Mathematical Modeling of Closed Loop Pulsating Heat Pipe by Using Artificial Neural Networks

Pulsating heat pipe is one of the prominent technology for thermal management electronic devices. It consists three sections namely evaporator, adiabatic and condenser section. PHP a two phase passive device having efficient quick ability transferring from evaporator section to At first an 8 turn pulsating closed loop ends (CLPHP) with copper tube capillary dimensions investigated experimentally different fill ratios inclinations by varying range inputs. Different working fluids viz Water, Acetone, Ethanol Methanol are considered experimentation. One recent analytical modelling CLPHPs Artificial Neural Network (ANN) approach. The models limited scope applicability they simple in nature. present paper describes Validation experimental data training prediction model ANN available data. Three input nodes such as heat, ratio angle inclination output node corresponding that resistance considered. feed forward neural network (FFNN) architecture adopted predictions. By using physical phenomena system clearly known obtaining feasible results which main function ANN. predicted validates satisfactory found be good agreement ± 10 percent.