Abstract:This document constitutes completion of the NEAMS milestone, which is titled: Demonstrate efficiency improvements in TRISO failure probability calculations and the effect of debonding on fission product transport in TRISO fuel particles in Bison. In this report we present the development of : (1) the anisotropic elasticity model of pyrolytic carbon and extended material models using the local coordinate system for aspherical particle geometry, (2) a capability of modeling interface debonding in TRISO particles… Show more
“…Engineering-scale FP transport modeling in TRISO fuel was recently reviewed [18][19][20] and demonstrated with the BISON code [21], validating against AGR-2 data. This work builds on previous efforts in developing BISON's TRISO FP release functionality, which was initially validated against AGR-1 data [22,23], and also utilizes some models previously implemented in the PARFUME code [24].…”
Section: Modeling Effortsmentioning
confidence: 98%
“…An understanding of TRISO particle failure modes is necessary to predict RN releases from failed particles. Recently, a methodology in calculating failure probability of a population of TRISO particles was demonstrated using BISON [18,20]. It relies on a Monte Carlo scheme in which each particle analyzed follows a distribution of statistically sampled parameters that characterize the geometry and material properties of the particle.…”
Section: Modeling Effortsmentioning
confidence: 99%
“…Figure 2-1: Monte Carlo scheme employed by BISON for calculating the failure probability of TRISO particles [20]. …”
“…Engineering-scale FP transport modeling in TRISO fuel was recently reviewed [18][19][20] and demonstrated with the BISON code [21], validating against AGR-2 data. This work builds on previous efforts in developing BISON's TRISO FP release functionality, which was initially validated against AGR-1 data [22,23], and also utilizes some models previously implemented in the PARFUME code [24].…”
Section: Modeling Effortsmentioning
confidence: 98%
“…An understanding of TRISO particle failure modes is necessary to predict RN releases from failed particles. Recently, a methodology in calculating failure probability of a population of TRISO particles was demonstrated using BISON [18,20]. It relies on a Monte Carlo scheme in which each particle analyzed follows a distribution of statistically sampled parameters that characterize the geometry and material properties of the particle.…”
Section: Modeling Effortsmentioning
confidence: 99%
“…Figure 2-1: Monte Carlo scheme employed by BISON for calculating the failure probability of TRISO particles [20]. …”
“…Alternatively, debonding failure occurs when the graphite matrix surrounding the TRISO particle swells and pulls the OPyC layer away from the SiC. Partial debonding at the OPyC-SiC interface then leads to undue tensile stress in the SiC layer [22]. Due to its current state of development, debonding failure was not enabled in this study, as suggested by the BISON development team.…”
High-fidelity multiphysics load following and accidental transient modeling of microreactors using NEAMS tools
Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts
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