Frequency-Dependent Material Motion Benchmarks for Radiative Transfer

by   Ryan G. McClarren, et al.

We present a general solution for the radiation intensity in front of a purely absorbing slab moving toward an observer at constant speed and with a constant temperature. The solution is obtained by integrating the lab-frame radiation transport equation through the slab to the observer. We present comparisons between our benchmark and results from the Kull simulation code for an aluminum slab moving toward the observer at 2 demonstrate that ignoring certain material motion correction terms in the transport equation can lead to 20-80 as the frequency resolution is improved. Our results also indicate that our benchmark can identify potential errors in the implementation of material motion corrections.




Nonlinear Iterative Projection Methods with Multigrid in Photon Frequency for Thermal Radiative Transfer

This paper presents nonlinear iterative methods for the fundamental ther...

Reconstructing the thermal phonon transmission coefficient at solid interfaces in the phonon transport equation

The ab initio model for heat propagation is the phonon transport equatio...

Parameter estimation of temperature dependent material parameters in the cooling process of TMCP steel plates

Accelerated cooling is a key technology in producing thermomechanically ...

A general higher-order shell theory for compressible isotropic hyperelastic materials using orthonormal moving frame

The aim of this study is three-fold: (i) to present a general higher-ord...

GPU accelerated computation of Polarized Subsurface BRDF for Flat Particulate Layers

BRDF of most real world materials has two components, the surface BRDF d...

Deep learning of material transport in complex neurite networks

Neurons exhibit complex geometry in their branched networks of neurites ...

Uncertain Transport in Unsteady Flows

We study uncertainty in the dynamics of time-dependent flows by identify...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.