HEAT TRANSFER PERFORMANCE MODEL OF PULSATING HEAT PIPE BASED ON NEURAL NETWORK
This paper presents artificial neural network (ANN) modeling of heat transfer performance for a pulsating heat pipe (PHP). The investigated PHP is a vertical closed loop copper/ethanol PHP. Fully connected multi-layer feed forward network is adopted and back propagation momentum algorithm, sigmoid node function are used. In the network, two input nodes correspond to heat load and fill rate and the output is a single node for thermal resistance. The matching of the ANN test output data and the experimental data is satisfying. It can be inferred that the ANN model can be applied to accurately model PHP performance.