Evolutionary simulated annealing for fuel loading optimization of VVER-1000 reactor

Tran, Viet-Phu; Phan, Giang T.T.; Hoang, Van-Khanh; Ha, Pham Nhu Viet; Yamamoto, Akio; Tran, Hoai-Nam

doi:10.1016/j.anucene.2020.107938

Cited by 14 publications

(1 citation statement)

References 32 publications

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“…Ordinarily, a fitness function is used to combine these objectives in the optimization process. Various meta-heuristic approaches have been contributed to solve the ICFM problem, such as Simulated Annealing [1], Genetic Algorithm [2][3], Particle Swarm Optimization [4], Differential Evolution [5], and so on. Genetic Algorithm (GA), initially developed by Holland, is among the meta-heuristic search algorithms based on Darwin's principle of the natural selection and evolution of the population [6].…”

Section: Iintroductionmentioning

confidence: 99%

Improved Genetic algorithm for fuel loading optimization of the DNRR with HEU fuel

Phan,

Tran,

2023

Nucl. Sci. and Tech.

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This paper investigates the performance of genetic algorithm (GA) with improved selection techniques, i.e. Tournament and Roulette Wheel, applied to in-core fuel management of the Dalat nuclear research reactor (DNRR). Numerical calculations have been performed based on the DNRR core with 100 HEU fuel bundles. The optimal fitness function was chosen to maximize the keff and minimize the power peaking factor. The statistical analysis using Mann-Whitney test shows that the performance of GA with Tournament selection is advantageous over the Roulette Wheel selection in the ICFM problem of the DNRR. The optimal core configurations obtained with the improved GA methods have the keff values greater by about 500 pcm, and the PPF lower by about 4.0% compared to the reference core.

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Section: Iintroductionmentioning

confidence: 99%

Improved Genetic algorithm for fuel loading optimization of the DNRR with HEU fuel

Phan,

Tran,

2023

Nucl. Sci. and Tech.

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Feed Formula Optimization Based on Improved Tabu Search Algorithm

Zhang

Shen

2021

Neural Computing for Advanced Applications

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Employing adaptive fuzzy computing for RCP intelligent control and fault diagnosis

Aboshosha,

Hamad

2023

NUCL SCI TECH

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Loss of coolant accident (LOCA), loss of fluid accident (LOFA), and loss of vacuum accident (LOVA) are the most severe accidents that can occur in nuclear power reactors (NPRs). These accidents occur when the reactor loses its cooling media, leading to uncontrolled chain reactions akin to a nuclear bomb. This article is focused on exploring methods to prevent such accidents and ensure that the reactor cooling system remains fully controlled. The reactor coolant pump (RCP) has a pivotal role in facilitating heat exchange between the primary cycle, which is connected to the reactor core, and the secondary cycle associated with the steam generator. Furthermore, the RCP is integral to preventing catastrophic events such as LOCA, LOFA, and LOVA accidents. In this study, we discuss the most critical aspects related to the RCP, specifically focusing on RCP control and RCP fault diagnosis. The AI-based adaptive fuzzy method is used to regulate the RCP’s speed and torque, whereas the neural fault diagnosis system (NFDS) is implemented for alarm signaling and fault diagnosis in nuclear reactors. To address the limitations of linguistic and statistical intelligence approaches, an integration of the statistical approach with fuzzy logic has been proposed. This integrated system leverages the strengths of both methods. Adaptive fuzzy control was applied to the VVER 1200 NPR-RCP induction motor, and the NFDS was implemented on the Kori-2 NPR-RCP.

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Evolutionary simulated annealing for fuel loading optimization of VVER-1000 reactor

Cited by 14 publications

References 32 publications

Improved Genetic algorithm for fuel loading optimization of the DNRR with HEU fuel

Improved Genetic algorithm for fuel loading optimization of the DNRR with HEU fuel

Feed Formula Optimization Based on Improved Tabu Search Algorithm

Employing adaptive fuzzy computing for RCP intelligent control and fault diagnosis

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