Predicting Neutron Noise Detector Responses for Zero-Power Molten Salt Reactor Experiments

We use Monte Carlo simulations to predict the responses of neutron noise experiments in zero-power Molten Salt Reactors (MSRs). As for conventional reactors, the initial testing of a newly constructed reactor often comprises zero-power tests and criticality experiments. In zero-power environments, neutron noise experiments can be part of the experimental portfolio to provide experimental data on integral kinetic parameters such as the prompt neutron decay constant or the effective delayed neutron fraction. Neutron noise experiments exploit the statistical correlations in neutron detector signals via noise analysis methods, such as the Rossi-α or PSD method. The results are then used for code validation, nuclear data feedback or safety monitoring purposes. For MSRs, the flowing fuel and the therefore flowing precursors leads to a unique dynamic behavior that could be experimentally studied with neutron noise techniques. For example, βeff depends on the fluid velocity: For higher velocities the precursors are swept out of the core and therefore might not contribute to the reactivity, and in many MSR designs βeff therefore goes down with higher flow rate. In this work, we present simulations using the MSRE model in Serpent 2 to predict neutron noise curves for different flow rates. Our approach is new in its use of explicit Monte Carlo modeling for noise experiments in MSRs, with a simplified treatment of the precursor flow. Our results indicate that noise experiments in zero-power MSRs are feasible and that noise experiments could be used to measure recirculation time and kinetic parameters.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-11-06
DOI
https://doi.org/10.1051/epjconf/202533804011/pdf
Primary Topic
Nuclear reactor physics and engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting Neutron Noise Detector Responses for Zero-Power Molten Salt Reactor Experiments

Springer Link (Chiba Institute of Technology)
Nuclear reactor physics and engineering
article

Predicting Neutron Noise Detector Responses for Zero-Power Molten Salt Reactor Experiments

article en

Abstract

We use Monte Carlo simulations to predict the responses of neutron noise experiments in zero-power Molten Salt Reactors (MSRs). As for conventional reactors, the initial testing of a newly constructed reactor often comprises zero-power tests and criticality experiments. In zero-power environments, neutron noise experiments can be part of the experimental portfolio to provide experimental data on integral kinetic parameters such as the prompt neutron decay constant or the effective delayed neutron fraction. Neutron noise experiments exploit the statistical correlations in neutron detector signals via noise analysis methods, such as the Rossi-α or PSD method. The results are then used for code validation, nuclear data feedback or safety monitoring purposes. For MSRs, the flowing fuel and the therefore flowing precursors leads to a unique dynamic behavior that could be experimentally studied with neutron noise techniques. For example, βeff depends on the fluid velocity: For higher velocities the precursors are swept out of the core and therefore might not contribute to the reactivity, and in many MSR designs βeff therefore goes down with higher flow rate. In this work, we present simulations using the MSRE model in Serpent 2 to predict neutron noise curves for different flow rates. Our approach is new in its use of explicit Monte Carlo modeling for noise experiments in MSRs, with a simplified treatment of the precursor flow. Our results indicate that noise experiments in zero-power MSRs are feasible and that noise experiments could be used to measure recirculation time and kinetic parameters.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 28%
Nuclear reactor physics and engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.