MOOSE Stochastic Tools: A module for performing parallel, memory-efficient in situ stochastic simulations

Slaughter, Andrew E.; Prince, Zachary M.; German, Péter; Halvic, Ian; Jiang, Wen; Spencer, Benjamin W.; Dhulipala, Somayajulu L. N.; Gaston, Derek

doi:10.1016/j.softx.2023.101345

Cited by 13 publications

(5 citation statements)

References 8 publications

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“…The impact of parameter changes and deviations from baseline conditions can be further explored to close information gaps in understanding the MSRE tritium distribution and its pathways. For instance, the MOOSE Stochastic Tools [22] can be utilized to perform sensitivity analyses on a large number of the parameters related to multiphysics phenomena at reduced computational expenses. The sensitivity study is expected to provide useful information in analyzing radiological consequence of tritium releases from MSRs to assess the risks associated with MSRs that produce larger tritium inventories than other reactors.…”

Section: Tritium Distribution In the Msrementioning

confidence: 99%

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

Cao,

Fang,

Jeong

et al. 2023

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Section: Tritium Distribution In the Msrementioning

confidence: 99%

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

Cao,

Fang,

Jeong

et al. 2023

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“…In this paper, the Sobol method is utilized to perform sensitivity analysis on material properties based on the transient output parameters of the Godiva fast-pulsed reactor. The analysis is conducted using the Stochastic Tools module [26] under the MOOSE platform. The chosen technique for the analysis is the second-order Sobol sensitivity analysis tool, which employs the Sobol sampling scheme.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Transient Simulation and Parameter Sensitivity Analysis of Godiva Experiment Based on MOOSE Platform

Wang,

Guo,

et al. 2023

Energies

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The fast-neutron burst reactor is a chain reactor that can operate in a prompt critical state. In order to ensure the operational safety of the fast-neutron-pulse reactor and prevent the supercritical pulse from causing physical damage to the material, it is necessary to simulate and analyze the pulse operating conditions of the fast-neutron-pulse reactor. Godiva-I is a spherical assembly of highly enriched uranium metal made during the 1950s. A prompt-critical transient in such a nuclear system impels a quick power excursion, which will cause a temperature rise and a subsequent reactivity reduction because of the metal sphere’s expansion. The overall transient lasts for a few fractions of a millisecond. Based on the point kinetics and Monte Carlo method, the temporal and spatial characteristics of transient input power were calculated, the difference of the average reactivity temperature coefficient between uniform density and non-uniform density was compared, and the transient power distribution condition was loaded into the thermal–mechanics calculation of the MOOSE platform; thus, the pulse process of Godiva-I with different initial reactivity periods was simulated. The JFNK (Jacobian–Free–Newton–Krylov) direct method and multi-app indirect method were used to analyze the transient response of the pulse dynamic process using the heat conduction module and tenor mechanics module, respectively. After considering the influence of the inertia effect and wall-reflected neutrons, the simulation results were much closer to the experimental values. Based on the stochastic tools module, the uncertainty propagation and sensitivity analysis of the Godiva-I model were carried out, the uncertainty of external surface displacement of Godiva under input disturbance of material properties and heat source amplitude factor was obtained, and the sensitivity of different input parameters to output parameters was quantified. The research results can lay a technical foundation for the thermal–mechanics coupling analysis and uncertainty quantification of the metal fast reactor.

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“…To reflect significant improvements recently made to the TRISO modeling capabilities in BISON, failure analyses of the HP-MR TRISO were performed for the unit cell and 1/6-core HP-MR multiphysics models. These analyses use the MOOSE Stochastic Tools module [20] and MultiApp functionality to conduct a Monte Carlo sampling scheme for several one-dimensional TRISO particles, accounting for microscopic particle-to-particle variations in geometry and material properties, such as layer thicknesses and bond strengths, respectively, that arise during TRISO fabrication.…”

Section: Triso Failure Probabilitymentioning

confidence: 99%

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

Stauff,

Abdelhameed,

Cao

et al. 2023

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MOOSE Stochastic Tools: A module for performing parallel, memory-efficient in situ stochastic simulations

Cited by 13 publications

References 8 publications

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

Multiphysics Simulations of MSRE with NEAMS Thermal Hydraulics Tools

Transient Simulation and Parameter Sensitivity Analysis of Godiva Experiment Based on MOOSE Platform

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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