ORIGINAL RESEARCH article
Front. Nucl. Eng.
Sec. Nuclear Reactor Design
This article is part of the Research TopicMultiphysics Methods and Analysis Applied to Nuclear Reactor Systems - Volume IIView all articles
Enhancing Fast Neutron Irradiation in Thermal Neutron Spectrum Reactors Through Python-Based Multi-Objective Optimization
Provisionally accepted
- Idaho National Laboratory (DOE), Idaho Falls, United States
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This work reports on a pilot study for optimizing the design of a fast neutron irradiation experiment in a thermal neutron spectrum, specifically the Advanced Test Reactor (ATR). A fast and robust multi-objective optimization workflow that leverages Python-based open-source tools was developed and applied to the ATR to optimize experiment design and boost fast energy neutrons at a desired irradiation location. Three design options were explored to minimize thermal and epithermal neutron flux, deposited heat, and total estimated cost while maximizing the absolute fast neutron flux. This was achieved by considering several irradiation positions in the ATR with different combinations and thicknesses of filter and booster materials. The developed workflow utilizes high-fidelity Monte Carlo calculations to train a surrogate model of each objective function being optimized, thereby reducing computational efforts while searching for the optimized set of solutions. The results show that absolute fast neutron flux increased approximately 30% to 55% in regions with a harder spectrum, while the absolute fast neutron flux increased significantly by 7 to 10 times in regions with a softer spectrum outside the core but still lower than the regions with harder spectrum. Also, The predictions of the surrogate models were verified against the high-fidelity Monte Carlo calculations, and these tests showed that the surrogate models made accurate predictions.
Keywords: ATR, Fast Neutron Booster, multi-objective optimization, Surrogate model, Thermal NeutronFilter
Received: 28 Dec 2025; Accepted: 10 Feb 2026.
Copyright: © 2026 Jaradat and Brookman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mustafa K Jaradat
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