Manufacturing simulation is an encouraging field in every manufacturing industry. The manufacturing simulation facilitate to virtually analysis the performance of the product before manufacturing. So for most of the manufacturing activities are simulated effective and researchers have developed adequate tool for the simulation of various activities of manufacturing. Heat exchanger is one of the important devices used for the purposes including medical, food processing, air conditioning system, etc. Performance of these heat exchangers also important for achieving better performance in those fields. So simulation of heat exchanger gives more beneficial to the engineers to analysis its performance before manufacturing. Hence in this paper, a machine learning approach for the modelling and simulation of heat exchanger is proposed. The proposed technique uses support vector machine technique for the prediction of performance of the heat exchanger. The performance of the proposed technique is validated in terms of prediction accuracy. Ultimately the analysis proves that the proposed technique is more beneficial for the modelling of heat exchanger.

Air conditioning system is used for various application, in passenger car it gives comfort to the passenger. Now a days huge advancement have been included in the air conditioning system, especially automatic air conditioning system plays a vital role in passenger car. These air conditioning systems are performing well and have the capability of maintaining the temperature for long time with energy consumption. However, in some vehicle the performance of these air conditioning system is not achieved, while some vehicle achieved better performance. In later study it is found that, the structure of vehicle body also influence the performance of air conditioning system. In some structure the air conditioning air-flow a long distance in short time and have the capability to enhance the air conditioning performance. It is also found that the air conditioning performance can be improved by the structure of vehicle body. In this paper, we considered an Indian small budget car. The structure of the car is slightly modified and replaced the position of the air conditioning outlet. Then the residual temperature inside the car is analyzed with and without air conditioning. Here the CFD is used to analysis the temperature inside car at various position.

Heat exchangers are widely used in many field for the purpose of heat from one medium to another. In heat exchanger one or more fluids are used, and which are various types based on its flow and construction. Design of heat exchanger is one of the important field, in the research due to its application. In recent decade the simulation is used in most of the engineering application. A proper simulation technique can effectively analysis the functionality and behavior of any machine before its construction or production. In this sense the machine learning techniques are used in some simulation analysis to model the machine or engine. In this work we used a hybrid neural network for the modeling of shell and tube type heat exchanger and its heat transfer rate is predicted effectively. The computational performance of the proposed technique is compared with the conventional technique and it is proved the effectiveness of the hybrid machine learning technique.

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Nowadays ensure the performance of heat exchanger is one of the toughest roles in industries. In this work focused on improve the performance of shell and tube heat exchangers by reducing the pressure drop as well as raising the overall heat transfer. This work considered as a different nanoparticles such as Aluminium oxide (Al2O3), Silicon dioxide (SiO2), Titanium oxide (TiO2) and Zirconium dioxide (ZrO2) to form a nanofluids. This nanofluids possesses high thermal conductivity by using of this increase the heat transfer rate in shell and tube heat exchanger. The selected nanofluids are compared to base fluid based on the thermophysical properties as well as heat transfer characteristics. All the heat transfer characteristics are improved by applying of nanofluids particularly higher results are obtained with using of TiO2 and Al2O3 compared to SiO2 and ZrO2. Mixing of nanoparticles increased in terms of volume percentage it will be increases the all Heat transfer characteristics as well as performance of the heat exchanger.