Enhancing Reduced-Order Models in High-Dimensional Engineering Applications through Gradient Boosting Tree
Addressing forward problems with high-fidelity models like Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) presents significant challenges due to their computational demands from high-dimensional spatial discretization. These models are expensive, requiring powerful solvers and extensive computatio...