Search Results for author: Yingda Cheng

Found 5 papers, 2 papers with code

An adaptive high-order piecewise polynomial based sparse grid collocation method with applications

1 code implementation9 Dec 2019 Zhanjing Tao, Yan Jiang, Yingda Cheng

The contribution of this work is the introduction of a systematic framework for collocation onto high-order piecewise polynomial space that is allowed to be discontinuous.

Numerical Analysis Numerical Analysis

An adaptive multiresolution discontinuous Galerkin method with artificial viscosity for scalar hyperbolic conservation laws in multidimensions

1 code implementation3 Jun 2019 Juntao Huang, Yingda Cheng

Theoretical and numerical studies are performed taking into consideration of accuracy and stability with regard to the choice of the interpolatory multiwavelets.

Numerical Analysis Numerical Analysis

Machine learning moment closure models for the radiative transfer equation I: directly learning a gradient based closure

no code implementations12 May 2021 Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts

In this paper, we take a data-driven approach and apply machine learning to the moment closure problem for radiative transfer equation in slab geometry.

BIG-bench Machine Learning

Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures

no code implementations30 May 2021 Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts, Wen-An Yong

This is the second paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation (RTE).

RTE

Machine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds

no code implementations2 Sep 2021 Juntao Huang, Yingda Cheng, Andrew J. Christlieb, Luke F. Roberts

In our second paper \cite{huang2021hyperbolic}, we identified a symmetrizer which leads to conditions that enforce that the gradient based ML closure is symmetrizable hyperbolic and stable over long time.

RTE

Cannot find the paper you are looking for? You can Submit a new open access paper.