Optimizing the core loading pattern and fuel composition in a hexagonal small modular nuclear reactor via ANN-PSO approach Article Swipe
G.R. Ansarifar
,
Masoud Karimi
,
H. Zayermohammadi Rishehri
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rineng.2025.104895
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.rineng.2025.104895
Small Modular Reactors (SMRs), such as the NuScale Power Module (NPM), have gained considerable attention in recent years. However, significant efforts are needed to enhance safety. The utilization of hexagonal Fuel Assemblies (FAs) offers numerous benefits from both neutronic and thermal-hydraulic perspectives. By leveraging these advantages, reactors performance can be improved without compromising safety regulations. Additionally, there has been consideration given to the use of burnable neutron absorbers, such as gadolinia, in novel nuclear fuels. This paper focuses on the redesign and evaluation of the NPM core with hexagonal FAs. The study investigates the impact of altering the arrangement pattern of FAs and the quantity of gadolinia-containing rods within these assemblies. Various models featuring hexagonal FAs, containing different mixed fuels, were tested through a series of simulations. Calculations were repeated under both Clean-Cold and Hot Full Power (HFP) conditions for each model. To examine different aspects of reactor performance, the concentration of the gadolinia absorber was varied, and its impact on parameters such as Temperature Coefficients (TCs), Power Peaking Factors (PPFs), and excess reactivity was investigated. The investigation involved simulations using the WIMS and CITATION neutronic calculation codes. The gadolinia concentration was effectively optimized using the Particle Swarm Optimization (PSO) algorithm. The best model, based on TCs and PPFs, was selected. The analysis findings revealed significant improvements in safety parameters such as TCs and PPFs for optimal core loading pattern with optimized gadolinia (Gd2O3) Concentration.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.rineng.2025.104895
- OA Status
- gold
- Cited By
- 3
- References
- 28
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4409371258Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.rineng.2025.104895Digital Object Identifier
- Title
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Optimizing the core loading pattern and fuel composition in a hexagonal small modular nuclear reactor via ANN-PSO approachWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-11Full publication date if available
- Authors
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G.R. Ansarifar, Masoud Karimi, H. Zayermohammadi RishehriList of authors in order
- Landing page
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https://doi.org/10.1016/j.rineng.2025.104895Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.rineng.2025.104895Direct OA link when available
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Modular design, Hexagonal crystal system, Nuclear engineering, Core (optical fiber), Composition (language), Materials science, Chemical engineering, Computer science, Chemistry, Engineering, Composite material, Crystallography, Operating system, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
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3Total citation count in OpenAlex
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2025: 3Per-year citation counts (last 5 years)
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28Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.excess | 172 |
| abstract_inverted_index.fuels, | 119 |
| abstract_inverted_index.fuels. | 74 |
| abstract_inverted_index.gained | 12 |
| abstract_inverted_index.impact | 94, 159 |
| abstract_inverted_index.model, | 203 |
| abstract_inverted_index.model. | 141 |
| abstract_inverted_index.models | 112 |
| abstract_inverted_index.needed | 22 |
| abstract_inverted_index.offers | 33 |
| abstract_inverted_index.recent | 16 |
| abstract_inverted_index.safety | 53, 218 |
| abstract_inverted_index.series | 124 |
| abstract_inverted_index.tested | 121 |
| abstract_inverted_index.within | 108 |
| abstract_inverted_index.years. | 17 |
| abstract_inverted_index.(Gd2O3) | 233 |
| abstract_inverted_index.(PPFs), | 170 |
| abstract_inverted_index.(SMRs), | 3 |
| abstract_inverted_index.Factors | 169 |
| abstract_inverted_index.Modular | 1 |
| abstract_inverted_index.NuScale | 7 |
| abstract_inverted_index.Peaking | 168 |
| abstract_inverted_index.Various | 111 |
| abstract_inverted_index.aspects | 145 |
| abstract_inverted_index.efforts | 20 |
| abstract_inverted_index.enhance | 24 |
| abstract_inverted_index.examine | 143 |
| abstract_inverted_index.focuses | 77 |
| abstract_inverted_index.loading | 228 |
| abstract_inverted_index.neutron | 66 |
| abstract_inverted_index.nuclear | 73 |
| abstract_inverted_index.optimal | 226 |
| abstract_inverted_index.pattern | 99, 229 |
| abstract_inverted_index.reactor | 147 |
| abstract_inverted_index.safety. | 25 |
| abstract_inverted_index.through | 122 |
| abstract_inverted_index.varied, | 156 |
| abstract_inverted_index.without | 51 |
| abstract_inverted_index.CITATION | 184 |
| abstract_inverted_index.However, | 18 |
| abstract_inverted_index.Particle | 196 |
| abstract_inverted_index.Reactors | 2 |
| abstract_inverted_index.absorber | 154 |
| abstract_inverted_index.altering | 96 |
| abstract_inverted_index.analysis | 212 |
| abstract_inverted_index.benefits | 35 |
| abstract_inverted_index.burnable | 65 |
| abstract_inverted_index.findings | 213 |
| abstract_inverted_index.improved | 50 |
| abstract_inverted_index.involved | 178 |
| abstract_inverted_index.numerous | 34 |
| abstract_inverted_index.quantity | 104 |
| abstract_inverted_index.reactors | 46 |
| abstract_inverted_index.redesign | 80 |
| abstract_inverted_index.repeated | 129 |
| abstract_inverted_index.revealed | 214 |
| abstract_inverted_index.attention | 14 |
| abstract_inverted_index.different | 117, 144 |
| abstract_inverted_index.featuring | 113 |
| abstract_inverted_index.gadolinia | 153, 189, 232 |
| abstract_inverted_index.hexagonal | 29, 88, 114 |
| abstract_inverted_index.neutronic | 38, 185 |
| abstract_inverted_index.optimized | 193, 231 |
| abstract_inverted_index.selected. | 210 |
| abstract_inverted_index.Assemblies | 31 |
| abstract_inverted_index.Clean-Cold | 132 |
| abstract_inverted_index.absorbers, | 67 |
| abstract_inverted_index.algorithm. | 200 |
| abstract_inverted_index.conditions | 138 |
| abstract_inverted_index.containing | 116 |
| abstract_inverted_index.evaluation | 82 |
| abstract_inverted_index.gadolinia, | 70 |
| abstract_inverted_index.leveraging | 43 |
| abstract_inverted_index.parameters | 161, 219 |
| abstract_inverted_index.reactivity | 173 |
| abstract_inverted_index.Temperature | 164 |
| abstract_inverted_index.advantages, | 45 |
| abstract_inverted_index.arrangement | 98 |
| abstract_inverted_index.assemblies. | 110 |
| abstract_inverted_index.calculation | 186 |
| abstract_inverted_index.effectively | 192 |
| abstract_inverted_index.performance | 47 |
| abstract_inverted_index.significant | 19, 215 |
| abstract_inverted_index.simulations | 179 |
| abstract_inverted_index.utilization | 27 |
| abstract_inverted_index.Calculations | 127 |
| abstract_inverted_index.Coefficients | 165 |
| abstract_inverted_index.Optimization | 198 |
| abstract_inverted_index.compromising | 52 |
| abstract_inverted_index.considerable | 13 |
| abstract_inverted_index.improvements | 216 |
| abstract_inverted_index.investigates | 92 |
| abstract_inverted_index.performance, | 148 |
| abstract_inverted_index.regulations. | 54 |
| abstract_inverted_index.simulations. | 126 |
| abstract_inverted_index.Additionally, | 55 |
| abstract_inverted_index.concentration | 150, 190 |
| abstract_inverted_index.consideration | 59 |
| abstract_inverted_index.investigated. | 175 |
| abstract_inverted_index.investigation | 177 |
| abstract_inverted_index.perspectives. | 41 |
| abstract_inverted_index.Concentration. | 234 |
| abstract_inverted_index.thermal-hydraulic | 40 |
| abstract_inverted_index.gadolinia-containing | 106 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.7200000286102295 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.98100697 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |