Review of Modeling the Performance of Heat Pipes using Artificial Neural Network

Neeraj K. Chavda


Heat pipes are two phase heat transfer devices largely employed in various applications to transfer the heat mainly due to their high effective thermal conductivity, ease in operation and maintenance and flexibility in location. Conventional fluids like water, methanol, etc. and non-conventional fluids like nanofluid, hybrid nanofluids are used as working medium in heat pipes. The thermal performance of heat pipe depends on the various parameters of both i.e. heat pipe and working fluid. Therefore it requires performing multiple extensive experiments to identify the optimum values of heat pipe and working fluid parameters suitable for a particular application. Although, the results of experiments carried out once can be modeled using artificial neural network to predict the performance of heat pipe under wide range of affecting parameters without actually performing the experiments. The present paper deals  with the comprehensive review of literatures related to modeling of various heat pipes using artificial neural networks considering various parameters related to heat pipe, working medium and ANN parameters. The outcome based on the study has been discussed which will form a basis for further investigations in modeling of heat pipe.


Review, Heat Pipe, Artificial Neural Network, Performance, Nanofluid

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