Convergence analysis of the Random ordinate method for mitigating the ray effect

The Discrete Ordinates Method (DOM) is widely used for velocity discretization in radiative transport simulations. However, DOM tends to exhibit the ray effect when the velocity discretization is not sufficiently refined, a limitation that is well documented. To counter this, we have developed the Random Ordinates Method (ROM) by integrating randomness into the velocity discretization, which mitigates the ray effect without incurring additional computational costs. ROM partitions the velocity space into $ n $ cells, selects a random ordinate from each cell, and solves a DOM system with these ordinates. It leverages the average of multiple samples to achieve a higher convergence order, especially for solutions with low regularity in the velocity variable. In this work, we provide a detailed convergence analysis for ROM, focusing on bias and single-run errors. This analysis is crucial for determining the necessary mesh size and the optimal number of samples required to attain a specified level of accuracy.

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Publication Details

Journal
Kinetic and Related Models
Published
2026-10-16
DOI
https://doi.org/10.3934/krm.2026.100765
Primary Topic
Radiative Heat Transfer Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Convergence analysis of the Random ordinate method for mitigating the ray effect

Yuqi Yang, Min Ming Tang, Lei Li
Kinetic and Related Models
Radiative Heat Transfer Studies
article

Convergence analysis of the Random ordinate method for mitigating the ray effect

Yuqi Yang, Min Ming Tang, Lei Li
article en

Abstract

The Discrete Ordinates Method (DOM) is widely used for velocity discretization in radiative transport simulations. However, DOM tends to exhibit the ray effect when the velocity discretization is not sufficiently refined, a limitation that is well documented. To counter this, we have developed the Random Ordinates Method (ROM) by integrating randomness into the velocity discretization, which mitigates the ray effect without incurring additional computational costs. ROM partitions the velocity space into $ n $ cells, selects a random ordinate from each cell, and solves a DOM system with these ordinates. It leverages the average of multiple samples to achieve a higher convergence order, especially for solutions with low regularity in the velocity variable. In this work, we provide a detailed convergence analysis for ROM, focusing on bias and single-run errors. This analysis is crucial for determining the necessary mesh size and the optimal number of samples required to attain a specified level of accuracy.

Kinetic and Related ModelsVol. 26(0)
Shanghai Jiao Tong University (CN), Institute of Natural Science (KP)
National Natural Science Foundation of China, Chinese Academy of Sciences
Openalex Percentile: Top 99%
Radiative Heat Transfer Studies
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