Estimation of the windage loss and heat transfer characteristics inside the finite length of electrical machines’ airgap based on CFD and MLA

The dataset provided is used to train three machine learning algorithms—Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Regression (SVR)—for estimating heat transfer and windage loss in the air gap of electric motors. The dataset comprises results from 1,200 computational fluid dynamics (CFD) simulations. Additionally, MATLAB code is supplied for each of the trained machine learning models (ANN, RF, and SVR).

本数据集用于训练三类机器学习算法——人工神经网络（Artificial Neural Network，ANN）、随机森林（Random Forest，RF）与支持向量回归（Support Vector Regression，SVR），以实现电机气隙内传热与风摩损耗的估算。该数据集包含1200项计算流体动力学（Computational Fluid Dynamics，CFD）仿真结果。此外，还为每一类训练完成的机器学习模型（ANN、RF、SVR）提供了MATLAB代码。