Nuclear reactor optimization method, device, computer equipment and storage medium

Abstract

The present application relates to a nuclear reactor optimization method, apparatus, computer device, and storage medium. The method comprises: constructing a first objective function based on the optimization requirements for the nuclear reactor; constructing a second objective function including the intermediate characteristic variables based on the functional relationship between the intermediate characteristic variables and the optimization parameters, as well as the first objective function; probabilistically modeling the second objective function based on candidate nuclear reactor designs to obtain a probability distribution for the second objective function; and determining target values for the optimization parameters based on the probability distribution and the optimization requirements. By introducing intermediate characteristic variables, this method decomposes the first objective function for the optimization parameters into two relatively simple optimization problems: the functional relationship between the intermediate characteristic variables and the optimization parameters, and the second objective function for the intermediate characteristic variables, thereby shortening optimization time and reducing computational complexity.

Description

Technical Field

[0001] The present application relates to the technical field of nuclear reactors, and in particular to a method, apparatus, computer equipment, and storage medium for optimizing a nuclear reactor. Background Art

[0002] The generation of nuclear reactor design plans is a prerequisite and an important link for the engineering construction and safe operation of nuclear reactors.

[0003] Nuclear reactor design involves a wide range of disciplines, including physics, shielding, fuel, thermal engineering, and safety. As the application scenarios of advanced nuclear reactors continue to evolve, their design requirements, such as economic efficiency, safety, external volume capacity, and transportability, continue to increase. Under certain constraints, relying solely on existing reactor design experience makes it difficult to efficiently design a reasonable reactor optimization solution in a short period of time. Furthermore, human error caused by frequent manual design iterations and changes is a significant source of delays and quality deviations in engineering design.

[0004] To address these needs, a multidisciplinary intelligent design platform for advanced reactors was developed to address the comprehensive optimization of nuclear reactors and guide the optimization of nuclear reactor engineering design. However, the platform's optimization using metaheuristic algorithms was time-consuming and computationally intensive. Summary of the Invention

[0005] Based on this, it is necessary to provide a nuclear reactor optimization method, device, computer equipment and storage medium to address the above technical problems, which can decompose a complex optimization problem into two relatively simple optimization problems, reduce the amount of calculation and shorten the optimization time.

[0006] In a first aspect, the present application provides a method for optimizing a nuclear reactor, the method comprising:

[0007] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0008] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0009] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0010] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0011] In one embodiment, based on the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function, a second objective function including the intermediate characteristic variables is constructed, including:

[0012] Determine the intermediate characteristic variables according to the optimization parameters and the optimization objectives in the optimization requirements;

[0013] According to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function, a second objective function including the intermediate characteristic variables is constructed.

[0014] In one embodiment, determining the intermediate characteristic variables according to the optimization parameters and the optimization target in the optimization requirements includes:

[0015] Determine candidate feature variables based on optimization objectives and optimization parameters;

[0016] According to the functional relationship between the candidate feature variables and the optimization parameters, intermediate feature variables are selected from the candidate feature variables.

[0017] In one embodiment, determining target values of optimization parameters based on probability distribution and optimization requirements includes:

[0018] Determine the optimal value of the intermediate characteristic variable based on the probability distribution and the optimization goal in the optimization requirement;

[0019] According to the functional relationship between the intermediate characteristic variables and the optimization parameters, as well as the optimal values, the target values of the optimization parameters are determined.

[0020] In one embodiment, a first objective function is constructed based on optimization requirements for a nuclear reactor, including:

[0021] Selecting optimization parameters from design parameters of the nuclear reactor according to optimization objectives and constraints in optimization requirements for the nuclear reactor;

[0022] A first objective function is constructed based on the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters.

[0023] In one embodiment, the method further comprises:

[0024] Determine the function value of the first objective function according to the target value;

[0025] Output the target value and function value.

[0026] In a second aspect, the present application further provides a nuclear reactor optimization device, the device comprising:

[0027] A first constructing module is configured to construct a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0028] a second constructing module, configured to construct a second objective function including the intermediate characteristic variables according to a functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0029] a probability modeling module, configured to perform probability modeling on the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0030] The value determination module is used to determine the target value of the optimization parameter according to the probability distribution and optimization requirements; wherein the target value is used to optimize the nuclear reactor.

[0031] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are performed:

[0032] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0033] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0034] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0035] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the following steps:

[0037] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0038] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0039] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0040] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0041] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the following steps:

[0042] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0043] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0044] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0045] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0046] The above-mentioned nuclear reactor optimization method, apparatus, computer equipment, and storage medium construct a first objective function for the optimization parameters of the nuclear reactor based on the optimization requirements of the nuclear reactor; then, based on the functional relationship between the intermediate characteristic variables and the optimization parameters, a second objective function for the intermediate characteristic variables is constructed in combination with the first objective function; based on the provided candidate design schemes for the nuclear reactor, the second objective function is probabilistically modeled to obtain a probability distribution of the second objective function; and then, based on the obtained probability distribution and the optimization requirements of the nuclear reactor, the target values of the optimization parameters are determined. In the above scheme, by introducing intermediate characteristic variables, the first objective function for the optimization parameters is decomposed into two relatively simple optimization problems: the functional relationship between the intermediate characteristic variables and the optimization parameters, and the second objective function for the intermediate characteristic variables, thereby shortening the optimization time and reducing the amount of calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 FIG. 1 is an application environment diagram of a method for optimizing a nuclear reactor in one embodiment;

[0048] Figure 2 is a schematic flow chart of a method for optimizing a nuclear reactor in one embodiment;

[0049] Figure 3 A schematic diagram of a process for constructing a first objective function in one embodiment;

[0050] Figure 4 A schematic diagram of a process for constructing a second objective function in one embodiment;

[0051] Figure 5 is a schematic flow chart of a method for optimizing a nuclear reactor in another embodiment;

[0052] Figure 6 is a structural block diagram of a nuclear reactor optimization device in one embodiment;

[0053] Figure 7 is a structural block diagram of a nuclear reactor optimization device in another embodiment;

[0054] Figure 8 is a structural block diagram of a nuclear reactor optimization device in yet another embodiment;

[0055] Figure 9 is a structural block diagram of a nuclear reactor optimization device in yet another embodiment;

[0056] Figure 10 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0058] The optimization method of the nuclear reactor provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104 or placed in the cloud or on another network server. Optionally, terminal 102 can integrate a nuclear reactor optimization tool provided by the server; further, the nuclear reactor optimization tool can be presented in the form of a mini-program, a webpage, or a standalone app.

[0059] Specifically, the user can input the optimization requirements for the nuclear reactor through the nuclear reactor optimization tool in the terminal 102, and the terminal 102 transmits the optimization requirements for the nuclear reactor input by the user to the server 104; the server 104 obtains the optimization requirements for the nuclear reactor, analyzes the optimization requirements, determines the optimization parameters, and constructs the first objective function and the second objective function; further, the second objective function is probabilistically modeled to determine the target values of the optimization parameters and obtain an optimized design scheme.

[0060] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices, wherein the portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0061] In one embodiment, Figure 2 As shown, a method for optimizing a nuclear reactor is provided, which is described by taking the method applied to a server as an example, and includes the following steps:

[0062] S201: Construct a first objective function based on optimization requirements for the nuclear reactor.

[0063] The optimization requirement is the requirement for optimizing the nuclear reactor, which may include the optimization target, constraints, etc. The optimization target is the goal to be achieved by optimizing the nuclear reactor, and the constraints are the constraints existing in the process of optimizing the nuclear reactor.

[0064] The first objective function is an objective function for optimizing parameters of a nuclear reactor, constructed based on optimization requirements. Optionally, the first objective function includes optimization parameters for the nuclear reactor. Optimization parameters refer to parameters involved in optimizing the design of a nuclear reactor, such as physical parameters such as geometry, structure, material, density, and flow rate, and / or various indicative parameters obtained through calculations using nuclear reactor design software, such as the effective breeding parameter keff and the three-dimensional power distribution of the core. Optionally, in this embodiment, the number of optimization parameters can be one or more.

[0065] In an optional embodiment, a user may send a nuclear reactor optimization request to a server via a nuclear reactor optimization tool integrated into a terminal. Upon receiving the user's input of the nuclear reactor optimization request, the server may input the optimization request into a pre-defined analysis model. The analysis model then analyzes and determines the optimization parameters for the nuclear reactor involved in the optimization request and constructs a first objective function for the optimization parameters of the nuclear reactor based on the optimization request.

[0066] Furthermore, the server can also feed back the determined optimization parameters and the generated first objective function to the user through the nuclear reactor optimization tool. The user can supplement or delete the optimization parameters determined by the server and modify the first objective function based on his or her own experience or needs.

[0067] S202: Construct a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function.

[0068] In this embodiment, the intermediate characteristic variables are characteristic variables introduced during the optimization process that can characterize specific optimization requirements. There can be one or more intermediate characteristic variables. Furthermore, the number of intermediate characteristic variables is not greater than the number of optimization parameters. Each intermediate characteristic variable can establish a simple functional relationship with the optimization parameter. For example, for typical material change optimization requirements, the optimization parameter can be the fuel consumption of each component. Furthermore, the average fuel consumption value of each component can be selected as the intermediate characteristic variable. If the fuel consumption of components 1 to 4 are BU1, BU2, BU3 and BU4 respectively, the intermediate characteristic variable can be Average (BU1, BU2, BU3, BU4). This intermediate characteristic variable can better characterize the overall fuel consumption of the area where components 1 to 4 are located.

[0069] Specifically, after determining the optimization parameters for the nuclear reactor based on the optimization requirements, intermediate characteristic variables can be determined based on the specific optimization requirements, and a functional relationship between the intermediate characteristic variables and the optimization parameters can be established. Furthermore, an objective function for the intermediate characteristic variables can be generated as a second objective function, combining the first objective function for the optimization parameters of the nuclear reactor generated in S201 above.

[0070] S203 , performing probability modeling on the second objective function according to the candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function.

[0071] The candidate nuclear reactor design schemes are existing nuclear reactor design schemes, and there may be multiple candidate schemes. Probabilistic modeling involves modeling the second objective function according to a certain probability distribution. The resulting probability distribution may be a curve graph.

[0072] Specifically, a set of candidate nuclear reactor designs can be selected from historical data. Based on these candidate designs, a matrix of optimized parameters for the nuclear reactor and the first objective function can be constructed. Furthermore, by combining the functional relationship between the intermediate characteristic variables and the optimized parameters for the nuclear reactor, the constructed matrix of optimized parameters for the nuclear reactor and the first objective function can be converted into a matrix of intermediate characteristic variables and the second objective function. Based on this matrix of intermediate characteristic variables and the second objective function, a probabilistic modeling of the second objective function can be performed to obtain the probability distribution of the second objective function.

[0073] S204: Determine target values of optimization parameters based on the probability distribution and optimization requirements.

[0074] Among them, the target value is used to optimize the nuclear reactor.

[0075] One possible implementation method is to obtain the probability distribution of the second objective function and, in combination with the optimization requirements for the nuclear reactor, determine the target values of the optimization parameters through a pre-set reverse deduction model.

[0076] Another possible implementation method is to obtain the probability distribution of the second objective function, and then determine the optimal value of the intermediate characteristic variable according to the probability distribution and the optimization goal in the optimization requirement; and determine the target value of the optimization parameter according to the functional relationship between the intermediate characteristic variable and the optimization parameter, as well as the optimal value.

[0077] Specifically, after obtaining the probability distribution of the second objective function, according to the optimization goal in the optimization requirements, the optimal value of the intermediate characteristic variable can be determined in the global probability distribution based on the existing EI (Expected Improvement) method in Scikit-learn (a free software machine learning library) to maximize the expectation of obtaining the optimal second objective function; further, after determining the optimal value of the intermediate characteristic variable, the target value of the optimization parameter is determined in combination with the functional relationship between the intermediate characteristic variable and the optimization parameter. It should be noted that since the functional relationship between the intermediate characteristic variable and the optimization parameter is relatively simple, even if a large number of random calculations or other algorithms with relatively poor optimization efficiency are used to obtain the target value of the optimization parameter, the time consumption is still acceptable in the overall engineering design.

[0078] The above-mentioned nuclear reactor optimization method establishes a first objective function for the optimization parameters of the nuclear reactor based on the optimization requirements of the nuclear reactor; then, based on the functional relationship between the intermediate characteristic variables and the optimization parameters, a second objective function for the intermediate characteristic variables is constructed in combination with the first objective function; based on the provided candidate design schemes of the nuclear reactor, the second objective function is probabilistically modeled to obtain a probability distribution of the second objective function; and then, based on the obtained probability distribution and the optimization requirements of the nuclear reactor, the target values of the optimization parameters are determined. In the above scheme, by introducing intermediate characteristic variables, the first objective function for the optimization parameters is decomposed into two relatively simple optimization problems: the functional relationship between the intermediate characteristic variables and the optimization parameters, and the second objective function for the intermediate characteristic variables, thereby shortening the optimization time and reducing the amount of calculation.

[0079] Furthermore, after determining the target value of the optimization parameter, the function value of the first objective function is determined according to the target value; and the target value and the function value are output.

[0080] Specifically, after determining the target values of the optimization parameters, the target values are substituted into the first objective function to determine the function value of the first objective function. Furthermore, the target values and function values can be displayed to the user for reference via the nuclear reactor optimization tool integrated into the terminal. Optionally, if the user is dissatisfied with the currently generated function values, they can reselect candidate design solutions and iterate until they ultimately obtain satisfactory target values and function values, which will be used as the optimized design solution.

[0081] It can be understood that the function value of the first objective function is obtained by taking the target value, and the target value and function value are displayed to the user, so that the user can obtain the target value and function value more intuitively to determine whether further iteration is needed to regenerate the optimized design plan.

[0082] In one embodiment, Figure 3 As shown, the above S201 is further refined. Specifically, the following steps may be included:

[0083] S301 : selecting optimization parameters from design parameters of the nuclear reactor according to optimization objectives and constraints in optimization requirements for the nuclear reactor.

[0084] Specifically, after receiving the optimization request input by the user, the server analyzes the nuclear reactor to be optimized and determines the design parameters of the nuclear reactor to be optimized. Furthermore, based on the optimization objectives and constraints in the optimization request, the server selects relevant optimization parameters from the design parameters of the nuclear reactor to be optimized. Optionally, the server can display the selected optimization parameters to the user through an interface. Furthermore, the user can modify or supplement the optimization parameters based on their own experience and needs.

[0085] S302: Construct a first objective function according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters.

[0086] Specifically, after determining the optimization parameters, the optimization objectives and constraints in the optimization requirements are analyzed to construct the correlation between the optimization parameters and the optimization objectives, and the correlation between the constraints and the optimization parameters; further, the correlation between the optimization parameters and the optimization objectives, and the correlation between the constraints and the optimization parameters are established as a unified function, and the unified function is used as the first objective function.

[0087] It can be understood that by determining the optimization parameters according to the optimization objectives and constraints, the association between the optimization parameters and the optimization objectives, and the association between the constraints and the optimization parameters are established as the first objective function, so that the established first objective function is more comprehensive and accurate.

[0088] Based on the above embodiment, in one embodiment, Figure 4 As shown, the above S202 is further refined. Specifically, the following steps may be included:

[0089] S401: Determine intermediate characteristic variables according to the optimization parameters and the optimization target in the optimization requirements.

[0090] One possible implementation involves determining the optimization parameters for a nuclear reactor and, in combination with the optimization objectives in the optimization requirements, performing an analysis based on pre-designed logic to determine intermediate characteristic variables. Optionally, the server can provide feedback to the user via an interface regarding the determined intermediate characteristic variables. Furthermore, the user can modify or supplement the intermediate characteristic variables determined by the server based on their own experience or needs.

[0091] Another possible implementation method is to determine the optimization parameters for the nuclear reactor, determine candidate characteristic variables according to the optimization target and the optimization parameters, and select intermediate characteristic variables from the candidate characteristic variables according to the functional relationship between the candidate characteristic variables and the optimization parameters.

[0092] Specifically, after determining the optimization parameters for the nuclear reactor, the server can match candidate feature variables from a pre-set historical feature variable library, combining the optimization objectives and the determined optimization parameters. Furthermore, the server analyzes the functional relationship between the candidate feature variables and the optimization parameters, and selects intermediate feature variables from the candidate feature variables based on pre-set logic. For example, if the complexity of the functional relationship between the candidate feature variable and the optimization parameter is greater than a preset threshold, the candidate feature variable cannot be used as an intermediate feature variable. If the complexity of the functional relationship between the candidate feature variable and the optimization parameter is not greater than the preset threshold, the candidate feature variable can be used as an intermediate feature variable.

[0093] It can be understood that in this embodiment, the intermediate characteristic variables are selected by introducing the functional relationship between the candidate characteristic variables and the optimization parameters, so that the determined intermediate characteristic variables are more reasonable, that is, the functional relationship between the determined intermediate characteristic variables and the optimization parameters is relatively simple, thereby reducing the amount of calculation for subsequent solving the optimization design scheme.

[0094] S402: Construct a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function.

[0095] Specifically, after determining the intermediate characteristic variables, based on the functional relationship between the intermediate characteristic variables and the optimization parameters, combined with the first objective function for the optimization parameters, the first objective function is converted into an objective function for the intermediate characteristic variables, that is, the second objective function.

[0096] It can be understood that by combining the optimization parameters and the optimization objectives to determine the intermediate characteristic variables, the determined intermediate characteristic variables can be made more reasonable; thereby, the complexity of the second objective function constructed for the intermediate characteristic variables based on the functional relationship between the intermediate characteristic variables and the optimization parameters, as well as the first objective function, is reduced, thereby reducing the amount of calculation and shortening the time for subsequently obtaining the optimal design solution.

[0097] In one embodiment, Figure 5 As shown, an optional example of a nuclear reactor optimization method is provided. The specific process is as follows:

[0098] S501 , selecting optimization parameters from design parameters of the nuclear reactor according to optimization objectives and constraints in optimization requirements for the nuclear reactor.

[0099] S502: Establish a first objective function according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters.

[0100] S503: Determine candidate feature variables according to the optimization target and optimization parameters.

[0101] S504: Selecting intermediate feature variables from the candidate feature variables according to the functional relationship between the candidate feature variables and the optimization parameters.

[0102] S505 : Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function.

[0103] S506 , performing probability modeling on the second objective function according to the candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function.

[0104] S507: Determine the optimal value of the intermediate characteristic variable according to the probability distribution and the optimization goal.

[0105] S508: Determine target values of the optimization parameters based on the functional relationship between the intermediate characteristic variables and the optimization parameters, as well as the optimal values.

[0106] S509: Determine the function value of the first objective function according to the target value.

[0107] S510, output the target value and function value.

[0108] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0109] Based on the same inventive concept, embodiments of the present application also provide a nuclear reactor optimization device for implementing the aforementioned nuclear reactor optimization method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more of the following embodiments of the nuclear reactor optimization device can be found in the aforementioned limitations of the nuclear reactor optimization method and will not be further elaborated here.

[0110] In one embodiment, Figure 6 As shown, a nuclear reactor optimization device 1 is provided, comprising: a first building module 10, a second building module 20, a probability modeling module 30 and a value determination module 40, wherein:

[0111] A first constructing module 10 is configured to construct a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0112] A second construction module 20 is configured to construct a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0113] a probability modeling module 30 for performing probability modeling on the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0114] The value determination module 40 is used to determine the target value of the optimization parameter according to the probability distribution and the optimization requirement; wherein the target value is used to optimize the nuclear reactor.

[0115] In one embodiment, in the above Figure 6 On the basis of Figure 7 As shown above Figure 6 The second building block 20 in may include:

[0116] The variable determination unit 21 is used to determine the intermediate characteristic variables according to the optimization parameters and the optimization target in the optimization requirements;

[0117] The second constructing unit 22 is configured to construct a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function.

[0118] In one embodiment, the above Figure 7 The variable determination unit 21 in may include:

[0119] The first subunit is used to determine candidate feature variables according to the optimization target and optimization parameters;

[0120] The second subunit is configured to select intermediate feature variables from the candidate feature variables according to a functional relationship between the candidate feature variables and the optimization parameters.

[0121] In one embodiment, in the above Figure 6 or Figure 7 On the basis of Figure 8 As shown, the value determination module 40 may include:

[0122] A first determining unit 41 is configured to determine an optimal value of an intermediate characteristic variable according to the probability distribution and the optimization target in the optimization requirement;

[0123] The second determining unit 42 is configured to determine a target value of the optimization parameter according to a functional relationship between the intermediate characteristic variable and the optimization parameter, and an optimal value.

[0124] In one embodiment, in the above Figure 6 、 Figure 7 or Figure 8 On the basis of Figure 9 As shown, the first building block 10 may include:

[0125] A parameter selection unit 11 is used to select optimization parameters from the design parameters of the nuclear reactor according to the optimization target and constraint conditions in the optimization requirements for the nuclear reactor;

[0126] The first constructing unit 12 is configured to construct a first objective function according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters.

[0127] In one embodiment, the nuclear reactor optimization device may further include:

[0128] The value output module is used to determine the function value of the first objective function according to the target value; and output the target value and the function value.

[0129] Each module in the aforementioned nuclear reactor optimization device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a computer device memory in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0130] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 10 As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data such as design parameters and candidate design schemes of a nuclear reactor. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for optimizing a nuclear reactor.

[0131] Those skilled in the art will understand that Figure 10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0132] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0133] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0134] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0135] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0136] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0137] In one embodiment, when the processor executes the computer program to construct the logic of the second objective function including the intermediate feature variables based on the functional relationship between the intermediate feature variables and the optimization parameters and the first objective function, the processor further implements the following steps:

[0138] According to the optimization parameters and the optimization target in the optimization requirements, the intermediate characteristic variables are determined; according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function, a second objective function including the intermediate characteristic variables is constructed.

[0139] In one embodiment, when the processor executes the computer program to determine the logic of the intermediate feature variables according to the optimization parameters and the optimization target in the optimization requirements, the processor further implements the following steps:

[0140] According to the optimization target and the optimization parameters, candidate feature variables are determined; according to the functional relationship between the candidate feature variables and the optimization parameters, intermediate feature variables are selected from the candidate feature variables.

[0141] In one embodiment, when the processor executes the logic of the computer program to determine the target value of the optimization parameter based on the probability distribution and the optimization requirements, the processor further implements the following steps:

[0142] According to the probability distribution and the optimization goal in the optimization requirements, the optimal value of the intermediate characteristic variable is determined; according to the functional relationship between the intermediate characteristic variable and the optimization parameter, as well as the optimal value, the target value of the optimization parameter is determined.

[0143] In one embodiment, when the processor executes the computer program to construct the logic of the first objective function according to the optimization requirements of the nuclear reactor, the processor further implements the following steps:

[0144] According to the optimization objectives and constraints in the optimization requirements for the nuclear reactor, optimization parameters are selected from the design parameters of the nuclear reactor; according to the correlation between the optimization parameters and the optimization objectives, and the correlation between the constraints and the optimization parameters, a first objective function is constructed.

[0145] In one embodiment, when the processor executes the computer program, it further implements the following steps:

[0146] According to the target value, the function value of the first objective function is determined; and the target value and the function value are output.

[0147] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0148] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0149] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0150] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0151] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0152] In one embodiment, the computer program, when executed by a processor, further implements the following steps for constructing logic of a second objective function including the intermediate feature variables based on the functional relationship between the intermediate feature variables and the optimization parameters and the first objective function:

[0153] Determine the intermediate characteristic variables according to the optimization parameters and the optimization objectives in the optimization requirements;

[0154] According to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function, a second objective function including the intermediate characteristic variables is constructed.

[0155] In one embodiment, the computer program further implements the following steps when the processor executes the logic for determining the intermediate feature variables based on the optimization parameters and the optimization target in the optimization requirements:

[0156] According to the optimization target and the optimization parameters, candidate feature variables are determined; according to the functional relationship between the candidate feature variables and the optimization parameters, intermediate feature variables are selected from the candidate feature variables.

[0157] In one embodiment, the computer program further implements the following steps when the processor executes the logic for determining target values of optimization parameters based on the probability distribution and optimization requirements:

[0158] According to the probability distribution and the optimization goal in the optimization requirements, the optimal value of the intermediate characteristic variable is determined; according to the functional relationship between the intermediate characteristic variable and the optimization parameter, as well as the optimal value, the target value of the optimization parameter is determined.

[0159] In one embodiment, the computer program constructs the logic of the first objective function according to the optimization requirements of the nuclear reactor and further implements the following steps when executed by the processor:

[0160] According to the optimization objectives and constraints in the optimization requirements for the nuclear reactor, optimization parameters are selected from the design parameters of the nuclear reactor; according to the correlation between the optimization parameters and the optimization objectives, and the correlation between the constraints and the optimization parameters, a first objective function is established.

[0161] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0162] According to the target value, the function value of the first objective function is determined; and the target value and the function value are output.

[0163] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0164] Constructing a first objective function according to optimization requirements for the nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor;

[0165] Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters and the first objective function;

[0166] Probabilistically modeling the second objective function based on candidate design schemes of the nuclear reactor to obtain a probability distribution of the second objective function;

[0167] According to the probability distribution and optimization requirements, target values of the optimization parameters are determined; wherein the target values are used to optimize the nuclear reactor.

[0168] In one embodiment, the computer program, when executed by a processor, further implements the following steps for constructing logic of a second objective function including the intermediate feature variables based on the functional relationship between the intermediate feature variables and the optimization parameters and the first objective function:

[0169] Determine the intermediate characteristic variables according to the optimization parameters and the optimization objectives in the optimization requirements;

[0170] According to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function, a second objective function including the intermediate characteristic variables is constructed.

[0171] In one embodiment, the computer program further implements the following steps when the processor executes the logic for determining the intermediate feature variables based on the optimization parameters and the optimization target in the optimization requirements:

[0172] According to the optimization target and the optimization parameters, candidate feature variables are determined; according to the functional relationship between the candidate feature variables and the optimization parameters, intermediate feature variables are selected from the candidate feature variables.

[0173] In one embodiment, the computer program further implements the following steps when the processor executes the logic for determining target values of optimization parameters based on the probability distribution and optimization requirements:

[0174] According to the probability distribution and the optimization goal in the optimization requirements, the optimal value of the intermediate characteristic variable is determined; according to the functional relationship between the intermediate characteristic variable and the optimization parameter, as well as the optimal value, the target value of the optimization parameter is determined.

[0175] In one embodiment, the computer program constructs the logic of the first objective function according to the optimization requirements of the nuclear reactor and further implements the following steps when executed by the processor:

[0176] According to the optimization objectives and constraints in the optimization requirements for the nuclear reactor, optimization parameters are selected from the design parameters of the nuclear reactor; according to the correlation between the optimization parameters and the optimization objectives, and the correlation between the constraints and the optimization parameters, a first objective function is established.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0178] According to the target value, the function value of the first objective function is determined; and the target value and the function value are output.

[0179] It should be noted that the data involved in this application (including but not limited to nuclear reactor design parameters, candidate design schemes, etc.) are all information and data that have been authorized or fully authorized by all parties.

[0180] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0181] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0182] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for optimizing a nuclear reactor, characterized in that: The method comprises: Constructing a first objective function according to optimization requirements for a nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor; Determining candidate feature variables according to the optimization target and the optimization parameters in the optimization requirement; selecting intermediate feature variables from the candidate feature variables according to a functional relationship between the candidate feature variables and the optimization parameters; Constructing a second objective function including the intermediate characteristic variables according to the functional relationship between the intermediate characteristic variables and the optimization parameters, and the first objective function; constructing a matrix for the optimization parameters and the first objective function according to the candidate design schemes of the nuclear reactor; According to the functional relationship between the intermediate characteristic variables and the optimization parameters, converting the constructed matrix for the optimization parameters and the first objective function into a matrix for the intermediate characteristic variables and the second objective function; Performing probability modeling on the second objective function according to the matrix of the intermediate characteristic variables and the second objective function to obtain a probability distribution of the second objective function; According to the probability distribution and the optimization requirement, a target value of the optimization parameter is determined; wherein the target value is used to optimize the nuclear reactor.

2. The method according to claim 1, characterized in that The selecting of intermediate feature variables from the candidate feature variables according to the functional relationship between the candidate feature variables and the optimization parameters includes: For each candidate feature variable, if the complexity of the functional relationship between the candidate feature variable and the optimization parameter is less than or equal to a preset threshold, the candidate feature variable is used as an intermediate feature variable.

3. The method according to claim 1, characterized in that Determining the target value of the optimization parameter according to the probability distribution and the optimization requirement includes: Determining the optimal value of the intermediate characteristic variable according to the probability distribution and the optimization target in the optimization requirement; The target value of the optimization parameter is determined based on the functional relationship between the intermediate characteristic variable and the optimization parameter, and the optimal value.

4. The method according to claim 1, wherein The first objective function is constructed according to the optimization requirements for the nuclear reactor, including: selecting optimization parameters from design parameters of the nuclear reactor according to optimization objectives and constraints in optimization requirements for the nuclear reactor; A first objective function is constructed according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters.

5. The method according to claim 4, characterized in that The step of selecting the optimization parameters from the design parameters of the nuclear reactor according to the optimization objectives and constraints in the optimization requirements for the nuclear reactor includes: determining design parameters of the nuclear reactor; The optimization parameters are selected from the design parameters according to the optimization objectives and constraints in the optimization requirements for the nuclear reactor.

6. The method according to claim 4, characterized in that The constructing of a first objective function according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters, includes: Analyzing the optimization objectives and constraints in the optimization requirements, and establishing associations between the optimization parameters and the optimization objectives, and between the constraints and the optimization parameters; A unified function is constructed according to the association relationship between the optimization parameters and the optimization target, and the association relationship between the constraint conditions and the optimization parameters, and the unified function is used as the first objective function.

7. The method according to claim 1, characterized in that The method further comprises: Determining a function value of the first objective function according to the target value; Output the target value and the function value.

8. The method according to claim 7, characterized in that Determining the function value of the first objective function according to the target value includes: Substitute the target value into the first objective function to calculate the function value of the first objective function.

9. The method according to claim 1, characterized in that The probability distribution is a curve graph.

10. A nuclear reactor optimization device, characterized in that: The device comprises: A first constructing module is configured to construct a first objective function according to optimization requirements for a nuclear reactor; wherein the first objective function includes optimization parameters for the nuclear reactor; a second constructing module, configured to determine candidate feature variables according to the optimization objective and the optimization parameters in the optimization requirement; select intermediate feature variables from the candidate feature variables according to a functional relationship between the candidate feature variables and the optimization parameters; and construct a second objective function including the intermediate feature variables according to the functional relationship between the intermediate feature variables and the optimization parameters and the first objective function; a probability modeling module, configured to construct a matrix for the optimization parameters and the first objective function; convert the constructed matrix for the optimization parameters and the first objective function into a matrix for the intermediate characteristic variables and the second objective function based on a functional relationship between the intermediate characteristic variables and the optimization parameters; and perform probability modeling on the second objective function based on the matrix of the intermediate characteristic variables and the second objective function to obtain a probability distribution of the second objective function; A value determination module is used to determine the target value of the optimization parameter according to the probability distribution and the optimization requirement; wherein the target value is used to optimize the nuclear reactor.

Images