (Euro V onward). Rapid growth of automobile sector coupled with cutting edge technology development is also leading demand for highly efficient as well as compact solutions for charge air cooler. This provide motivation and challenge to design highly optimized new technology based system, which can provide increased rate of heat transfer with lesser pressure drop & overall compact size. To overcome discussed limitations of conventional air to air charge air cooler; the present research explores thermal design of liquid cooled charge air cooling device with unique charge air flow mechanism. The new design of liquid cooled charge air cooler provides multiple flow passes in order to achieve advantages of both cross flow as well as counter flow type heat exchangers. Multiple flow passes basically ensure maximum interaction of two heat exchanging fluids; hence heat exchanger effectiveness gets improved. Charge air is introduced to the heat exchanger with the help of an inlet tank header. The flow of charge air around the heat exchanger is precisely controlled by a casing, which ensures a uniform guided flow to successive passes of heat exchanger. An outlet tank header serves the purpose of supplying charge air to the engine intake manifold. A Computational Fluid Dynamics (CFD) methodology is used to optimize flow dynamics of two working fluids, namely liquid water and charged air coming out of turbocharger. Key words : Automotive, CFD, Heat Transfer, Liquid Cooled Charge Air Cooler, Radiator, Emission, Turbocharger 1. Introduction With the rapid advancement of emission norms, Turbochargers has become the integral part of engine system these days. It not only helps to reduce the pollutant emissions but also improves the fuel efficiency. Turbochargers are used to compress the ambient air to a certain boost pressure prior to its admission Invertis Journal of Renewable Energy, Vol. 7, No. 3, 2017 ; pp. 147-157 into the intake manifold in internal combustion engines. So by compressing the air in turbocharger, large amount of charge air is being inducted into combustion chamber, So as to improve combustion efficiency along with reduced pollutant emission. However along with the compression, it also raises the temperature of air; which in turns results in decrease in density of combustion air. To overcome this limitation a heat exchanger, DOI No. : 10.5958/2454-7611.2017.00021.2

38. 148 Tribhuwan Chandra Joshi and Yogendra Singh Kushwah commonly known as Charge Air Cooler is being used between turbo-charger and the intake manifold. Wherein high temperature & high pressure air loses its heat to cooling media (air or water). This basically results in increased density of combustion air & ultimately improved combustion/fuel efficiency of vehicle. Further high boost pressure requirements of intake air to meet latest emission norms (Euro V/ Euro VI) has emphasized the need of highly efficient and durable design of heat exchangers. This will ensure increased heat transfer rate along and less charge air side pressure drop & overall compactness. This requirement has enforced the technology developers to explore liquid based charge air cooling instead of traditional air to air charge air coolers. To achieve the aforementioned objective, some work has been done by researchers in the areas of liquid cooled charge air coolers, Lamich et al. [1] has disclosed a cross flow type liquid charge air cooler, where liquid water is flowing in a U flow manner through equally spaced tube banks, whereas charge air flows through inter tube spacing to make a Charge air flow path. Maceroni et al.[2] has disclosed a Liquid cooled charge air cooler directly integrated with Intake manifold, in this arrangement charge air from inlet tank flows through heat exchanger, where it loses its heat with liquid water flowing through heat exchanger tubes. The majority of the work reported in existing literature suggests either straight or U flow type flow arrangement for liquid water, whereas charge air flows through tube banks in the direction normal to tube bank, to form a Cross flow type heat exchanger. Thus better heat transfer characteristics possible with counter flow type arrangements can't be utilized. Hence there is a scope of flow path optimization, So as to achieve advantages of both cross as well as counter flow type arrangements. Present study explores an innovative charge air flow mechanism, to form a cross- counter flow type arrangement[3]. So as to ensure increased heat transfer rate along with comparable charge air side pressure drop and overall heat exchanger compactness. A CFD methodology to evaluate the various performance parameters of heat exchanger is used. Fin Surfaces associated with the heat exchanger has been modeled as a shell region[4], So as to take into account conduction heat transfer though fins. The CFD modeling strategy for heat exchangers has been correlated with test results of baseline liquid to air heat exchanger (radiator configuration) & it has been found that CFD results are in close agreement with test results. In a different study to develop correlation between liquid water temperature and cooling air Anders et al.[5] have also used CFD modeling strategy for estimating the liquid water temperatures at radiator inlet and found that estimated values were within ± 4°C of the experimental data. 2. Theoretical Background Overall heat transfer rate (Q) for heat exchangers can be expressed by equation (1), (2) & (3). Q =  .Cmin. (Tca_in-Tc_in)/3600 (1) Charge Air Side : Qca = mca .Cp_ca . (Tca_in-Tca_out) /3600 (2) Liquid Water Side : Qc = mc .Cp_c . (Tc_in-Tc_out) /3600 (3) In perfect isolated system, heat gained by the cold fluid (liquid) will be equal to heat lost by the hot fluid (charge air). Qc = Qca (4) Where Heat exchanger effectiveness () is defined as the ratio of the actual heat transfer rate (Q) to the maximum possible heat transfer rate (Qmax); and Cmin is minimum of heat capacities of both the fluids:  = Q/Qmax (5) Qmax = Cmin. (Tca_in-Tc_in) (6) Cmin =Min. (mca .Cp_ca, mc .Cp_c) (7) In current study a detailed investigation of various flow configurations & their impact on various design parameters has been discussed. Where : WHX : Weight of heat exchanger (kg) VHX : Heat exchanger volume (m3) W* H* D* fp : Width* Height* Depth* fin pitch (all in mm)

39. Thermal design of liquid cooled charge air cooler: A computational approach 149 Q : Heat rejection capacity (kW) Qc : Liquid water (liquid) side heat rejection capacity (kW) Qca : Charge air side heat rejection capacity (kW)  : Heat exchanger effectiveness mca : Mass flow rate of charge air (kg/h) Va : Flow velocity of cooling air (m/s) Cp_ca : Specific heat of charge air (kJ/kg. K) Ta_in : Cooling air inlet temperature (ºC) Tca_in : Charge air inlet temperature (ºC) Tca_out : Charge air out temperature (ºC) mc : Mass flow rate of liquid water (kg/min) Cp_c : Specific heat of liquid water (kJ/kg. K) Tc_in : Liquid water inlet temperature (ºC) Tc_out : Liquid water out temperature (ºC) (cs) : Heat exchanger Section BC : Boundary conditions Temp. : Temperature (ºC) 3. CFD Modeling This section presents CFD model considered for the analysis, governing assumptions and validation of CFD results with test data. Modeling of Heat exchanger geometry has been done in commercially available preprocessing software called ANSA (Version 15.1.2). A commercial CFD code called Star CCM V 11.04 has been used as a solver and as a post processer. Volume meshing has been carried out in the same software. For the simplicity of the analysis following assumptions has been considered.  Steady state based solver has been considered for both heat exchanging fluids.  Within heat exchanger liquid water side as well as charge air side flow is incompressible.  Liquid water flow rate through heat exchanger tubes is uniformly distributed  Charge air side inlet/outlet headers have been considered as longitudinally extending rectangular ducts. Further size of rectangular duct is defined by available free flow area with various flow configurations.  To take into account effect of change in fluid properties, all the properties specified to the CFD code are based on estimated mean temperature values of hot and cold fluid. 3.1 Heat Exchanger Geometry Modeling & Result Deduction Methodology For the simplification of the analysis & to save the overall computational time, a small section (Fig. 1) of heat exchanger has been modeled. This model consists of geometry of two fins separated apart by a tube. Further both the fins are covered by half tube sections on both the sides. Liquid water flows through both single tube & half tube sections & spacing between tubes forms the flow path for air. Inlet mass flow rate for both the working fluids (i.e. liquid water & air) has been calculated based on overall mass flow rate through the complete heat exchanger. Complete flow length (i.e. tube length for the liquid water side & core depth for the air Side) for both the heat exchanging mediums has been modeled, So as to closely estimate the outlet temperatures for both the fluids leaving the heat exchanger. Fig. 1. Tube, fin Heat Exchanger cut Section for CFD modeling A lot of complexity involved with design of charge air side inlet-outlet headers; which depends on specific packaging space & piping layout associated with turbo charger & air intake manifold, Therefore; in current study charge air inlet and outlet headers for various flow configurations mentioned in section 4, has been considered as rectangular ducts extended from available free flow area for a particular flow configuration (D1-D4). This will ensure uniform flow through inlet headers. As complete flow length of both the fluids being considered in CFD model, hence outlet temperatures for both the fluids calculated from CFD analysis can

40. 150 Tribhuwan Chandra Joshi and Yogendra Singh Kushwah be used for calculating the various performance parameters of complete heat exchanger. 3.2 Solver Numeric & Boundary Condition's Governing momentum and energy equations are Reynolds-averaged Navier-Stokes equations and realizable k- turbulence model with all Y+ wall treatment being used for modeling turbulent nature of flow. All the heat exchanger surfaces, where modeling of wall thickness & subsequently mesh generation was possible have been modeled as a solid. However, in case of fins, where modeling of thickness is not possible; all the fin walls has been modeled as a zero thickness surfaces. Further to take into account heat conduction through fins, three dimensional Shell feature of Star CCM software has been used. Following type of BC specification method has been used for the analysis.  Inlet boundaries for both the fluids have been defined as Mass Flow inlets with associated fluid temperatures.  However outlet boundaries have been defined as Pressure outlets. 3.3 Validation of CFD Approach & Results To validate the CFD modeling strategy, an available reference heat exchanger also called as radiator having certain tube fin configuration has been first tested in calorimeter lab (Fig. 2). CFD results have been extracted for a range of liquid water flow rates with fixed liquid water in temperature. However, cooling air side parameters at the inlet have been kept fixed for all the cases. Typical specifications & Boundary conditions for reference heat exchanger have been specified in Table 1. Fig. 3 shows temperature distribution at the centre plane of the heat exchanger obtained from CFD simulations. From temperature profile it is quite evident that high temperature water is flowing through tubes, whereas cooling air is allowed to flow through inter tube spacing & external fins. Table 1. BC & Corce size specification for radiator sample Radiator Core Air Liquid Flow Liquid Air Velocity (100% Water) Inlet Temp. Inlet Temp. Width : 295 mm; Height : 202.6 mm; Depth : 16 mm; Fin Pitch :2.4 mm 4.5 m/s (40 - 60) kg/min 85 °C 20 °C Fig. 2. Component Calorimeter test setup for radiator testing Fig. 3. Temperature distribution across the HX obtained from CFD The comparisons of CFD results and calorimeter lab have been presented in Fig. 4 & 5. From Fig. 4, it is evident that liquid water out temperature obtained from CFD are in close agreement with calorimeter results. Further liquid water side heat rejection rate (Fig. 5) calculated from CFD results are closely matching with test results with an accuracy of ± 5 %.

41. Thermal design of liquid cooled charge air cooler: A computational approach 151 Fig. 4. Liquid water out Temp Vs Liquid water mass flow rate Fig. 6. Single Pass Cross Flow Heat Exchanger Fig. 5. Heat Rejection Capacity Vs Liquid water mass flow rate 4. Investigations of various flow configurations of liquid cooled charge air cooler Based on physics several flow configurations are possible in liquid cooled charge air coolers. To identify the optimum flow configuration following four flow configurations (D1 to D4) has been studied. A "flat-tube & fin" type heat exchanger having core Size of Width 295mm*Height 202.6mm*depth 16mm*fin pitch 2.4 mm, is being considered for all the flow configurations. Further In case of configuration D2, two heat exchanger core's are spaced at a gap of 4 mm. 4.1 Flow Configuration 1 (D1) Fig. 6 shows the flow configuration for single pass cross flow heat exchanger (D1). In this arrangement charge air (fluid 1) enters normal to tube bank, whereas liquid water (fluid 2) is flowing through tubes. 4.2 Flow Configuration 2 (D2) Fig. 7 shows the flow configuration for two banks cross flow heat exchanger (D2). In this arrangement charge air (fluid 1) enters normal to front tube bank and exits through rear tube bank, whereas liquid water (fluid 2) is allowed to flow from rear tube bank first and then it is transferred to front tube bank via intermediate headers. Fig. 7. Two Bank Cross Flow Heat Exchanger 4.3 Flow Configuration 3 (D3) Fig. 8 shows the flow configuration for two pass cross-counter flow heat exchanger (D3). In this arrangement charge air (fluid 1) is being circulated around the tube bank in two numbers of passes. Charge air is first allowed to flow through 50% of

Ijre published paper 7(3), 2017

Ijre published paper 7(3), 2017

Ijre published paper 7(3), 2017

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