Moment-based adaptive time integration for thermal radiation transport

Southworth, Ben Scott; Walton, Steven Taylor; Roberts, Steven B.; Park, HyeongKae

doi:10.1016/j.jcp.2025.114417

Moment-based adaptive time integration for thermal radiation transport

Journal Article · Thu Oct 02 00:00:00 EDT 2025 · Journal of Computational Physics

DOI:https://doi.org/10.1016/j.jcp.2025.114417· OSTI ID:2998249

^[1]; ^[1]; Roberts, Steven B. ^[2]; ^[1]

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Here, in this paper we develop a framework for moment-based adaptive time integration of deterministic multifrequency thermal radiation transpot (TRT). We generalize our recent semi-implicit-explicit (IMEX) integration framework for gray TRT to multifrequency TRT, and also introduce a semi-implicit variation that facilitates higher-order integration of TRT, where each stage is implicit in all components except opacities. To appeal to the broad literature on adaptivity with Runge–Kutta methods, we derive new embedded methods for four asymptotic preserving IMEX Runge–Kutta schemes we have found to be robust in our previous work on TRT and radiation hydrodynamics. We then use a moment-based high-order-low-order representation of the transport equations. Due to the high dimensionality, memory is always a concern in simulating TRT. We form error estimates and adaptivity in time purely based on temperature and radiation energy, for a trivial overhead in computational cost and memory usage compared with the base second order integrators. We then test the adaptivity in time on the tophat and Larsen problem, demonstrating the ability of the adaptive algorithm to naturally vary the timestep across 4–5 orders of magnitude, ranging from the dynamical timescales of the streaming regime to the thick diffusion limit.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: 89233218CNA000001; AC52-07NA27344

OSTI ID:: 2998249

Report Number(s):: LA-UR--25-20758; 10.1016/j.jcp.2025.114417

Journal Information:: Journal of Computational Physics, Journal Name: Journal of Computational Physics Vol. 543; ISSN 0021-9991

Publisher:: Elsevier BVCopyright Statement

Country of Publication:: United States

Language:: English

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