The ability of an artificial neural network model, using a back propagation learning algorithm, t... more The ability of an artificial neural network model, using a back propagation learning algorithm, to predict specific fuel consumption and exhaust temperature of a Diesel engine for various injection timings is studied. The proposed new model is compared with experimental results. The comparison showed that the consistence between experimental and the network results are achieved by a mean absolute relative
In the recent years, the studies on hybrid electric vehicles have been increased in automotive in... more In the recent years, the studies on hybrid electric vehicles have been increased in automotive industry. Particularly, the studies focused on passenger cars. However, the studies conducted on Non-Automotive Vehicle (Vehicles not suitable for standard driving cycles) are not adequate. Additionally, the current driving cycles are not appropriate to simulate these vehicles. In this work, a series hybrid electric street sweeper is modeled and simulated by using AVL Cruise. This study aims that performing a series hybrid electric vehicle simulation and presenting its fuel consumption, vehicle performance and exhaust emissions theoretically. An appropriate driving cycle was constructed by using Random Cycle Generator of AVL Cruise in terms of velocity and functionality. The simulations were performed depending on this driving cycle. Vehicle block diagrams were created in software and the connections of vehicle such as mechanical, electrical and informational were demonstrated. Consequentl...
Engine tests are both costly and time consuming in developing a new internal combustion engine. T... more Engine tests are both costly and time consuming in developing a new internal combustion engine. Therefore, it is of great importance to predict engine characteristics with high accuracy using artificial intelligence. Thus, it is possible to reduce engine testing costs and speed up the engine development process. Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples. The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition (HCCI) engine for various excess air coefficients by using Deep Neural Network, which is one of the Deep Learning methods and is based on the Artificial Neural Network (ANN). The Deep Learning results were compared with the ANN and experimental results. The results show that the difference between experimental and the Deep Neural Network (DNN) results were less than 1%. The best r...
The shell-and-tube type heat exchangers have long been widely used in many fields of industry. Th... more The shell-and-tube type heat exchangers have long been widely used in many fields of industry. These types of heat exchangers are generally easy to design, manufacturing, and maintenance, but require relatively large spaces to install. Therefore, the optimization of such heat exchangers from thermal and economical points of view is of particular interest. In this article, an optimization procedure based on the minimum total cost (initial investment plus operational costs) has been applied. Then the flow analysis of the optimized heat exchanger has been carried out to reveal possible flow field and temperature distribution inside the equipment using CFD. The experimental results were compared with CFD analyses results. It has been concluded that the baffles play an important role in the development of the shell side flow field. This prompted us to investigate new baffle geometries without compromising from the overall thermal performance. It has been found that the heat exchanger wit...
The moisture content of oil-filled transformers insulation paper that is a cellulose-containing m... more The moisture content of oil-filled transformers insulation paper that is a cellulose-containing material comprises 8% to 10% of moisture by weight at ambient temperature and it is highly important to decrease the moisture content for effective use of a transformer. Vapor phase drying is more effective method for drying the insulation paper of the transformer as compared with other conventional methods due to less cycle time and energy consumption. The purpose of this paper is to design a solvent operated drying chamber in which drying of the insulation paper of oil filled transformer carried out. The approach of the present paper is to develop a numerical model to reduce the cycle time of the drying process. The unsteady flow, heat, and mass transfer phenomena were simulated by using CFD solver. Theoretical studies and a numerical model were conducted over thermal calculation in the drying process using solvent at different pressures. Theoretical calculations were used to validate t...
In this study, performance of a heat exchanger used in combi boilers was investigated numerically... more In this study, performance of a heat exchanger used in combi boilers was investigated numerically for different fin geometries. Analyses were performed at the boiler operation conditions. A commercial CFD software package, FLUENT, was used for numerical simulations. The 3-D steady-state turbulent flow field analysis was carried out and k-? model was preferred as the turbulence model. In the analysis, it was assumed that the heat transfer phenomenon occurred both by conduction and convection. Flat fin geometry was taken as a reference for the investigation. Variation of the heat transfer and pressure drop values for the wavy fin were compared with the reference geometry. The wave angle and wave radius were taken as the parameters for the wavy fins. For different fin geometries: the outlet temperaTure of the combustion gases, the heat transfer to the water, and the pressure drop were calculated and the results were presented. Compared with flat fin, average decrease for the outlet tem...
The ability of an artificial neural network model, using a back propagation learning algorithm, t... more The ability of an artificial neural network model, using a back propagation learning algorithm, to predict specific fuel consumption and exhaust temperature of a Diesel engine for various injection timings is studied. The proposed new model is compared with experimental results. The comparison showed that the consistence between experimental and the network results are achieved by a mean absolute relative
In the recent years, the studies on hybrid electric vehicles have been increased in automotive in... more In the recent years, the studies on hybrid electric vehicles have been increased in automotive industry. Particularly, the studies focused on passenger cars. However, the studies conducted on Non-Automotive Vehicle (Vehicles not suitable for standard driving cycles) are not adequate. Additionally, the current driving cycles are not appropriate to simulate these vehicles. In this work, a series hybrid electric street sweeper is modeled and simulated by using AVL Cruise. This study aims that performing a series hybrid electric vehicle simulation and presenting its fuel consumption, vehicle performance and exhaust emissions theoretically. An appropriate driving cycle was constructed by using Random Cycle Generator of AVL Cruise in terms of velocity and functionality. The simulations were performed depending on this driving cycle. Vehicle block diagrams were created in software and the connections of vehicle such as mechanical, electrical and informational were demonstrated. Consequentl...
Engine tests are both costly and time consuming in developing a new internal combustion engine. T... more Engine tests are both costly and time consuming in developing a new internal combustion engine. Therefore, it is of great importance to predict engine characteristics with high accuracy using artificial intelligence. Thus, it is possible to reduce engine testing costs and speed up the engine development process. Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples. The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition (HCCI) engine for various excess air coefficients by using Deep Neural Network, which is one of the Deep Learning methods and is based on the Artificial Neural Network (ANN). The Deep Learning results were compared with the ANN and experimental results. The results show that the difference between experimental and the Deep Neural Network (DNN) results were less than 1%. The best r...
The shell-and-tube type heat exchangers have long been widely used in many fields of industry. Th... more The shell-and-tube type heat exchangers have long been widely used in many fields of industry. These types of heat exchangers are generally easy to design, manufacturing, and maintenance, but require relatively large spaces to install. Therefore, the optimization of such heat exchangers from thermal and economical points of view is of particular interest. In this article, an optimization procedure based on the minimum total cost (initial investment plus operational costs) has been applied. Then the flow analysis of the optimized heat exchanger has been carried out to reveal possible flow field and temperature distribution inside the equipment using CFD. The experimental results were compared with CFD analyses results. It has been concluded that the baffles play an important role in the development of the shell side flow field. This prompted us to investigate new baffle geometries without compromising from the overall thermal performance. It has been found that the heat exchanger wit...
The moisture content of oil-filled transformers insulation paper that is a cellulose-containing m... more The moisture content of oil-filled transformers insulation paper that is a cellulose-containing material comprises 8% to 10% of moisture by weight at ambient temperature and it is highly important to decrease the moisture content for effective use of a transformer. Vapor phase drying is more effective method for drying the insulation paper of the transformer as compared with other conventional methods due to less cycle time and energy consumption. The purpose of this paper is to design a solvent operated drying chamber in which drying of the insulation paper of oil filled transformer carried out. The approach of the present paper is to develop a numerical model to reduce the cycle time of the drying process. The unsteady flow, heat, and mass transfer phenomena were simulated by using CFD solver. Theoretical studies and a numerical model were conducted over thermal calculation in the drying process using solvent at different pressures. Theoretical calculations were used to validate t...
In this study, performance of a heat exchanger used in combi boilers was investigated numerically... more In this study, performance of a heat exchanger used in combi boilers was investigated numerically for different fin geometries. Analyses were performed at the boiler operation conditions. A commercial CFD software package, FLUENT, was used for numerical simulations. The 3-D steady-state turbulent flow field analysis was carried out and k-? model was preferred as the turbulence model. In the analysis, it was assumed that the heat transfer phenomenon occurred both by conduction and convection. Flat fin geometry was taken as a reference for the investigation. Variation of the heat transfer and pressure drop values for the wavy fin were compared with the reference geometry. The wave angle and wave radius were taken as the parameters for the wavy fins. For different fin geometries: the outlet temperaTure of the combustion gases, the heat transfer to the water, and the pressure drop were calculated and the results were presented. Compared with flat fin, average decrease for the outlet tem...
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Papers by Halit Yasar