Applied Surrogate Model: Performance Prediction of Heat Pipe with Mesh Wick

Results are provided for an investigation of a heat pipe with mesh wick applied with surrogate model. The model including radial basis function interpolation (RBF), Kriging model (KRG), and the k-nearest neighborhood model (K-NN) were studied and compared. A set of training and validating populations were classified using a k-means clustering technique. The design variable included the geometric shape of heat pipe such as its diameter, the properties and percentage used of working fluid, and the temperature at the evaporator. The prediction case study included the heat transfer rate (q), and total difference temperature between evaporator and condenser section (DT). The prediction results found that the heat transfer rate gave the most accurate indicator while the DT is passable to applied. The most accurate model was presented as a Kriging model with percentage errors 13.0622 and 14.7184 for heat transfer rate and total difference temperature respectively. The second best accuracy was achieved with the RBF model with linear kernel while the third and fourth best are including thin plate and cubic spline kernel respectively.