Yazar "Afzal, Asif" seçeneğine göre listele
Listeleniyor 1 - 20 / 21
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Battery thermal management of a novel helical channeled cylindrical Li-ion battery with nanofluid and hybrid nanoparticle-enhanced phase change material(Pergamon-Elsevier Science Ltd, 2023) Jilte, Ravindra; Afzal, Asif; Agbulut, Uemit; Shaik, Saboor; Khan, Sher Afghan; Linul, Emanoil; Asif, MohammadElectric vehicles (EVs) have emerged as a viable alternative to Internal Combustion (IC) engine-powered vehicles, and efforts have been directed toward developing EVs that are more reliable and safer to operate. The safe working of EVs necessitates the use of an efficient battery cooling system. In this paper, cooling of cylindrical type Li-ion battery embedded with helical coolant channels is proposed. The effects of nanoparticles on removing heat from the battery cooling system have been investigated for four different nanoparticle concentrations: 0, 2, 5, and 10% of Al2O3 in the base fluid. Two cases of base fluids are considered: phase change material kept in a concentric container surrounding battery volume and coolant water circulated through liquid channels attached to the outer walls of the PCM (phase change material) cylindrical container. This study presented the three configurations (i) base case PCM-WLC: battery cooling system with a cylindrical enclosure filled with RT-42 phase change material. (ii) base case nePCM-WLC: battery cooling system filled with nano-enhanced phase change material. (iii) nePCM-LC: battery cooling system with helical liquid channels and filled with nanoenhanced PCM. The nanofluid was circulated through the liquid passages connected to the PCM container. Results showed using the helical channels, the nePCM-LC arrangement efficiently removes accumulated heat from the phase change material and provides better battery cooling than straight rectangular channel-based BTMS (battery thermal management system).Öğe Blends of scum oil methyl ester, alcohols, silver nanoparticles and the operating conditions affecting the diesel engine performance and emission: an optimization study using Dragon fly algorithm(Springer Heidelberg, 2021) Afzal, Asif; Agbulut, Umit; Soudagar, Manzoore Elahi M.; Razak, R. K. Abdul; Buradi, Abdulrajak; Saleel, C. AhamedThe effect of the addition of different proportions of silver (Ag) nanoparticles and alcohols in milk scum oil methyl ester on the performance of engine and emission are studied. B20 blend is added with 5% of ethanol, n-butanol, and iso-butanol as ternary additives for the experimental analysis from no load to full load. Furthermore, at a fixed load, operating conditions such as injection pressure (12 and 15 bar) and injection timing (23 degrees and 26 degrees) are varied without and with the addition of 0.8 vol% of Ag (silver) nanoparticles to the fuel blends. Also, the concentrations of Ag nanoparticles are increased from 0.2 to 1 vol% and comparisons are made with diesel and B60 blend. Mathematical models are developed for selected features of engine performance which fits with the experimental values for the purpose of optimization using the Dragon fly algorithm (DA) by considering these models as the objective functions. The concentration of nanoparticles lowers the BSFC significantly and helps in reducing the emission with an increased percentage. Using full biodiesel, 16.6% reduction in BTE was obtained, while use of alcohols prevented this reduction approximately by 5%. A highest of 4.6% improvement was obtained with the addition of Ag nanoparticles. 4.5% reduction in HC and 13% in NOx emission using nanoparticles are obtained. The DA algorithm provided the same optimized value at the end of 30 iterations in different cycles of execution. Nanoparticle addition and use of pressure in the range of 20 bar gives the lowest emission from the engine.Öğe A comprehensive review on the usage of the nano-sized particles along with diesel/biofuel blends and their impacts on engine behaviors(Elsevier Ltd, 2023) Gad, Mohammed Sayed; Ağbulut, Ümit; Afzal, Asif; Panchal, H.; Jayaraj, S.; Qasem, N.A.A.; El-Shafay, A. S.Global warming, climate change, air pollution, and harmful exhaust emissions for human health are highly associated with the burning of petroleum fuels at a huge level. In the beginning, biodiesel fuels have been introduced as a promising alternative fuel to mitigate these problems. However, poor atomization, low energy content, high viscosity, and density of biodiesels are the main obstacles to the frequent usage of biodiesel fuels in diesel engines. That is because biodiesel fuels in CI engines have generally resulted in higher fuel consumption, lower thermal efficiency, and higher NOx emission. On the other hand, most fuel researchers recently announced that the addition of nanoparticles in biodiesel blends has led to making biodiesels attractive again by significantly improving their poor biodiesel properties such as thermophysical properties, calorific value, heat transfer rate, evaporation rate, etc. From this point of view, many published papers in the area demonstrated that the addition of nanoparticles in biodiesel blended fuels has simultaneously provided fewer exhaust emissions, better performance, and combustion characteristics thanks to the high catalyst effect of nanoparticles. In the conclusion, the present review paper clearly announced that the addition of nanoparticles is a very strong way to re-improving the worsened engine combustion, performance, and emission characteristics of biodiesel-diesel blends. © 2023 Elsevier LtdÖğe A critical review on renewable battery thermal management system using heat pipes(Springer, 2023) Afzal, Asif; Razak, R. K. Abdul; Samee, A. D. Mohammed; Kumar, Rahul; Agbulut, smit; Park, Sung GoonThe critical review presented here exclusively covers the studies on battery thermal management systems (BTMSs), which utilize heat pipes of different structural designs and operating parameters as a cooling medium. The review paper is divided into five major parts, and each part addresses the role of heat pipes in BTMS categorically. Experimental studies, numerical analyses, combined experimental and numerical investigations, optimum utilization of a phase-change material (PCM) with a heat pipe (HP), oscillating heat pipe (OHP), and micro heat pipes combined with PCM for Li-ion BTMS using heat pipes are presented. The usage of HP's and PCM can keep the temperature of the battery system in the desirable limit for a longer duration compared to other traditional and passive methods. More emphasis is made on how one can achieve a suitable cooling system design and structure, which may tend to enhance the energy density of the batteries, improve thermal performance at maximum and minimum temperature range. Arrangement of battery cells in a pack or module, type of cooling fluid used, heat pipe configuration, type of PCM used, working fluid in a heat pipe, and surrounding environmental conditions are reviewed. According to the study, the battery's effectiveness is significantly influenced by temperature. The usage of flat HPs and heat sink proves to be the best cooling method for keeping the battery working temperature below 50 degrees C and reduces the heat sink thermal resistance by 30%. With an intake temperature of 25 degrees C and a discharge rate of 1 L per minute, an HP that uses water as a coolant is also effective at regulating battery cell temperature and maintaining it below the permissible 55 degrees C range. Using beeswax as a PCM in HPs reduces the temperature of BTMS by up to 26.62 degrees C, while the usage of RT44 in HPs reduces the temperature of BTMS by 33.42 degrees C. The use of fins along with copper spreaders drastically decreases the temperature capability of HPTMS by 11 degrees C. MHPA shows excellent performance in controlling the battery temperature within 40 degrees C. The effective thermal management can be done by incorporating heat pipe alone or by coupling with liquid cooling or metal plate. However, extensive and extended research is required to improve thermal management to safely and effectively use the battery for day-to-day applications.Öğe Effects of high-dosage copper oxide nanoparticles addition in diesel fuel on engine characteristics(Pergamon-Elsevier Science Ltd, 2021) Agbulut, Umit; Saridemir, Suat; Rajak, Upendra; Polat, Fikret; Afzal, Asif; Verma, Tikendra NathThis paper examines the effect of adding high dosage of copper oxide (CuO) nanomaterials (<77 nm) directly to conventional diesel fuel. The performance of the fuel with CuO added is assessed using a single cylinder, naturally aspirated, direct injection, air-cooled diesel engine. Examined were the char-acteristics of combustion and emissions for blends of 1000 and 2000 ppm CuO nanoparticles. The CuO blends were tested in the speed range between 2000 and 3000 rpm at intervals of 250 rpm. The CuO nanoparticles have the potential to accelerate the process of combustion by supplying molecules of oxygen and acting as a catalyst. The CuO enhances the thermal conductivity of the test fuels and in-creases heat dissipation from the combustion chamber. Experimental results show exhaust gas tem-perature (EGT) is reduced as well as unburnt hydro-carbons (HC) and oxides of carbon and nitrogen (CO and NOx). For CuO additions of 1000 and 2000 ppm, CO emissions fell by 14.6% and 20.8%, HC emissions by 6.2% and 13.4%, and NOx emissions by 4%, and 4.7%. Both blends of CuO increased the heating value of the diesel fuel. Brake-specific fuel consumption (BSFC) dropped by 4.5% and 8% while brake thermal efficiency (BTE) increased by 5.5% and 14.6% for 1000-CuO and 2000-CuO, respectively. On the other hand, nanoparticles accelerated the chemical reactions and the ignition delay (ID) period was shortened by 3.03% and 5.45% for CuO additions of 1000, and 2000 ppm, respectively. It was also observed that CuO nanoparticles up to 2000 ppm can be suspended in diesel fuel without clogging the filter on the injection system. (c) 2021 Elsevier Ltd. All rights reserved.Öğe Energetic, exergetic, and thermoeconomic analyses of different nanoparticles-added lubricants in a heat pump water heater(Elsevier, 2022) Yıldız, Gökhan; Ağbulut, Ümit; Gürel, Ali Etem; Ergün, Alper; Afzal, Asif; Saleel, C. AhamedThe heat pumps are frequently used in domestic and industrial applications for hot water supply. The present paper aims to thermodynamically investigate the impacts of the nanoparticle-addition into the lubricants on the energetic, exergetic, and thermoeconomic aspects of a heat pump. In the experiments, air to the water heat pump is separately charged with various metal oxide-based nanoparticles (Al2O3, CuO, and TiO2)-added oils at a constant mass fraction of 0.5%. Polyolester (POE) and 134a are used as a lubricant, and refrigerant, respectively. The mass flow rates of the water passed through the condenser are varied from 10 to 25 g/s with an interval of 5 g/s. In the results, it is observed that the thermal conductivity value noteworthy increases with the presence of nanoparticles in POE. The highest increment in thermal conductivity is found to be 39% for POE + CuO in comparison with that of pure POE. Furthermore, with nanoparticles addition, it is noticed that the COP value generally improves, and the highest improvement for COP value is noticed to be 8% for POE + TiO2 nanolubricant at the mass flow of 25 g/s. Furthermore, exergy efficiency enhances by 3.6%, 1.8%, and 4.5% for POE + Al2O3, POE + CuO, and POE + TiO2, respectively. The lowest heating cost is calculated to be 3.465 c/kWh at 20 g/s flow rate for POE + Al2O3. In conclusion, this paper clearly reports that usage of nanoparticles along with lubricants is presenting better energetic, exergetic, and thermoeconomic results rather than the usage of lubricant alone in the heat pumps.Öğe An enhancement in diesel engine performance, combustion, and emission attributes fueled with Eichhornia crassipes oil and copper oxide nanoparticles at different injection pressures(Taylor & Francis Inc, 2022) Khan, Osama; Khan, Mohd Zaheen; Khan, Emran; Bhatt, Bhupendra Kumar; Afzal, Asif; Ağbulut, Ümit; Shaik, SaboorCurrent scenario of crude oil exhaustion and price rise has motivated researchers to opt and explore other forms of energy which are renewable and sustainable in nature. Waste plant oils have significant potential to become a viable alternative to petro-diesel fuel for transportation and manufacturing purposes. Esterification of unrefined waste oils has significantly addressed the issues mainly occurring due to highly viscous nature of the oil. This analysis aims to conduct a controlled study to examine the impact of injection pressure on the engine parameters amalgamated with copper (III) oxide composites as a nanofuel additive. Biofuel obtained from waste plants (Eichhornia Crassipes) is amalgamated with plain diesel in a 30:70 ratio and copper (III) oxide (Cu2O3) as nano-additive. It is essential to operate the engine over a wide range of injection pressures (180, 200, and 220 bar) for furnishing maximum efficiency when mixed with 90 ppm nano-additive volume fraction. The current analysis shows that the injection of nano-additives raises the injection pressure leads to enhanced engine combustion characteristics, including a maximum peak pressure and a faster heat release rate. At 220 bar, injection pressure with a 90-ppm volumetric fraction of nano-additives yielded superior results in comparison with its counterpart blends. The inclusion of nano-additives for increased injection pressures decreases emissions of hydrocarbon, oxides of nitrogen, and soot particles. Thus, biofuels engines benefit by enhanced injection pressure and decreased emission levels by successfully amalgamating copper (III) oxide as nano-additives. Combined effect of high pressure and nano-additive fuel furnishes a maximal progression of 3.5% in combustion efficacy and a 14% drop in BSEC with reduction of 14% in HC, 15% in NOx, and 15% in smoke.Öğe Exergy, sustainability and performance analysis of ground source direct evaporative cooling system(Elsevier, 2022) Yıldız, Gökhan; Ergun, Alper; Gürel, Ali Etem; Ceylan, İlhan; Ağbulut, Ümit; Eser, Servet; Afzal, AsifA significant portion of global energy consumption is due to energy consumption in the buildings. Heating, cooling, and air conditioning systems have the largest share in this energy consumption. Evaporative cooling systems, which have the advantage of being economical, zero pollution, and easy maintenance are preferred to reduce energy consumption in buildings. These systems are used in many areas such as greenhouses, broiler houses, and warehouses. In this study, analyzes of exergy, sustainability, and cooling efficiency in four different situations of a ground source direct evaporative cooling system were made. The system was studied in four different cases. While the highest exergy efficiency was obtained in case 3 with 20.83%, the exergy efficiencies in other cases were obtained as 16.83%, 17.49%, and 18.36%, respectively. In addition, the highest specific exergy loss was determined as 100.51 J/kg in case 2, while it was calculated as 73.08 J/ kg, 80.23 J/kg, and 73.05 J/kg for the other cases, respectively. It is seen that the sustainability values are in parallel with the exergy efficiency when the evaporative cooling system is examined for four different cases. The sustainability values were determined as 1.20 for case 1, 1.21 for case 2, 1.26 for case 3, and 1.22 for case 4. It is determined that the exergy efficiency gives precise information about the usability and sustainability of the system when these situations are evaluated. The exergetic improvement potential (EIP) was determined as 0.061 for case 1, 0.082 for case 2, 0.063 for case 3, and 0.059 for case 4, respectively. Although the highest exergy efficiency is obtained in case 3, it has a higher recovery potential than case 1 and case 4. In addition, cooling efficiencies for four different cases were obtained as 33.70%, 34.81%, 41.69%, and 36.95%, respectively. The temperature differences between the room and ambient temperatures were determined as 1.45 degrees C, 1.21 degrees C, 1.6 degrees C, and 1.48 degrees C for each case, respectively.Öğe Experimental and numerical assessment of the rotary bed reactor for fuel-processing and evaluation of produced oil usability as fuel substitute(Elsevier, 2022) Gad, Mohammed Sayed; Ağbulut, Ümit; El-Shafay, A. S.; Panchal, Hitesh; Emara, Kareem; Al-Mdallal, Qasem M.; Afzal, AsifIn current work, waste tires recycling using pyrolysis was performed inside a rotary bed reactor without oxygen-producing oil, black carbon, and synthetic gas. In that respect, CFD analysis was applied using ANSYS software to design the reactor and test its material resistance to the temperature rise. Thermal and mechanical stresses were evaluated to find an acceptable reactor design. Pyrolysis of tires to oil was performed at a temperature of 420 degrees C. Tire and diesel oils blends of 5, 10, and 20% volume percentages were prepared for experimentation. Tire oil blends properties were close to crude diesel. Characteristics of combustion, performance and emissions of diesel engines that used tire oil blends were investigated compared to crude diesel. The thermal efficiency maximum decrease of TO20 was 21% in comparison to pure diesel. The maximum increases in CO, smoke, and HC emissions of TO20 were 35, 20, and 25% compared to diesel fuel, respectively. The highest decline in NOx emission of TO20 was 19% related to crude diesel fuel. Oil blends achieved the higher peak cylinder pressures about diesel fuel. In conclusion, lower volume percentages of up to 20% of tire and diesel oil blends are recommended to be used without any engine modifications.Öğe Hydrogen and dual fuel mode performing in engine with different combustion chamber shapes: Modelling and analysis using RSM-ANN technique(Elsevier Ltd, 2022) Khandal, Sanjeevakumar Veerasangappa; Razak, A.; Veza, I.; Afzal, Asif; Alwetaishi, Mamdooh; Shaik, S.; Ağbulut, ÜmitThis study investigates the impacts of hydrogen (H2) induction along with injected liquid honne biodiesel (BHO)/uppage biodiesel (BUO) as secondary pilot fuel in diesel engine. The effects of compression ratio (CR), hydrogen fuel flow rate (HFR) and different combustion chamber shapes in dual fuel (DF) mode were investigated. In the first phase of experiments, the effects of three different CR (15.5, 16.5, and 17.5) on engine efficacy and emission were presented. In the second phase, the effects of three HFR (0.1, 0.17, and 0.24 kg/h) on engine efficacy and emission, as well as the maximum possible HFR were reported. In the last phase, performance with different combustion chambers i.e., Hemispherical Combustion Chamber (HCC), Toroidal Reentrant Combustion Chamber (TRCC), and Toroidal Combustion Chamber (TCC) at maximum possible CR and HFR was highlighted. The study revealed that for knock free operation of the DF engine, the highest probable HFR was 0.24 kg/h at a CR of 17.5, fuel IT of 27obefore top dead center (bTDC) and injector opening pressure (IOP) of 250 bar. The toroidal re-entrant combustion chamber (TRCC) shape yielded 8%–12% better brake thermal efficiency (BTE) with lower emissions but 20–29% higher oxides of nitrogen (NOx) at 80% load in DF mode as contrasted to the single CI mode. Both peak pressure (PP) and heat release rate (HRR) were 12–15% higher. Response surface methodology (RSM) was used to design the experiments and to carry the optimization process. Artificial Neural Network (ANN) was used to forecast the performance and emission behaviors of the test engine. The findings demonstrated that RSM and ANN were excellent modelling techniques with good accuracy. In addition, ANN's prediction performance (R2 = 0.975 for BTE) was somewhat better than RSM's (R2 = 0.974 for BTE). Both the techniques were found to be successful in terms of agreement with experimental findings with ratios varying from 95% to 98% respectively. The prediction of BTE and NOx was also carried using different machine learning algorithms. It can be seen that R2 value for these models were slightly lower than ANN and RSM models indicating good predicting capability of ANN modelling. © 2022 Hydrogen Energy Publications LLCÖğe Impact of injector nozzle diameter and hole number on performance and emission characteristics of CI engine powered by nanoparticles(Springer, 2022) Kothiwale, G. R.; Akkoli, K. M.; Doddamani, B. M.; Kattimani, S. S.; Ağbulut, Ümit; Afzal, Asif; Kaladgi, A. R.To have energy sustainability and reduce emissions, it is essential to use alternative fuels in IC engines and improve their performance by using fuel combinations. In diesel engines, the fuel atomization process strongly affects combustion and emissions. The injector hole number of a fuel injector nozzle also plays a critical role in influencing the performance and emissions of diesel engines and is an important part of the diesel engine. In general, both parameters affect the spray parameters like droplet size and penetration length and thus the combustion process. In the present work, different injectors (4-hole injector with a nozzle diameter of 0.25 mm, 3-hole injector with a nozzle diameter of 0.20 mm) are used to study the performance and emissions characteristics of DI-CI diesel engine fuelled with a blend of Multi-Walled Carbon Nanotubes and Tallow Oil Methyl Ester. Multi-Walled Carbon Nanotubes were doped at 5, 10, 15, and 20 ppm into the test fuels. The experimental results revealed that the brake thermal efficiency of the engine slightly decreases when the engine is fueled by completely TOME biodiesel. Then the addition of Multi-Walled Carbon Nanotubes into the diesel-Tallow oil biodiesel blend improves the BTE. Furthermore, Multi-Walled Carbon Nanotubes lead to a noteworthy reduction in exhaust pollutants. Accordingly, all emissions (CO, HC, NOx, and smoke) were reduced with Multi-Walled Carbon Nanotubes in the test fuels thanks to the high surface area to volume ratio, higher energy content, catalyst role, accelerating chemical reactions, and oxidization of more unburnt fuels. Diesel-biodiesel blend with 20 ppm Multi-Walled Carbon Nanotubes exhibits superior performance and emissions characteristics among all blends. The BTE of the B40D60C20 blend was almost equivalent to that of diesel and has nearly equal emissions levels compared to diesel fuel under full and part load conditions. The B40D60C20 blend showed a maximum BTE of 30.9% which is 15.53% higher than raw TOME and 3.43% lower than diesel fuel. In addition to that, the blend B40D60C20 showed a significant reduction in CO emissions by 45.46%, HC by 17.29%, NOx by 15.25%, and smoke by 21.28% compared to the raw TOME. Therefore, the optimized fuel blend is B40D60C20 with a dose level of 20 mg/L, where a reasonable improvement in performance and emissions characteristics has been achieved. Additionally, a smaller nozzle diameter for injectors leads to better injection characteristics and a small size for atomized fuel droplets. Accordingly, better results in terms of engine performance and emissions characteristics are achieved for the injector having three-hole with a diameter of 0.20 mm. The optimized fuel combinations with the optimized nozzle geometry will lead to better IC engine performance. The response surface methodology and artificial neural network outcomes demonstrated that these two are excellent modelling techniques, with good accuracy. In addition, the artificial neural network's prediction performance was somewhat better than the response surface methodology.Öğe Influences of hydrogen addition from different dual-fuel modes on engine behaviors(Wiley, 2022) Khandal, Sanjeevakumar Veerasangappa; Ağbulut, Ümit; Afzal, Asif; Sharifpur, Mohsen; Abdul Razak, Kaladgi; Khalilpoor, NimaCompression ignition (CI) engines have good performance but more exhaust emissions. Dual fuel (DF) engines have better performance and lower emissions compared to CI mode. Also, the scarcity of fossil fuels made the researchers to find alternative fuels to power CI engines. Therefore, the present work aims to use hydrogen (H-2) and honne oil biodiesel (BHO) to investigate the performance of CI engines in DF mode. Also, it aims to compare the performance of CI engines in various DF modes, namely induction, manifold injection, and port injection. First, the CI engine was fuelled completely by diesel fuel and BHO. The data were gathered when the engine ran at a constant engine speed of 1500 rpm and at 80% load. Second, the CI engine was operated in various DF modes and data were generated. CI engine operation in DF mode was smooth with biodiesel and H-2. The brake thermal efficiency (BTE) of 32% and 31.1% was reported with diesel and biodiesel, respectively, for manifold injection due to low energy content and high viscosity of biodiesel. These values were higher than CI mode and other DF modes. Fuel substitution percentage for DF manifold injection was 60% and 57% with diesel and biodiesel, respectively. Smoke, hydrocarbon (HC), and carbon monoxide (CO) emissions were lower than conventional mode, but a reverse trend was observed for oxides of nitrogen (NOx) emissions. Heat release rate (HRR) and peak pressure (PP) were higher than conventional mode due to the fast combustion rate of hydrogen. The shortest ignition delay (ID) period was noticed for traditional diesel fuel, but it was longer for BHO biodiesel due to its higher viscosity and lower cetane number. On the contrary, the presence of hydrogen led to an increment in the combustion duration (CD) owing to the scarcity of oxygen in CD. Consequently, the paper clearly showed that the injection way of hydrogen plays a respectable role in the engine characteristics.Öğe Integrated Taguchi-GRA-RSM optimization and ANN modelling of thermal performance of zinc oxide nanofluids in an automobile radiator(Elsevier, 2021) Kaladgi, Abdul Razak; Afzal, Asif; Manokar, A. Muthu; Thakur, Deepak; Agbulut, Umit; Alshahrani, Saad; Subbiah, RamImpact of different input variables on the thermal performance features of an automobile radiator was investigated, statistically analyzed, and optimized using the powerful technique-Taguchi's grey relational analysis (GRA) and Response surface methodology (RSM). Polyethylene glycol (PEG) nanofluids containing ZnO nanoparticles of various volume concentrations (0.2%-0.6%) were used. 1-Butyl 3-methylimidazolium bromide [C4mim][Br] ionic liquid was added to reduce particle accumulation and increase nanofluid dispersion. The mini radiator used was an unmixed crossflow type. The analyses were carried out at various flow rates. Thermal performance parameters like Nusselt number (Nu), heat transfer coefficient (htc), pressure drop, and pumping power were optimized by using weighted grey relational grade, depending on the experiments designed using Taguchi's Experiment Design. ANN modelling was used to get a better prediction of the non-linear form of critical data. Optimized Nu, htc, pressure drop, and pumping power were obtained for different combination of Re, air velocity, and nanofluid concentration to maximize. The htc estimated by ANN is found to be reasonably consistent with the experimental findings. From the research findings, it is also inferred that heat transfer enhancement does occur in radiators employing nanofluids but at the expense of the pressure drop and pumping power.Öğe Melting numerical simulation of hydrated salt phase change material in thermal management of cylindrical battery cells using enthalpy-porosity model(Elsevier, 2023) Afzal, Asif; Jilte, Ravindra; Samee, Mohammed; Agbulut, Umit; Shaik, Saboor; Park, Sung Goon; Alwetaishi, MamdoohBattery thermal management using different cooling techniques is rapidly growing. Understanding the proper cooling and melting process when phase change materials (PCM) are used is of prime importance in this area. Hence, a transient thermal-fluid and melting process of hydrated salt PCM enclosed in a battery module with six cylindrical cells is numerically investigated to understand the melting process of the PCM. Four structural models S1, S2, S3, and S4 are constructed for the present numerical simulation. The battery cell wall is kept at a constant temperature of 35celcius, while the rectangular enclosure walls are assumed to be insulated. A finite volume scheme -based CFD (computational fluid dynamics) software is used to simulate the melting process of hydrated salt PCM. In order to capture the phase change phenomenon from solid to liquid, an enthalpy-porosity equation is solved. The temporal temperature distribution, liquid fraction, velocity and enthalpy are analyzed. The results obtained by the numerical computation suggest that the battery cell arrangement used in S1 and S2 model at the initial time step gives better space for temperature distribution and liquid fraction up to the time step of 420 s, while S3 and S4 model after a time interval of 420 s provide better scope for temperature distribution and complete melting of hydrated PCM.Öğe Modifying diesel fuel with nanoparticles of zinc oxide to investigate its influences on engine behaviors(Elsevier Sci Ltd, 2023) Rajak, Upendra; Reddy, V. Nageswara; Agbulur, Umit; Saridemir, Suat; Afzal, Asif; Verma, Tikendra NathIn this paper, we used experimental and numerical methods to explore the effects of a diesel fuel blend con-taining zinc oxide (ZnO) nanoparticles at three different concentrations (0.025%, 0.05%, and 0.1%) on the combustion, injection, performance, and emission characteristics of a diesel engine running at constant speeds of 2000 rpm, 2250 rpm, 2500 rpm, 2750 rpm, and 3000 rpm, with the engine operating at full load. The results of the experiments demonstrate that DF + 0.1% ZnO increases BTE by 11.7% at 2500 rpm, while decreasing SFC by 1.67%, exhaust gas temperature by 11.4%, and NOx emissions by 10.67%. The advanced injection time and load were kept same, but a 2.3% rise in cylinder pressure was achieved when ZnO nano additions to diesel fuel were used. Moreover, CO2 emissions were reduced by 7.6% compared to 2500 rpm. In conclusion, the results prove that the nanoparticle-added test fuels improve engine efficiency, and combustion yield by reducing exhaust pollutants, and the numerical results are in good agreement with the experimental results.Öğe Optimization of Thermal and Structural Design in Lithium-Ion Batteries to Obtain Energy Efficient Battery Thermal Management System (BTMS): A Critical Review(Springer, 2021) Fayaz, H.; Afzal, Asif; Samee, A. D. Mohammed; Soudagar, Manzoore Elahi M.; Akram, Naveed; Mujtaba, M. A.; Saleel, C. AhamedCovid-19 has given one positive perspective to look at our planet earth in terms of reducing the air and noise pollution thus improving the environmental conditions globally. This positive outcome of pandemic has given the indication that the future of energy belong to green energy and one of the emerging source of green energy is Lithium-ion batteries (LIBs). LIBs are the backbone of the electric vehicles but there are some major issues faced by the them like poor thermal performance, thermal runaway, fire hazards and faster rate of discharge under low and high temperature environment,. Therefore to overcome these problems most of the researchers have come up with new methods of controlling and maintaining the overall thermal performance of the LIBs. The present review paper mainly is focused on optimization of thermal and structural design parameters of the LIBs under different BTMSs. The optimized BTMS generally demonstrated in this paper are maximum temperature of battery cell, battery pack or battery module, temperature uniformity, maximum or average temperature difference, inlet temperature of coolant, flow velocity, and pressure drop. Whereas the major structural design optimization parameters highlighted in this paper are type of flow channel, number of channels, length of channel, diameter of channel, cell to cell spacing, inlet and outlet plenum angle and arrangement of channels. These optimized parameters investigated under different BTMS heads such as air, PCM (phase change material), mini-channel, heat pipe, and water cooling are reported profoundly in this review article. The data are categorized and the results of the recent studies are summarized for each method. Critical review on use of various optimization algorithms (like ant colony, genetic, particle swarm, response surface, NSGA-II, etc.) for design parameter optimization are presented and categorized for different BTMS to boost their objectives. The single objective optimization techniques helps in obtaining the optimal value of important design parameters related to the thermal performance of battery cooling systems. Finally, multi-objective optimization technique is also discussed to get an idea of how to get the trade-off between the various conflicting parameters of interest such as energy, cost, pressure drop, size, arrangement, etc. which is related to minimization and thermal efficiency/performance of the battery system related to maximization. This review will be very helpful for researchers working with an objective of improving the thermal performance and life span of the LIBs.Öğe Poultry fat biodiesel as a fuel substitute in diesel-ethanol blends for DI-CI engine: Experimental, modeling and optimization(Elsevier Ltd, 2023) N., Santhosh; Afzal, Asif; V., Srikanth H.; Ağbulut, Ümit; Alahmadi, Ahmad Aziz; Gowda, Ashwin C.; Alwetaishi, MamdoohThe purpose of the present study is to evolve an alternate non-edible source for the synthesis of biodiesel and use it as a fuel substitute in diesel-ethanol blends for DI-CI engines. The use of discarded poultry fat feedstocks for the sustainable production of biofuels in the current day scenario is a novel approach that is still in its embryonic stage. For the effective utilization of these processed biofuels, it is very much required to ascertain the characteristics and their performance attributes for different blends. In this regard, a set of experiments are planned to study the emission and performance attributes of a direct injection (DI) diesel engine operating on poultry fat biodiesel, and the three proportions of diesel-biodiesel-ethanol blends with varying vol. % over the wide load range on a diesel engine. The ethanol percentage in the blend is varied from 5 vol % to 15 vol % in increments of 5 vol % with the amount of poultry fat-based biodiesel kept constant at 10 vol %. The performance and emission characteristics, particularly, the CO, CO2, NOx, unused Oxygen, and hydrocarbon emissions are experimentally determined for different fuel blends. From the results, it is evident that the performance characteristics of the fuel blends improve with the addition of ethanol in the diesel-biodiesel blend. Further, regression modeling of the performance characteristics is carried out to optimize the blend and operating load conditions, and the regression model is evolved for developing a mathematical relation for predictions of the results for different operating conditions. Also, Artificial Neural Network (ANN) modeling of the performance characteristics is carried out at each stage to predict the outcomes for different blends and load conditions and provide a set of empirical relations for analyzing the performance characteristics of the engines operating on poultry fat-based biodiesel-diesel-ethanol blends. Excellent predictions are obtained using regression modeling and ANN with R-squared values above 0.9. Thus, the present work provides a newer model of effectively using the ANN for the systematic study of the performance characteristics of the biodiesel blends obtained from a set of experiments through various optimization methods for better performance and a significant reduction in emissions. © 2023 Elsevier LtdÖğe Single- and combined-source typical metrological year solar energy data modelling(Springer, 2023) Afzal, Asif; Buradi, Abdulrajak; Alwetaishi, Mamdooh; Agbulut, Umit; Kim, Boyoung; Kim, Hyun-Goo; Park, Sung GoonPrediction of solar energy data is very crucial for the effective utilization of freely available renewable energy abundantly in nature. Solar energy data are widely available which must be carefully prepared and arranged for modelling. In this work, typical meteorological year (TMY) data made available by the Korea institute of energy research (KIER) and the National renewable energy laboratory (NREL) are used for modelling in different phases. TMY data at single-point location and multiple locations from KIER are initially used for training of machine learning (ML) algorithms. Later, the TMY data from NREL and KIER are combined and then modelled using radius nearest neighbour (RNN), decision tree regressor (DTR), random forest regressor (RFR), and X-gradient boosting (XGB) algorithms. The solar energy parameters modelled in this work are dew point temperature (DPT), dry bulb temperature (DBT), relative humidity (RH), surface pressure (SP), windspeed (WS), and solar insolation of horizontal plane (IHP). Quantitative analysis of the algorithms is also performed in each stage of the work. The modelling indicates that the DBT, DPT, RH, and SP are able to be predicted with a minimum accuracy of over 90% in each stage. The WS and IHP data when modelled from a single-source TMY data provide superior accuracy than when they are combined. RFR and XGB have outperformed overall as they provide good accuracy for WS and IHP data as well. RNN and DTR achieved 100% accuracy in training, while RFR and XGB showed slightly lower training accuracy due to their avoidance of overfitting. There are errors in testing for RNN/DTR. Using RNN/DTR, the training errors are 0% in all cases, while in some cases like DTP the error by RFR/XGB up to 3%, whereas RNN/DTR testing errors go up to 5% and in case of RFR/XGB they are up to 7.5%. For RH modelling RFR/XGB, training errors are max 6%. RNN/DTR testing errors go up to 11%, while for RFR/XGB up to 7.5% which indicates their robustness. It is observed that many solar parameters, when combined with different source data, can be predicted easily with good accuracy, while WS and IHP become a little bit challenging to model.Öğe A study on a milk chiller latent storage system with phase change material encapsulated spherical balls(Elsevier Ltd, 2023) Jilte, Ravindra; Afzal, Asif; Ağbulut, Ümit; Alahmadi, Ahmad Aziz; Alwetaishi, Mamdooh; Alzaed, Ali NasserFor dispersed or remotely located families, the collection of raw milk takes place less frequently or transportation to the nearest center is not feasible. It requires chilling of collected milk from udder temperature (?35 °C) to storage temperature (?4 °C) and maintaining it throughout thus it demands running chilling at the discrete locations. In this study, a novel design of a milk chiller for coolness storage of 12/24 h based on phase change material is presented. System performance has been demonstrated following the prevailing practice of milk collection and loading/unloading of milk. By switching off the refrigeration after a certain interval, the coolness storage was demonstrated to meet the chilling conditions even during the non-availability of power. The study proposes an integrated portable mobile milk chilling system that can move between solar PV plants and the nearest electric grid during non-sunny days. The proposed milk chiller latent storage system (MC-LSS) contains three major components: a helical coil for refrigerant circulation during charging of the system, spherical capsules for encapsulating phase change materials and interspaced occupied brine solution for storing coolness and circulating throughout PCM-filled capsules. MC-LSS is tested under two cases: FLS-12(first loading of milk chiller and storage for 12 h) and SLS-12 (second loading of milk and storage for 12 h). The temperature history of the Milk chiller latent storage system for the FLS-12 h case is qualitatively analyzed which shows an appreciable reduction in milk temperature around 10–15 °C within the first 20 min and in another ?40 min of further cooling, milk temperature attains the desired storage temperature (4–5 °C). © 2023 Elsevier LtdÖğe Synthesis of graphene oxide nanoparticles and the influences of their usage as fuel additives on CI engine behaviors(Pergamon-Elsevier Science Ltd, 2022) Ağbulut, Ümit; Elibol, Erdem; Demirci, Tuna; Sarıdemir, Suat; Gürel, Ali Etem; Rajak, Upendra; Afzal, AsifThe present paper aims to investigate the synthesis of graphene oxide (GO) nanoparticles, and the comprehensive investigation of their use along with the waste cooking oil methyl ester (WCO) and diesel fuel blend on combustion, injection, performance, and emission characteristics of a diesel engine under varying engine loads from 3 to 12 Nm with the gaps of 3 Nm at a fixed speed of 2400 rpm. The test fuels named B0 (completely neat diesel fuel), B15 (85% diesel and 15% WCO), B15 + 100 ppm GO (B15 and 100 ppm GO), B15 + 500 ppm GO (B15 and 500 ppm GO), B15 + 1000 ppm GO (B15 and 1000 ppm GO). In the results, it is noticed that blending of biodiesel into conventional diesel fuel drops the brake thermal efficiency (BTE) by 2.67%, CO by 7.5%, HC emissions by 8.53%, and increases the brake specific fuel consumption (BSFC) by 5.54%, and NOx emissions by 3.37% compared to those of reference-fuel B0. However, nanoparticle-added test fuels exhibit a respectable enhancement in all performance and emission characteristics. With the addition of GO nanoparticles, BTE increases by 7.90%, and BSFC drops by 9.72% due to the improved energy content of test fuels. On the other hand, NOx is pulled back by 15.17% due to both superior surface to volume area ratio and thermal properties of GO nanoparticles. Moreover, GO nanoparticles act as the oxygen buffer, and catalyst the chemical reactions until the combustion process. Accordingly, GO ensures more complete combustion, and therefore reduces CO emission by 22.5% and HC emission by 30.23%. In the conclusion, the present paper declares that GO nanoparticles can give a satisfying solution to improve the worsened characteristics arising from bio-diesel and diesel binary blends in CI engines. (c) 2021 Elsevier Ltd. All rights reserved.
