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Hybrid of the fuzzy logic controller with the harmony search algorithm to PWR in-core fuel management optimization

NUCLEAR ENGINEERING AND TECHNOLOGY 2021年第11期53卷 3665-3674页

作者： Mahmoudi, Sayyed Mostafa Rad, Milad Mansouri Ochbelagh, Dariush Rezaei Amirkabir Univ Technol Tehran Polytech Dept Energy Engn & Phys Tehran Iran

One of the important parts of the in-core fuel management is loading pattern optimization (LPO). The loading pattern optimization as a reasonable design of the in-core fuel management can improve both economic and safe aspects of the nuclear reactor. This work proposes the hybrid of fuzzy logic controller with harmony search algorithm (HS) for loading pattern optimization in a pressurized water reactor. The music improvisation process to find a pleasing harmony is inspiring the harmony search algorithm. In this work, the adjustment of the harmony search algorithm parameters such as the bandwidth and the pitch adjustment rate are increasing performance of the proposed algorithm which is done through a fuzzy logic controller. Hence, membership functions and fuzzy rules are designed to improve the performance of the HS algorithm and achieve optimal results. The objective of the method is finding an optimum core arrangement according to safety and economic aspects such as reduction of power peaking factor (PPF) and increase of effective multiplication factor (Keff). The proposed approach effectiveness has been tried in two cases, Michalewicz's bivariate function problem and NEACRP LWR core. The results show that by using fuzzy harmony search algorithm the value of the fitness function is improved by 15.35%. Finally, with regard to the new solutions proposed in this research it could be used as a trustworthy method for other optimization issues of engineering field. (c) 2021 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Harmony search algorithm Fuzzy logic controller loading pattern optimization NEACRP LWR core

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optimization of IEA-R1 reactor core parameters using the particle swarm algorithm

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NUCLEAR ENGINEERING AND DESIGN 2023年 415卷

作者： dos Santos, Thiago A. Genezini, Frederico A. de Stefani, Giovanni L. IPEN Nucl & Energy Res Inst Sao Paulo Brazil Univ Fed Rio de Janeiro UFRJ Rio De Janeiro Brazil

This work aims on the development of a FORTRAN 90 code to solve the loading pattern optimization Problem (LPOP) in the IEA-R1 research reactor at the Nuclear and Energy Research Institute (IPEN/CNEN-SP) in Sa similar to o Paulo, Brazil. The code integrates the Particle Swarm optimization (PSO) method, with the current reactor calculation methodology. The objective function seeks to maximize the effective multiplication factor (keff), minimize the peak power factor (PPF), and achieve the most uniform neutron flux distribution possible. A comparison with the parameters of the reactor's current configuration, and the code successfully finds solutions meeting the standard problem requirements. The new configuration enhances peak power (6.93%) and variance (9.62%), slightly increases neutron flux (0.48%), and marginally reduces in keff (0.45%). Additionally, it lowers the maximum fuel cladding temperature (0.7%), contributing to reactor safety.

关键词： loading pattern optimization Particle swarm Research reactors

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

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ANNALS OF NUCLEAR ENERGY 2021年 151卷 107938-107938页

作者： Viet-Phu Tran Phan, Giang T. T. Van-Khanh Hoang Pham Nhu Viet Ha Yamamoto, Akio Hoai-Nam Tran VINATOM Inst Nucl Sci & Technol 179 Hoang Quoc Viet Hanoi 100000 Vietnam Duy Tan Univ Inst Fundamental & Appl Sci Ho Chi Minh City 700000 Vietnam Duy Tan Univ Fac Nat Sci Da Nang 550000 Vietnam Nagoya Univ Grad Sch Engn Chikusa Ku Furo Cho Nagoya Aichi 4648603 Japan

An evolutionary simulated annealing (ESA) method has been developed for the problem of fuel loading optimization of VVER-1000 reactor. The ESA method improves original simulated annealing by using crossover and mutation operators to generate new trial loading patterns (LPs). A core physics calculation code for fuel LP optimization of VVER reactors (LPO-V) has been developed and verified based on a VVER-1000 MOX benchmark core in comparison with MCNP4c calculations. Calculations for optimizing fuel LP of the VVER-1000 MOX core have been conducted using the ESA method in comparison with simulated annealing (SA) and adaptive simulated annealing (ASA). Statistical differences between these methods were also evaluated based on the Mann-Whitney U test. The results show that the ESA method is advantageous over the SA and ASA. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Evolutionary simulated annealing loading pattern optimization VVER-1000

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Fuzzy Logics as an Integral Part of Evolutionary Algorithms

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NUCLEAR SCIENCE AND ENGINEERING 2019年第10期193卷 1160-1171页

作者： Thakur, Amit Kannan, Umasankari Bhabha Atom Res Ctr Reactor Phys Design Div Mumbai 400085 Maharashtra India

Evolutionary algorithms play an important role for solving various optimization problems related to fuel management in reactor physics like core loading pattern optimization (LPO) or refueling. In general, all algorithms make a sample of solution candidates and evaluate the fitness of all candidates, and then the candidates with better fitness value are used to generate the next sample of solution candidates. In optimization algorithms, internal parameters [like population size, weighting factor in estimation of distribution algorithm (EDA) and population size, cross-over rate, etc., in Genetic Algorithm (GA)] have a stiffness problem as the value of these parameters is fixed at the first generation and is not being changed subsequently. However, the flexibility of changing the value of even one internal parameter during the generations will make the algorithm more efficient. In this paper we propose that fuzzy logics can be used in an innovative way to eliminate the stiffness problem related to internal parameters in evolutionary algorithms. As a test case, EDA for initial core LPO of the advanced heavy water reactor is chosen, and the use of fuzzy logics has shown a significant improvement in the algorithm's performance. The appropriate value of weighting factor alpha in EDA has been predicted using fuzzy logics in each generation, and this has resulted in efficiency improvement of the algorithm. The improved methodology is expected to give better performance with other optimization algorithms, such as the GA or Ant Colony optimization Algorithm, etc.

关键词： loading pattern optimization advanced heavy water reactor estimation of distribution algorithm fuzzy logics

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An Improved Inverse Analysis Model for Fuel loading pattern optimization

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JOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY 2009年第12期46卷 1162-1169页

作者： Tran, Hoai Nam Yamamoto, Akio Yamane, Yoshihiro Nagoya Univ Dept Mat Phys & Energy Engn Chikusa Ku Nagoya Aichi 4648603 Japan

An improved inverse analysis model for fuel loading pattern (LP) optimization is proposed to reproduce a desired in-core power distribution from available fuel assemblies based on the inverse analysis of diffusion equations. In the present approach, the inverse analysis is simplified as a fixed-source problem rather than an eigenvalue problem in a previous work. By using the one-to-one correspondence between the power distribution and reactivity distribution, a target reactivity distribution is solved from a desired power distribution through the inverse analysis. The reactivity of available assemblies is evaluated using a modified effective fast-group model with a higher order correction of leakage effect. A candidate LP is determined by individually matching the reactivity of available assemblies to the target in-core reactivity distribution using a stable matching algorithm. The process of predicting the reactivity of available assemblies and matching them to the target reactivity distribution is repeated until the convergence condition is satisfied. Validation of the model has been confirmed with a reference PWR core. The model is expected to be applicable to a problem of multicycle loading pattern optimization.

关键词： inverse analysis power distribution loading pattern optimization modified effective fast-group model stable matching algorithm

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Development of a core management tool for MYRRHA

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ENERGY CONVERSION AND MANAGEMENT 2013年第Oct.期74卷 562-568页

作者： Jaluvka, David Van den Eynde, Gert Vandewalle, Stefan CEN SCK Nucl Syst Phys Grp B-2400 Mol Belgium Katholieke Univ Leuven Dept Comp Sci B-3001 Heverlee Belgium

MYRRHA is an advanced multi-purpose irradiation facility under development at *** in Mol, Belgium. In order to ensure an economical and safe operation of the reactor, an in-core fuel management tool is being developed within the project to address the loading pattern optimization problem. In the paper, the current version of the tool - its architecture and design, unique features, and the field of its application, are presented. In the second part of the paper, the tool's capabilities are demonstrated on simple MYRRHA in-core fuel management optimization problems. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： loading pattern optimization In-core fuel management optimization MYRRHA Genetic Algorithm

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Self-adaptive global best harmony search algorithm applied to reactor core fuel management optimization

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ANNALS OF NUCLEAR ENERGY 2013年 62卷 86-102页

作者： Poursalehi, N. Zolfaghari, A. Minuchehr, A. Valavi, K. Shahid Beheshti Univ Dept Nucl Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Dept Nucl Engn Tehran Iran

The aim of this work is to apply the new developed optimization algorithm, Self-adaptive Global best Harmony Search (SGHS), for PWRs fuel management optimization. SGHS algorithm has some modifications in comparison with basic Harmony Search (HS) and Global-best Harmony Search (GHS) algorithms such as dynamically change of parameters. For the demonstration of SGHS ability to find an optimal configuration of fuel assemblies, basic Harmony Search (HS) and Global-best Harmony Search (GHS) algorithms also have been developed and investigated. For this purpose, Self-adaptive Global best Harmony Search Nodal Expansion package (SGHSNE) has been developed implementing HS, GHS and SGHS optimization algorithms for the fuel management operation of nuclear reactor cores. This package uses developed average current nodal expansion code which solves the multi group diffusion equation by employment of first and second orders of Nodal Expansion Method (NEM) for two dimensional, hexagonal and rectangular geometries, respectively, by one node per a FA. loading pattern optimization was performed using SGHSNE package for some test cases to present the SGHS algorithm capability in converging to near optimal loading pattern. Results indicate that the convergence rate and reliability of the SGHS method are quite promising and practically, SGHS improves the quality of loading pattern optimization results relative to HS and GHS algorithms. As a result, it has the potential to be used in the other nuclear engineering optimization problems. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： loading pattern optimization Self-adaptive global best harmony search algorithm Nodal expansion method Rectangular and hexagonal geometries

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The optimum design of tight lattice reactor core with thin rod bundles

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PROGRESS IN NUCLEAR ENERGY 2012年 59卷 49-58页

作者： Dai, Chunhui Wei, Xinyu Tai, Yun Zhao, Fuyu Xi An Jiao Tong Univ Dept Nucl Engn Sch Energy & Power Engn Xian 710049 Shaanxi Peoples R China

The fuel height, rod diameter, pitch, and the loading pattern are all important parameters in the reactor core design process. Based on the analysis of the core performance, optimization calculation is performed on the three objective functions of ABV-6M reactor, i.e., power density, coolant temperature difference between the inlet and outlet, and flow-induced vibration are proposed for optimization calculation. Then a multi-objective problem (MOP) model is applied and computed optimally by non-dominated sorting genetic algorithm (NSGA-II) with the aim of maximizing power density and temperature difference as well as minimizing the flow-induced vibration. The results of optimal designs called 'Pareto-optimal solutions' are a set of multiple optimum solutions, from which the final optimization can be chosen after sensitivity analysis is performed. On the basis of lattice parameters optimization, the radial one-dimensional fuel loading pattern was optimized for achieving the optimum fuel utilization. The typical optimum design considered to be safe in a verification check showed that tight lattice effectively improved the reactor performances and saved the fuel consumption. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Tight-lattice Multi-objective optimization loading pattern optimization

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An Interval Bound Algorithm of optimizing reactor core loading pattern by using reactivity interval schema

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ANNALS OF NUCLEAR ENERGY 2011年第12期38卷 2787-2796页

作者： Gong, Zhaohu Wang, Kan Yao, Dong Tsinghua Univ Dept Engn Phys Beijing 100084 Peoples R China Nucl Power Inst China Sci & Technol Reactor Syst Design Technol Lab Chengdu 610041 Sichuan Peoples R China

In order to optimize the core loading pattern in Nuclear Power Plants, the paper presents a new optimization method - Interval Bound Algorithm (IBA). Similar to the typical population based algorithms, e.g. genetic algorithm, IBA maintains a population of solutions and evolves them during the optimization process. IBA acquires the solution by statistical learning and sampling the control variable intervals of the population in each iteration. The control variables are the transforms of the reactivity of fuel assemblies or the worth of burnable poisons, which are the crucial heuristic information for loading pattern optimization problems. IBA can deal with the relationship between the dependent variables by defining the control variables. Based on the IBA algorithm, a parallel loading pattern optimization code, named IBALPO, has been developed. To deal with multiple objectives and constraints, the Dynamic Discontinuous Weight Factors (DDWF) for the fitness function have been used in IBALPO. Finally, the code system has been used to solve a realistic reloading problem and a better pattern has been obtained compared with the ones searched by engineers and genetic algorithm, thus the performance of the code is proved. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： loading pattern optimization Interval Bound Algorithm Multi-objective optimization Dynamic Discontinuous Weight Factors Reactivity

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Application of neural network for loading pattern screening of in-core optimization calculations

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NUCLEAR TECHNOLOGY 2003年第1期144卷 63-75页

作者： Yamamoto, A Nucl Fuel Ind Ltd Fuel Engn & Dev Dept Kumatori Osaka 5900481 Japan

In this paper, neural networks are used to predict core characteristics, and the predicted results are used to screen poor loading patterns in order to improve optimization efficiency. The radial peaking factor, cycle length, and maximum burnup through the cycle depletion calculations were evaluated by the neural network, and these core characteristics were used for screening. The screened loading patterns were evaluated by the core calculation code as ordinary in-core optimizations. The calculation results of the test problem indicated that the loading pattern screening using the neural network effectively improves the optimization results. Since the computation time for a cycle depletion calculation with the neural network is quite short, the computation load for the screening is negligible. Since the neural network is periodically retrained using the latest evaluation results of the core calculation code, its prediction accuracy is continuously improved during the optimization. The typical prediction accuracies of the radial peaking factor, cycle length, and maximum burnup in the latter part of the optimizations were 3 to 4%, 0.01 to 0.02 GWd/t, and 0.2 GWd/t, respectively, in the test problem. These accuracies are satisfactory for loading pattern screening.

关键词： loading pattern optimization neural network candidate screening

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