3 papers
physics.flu-dyn2026
Manifold Learning with Implicit Physics Embedding for Reduced-Order Flow-Field Modeling
Weiji Wang, Chunlin Gong, Xuyi Jia +1
Nonlinear manifold learning (ML) based reduced-order models (ROMs) can substantially improve the quality of nonlinear flow-field modeling. However, noise and the lack of physical i…
physics.flu-dyn2025
A Kernel Ridge Regression Combining Nonlinear ROMs for Accurate Flow Field Reconstruction with Discontinuities
Weiji Wang, Chunlin Gong, Xuyi Jia +1
Nonlinear reduced-order models (ROMs), represented by manifold learning (ML), can effectively improve the modeling accuracy of nonlinear flow fields with discontinuities. However,…
physics.flu-dyn2024
Unsteady aerodynamic prediction using limited samples based on transfer learning
Wen Ji, Xueyuan Sun, Chunna Li +3
In this study, a method for predicting unsteady aerodynamic forces under different initial conditions using a limited number of samples based on transfer learning is proposed, aimi…