Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations
Miles, P. R., Cook, J. A., Angers, Z. V., Swenson, C. J., Kiedrowski, B. C., Mattingly, J., & Smith, R. C. (2020, May 29). Nuclear Technology, Vol. 207, pp. 37–53.
author keywords: Radiation detection; inverse problem; Bayesian inference; MCNP; surrogate modeling
topics (OpenAlex): Probabilistic and Robust Engineering Design; Gaussian Processes and Bayesian Inference; Nuclear reactor physics and engineering; Radiation Detection and Scintillator Technologies; Nuclear Physics and Applications
TL;DR:
The Monte Carlo N-Particle code is employed to provide high-fidelity simulations of radiation transport within an urban domain to develop efficient and accurate surrogate models of the detector responses that provide an efficient framework for Bayesian inference and experimental design.
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Sources: Web Of Science, NC State University Libraries