Subcooled boiling is the most effective form of heat exchange in the water
jacket of the cylinder head. Chen's model is the most widely used
correlation for predicting boiling heat transfer, but the selection of the
correlation for the nucleate boiling is controversial. The work of this
paper is to simulate the heat transfer process in the water jacket of the
cylinder head with a horizontal rectangular channel that is heated on one
side. Using the coolant flow velocity, inlet temperature and system pressure
as variables, the heat flux and heat transfer coefficient were obtained. The
results show that the increase of the coolant flow velocity can effectively
promote the convection heat transfer, and the change of inlet temperature
and system pressure will affect the occurrence of nucleate boiling. However,
the Chen?s model predictions doesn?t fit well with the experimental data.
Four nucleate boiling correlations were selected to replace Chen's model
nucleate boiling correlation. The correlation proposed by Pioro coincides
best with the experimental data. The mean error after correction is 18.2%.
Since the internal heat transfer is a complicated process, the heat pipe heat exchanger of the engine has not been fully understood yet, which is originated from its extreme complexity. In theoretical studies, the involvement of two-phase flow and phase change processes usually simplifies the processing very much, and the model built differs too much from the actual one, resulting in reduced simulation accuracy. In this study, the prediction model of heat transfer and heat resistance of the heat pipe intercooler is established based on artificial neural networks (ANNs). Then the performance of the heat pipe intercooler from heat transfer and heat resistance aspects is investigated. The average relative error between the heat transfer prediction model and the test value is 3.6%, and the average relative error between the resistance prediction model and the test value is 12.68%, which shows that the prediction model can predict the thermal performance of heat pipe intercooler more accurately. Finally, the proposed model is applied to optimize the structural parameters of the heat pipe intercooler, and the optimal parameters are obtained accordingly. These optimal design parameters can provide the basis for further investigation and development of the heat pipe intercooler in diverse applications.
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