Development of a new efficient method using genetic algorithm for increasing of fuel rod life time

Taheranpour, N.; Talebi, S.

doi:10.1016/j.pnucene.2020.103600

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…Unlike single‐objective optimization, in which usually only one unique optimal solution could be found, there might be a number of optimal solutions for multi‐objective optimization problems. A widely used approach to perform multi‐objective optimization is to convert the multi‐objective problem to a single objective problem by adding the weighting factors for each objective function 29 . However, this approach inevitably adds some biases of decision‐makers to the optimization problem, resulting in insufficient exploration of the optimal solution space.…”

Section: Multi‐objective Optimization Frameworkmentioning

confidence: 99%

“…A widely used approach to perform multi-objective optimization is to convert the multi-objective problem to a single objective problem by adding the weighting factors for each objective F I G U R E 4 Fuel-cladding gap width along with the increase of fuel burn up F I G U R E 5 Fuel rod inner pressure along with the increase of fuel burn up F I G U R E 6 Total fission gas produced in fuel along with the increase of fuel burn up function. 29 However, this approach inevitably adds some biases of decision-makers to the optimization problem, resulting in insufficient exploration of the optimal solution space. MOGA has the capability of global optimization and was employed in this work to get the non-dominated solutions (also refers to Pareto set), which could present more specific information about the design space.…”

Section: Objective Functions and Design Parametersmentioning

confidence: 99%

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Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Chen

Zhou

et al. 2022

Intl J of Energy Research

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Summary Among various accident tolerant fuel (ATF) concepts, U3Si2–FeCrAl fuel systems are considered as ones of the most potential fuel for the next generation light water reactor. In this work, a multi‐objective optimization framework based on multi‐objective genetic algorithm (GA) and Gaussian process (GP) was established for the optimal design of U3Si2–FeCrAl ATF fuel element. The coupling of GA and surrogate GP model could take advantage of the high fidelity of multi‐physics modeling and the global searching capability of GA, therefore allowing to perform a relatively fast and accurate multi‐objective optimization design for the U3Si2–FeCrAl ATF fuel element. Maximum fuel temperature, maximum cladding Von–Mises stress, and maximum plenum pressure are considered as the three objective functions for the optimization problem in this study. According to the Pareto approximation surface obtained in the optimization process, a lowest maximum fuel temperature of 871 K, a lowest maximum cladding stress of 87.9 MPa, and a lowest plenum pressure of 3.1 MPa for the U3Si2–FeCrAl ATF fuel element could be achieved based on different design parameters. The multi‐objective optimization framework developed in this work could perform as an efficient tool for the multi‐objective optimization design of the ATF fuel element.

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Section: Multi‐objective Optimization Frameworkmentioning

confidence: 99%

Section: Objective Functions and Design Parametersmentioning

confidence: 99%

Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Chen

Zhou

et al. 2022

Intl J of Energy Research

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“…Genetic algorithms are metaheuristic algorithms inspired by natural selection processes and belong to the broad category of evolutionary algorithms. Genetic algorithms typically rely on biologically inspired operators such as variation, crossover and selection to generate high-quality solutions to optimize and search for problems [ 41 , 42 ]. Its main advantages are robustness, simplicity and generality.…”

Section: Optimization Of Hot Stamping Process Parameters Of Automobile S-railmentioning

confidence: 99%

Research on High Temperature Stamping Forming Performance and Process Parameters Optimization of 7075 Aluminum Alloy

Huang

et al. 2021

Materials

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The stress strain curve of 7075 aluminum alloy in the temperature range of 310 °C to 410 °C was obtained by Gleeble-3800. By Nakazima test, the isothermal thermoforming limit diagrams of 7075 aluminum alloy at different deformation temperatures and stamping speeds were acquired. Moreover, the parameters of automotive S-rail hot stamping process were optimized by GA-BP neural network. The results show that the forming limit curve of 7075 aluminum alloy increases as the deformation temperature and stamping speed increase. The predicted optimal parameters for hot stamping of automotive S-rails by GA-BP neural network are: stamping speed is 50 mm/s, friction coefficient between die and blank is 0.1, and blank holder force is 5 kN. The maximum thinning rate at this process parameter is 9.37%, which provided a reference for 7075 aluminum alloy automotive S-rail hot stamping.

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“…As it is known, one of the priority tasks in the development of nuclear energy is the development of new types of nuclear fuel, which can significantly increase the productivity of nuclear installations by increasing the degree of fuel burnup [1][2][3]. The main criteria for new types of nuclear fuel are: (1) the possibility of operation in a wide temperature range; (2) high hardness and strength of fuel cells; (3) high resistance to the processes of phase transformations, as well as thermal expansion; (4) resistance to radiation damage and their accumulation during operation [4,5]. Additionally, an important factor in the development of new types of nuclear fuel is given to the possibility of replacing traditional uranium fuel with plutonium, the interest in which lies in the possibility of eliminating the accumulation of transuranium elements, uranium decay products, and radioactive waste [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Synthesis, Phase Transformations and Strength Properties of Nanostructured (1 − x)ZrO2 − xCeO2 Composite Ceramics

et al. 2022

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The aim of this work is to study the properties of nanostructured (1 − x)ZrO2 − xCeO2 composite ceramics, depending on the content of oxide components, as well as to establish the relationship between the phase composition of ceramics and strength properties. The choice of (1− x)ZrO2 − xCeO2 composite ceramics as objects of study is due to the great prospects for using them as the basis for inert matrix materials for nuclear dispersed fuel, which can replace traditional uranium fuel in high-temperature nuclear reactors. Using X-ray diffraction, it was found that the variation of the oxide components leads to phase transformations of the Monoclinic-ZrO2 → Monoclinic − Zr0.98Ce0.02O2/Tetragonal − ZrO2 → Tetragonal − Zr0.85Ce0.15O2 → Tetragonal − ZrCeO4/Ce0.1Zr0.9O2 type. As a result of mechanical tests, it was found that the formation of tetragonal phases in the structure of ceramics leads to strengthening of ceramics and an increase in crack resistance, which is due not only to an increase in the crystallinity degree, but also to the effect of dislocation hardening associated with a decrease in grain size. It has been established that a change in the phase composition due to phase transformations and displacement of the ZrO2 phase from the ceramic structure with its transformation into the phase of partial replacement of Zr0.85Ce0.15O2 or Ce0.1Zr0.9O2 leads to the strengthening of ceramics by more than 3.5–4 times. The results of resistance to crack formation under single compression showed that the formation of the ZrCeO4 phase in the structure of ceramics leads to an increase in the resistance of ceramics to cracking by more than 2.5 times.

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Development of a new efficient method using genetic algorithm for increasing of fuel rod life time

Cited by 4 publications

References 4 publications

Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Research on High Temperature Stamping Forming Performance and Process Parameters Optimization of 7075 Aluminum Alloy

Synthesis, Phase Transformations and Strength Properties of Nanostructured (1 − x)ZrO2 − xCeO2 Composite Ceramics

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Development of a new efficient method using genetic algorithm for increasing of fuel rod life time

Cited by 4 publications

References 4 publications

Multi‐objective optimization design of U 3 Si 2 –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Multi‐objective optimization design of U 3 Si 2 –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Research on High Temperature Stamping Forming Performance and Process Parameters Optimization of 7075 Aluminum Alloy

Synthesis, Phase Transformations and Strength Properties of Nanostructured (1 − x)ZrO2 − xCeO2 Composite Ceramics

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Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm

Multi‐objective optimization design of U ₃ Si ₂ –FeCrAl accident tolerant fuel elements based on Gaussian process and genetic algorithm