17 citations · 29 across the 6 of their papers we have counts for
6 papers
Stochastic reduced-order Koopman model for turbulent flows
Tianyi Chu, Oliver T. Schmidt
A stochastic data-driven reduced-order model applicable to a wide range of turbulent natural and engineering flows is presented. Combining ideas from Koopman theory and spectral mo…
Revealing Structure and Symmetry of Nonlinearity in Natural and Engineering Flows
Brandon Yeung, Tianyi Chu, Oliver T. Schmidt
Energy transfer across scales is fundamental in fluid dynamics, linking large-scale flow motions to small-scale turbulent structures in engineering and natural environments. Triadi…
Mesh-Free Hydrodynamic Stability
Tianyi Chu, Oliver T. Schmidt
A specialized mesh-free radial basis function-based finite difference (RBF-FD) discretization is used to solve the large eigenvalue problems arising in hydrodynamic stability analy…
Joint Optimization of Triangle Mesh, Material, and Light from Neural Fields with Neural Radiance Cache
Jiakai Sun, Weijing Zhang, Zhanjie Zhang +4
Traditional inverse rendering techniques are based on textured meshes, which naturally adapts to modern graphics pipelines, but costly differentiable multi-bounce Monte Carlo (MC)…
RBF-FD discretization of the Navier-Stokes equations on scattered but staggered nodes
Tianyi Chu, Oliver T. Schmidt
A semi-implicit fractional-step method that uses a staggered node layout and radial basis function-finite differences (RBF-FD) to solve the incompressible Navier-Stokes equations i…
A stochastic SPOD-Galerkin model for broadband turbulent flows
Tianyi Chu, Oliver T. Schmidt
The use of spectral proper orthogonal decomposition (SPOD) to construct low-order models for broadband turbulent flows is explored. The choice of SPOD modes as basis vectors is mot…