Solving Neutron Transport Using an Implementation of the Method of Characteristics (MOC) and its Assessment

The analysis of reactor design requires solving the neutron transport accurately for diverse scenarios. In this study, we wrote a neutron transport code utilizing the Method of Characteristics to explore and understand this technique. We tested the code against different benchmarks to assess its accuracy in fnding k-eigenvalue and pin-power. We then compared the results with those from the stochastic code OpenMC and other deterministic codes from the literature. We calculated the eigenvalues closer to other deterministic codes than the Monte Carlo code. However, these results were closer to the Monte Carlo code than most other deterministic codes. We then tested the code with four NEA Benchmark problems to study its performance in resolving pin-power distribution. While there were some discrepancies in the k-eigenvalue for benchmarks C1 and C4V, the other two benchmarks, showed excellent agreement. However, all these benchmark solutions had appreciable errors in pin-power distributions.

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Publication Details

Published
2024-12-18
DOI
https://doi.org/10.1109/icece64886.2024.11024675
Primary Topic
Nuclear reactor physics and engineering
Type
article
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article

Solving Neutron Transport Using an Implementation of the Method of Characteristics (MOC) and its Assessment

Khorshed Ahmad Kabir, Kazi Azman Rafee
Nuclear reactor physics and engineering
article

Solving Neutron Transport Using an Implementation of the Method of Characteristics (MOC) and its Assessment

Khorshed Ahmad Kabir, Kazi Azman Rafee
article en

Abstract

The analysis of reactor design requires solving the neutron transport accurately for diverse scenarios. In this study, we wrote a neutron transport code utilizing the Method of Characteristics to explore and understand this technique. We tested the code against different benchmarks to assess its accuracy in fnding k-eigenvalue and pin-power. We then compared the results with those from the stochastic code OpenMC and other deterministic codes from the literature. We calculated the eigenvalues closer to other deterministic codes than the Monte Carlo code. However, these results were closer to the Monte Carlo code than most other deterministic codes. We then tested the code with four NEA Benchmark problems to study its performance in resolving pin-power distribution. While there were some discrepancies in the k-eigenvalue for benchmarks C1 and C4V, the other two benchmarks, showed excellent agreement. However, all these benchmark solutions had appreciable errors in pin-power distributions.

Bangladesh University of Engineering and Technology (BD), University of Dhaka (BD)
Openalex Percentile: Top 51%
Nuclear reactor physics and engineering
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