activity
20192022
most citedMachine learning moment closure models for the radiative transfer equation III: enforcing hyperbolicity and physical characteristic speeds

2 citations · 3 across the 8 of their papers we have counts for

collaborators

13 papers

math.NA2022

Bound-preserving discontinuous Galerkin methods with modified Patankar time integrations for chemical reacting flows

Fangyao Zhu, Juntao Huang, Yang Yang

In this paper, we develop bound-preserving discontinuous Galerkin (DG) methods for chemical reactive flows. There are several difficulties in constructing suitable numerical scheme…

math.NA2022

Adaptive sparse grid discontinuous Galerkin method: review and software implementation

Juntao Huang, Wei Guo, Yingda Cheng

This paper reviews the adaptive sparse grid discontinuous Galerkin (aSG-DG) method for computing high dimensional partial differential equations (PDEs) and its software implementat…

math.NA2022

Superconvergence and accuracy enhancement of discontinuous Galerkin solutions for Vlasov-Maxwell equations

Andrés Galindo-Olarte, Juntao Huang, Jennifer K. Ryan +1

This paper considers the discontinuous Galerkin (DG) methods for solving the Vlasov-Maxwell (VM) system, a fundamental model for collisionless magnetized plasma. The DG methods pro…

math.NA2022

On the stability of strong-stability-preserving modified Patankar Runge-Kutta schemes

Juntao Huang, Thomas Izgin, Stefan Kopecz +2

In this paper, we perform stability analysis for a class of second and third order accurate strong-stability-preserving modified Patankar Runge-Kutta (SSPMPRK) schemes, which were…

math.NA20212 cited

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

Juntao Huang, Yingda Cheng, Andrew J. Christlieb +1

This is the third paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation (RTE). In our previous work \cite{huang2021g…

math.NA2021

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

Juntao Huang, Yingda Cheng, Andrew J. Christlieb +2

This is the second paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation (RTE). In our previous work \cite{huang2021…