Reactor primary loop corrosion product deposition prediction method, system, equipment and medium

Abstract

The invention discloses a reactor primary loop corrosion product deposition prediction method, system, equipment and medium, and the method comprises the steps: dividing a primary loop of a reactor into a plurality of subareas, and subdividing each subarea into a pipeline; the current temperature, pressure, pH, ion concentration and pipe bending angle of each pipeline are obtained; inputting the current temperature, pressure, pH, ion concentration and pipe bending angle of each pipeline into a corrosion product deposition prediction model to obtain a corrosion product deposition data prediction result of each pipeline; and integrating the corrosion product deposition data prediction results of the pipelines to obtain a corrosion product deposition data prediction result of the nuclear reactor primary loop, and the method, the system, the equipment and the medium can predict the corrosion product deposition condition of the pipelines.

Description

Technical Field

[0001] The invention belongs to the technical field of nuclear safety analysis, and relates to a method, system, equipment and medium for predicting deposition of corrosion products in a reactor primary loop. Background Art

[0002] Under high temperature and high pressure conditions, the corrosion of the structural materials of the primary loop system of a pressurized water reactor is unavoidable. The corrosion not only affects the safety of the reactor, but also the corrosion products produced by the corrosion will enter the core with the coolant, become activated corrosion products after being activated by the core, and then spread throughout the primary loop system with the coolant, deposited on the surface of the core and external equipment, forming a radiation field. The radiation field generated by the deposition of these activated corrosion products in various parts of the primary loop is the main source of personal doses received by maintenance personnel during the overhaul of the pressurized water reactor. According to statistics, under the premise of no special pollution, the deposits outside the core in the primary coolant system are the main source of radiation dose, of which the contribution of activated corrosion products can reach more than 80%.

[0003] The activated corrosion product source term calculation software currently widely used in my country mainly relies on software introduced from abroad, and most of them were introduced along with the nuclear power introduction project. Obviously, they are only applicable to the reactor type introduced by the nuclear power project. Moreover, the system design, operating status, selection, etc. of the power plants on which these calculation software are based are different from those of the newly built nuclear power plants in China. The empirical feedback data used for software parameter correction is old and lacks timely correction. The specific application leads to great uncertainty in the calculation of source terms, which directly affects the reliability of the radiation protection design of nuclear power plants. These software conduct research based on the coupling of multiple physical phenomena such as the diffusion, migration and mass transfer of activated corrosion products. The physical process is complex, the calculation amount is large, and a lot of resources are required. In addition, different software have different emphases on the consideration of physical phenomena, and the conclusions drawn may not be suitable for all reactor types. They can only take into account certain operating conditions or even specific reactor types. They are not comprehensive enough and may ignore some major influencing factors. They need to be adjusted for different reactor types and the accuracy may not be high. In addition, the operating conditions of each pipeline in a nuclear power plant, whether it is the core or the steam generator, are actually different, and the deposition conditions at different positions of each pipeline are also different. For example, the deposition probability at different positions of the elbow is different. The above model does not take these details into account, but only partitions several parts as a whole. It is impossible to accurately determine the deposition conditions at a specific point at different positions of the pipeline under different operating conditions, and lacks details. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the above-mentioned prior art and provide a method, system, equipment and medium for predicting corrosion product deposition in a reactor primary loop. The method, system, equipment and medium can predict the corrosion product deposition of pipelines.

[0005] In order to achieve the above object, the present invention adopts the following technical scheme:

[0006] In one aspect, the present invention provides a method for predicting corrosion product deposition in a reactor primary loop, comprising:

[0007] Divide the primary circuit of the reactor into several zones, and subdivide each zone into pipelines;

[0008] Obtain the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline;

[0009] The current temperature, pressure, pH, ion concentration and elbow angle of each pipeline are input into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline;

[0010] The corrosion product deposition data prediction results of each pipeline are integrated to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor.

[0011] Before inputting the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline into the corrosion product deposition prediction model, the method further includes:

[0012] Through finite element simulation, the corrosion product deposition data of each pipeline under different temperatures, pressures, pH values, ion concentrations and bend angles are calculated;

[0013] Construct a data set based on the corrosion product deposition data of pipelines at different temperatures, pressures, pH values, ion concentrations, and bend angles;

[0014] Build a neural network model;

[0015] Dividing the data set into a training set and a test set;

[0016] The training set and the test set are used to train and test the neural network model, and the trained and tested neural network model is used as a corrosion product deposition prediction model.

[0017] The neural network model is an artificial neural network, a recurrent neural network or a long short-term memory neural network.

[0018] The neural network model is a convolutional neural network or a long short-term memory neural network.

[0019] Also includes:

[0020] The data set is updated.

[0021] In a second aspect of the present invention, the present invention provides a reactor primary loop corrosion product deposition prediction system, comprising:

[0022] A partition module is used to divide the primary circuit of the reactor into several partitions, and each partition is subdivided into pipelines;

[0023] The acquisition module is used to obtain the current temperature, pressure, pH, ion concentration and bend angle of each pipeline;

[0024] The prediction module is used to input the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline;

[0025] The integration module is used to integrate the corrosion product deposition data prediction results of each pipeline to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor.

[0026] Also includes:

[0027] The simulation module is used to calculate the corrosion product deposition data of each pipeline under different temperatures, pressures, pH values, ion concentrations and bend angles through finite element simulation;

[0028] A construction module for constructing a data set based on the corrosion product deposition data of pipelines at different temperatures, pressures, pH values, ion concentrations, and bend angles;

[0029] Establish a module for building a neural network model;

[0030] A partitioning module, used for dividing the data set into a training set and a test set;

[0031] The training module is used to train and test the neural network model using the training set and the test set, and use the trained and tested neural network model as a corrosion product deposition prediction model.

[0032] Also includes:

[0033] An updating module is used to update the data set.

[0034] In a third aspect of the present invention, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for predicting the deposition of corrosion products in a first circuit of a reactor when executing the computer program.

[0035] In a fourth aspect of the present invention, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for predicting the deposition of corrosion products in a first loop of a reactor are implemented.

[0036] The present invention has the following beneficial effects:

[0037] During specific operation of the method, system, equipment and medium for predicting corrosion product deposition in the primary loop of a reactor described in the present invention, the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline are input into a corrosion product deposition prediction model to obtain prediction results of corrosion product deposition data of each pipeline, that is, the environmental parameters and geometric parameters of the pipeline are comprehensively considered to achieve prediction of the deposition data of the pipeline, and then the corrosion product deposition data of the entire primary loop of the reactor is obtained, providing a reference for accurate prediction of the dosage position of the primary loop of the reactor. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0039] Figure 1 is a flow chart of the method of the present invention;

[0040] Figure 2 A schematic diagram showing the division of the primary circuit of a nuclear power plant into three major zones;

[0041] Figure 3 The three major zones are further divided into 45 zones;

[0042] Figure 4 It is a schematic diagram of the deposition situation derived on the circumference of a certain cross section;

[0043] Figure 5 This is the sedimentation distribution map derived on the circumference of a certain cross section. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0047] Embodiment 1

[0048] refer to Figure 1 The method for predicting the deposition of corrosion products in a primary circuit of a nuclear reactor according to the present invention comprises the following steps:

[0049] 1) Build a dataset;

[0050] 11) Considering that the basic structure of a nuclear reactor includes the core and steam generator, the primary circuit of the reactor is divided into several partitions, and each partition is further subdivided into pipelines. For example, taking AP1000 as an example, 45 small partitions are established; then the pipeline structure of each partition is subdivided, such as Figure 2 and Figure 3 As shown;

[0051] 12) Collect the dose, corrosion product deposition, temperature, pH, pressure, ion concentration, boron content, lithium content, conductivity, material type, material yield strength and corrosion product deposition of the nuclear power plant;

[0052] 13) Through finite element simulation, calculate the corrosion product deposition data of each pipeline at different temperatures, pressures, pH values, ion concentrations and bend angles. If necessary, consider the coupling of physical fields such as electrochemical corrosion, hydrochemical corrosion and mechanical scouring, extract the simulation result data and the environmental data. The deposition data of the pipeline can be reflected in the deposition data of the section. The result form can be as follows: Figure 4 and Figure 5 shown.

[0053] 14) Construct a data set based on the deposition data of pipelines under different temperatures, pressures, pH values, ion concentrations, and bend angles.

[0054] 2) Construct a corrosion product deposition prediction model;

[0055] 21) Establish a neural network model;

[0056] When the amount of data is small, artificial neural network (ANN), recurrent neural network (RNN) or long short-term memory neural network (LSTM) is selected; when the amount of data is large, in order to improve the efficiency of training, convolutional neural network or long short-term memory neural network (CNN-LSTM) is selected.

[0057] 22) dividing the data set into a training set and a test set;

[0058] 23) Using the training set and the test set to train and test the neural network model, and using the trained and tested neural network model as a corrosion product deposition prediction model.

[0059] 3) The current temperature, pressure, pH, ion concentration and elbow angle of each pipeline are input into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline;

[0060] 4) The corrosion product deposition data prediction results of each pipeline are integrated to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor.

[0061] This example also includes: updating the data in the data set, so as to continuously improve the corrosion product deposition prediction model.

[0062] It should be noted that the present invention is not limited by the reactor type, environment, materials and other conditions, and realizes the calculation of corrosion products of various reactor types with one model; it does not rely on complex and computationally intensive multi-physical field coupling calculations, but is completely based on experimental data and finite element simulation results, and can update parameters based on neural network model learning data, and the calculation is simple; it can update data and correct the database in time, greatly reducing the uncertainty of source term calculation, and providing reliability for radiation protection to a certain extent; the database contains many environmental and material factors, and can comprehensively consider the influence of various environmental factors on deposition; based on finite element simulation, the deposition calculation can be accurately calculated to a specific pipeline, providing a reference for accurate prediction of the dose position of the reactor primary loop.

[0063] Embodiment 2

[0064] The present invention provides a reactor primary loop corrosion product deposition prediction system, comprising:

[0065] The simulation module is used to calculate the corrosion product deposition data of each pipeline under different temperatures, pressures, pH values, ion concentrations and bend angles through finite element simulation;

[0066] A construction module for constructing a data set based on the corrosion product deposition data of pipelines at different temperatures, pressures, pH values, ion concentrations, and bend angles;

[0067] Establish a module for building a neural network model;

[0068] A partitioning module, used for dividing the data set into a training set and a test set;

[0069] A training module, used to train and test the neural network model using the training set and the test set, and use the trained and tested neural network model as a corrosion product deposition prediction model;

[0070] A partition module is used to divide the primary circuit of the reactor into several partitions, and each partition is subdivided into pipelines;

[0071] The acquisition module is used to obtain the current temperature, pressure, pH, ion concentration and bend angle of each pipeline;

[0072] The prediction module is used to input the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline;

[0073] An integration module is used to integrate the corrosion product deposition data prediction results of each pipeline to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor;

[0074] An updating module is used to update the data set.

[0075] Embodiment 3

[0076] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for predicting the deposition of corrosion products in the first loop of a reactor are implemented. The memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc. The processor, the network interface, and the memory are interconnected through an internal bus. The internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard structure bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include a program code, and the program code includes computer operation instructions. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0077] Embodiment 4

[0078] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the reactor primary loop corrosion product deposition prediction method are implemented. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0079] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0080] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1The steps for the functions specified in one or more boxes.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting corrosion product deposition in a reactor primary loop, characterized in that: include: Divide the primary circuit of the reactor into several zones, and subdivide each zone into pipelines; Obtain the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline; The current temperature, pressure, pH, ion concentration and elbow angle of each pipeline are input into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline; The corrosion product deposition data prediction results of each pipeline are integrated to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor.

2. The method for predicting the deposition of corrosion products in the primary circuit of a reactor according to claim 1, characterized in that: Before inputting the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline into the corrosion product deposition prediction model, the method further includes: Through finite element simulation, the corrosion product deposition data of each pipeline under different temperatures, pressures, pH values, ion concentrations and bend angles are calculated; Construct a data set based on the corrosion product deposition data of pipelines at different temperatures, pressures, pH values, ion concentrations, and bend angles; Build a neural network model; Dividing the data set into a training set and a test set; The training set and the test set are used to train and test the neural network model, and the trained and tested neural network model is used as a corrosion product deposition prediction model.

3. The method for predicting the deposition of corrosion products in the primary circuit of a reactor according to claim 2, characterized in that: The neural network model is an artificial neural network, a recurrent neural network or a long short-term memory neural network.

4. The method for predicting the deposition of corrosion products in the primary circuit of a reactor according to claim 2, characterized in that: The neural network model is a convolutional neural network or a long short-term memory neural network.

5. The method for predicting the deposition of corrosion products in the reactor primary circuit according to claim 1, characterized in that: Also includes: The data set is updated.

6. A reactor primary circuit corrosion product deposition prediction system, characterized in that: include: A partition module is used to divide the primary circuit of the reactor into several partitions, and each partition is subdivided into pipelines; The acquisition module is used to obtain the current temperature, pressure, pH, ion concentration and bend angle of each pipeline; The prediction module is used to input the current temperature, pressure, pH, ion concentration and elbow angle of each pipeline into the corrosion product deposition prediction model to obtain the corrosion product deposition data prediction results of each pipeline; The integration module is used to integrate the corrosion product deposition data prediction results of each pipeline to obtain the corrosion product deposition data prediction results of the primary circuit of the nuclear reactor.

7. The reactor primary circuit corrosion product deposition prediction system according to claim 6, characterized in that: Also includes: The simulation module is used to calculate the corrosion product deposition data of each pipeline under different temperatures, pressures, pH values, ion concentrations and bend angles through finite element simulation; A construction module for constructing a data set based on the corrosion product deposition data of pipelines at different temperatures, pressures, pH values, ion concentrations, and bend angles; Establish a module for building a neural network model; A partitioning module, used for dividing the data set into a training set and a test set; The training module is used to train and test the neural network model using the training set and the test set, and use the trained and tested neural network model as a corrosion product deposition prediction model.

8. The reactor primary circuit corrosion product deposition prediction system according to claim 6, characterized in that: Also includes: An updating module is used to update the data set.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for predicting the deposition of corrosion products in the first loop of a reactor as described in any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for predicting the deposition of corrosion products in the first loop of a reactor as claimed in any one of claims 1 to 5 are implemented.

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