Genetic algorithm-based optimization method and system for lead-bismuth reactor wire winding fuel assembly

Abstract

The invention relates to the technical field of nuclear reactor engineering, and discloses an optimization method and system for a lead-bismuth reactor wire-wound fuel assembly based on a genetic algorithm, and the method comprises the following steps: carrying out the modeling of the wire-wound fuel assembly of a lead-bismuth reactor; under the same fluid flow boundary condition, performing steady-state computational fluid mechanics simulation on the wire-wound fuel assembly model to calculate the pressure drop of the wire-wound fuel assembly; designing a relation between a high-order polynomial construction design variable and the pressure drop based on the pressure drop; the high-order polynomial is optimized through a genetic algorithm, and the optimal design of the wire winding fuel assembly is obtained. The method solves the problems that in the prior art, wire winding fuel assemblies are not considered, and parameter design is not comprehensive, and has the advantages of being capable of giving consideration to both global search and local fine adjustment.

Description

Technical Field

[0001] The present invention relates to the field of nuclear reactor engineering technology, and more specifically, to an optimization method and system for a lead-bismuth reactor wire-wound fuel assembly based on a genetic algorithm. Background Art

[0002] Lead-bismuth reactors have become the focus of attention in the international nuclear energy community due to their significant advantages in the comprehensive utilization of nuclear energy and military-civilian integration. Despite its wide range of applications, different mission requirements have significantly different standards for technical performance, resulting in a large diversity among design schemes. Therefore, it is necessary to conduct in-depth optimization on the basis of existing schemes to meet diversified requirements. At present, the optimization design of most lead-bismuth reactors still relies on the traditional experience-driven model, that is, it mainly relies on the professional judgment and trial and error method of designers for debugging. However, this method is not only inefficient, but also difficult to fully explore the design parameter space, which makes it extremely difficult to obtain the global optimal solution, limiting the potential for design optimization and the efficiency of application promotion.

[0003] The prior art includes a fuel rod design method, system and storage medium based on a genetic algorithm, the method comprising: obtaining design parameter data and generating an initial population according to the requirements of the fuel rod design criteria; generating a child population from the initial population according to preset algorithm rules, selecting the child population and the initial population for merging analysis to generate an optimal population; combining the comprehensive performance of the fuel rod under the optimal population with the requirements of the fuel rod design criteria, conducting a comprehensive evaluation and analysis, and verifying the rationality of the parameters of the optimal population.

[0004] However, the prior art does not take wire-wound fuel assemblies into consideration and has the problem of incomplete parameter design. Therefore, how to invent an optimization method for lead-bismuth reactor wire-wound fuel assemblies based on genetic algorithms is a technical problem that urgently needs to be solved in this technical field. Summary of the invention

[0005] In order to solve the problem that the prior art does not consider wound fuel assemblies and the parameter design is not comprehensive, the present invention provides an optimization method and system for lead-bismuth reactor wound fuel assemblies based on genetic algorithms, which has the characteristics of being able to take into account both global search and local fine adjustment.

[0006] In order to achieve the above-mentioned purpose of the present invention, the technical scheme adopted is as follows: A method for optimizing lead-bismuth reactor wire-wound fuel assemblies based on a genetic algorithm comprises the following specific steps: Modeling of wire-wound fuel assemblies for lead-bismuth reactors; Under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation is performed on the wire-wound fuel assembly model to calculate the pressure drop of the wire-wound fuel assembly. Based on the pressure drop, a high-order polynomial is designed to construct the relationship between the design variables and the pressure drop; The optimal design of the wire-wound fuel assembly is obtained by optimizing high-order polynomials through genetic algorithms.

[0007] Preferably, the wire-wound fuel assembly comprises a plurality of fuel rods and a wire wrap wound around each fuel rod.

[0008] Furthermore, when performing three-dimensional modeling, a mixed horizontal uniform test design is used to establish and set key parameters including the fuel rod diameter D, the winding diameter d, the fuel rod length L, and the winding pitch P.

[0009] Furthermore, under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation is performed on the wire-wound fuel assembly model. The specific steps are as follows: Set entry conditions; Set exit conditions; Set avoidance conditions; Based on the inlet, outlet, and avoidance conditions, CFD software was used to generate the computational grid for initial simulation; Select the corresponding flow model according to the selected flow characteristics; Set the solver parameters and run the steady-state simulation; Extract pressure information from simulation results and calculate the pressure drop of the wire-wound fuel assembly.

[0010] Furthermore, the inlet conditions include flow rate, pressure and temperature parameters of the inlet.

[0011] Furthermore, the outlet conditions include pressure and flow parameters at the outflow end.

[0012] Furthermore, the avoidance conditions include no-slip conditions on the wall and thermal boundary conditions.

[0013] Furthermore, the high-order polynomial is specifically:

[0014] in, Indicates the voltage drop, is a constant, is the first design variable, and is the second design variable, For the corresponding , , The design factor, N is the number of design variables.

[0015] Furthermore, the genetic algorithm is used to optimize the high-order polynomial to obtain the optimal design of the wire-wound fuel assembly. The specific steps are as follows: A set of individuals is randomly generated, each of which is composed of a combination of design variables as a chromosome; For each individual in the population, its fitness value is calculated according to a high-order polynomial; Taking the maximum pressure drop as the optimization goal, the objective function value is converted into a fitness value; Individuals are selected from the current population to become parents of the next generation for reproduction; Randomly pair the selected parents and exchange some of their genes to form new individuals. During the exchange, one or more genes of the offspring individuals are randomly changed to increase population diversity. The offspring individuals generated through crossover and mutation replace the individuals of the previous generation to form a new population; the fitness of the new population is evaluated to determine whether the termination condition has been reached; If the termination condition is met, the design of the wire-wound fuel assembly at this time is output as the optimal design; if the termination condition is not met, the fitness value calculation step is returned to perform iterative optimization until the termination condition is met.

[0016] An optimization system for lead-bismuth reactor wire-wound fuel assemblies based on genetic algorithms, comprising a modeling module, a simulation module, and an optimization module; The modeling module is used to model the wire-wound fuel assembly of the lead-bismuth reactor; The simulation module is used to perform steady-state computational fluid dynamics simulation on the wire-wound fuel assembly model under the same fluid flow boundary conditions to calculate the pressure drop of the wire-wound fuel assembly; The optimization module is used to design a high-order polynomial based on the pressure drop to construct a display relationship between the design variables and the pressure drop; the high-order polynomial is optimized by a genetic algorithm to obtain the optimal design of the wire-wound fuel assembly.

[0017] The beneficial effects of the present invention are as follows: The present invention proposes an optimization method and system for lead-bismuth reactor wound fuel assemblies based on genetic algorithms. As a bionic optimization technology, genetic algorithms can efficiently solve complex multi-objective optimization problems with the help of population search and evolutionary strategies. By introducing this algorithm, the parameters of the wound fuel assemblies of the lead-bismuth reactor can be quickly iterated and intelligently optimized, significantly improving the design efficiency and solution quality. In addition, this method can take into account both global search and local fine adjustment, avoiding premature convergence or local optimal problems in traditional design patterns, thereby providing a high-performance design solution for multi-scenario applications of lead-bismuth reactors. The application of this innovative method will open up new directions for the development of lead-bismuth reactor technology and help it achieve more efficient and reliable applications in more fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1The invention discloses a method for optimizing a lead-bismuth reactor wire-wound fuel assembly based on a genetic algorithm.

[0019] Figure 2 This is a schematic diagram of the wire-wound fuel assembly of the lead-bismuth reactor in Example 1.

[0020] Figure 3 It is a schematic diagram of the process of optimizing the high-order polynomial by genetic algorithm in Example 2 to obtain the optimal design of the wire-wound fuel assembly. DETAILED DESCRIPTION

[0021] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Example 1 like Figure 1 As shown, a method for optimizing lead-bismuth reactor wire-wound fuel assemblies based on a genetic algorithm comprises the following specific steps: Modeling of wire-wound fuel assemblies for lead-bismuth reactors; Under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation is performed on the wire-wound fuel assembly model to calculate the pressure drop of the wire-wound fuel assembly. Based on the pressure drop, a high-order polynomial is designed to construct the relationship between the design variables and the pressure drop; The optimal design of the wire-wound fuel assembly is obtained by optimizing high-order polynomials through genetic algorithms.

[0023] In a specific embodiment, the wire-wound fuel assembly includes a plurality of fuel rods and a wire-wound wound around each fuel rod.

[0024] In this embodiment, a wire-wound fuel assembly of a lead-bismuth reactor is modeled, and the specific steps are as follows: like Figure 2 As shown, based on experimental data, three-dimensional modeling is performed considering the seven fuel rods of the wire-wound fuel assembly and the wires wound thereon.

[0025] In a specific embodiment, when performing three-dimensional modeling, a mixed horizontal uniform test design is used to establish and set key parameters including the fuel rod diameter D, the winding wire diameter d, the fuel rod length L, and the winding wire pitch P.

[0026] In a specific embodiment, under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation is performed on the wire-wound fuel assembly model, and the specific steps are as follows: Set entry conditions; Set exit conditions; Set avoidance conditions; Based on the inlet, outlet, and avoidance conditions, CFD software was used to generate the computational grid for initial simulation; Select the corresponding flow model according to the selected flow characteristics; Set the solver parameters and run the steady-state simulation; Extract pressure information from simulation results and calculate the pressure drop of the wire-wound fuel assembly.

[0027] In a specific embodiment, the inlet conditions include flow rate, pressure, and temperature parameters of the inlet.

[0028] In a specific embodiment, the outlet conditions include pressure and flow parameters at the outflow end.

[0029] In a specific embodiment, the avoidance conditions include a no-slip condition of the wall and a thermal boundary condition.

[0030] In this embodiment, coolant conditions are also set; the coolant simulated by CFD is lead bismuth, and its physical properties are fitted according to ρ(T)=11,080−1.293⋅T(kg / m³), where the unit of temperature T is ℃.

[0031] In a specific embodiment, the high-order polynomial is specifically:

[0032] in, Indicates the voltage drop, is a constant, is the first design variable, and is the second design variable, For the corresponding , , The design factor, N is the number of design variables.

[0033] Example 2 like Figure 3 As shown, in a specific embodiment, a high-order polynomial is optimized by a genetic algorithm to obtain an optimal design of a wire-wound fuel assembly, and the specific steps are: A set of individuals is randomly generated, each of which is composed of a combination of design variables as a chromosome; For each individual in the population, its fitness value is calculated according to a high-order polynomial; Taking the maximum pressure drop as the optimization goal, the objective function value is converted into a fitness value; Individuals are selected from the current population to become parents of the next generation for reproduction; In this embodiment, any of roulette wheel selection, tournament selection or random competition selection is used to select individuals from the current population; Randomly pair the selected parents and exchange some of their genes to form new individuals. During the exchange, one or more genes of the offspring individuals are randomly changed to increase population diversity. In this embodiment, the exchange method is any one of single-point crossover, double-point crossover and uniform crossover; The offspring individuals generated through crossover and mutation replace the individuals of the previous generation to form a new population; the fitness of the new population is evaluated to determine whether the termination condition has been reached; If the termination condition is met, the design of the wire-wound fuel assembly at this time is output as the optimal design; if the termination condition is not met, the fitness value calculation step is returned to perform iterative optimization until the termination condition is met.

[0034] In this embodiment, after obtaining the optimal design, it is necessary to verify the feasibility through experiments. If it is not feasible, iterative optimization is continued.

[0035] Example 3 An optimization system for lead-bismuth reactor wire-wound fuel assemblies based on genetic algorithms, comprising a modeling module, a simulation module, and an optimization module; The modeling module is used to model the wire-wound fuel assembly of the lead-bismuth reactor; The simulation module is used to perform steady-state computational fluid dynamics simulation on the wire-wound fuel assembly model under the same fluid flow boundary conditions to calculate the pressure drop of the wire-wound fuel assembly; The optimization module is used to design a high-order polynomial based on the pressure drop to construct a display relationship between the design variables and the pressure drop; the high-order polynomial is optimized by a genetic algorithm to obtain the optimal design of the wire-wound fuel assembly.

[0036] The present invention proposes a rod bundle structure optimization design system based on genetic algorithm, which aims to quickly iterate and intelligently optimize the key design parameters of lead-bismuth wound fuel assemblies, improve the design efficiency and quality, and provide key technical support for the design and operation of reactors.

[0037] Obviously, the above embodiments of the present invention are only examples for clearly explaining the present invention, and are not intended to limit the implementation methods of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. A method for optimizing lead-bismuth reactor wire-wound fuel assemblies based on genetic algorithms, characterized in that: The specific steps include: Modeling of wire-wound fuel assemblies for lead-bismuth reactors; Under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation is performed on the wire-wound fuel assembly model to calculate the pressure drop of the wire-wound fuel assembly. Based on the pressure drop, a high-order polynomial is designed to construct the relationship between the design variables and the pressure drop; The optimal design of the wire-wound fuel assembly is obtained by optimizing high-order polynomials through genetic algorithms.

2. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 1, characterized in that: The wire-wound fuel assembly comprises a plurality of fuel rods and a wire wound around each fuel rod.

3. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 2, characterized in that: When performing three-dimensional modeling, a mixed horizontal uniform test design is used to establish and set key parameters including the fuel rod diameter D, the winding diameter d, the fuel rod length L, and the winding pitch P.

4. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 1, characterized in that: Under the same fluid flow boundary conditions, a steady-state computational fluid dynamics simulation of the wire-wound fuel assembly model is carried out. The specific steps are as follows: Set entry conditions; Set exit conditions; Set avoidance conditions; Based on the inlet, outlet, and avoidance conditions, CFD software was used to generate the computational grid for initial simulation; Select the corresponding flow model according to the selected flow characteristics; Set the solver parameters and run the steady-state simulation; Extract pressure information from simulation results and calculate the pressure drop of the wire-wound fuel assembly.

5. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 4, characterized in that: The inlet conditions include flow rate, pressure and temperature parameters of the inlet.

6. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 4, characterized in that: The outlet conditions include pressure and flow parameters at the outflow end.

7. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 4, characterized in that: The avoidance conditions include no-slip conditions on the wall and thermal boundary conditions.

8. The optimization method of lead-bismuth reactor wire fuel assembly based on genetic algorithm according to any one of claims 1 to 7, characterized in that: The high-order polynomial is specifically: in, Indicates the voltage drop, is a constant, is the first design variable, and is the second design variable, For the corresponding , , The design factor, N is the number of design variables.

9. The optimization method of lead-bismuth reactor wire-wound fuel assembly based on genetic algorithm according to claim 8, characterized in that: The genetic algorithm is used to optimize the high-order polynomial to obtain the optimal design of the wire-wound fuel assembly. The specific steps are as follows: A set of individuals is randomly generated, each of which is composed of a combination of design variables as a chromosome; For each individual in the population, its fitness value is calculated according to a high-order polynomial; Taking the maximum pressure drop as the optimization goal, the objective function value is converted into a fitness value; Individuals are selected from the current population to become parents of the next generation for reproduction; Randomly pair the selected parents and exchange some of their genes to form new individuals. During the exchange, one or more genes of the offspring individuals are randomly changed to increase population diversity. The offspring individuals generated through crossover and mutation replace the individuals of the previous generation to form a new population; the fitness of the new population is evaluated to determine whether the termination condition has been reached; If the termination condition is met, the design of the wire-wound fuel assembly at this time is output as the optimal design; if the termination condition is not met, the fitness value calculation step is returned to perform iterative optimization until the termination condition is met.

10. An optimization system for lead-bismuth reactor wire-wound fuel assemblies based on genetic algorithms, characterized in that: Includes modeling module, simulation module, and optimization module; The modeling module is used to model the wire-wound fuel assembly of the lead-bismuth reactor; The simulation module is used to perform steady-state computational fluid dynamics simulation on the wire-wound fuel assembly model under the same fluid flow boundary conditions to calculate the pressure drop of the wire-wound fuel assembly; The optimization module is used to design a high-order polynomial based on the pressure drop to construct a display relationship between the design variables and the pressure drop; the high-order polynomial is optimized by a genetic algorithm to obtain the optimal design of the wire-wound fuel assembly.

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