Goal-Oriented Regional Angular Adaptive Algorithm for the S_N Equations

Angular discretization errors inherent in the discrete ordinates method are a major problem, especially for localized source problems and problems with strongly absorbing media or large-volume void regions, where angular discretization errors would be totally unacceptable. This paper proposes a regional angular adaptive algorithm together with a goal-oriented error estimate to solve the S_N equations. Standard angular adaptive refinement techniques are based on estimated local errors. We compare an interpolated angular flux value against a calculated value to generate local errors. The adaptive quadrature sets can be created by subdividing a spherical quadrilateral into four spherical subquadrilaterals that have positive weights and can be locally refined. Techniques for mapping angular fluxes from one quadrature set to another are developed to transfer angular fluxes on the interfaces of different spatial regions. To provide a better detector response, local errors are weighted by the importance of a given angular region toward the computational goal, providing an appropriate goal-oriented angular adaptivity. First collision source methods are employed to improve adjoint flux calculation accuracy. We tested the performance and accuracy of the proposed goal-oriented regional angular adaptive algorithm within the ARES code for a number of benchmark problems and present the results of a one-region test model and the Kobayashi benchmark problems. The reduction of angular number is at least one order of magnitude for adaptive refinement. The benchmarks demonstrate that the proposed goal-oriented adaptive refinement can achieve the same level of accuracy as the S_N method, which has significantly higher computation cost. Thus, adaptive refinement is a viable approach for investigating difficult particle radiation transport problems.