32 citations · 32 across the 3 of their papers we have counts for
4 papers
A novel parallelizable convergence accelerating method: Pointwise Frequency Damping
Zikun Liu, Xukun Wang, Yilang Liu +1
This paper proposes a novel class of data-driven acceleration methods for steady-state flow field solvers. The core innovation lies in predicting and assigning the asymptotic limit…
A data-driven convergence booster for accelerating and stabilizing pseudo time-stepping
Xukun Wang, Yilang Liu, Xiang Yang +1
This paper introduces a novel data-driven convergence booster that not only accelerates convergence but also stabilizes solutions in cases where obtaining a steady-state solution i…
Towards a Generalized SA Model: Symbolic Regression-Based Correction for Separated Flows
Xuxiang Sun, Xianglin Shan, Yilang Liu +1
This study focuses on the numerical simulation of high Reynolds number separated flows and proposes a data-driven approach to improve the predictive capability of the SA turbulence…
Acceleration of three-dimensional Tokamak magnetohydrodynamical code with graphics processing unit and OpenACC heterogeneous parallel programming
H. W. Zhang, J. Zhu, Z. W. Ma +3
In this paper, the OpenACC heterogeneous parallel programming model is successfully applied to modification and acceleration of the three-dimensional Tokamak magnetohydrodynamical…