Heat transfer performance and prediction of open pulsating heat pipe for self-cooling cutting tool

The pulsating heat pipe (PHP) can be used to transfer massive heat to reduce the thermal damage to the cutting tool when machining difficult-to-cut materials. To select a better open PHP, the heat transfer performance was experimentally investigated in this study. The operating characteristics of different types of working fluids under different heat flux were analyzed compared with the closed PHP. Visual experiments were established to verify the experimental characteristics. The effects of heat flux, length, ratio of inner/outer diameter, and inclination angle on equivalent thermal resistance were analyzed. Based on the experimental data and four boosting integrating learning methods, a model for heat transfer performance prediction was proposed. The prediction model based on the CatBoost method had better goodness-of-fit and the best prediction effect. The R-2, MAPE, and RMSE of the validation set were the best, which are 0.9258, 7.2564, and 0.1057 respectively. In addition, the contribution of input parameters to the output results was evaluated, while L, D-i/D-o, and Pr were the top three variables. Sub-tree structures used to explain the prediction model were also presented. This proposed prediction model can be used to select the most suitable open PHP before designing PHP self-cooling tools.

Automated summary

The heat transfer performance of open pulsating heat pipe (PHP) was experimentally investigated and a prediction model based on experimental data and boosting integrating learning methods was proposed. The model can be used to select the most suitable open PHP.