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.

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Renewable fuel is gaining more attention in the current energy crisis, and biomass is one of the potential sources of producing renewable fuel. The objective of the present research is to analyze the pyrolysis and kinetic behavior of neem seed biomass. Pyrolysis and kinetic behavior of neem seed were analyzed using thermogravimetric analysis (TGA) at different heating rates, viz. 5, 10, 15, and 20 K min−1. The kinetic study was conducted on the neem seed using various kinetic models such as Friedman, Kissinger, Flynn–Wall–Ozawa (FWO), and Kissinger–Akahira–Sunose (KAS). Thermodynamic analysis was carried out using the data extracted from the TGA curves. The results showed that the neem seed degraded in three stages, stage I: <100 °C, stage II: 100–550 °C, and stage III: >550 °C. A maximum mass loss of 73.14 % occurred at stage II owing to the loss of cellulose and hemicellulose. The activation energy determined by Friedman, KAS, and FWO models was 5.11–18.64, 10.62–57.41, and 13.77–61.51 kJ mol−1, respectively. Thermodynamic analysis revealed that the pyrolysis of neem seed was an endothermic and spontaneous process. Moreover, the previously reported average activation energy required for the pyrolysis of various seeds and shells was compared with the present study and concluded that the variation in activation energy of neem seed adheres to the outcomes reported earlier.