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).