... regression (SVR) and random forest regression (RFR) – are compared for their performance in surrogate modeling. A physical boundary condition is incorporated to expand the sample set, and its influence on model training is systematically evaluated. The proposed methodology uses a time-efficient alternative...

...Nenzi Wang; Chih-Ming Tsai Purpose In this study, artificial neural networks (ANNs) are constructed and validated by using the bearing data generated numerically from a thermohydrodynamic (THD) lubrication model. In many tribological simulations, a surrogate model (meta-model) for obtaining a fast...