Error Analysis and Uncertainty Quantification for the Heterogeneous Transport Equation in Slab Geometry

Ivan G. Graham, Matthew J. Parkinson, Robert Scheichl

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Abstract

We present an analysis of multilevel Monte Carlo techniques for the forward problem of uncertainty quantification for the radiative transport equation, when the coefficients ({\em cross-sections}) are heterogenous random fields. To do this, we first give a new error analysis for the combined spatial and angular discretisation in the deterministic case, with error estimates which are explicit in the coefficients (and allow for very low regularity and jumps). This detailed error analysis is done for the 1D space - 1D angle slab geometry case with classical diamond differencing. Under reasonable assumptions on the statistics of the coefficients, we then prove an error estimate for the random problem in a suitable Bochner space. Because the problem is not self-adjoint, stability can only be proved under a path-dependent mesh resolution condition. This means that, while the Bochner space error estimate is of order $\mathcal{O}(h^\eta)$ for some $\eta$, where $h$ is a (deterministically chosen) mesh diameter, smaller mesh sizes might be needed for some realisations. Under reasonable assumptions we show that the expected cost for computing a typical quantity of interest remains of the same order as for a single sample. This leads to rigorous complexity estimates for Monte Carlo and multilevel Monte Carlo: For particular linear solvers, the multilevel version gives up to two orders of magnitude improvement over Monte Carlo. We provide numerical results supporting the theory.
Original languageEnglish
Pages (from-to)2331–2361
JournalIMA Journal of Numerical Analysis
Volume41
Issue number4
Early online date8 Aug 2020
DOIs
Publication statusPublished - 31 Oct 2021

Funding

We thank The UK Engineering and Physical Sciences Research Council (EPSRC) and Wood plc for financial support for this project, and we particularly thank Prof. Paul Smith of the Answers Software Team for many helpful discussions. This research made use of the Balena High Performance Computing Service at the University of Bath. We thank The UK Engineering and Physical Sciences Research Council (EPSRC) and Wood plc for financial support for this project, and we particularly thank Prof. Paul Smith of the Answers Software Team for many helpful discussions. This research made use of the Balena High Performance Computing Service at the University of Bath. M.P. was supported by a scholarship from the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath under grant EP/L015684/1. M.P. was supported by a scholarship from the EPSRC Centre for Doctoral Training in Statistical Applied Mathematics at Bath under grant EP/L015684/1.

Keywords

  • math.NA
  • 65N12, 65R99, 65C30, 65C05

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