3 papers
physics.comp-ph2025
Neural operator-based super-fidelity: A warm-start approach for accelerating steady-state simulations
Xu-Hui Zhou, Jiequn Han, Muhammad I. Zafar +4
Recently, the use of neural networks to accelerate the solving of partial differential equations (PDEs) has gained significant traction in both academia and industry. However, empl…
physics.flu-dyn2025
Multi-Fidelity Machine Learning Applied to Steady Fluid Flows
Kazuko W. Fuchi, Eric M. Wolf, David S. Makhija +2
A machine learning method to predict steady external fluid flows using elliptic input features is introduced. Using data from as few as one high-fidelity simulation, the proposed m…
physics.flu-dyn2025
Acceleration of RANS Solver Convergence via Initialization with Wake Extension Models
Kazuko W. Fuchi, Eric M. Wolf, Christopher R. Schrock +1
Use of appropriate initialization to warm-start Reynolds-averaged Navier-Stokes (RANS) simulations of turbulent flow can facilitate convergence and lead to efficient use of computa…