1.5k citations · 5.1k across the 48 of their papers we have counts for
5 papers · 1 filter
Enforcing Boundary Conditions on Physical Fields in Bayesian Inversion
Carlos A. Michelén Ströfer, Xinlei Zhang, Heng Xiao +1
Inverse problems in computational mechanics consist of inferring physical fields that are latent in the model describing some observable fields. For instance, an inverse problem of…
Enforcing Deterministic Constraints on Generative Adversarial Networks for Emulating Physical Systems
Zeng Yang, Jin-Long Wu, Heng Xiao
Generative adversarial networks (GANs) were initially proposed to generate images by learning from a large number of samples. Recently, GANs have been used to emulate complex physi…
Flows Over Periodic Hills of Parameterized Geometries: A Dataset for Data-Driven Turbulence Modeling From Direct Simulations
Heng Xiao, Jin-Long Wu, Sylvain Laizet +1
Computational fluid dynamics models based on Reynolds-averaged Navier--Stokes equations with turbulence closures still play important roles in engineering design and analysis. Howe…
Regularized Ensemble Kalman Methods for Inverse Problems
Xin-Lei Zhang, Carlos Michelén-Ströfer, Heng Xiao
Inverse problems are common and important in many applications in computational physics but are inherently ill-posed with many possible model parameters resulting in satisfactory r…
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems
Jin-Long Wu, Karthik Kashinath, Adrian Albert +3
Simulating complex physical systems often involves solving partial differential equations (PDEs) with some closures due to the presence of multi-scale physics that cannot be fully…