Neutron flux uncertainty quantification method, system, computer equipment and medium
Through the neutron flux uncertainty quantization method, the uncertainty input parameter library and the joint covariance matrix are used to calculate the neutron flux uncertainty, which solves the problem of difficult to quantify the uncertainty of neutron flux in the prior art. An accurate understanding of the reactor state is achieved.
Patent Information
- Application Number
- CN202111370528.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-11-18
- Publication Date
- 2025-01-17
- Estimated Expiration
- 2041-11-18
AI Technical Summary
The prior art is difficult to accurately quantify the uncertainty of neutron flux in large pressurized water reactors, especially because the neutron flux cannot be measured directly and the model uncertainty cannot be obtained simply through theoretical calculations, resulting in the inability to accurately analyze the position of the SPND probe. neutron flux uncertainty.
By constructing the neutron flux uncertainty quantization method, uncertainty input parameters are obtained, uncertainty input parameter library is established, input parameters are randomly sampled and verified, neutron flux output parameters are calculated, and power and neutron flux are used to The joint covariance matrix and correlation coefficient calculate the neutron flux uncertainty.
Accurate quantification of neutron flux uncertainty is achieved, allowing a more accurate understanding of the state of the reactor, avoiding the consideration of model and measurement uncertainty while a large number of experiments.
Smart Images
Figure CN114239222B_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of nuclear data quantification of a nuclear reactor core, and in particular to a neutron flux uncertainty quantification method, system, computer equipment and storage medium. Background Art
[0002] In some large pressurized water reactors, a fixed self-contained neutron detector system (SPND) is used to measure flux diagrams. In order to confirm the uncertainty of the SPND measurement results, it is necessary to quantify the neutron flux uncertainty at the SPND probe position and the uncertainty of the SPND probe sensitivity in advance. Both are indispensable.
[0003] Among them, the uncertainty of the SPND probe sensitivity can be quantified using an experimental reactor, but the neutron flux is not a neutronic parameter that can be directly measured, so the uncertainty cannot be quantified using experimental methods alone.
[0004] In addition, since model uncertainty and measurement uncertainty cannot be obtained by pure theoretical calculation, the neutron flux at the SPND probe position cannot be quantified simply by using the forward transfer method of theoretical calculation uncertainty.
[0005] At present, in some schemes, the method of quantifying the uncertainty of neutron flux based on experimental values often obtains an envelope value, and it is impossible to accurately obtain each uncertainty. Considering the lack of experimental data for new reactor types, this method is strictly speaking not applicable. Summary of the invention
[0006] The technical problem to be solved by the present invention is to provide a neutron flux uncertainty quantification method, system, computer equipment and storage medium.
[0007] The technical solution adopted by the present invention to solve the technical problem is: constructing a neutron flux uncertainty quantification method, comprising the following steps:
[0008] S1: Acquire uncertainty input parameters; output calculation parameters of the target reactor under different states according to the uncertainty input parameters; the calculation parameters include core neutron flux output parameters;
[0009] S2: Taking the calculation parameter and the power of the target reactor as response parameters, the neutron flux uncertainty is calculated.
[0010] Preferably, in step S1, it includes:
[0011] S1-1: Establishing an uncertain input parameter library, wherein the uncertain input parameter library includes the uncertain input parameters;
[0012] S1-2: Calling the uncertain input parameter in the uncertain input parameter library.
[0013] Preferably, the uncertainty input parameter library includes a random sampling input parameter library and a verification input parameter library; correspondingly, the random sampling input parameter library includes a number of random sampling input parameters, and the verification input parameter library includes a number of verification input parameters;
[0014] In the step S1-2, it includes:
[0015] S1-2-1: randomly call the random sampling input parameter library to obtain the random sampling input parameter;
[0016] S1-2-2: randomly retrieve the verification input parameter from the verification input parameter library, and obtain the verification input parameter after verification.
[0017] Preferably, the random sampling input parameters include nuclear fuel assembly manufacturing parameters and thermal fluid parameters; correspondingly, the random sampling input parameter library includes a nuclear fuel assembly manufacturing parameter library and a thermal fluid parameter library;
[0018] The verification input parameters include nuclide cross-section parameters; correspondingly, the verification input parameter library includes a multi-group cross-section library composed of the nuclide cross-section parameters.
[0019] Preferably, in the step S1-2-1, a plurality of the nuclear fuel assembly manufacturing parameters in the nuclear fuel assembly manufacturing parameter library are randomly called to obtain the core neutron flux output parameter;
[0020] A plurality of the thermal fluid parameters in the thermal fluid parameter library are randomly called to obtain the core neutron flux output parameter.
[0021] Preferably, the nuclide cross section parameter is a nuclide cross section parameter with covariance information;
[0022] In the step S1-2-2, it includes:
[0023] S1-2-2-1: randomly calling a number of nuclide cross-section parameters from the multi-group cross-section library;
[0024] S1-2-2-2: Generate a cross-section disturbance factor for the covariance information of the nuclide cross-section parameter;
[0025] S1-2-2-3: Perform multi-group microscopic cross-sectional perturbations according to the cross-sectional perturbation factors;
[0026] S1-2-2-4: making the multi-group microscopic cross sections self-consistent;
[0027] S1-2-2-5: reconstructing the plurality of groups of microscopic cross sections;
[0028] S1-2-2-6: Perform full core neutronics calculation on the reconstructed core to obtain the core neutron flux output parameters;
[0029] S1-2-2-7: Calculate the correspondence between the nuclide cross-section parameter and the core neutron flux output parameter;
[0030] S1-2-2-8: Determine whether the confidence level of the core neutron flux output parameter meets the set conditions; if so, terminate and output the core neutron flux output parameter; otherwise, execute step S1-2-2-2.
[0031] Preferably, in step S2, it includes:
[0032] S2-1: taking the core neutron flux output parameter and the power of the target reactor as response parameters, obtaining a joint covariance matrix M of neutron flux and power and a correlation coefficient a of neutron flux and power;
[0033] S2-2: Obtain the neutron flux uncertainty according to the correlation coefficient a.
[0034] Preferably, in step S2-1, the correlation coefficient a is calculated by the following formula:
[0035]
[0036] Among them, the power variance is Fpc, the neutron flux variance is Fnc, and the covariance of power-neutron flux is Xpn.
[0037] Preferably, in step S2-2, the neutron flux uncertainty Unz is calculated by the following formula:
[0038]
[0039] Among them, the covariance of power-neutron flux Xpn, the total power uncertainty Upz, and the correlation coefficient a between neutron flux and power.
[0040] The present invention also provides a neutron flux uncertainty quantification system, comprising:
[0041] An acquisition module, used to obtain uncertain input parameters;
[0042] an output calculation module, configured to output calculation parameters of the target reactor under different states according to the uncertainty input parameters; the calculation parameters include core neutron flux output parameters; and
[0043] The neutron flux uncertainty calculation module is used to calculate the neutron flux uncertainty by taking the calculation parameter and the power of the target reactor as response parameters.
[0044] Preferably, the system further comprises an uncertainty input parameter library, wherein the uncertainty input parameter library contains the uncertainty input parameter, and is used by the acquisition module to call and acquire the uncertainty input parameter;
[0045] The uncertainty input parameter library includes a random sampling input parameter library and a verification input parameter library.
[0046] The present invention also provides a computer device, comprising: a processor and a memory for storing a computer program that can be run on the processor, wherein the processor is used to implement any of the above-mentioned neutron flux uncertainty quantification methods when running the computer program.
[0047] The present invention also provides a computer storage medium storing an executable program, wherein when the executable program is executed by a processor, the neutron flux uncertainty quantification method as described in any one of the above items is implemented.
[0048] The implementation of the present invention has the following beneficial effects: by obtaining uncertain input parameters and combining power as a response parameter, the model uncertainty and measurement uncertainty related to the neutron flux are enveloped, so that the operator can understand the real state of the reactor more accurately. BRIEF DESCRIPTION OF THE DRAWINGS
[0049] The present invention will be further described below with reference to the accompanying drawings and embodiments, in which:
[0050] Figure 1 It is a schematic flow chart of an embodiment of a method for quantifying neutron flux uncertainty of the present invention;
[0051] Figure 2 It is a schematic diagram of the calling and verification process of the nuclide cross section parameters in the neutron flux uncertainty quantification method of the present invention;
[0052] Figure 3 is a schematic diagram of a specific application example of the neutron flux uncertainty quantification method of the present invention;
[0053] Figure 4 It is a schematic diagram of a neutron flux uncertainty quantification process caused by nuclear data of a specific application example of the neutron flux uncertainty quantification method of the present invention;
[0054] Figure 5 It is a schematic block diagram of an embodiment of a neutron flux uncertainty quantification system of the present invention. DETAILED DESCRIPTION
[0055] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific embodiments of the present invention are now described in detail with reference to the accompanying drawings. In the following description, it should be understood that the directions or positional relationships indicated by "front", "back", "up", "down", "left", "right", "longitudinal", "horizontal", "vertical", "horizontal", "top", "bottom", "inside", "outside", "head", "tail", etc. are based on the directions or positional relationships shown in the accompanying drawings, are constructed and operated in a specific direction, and are only for the convenience of describing the present technical solution, rather than indicating that the device or element referred to must have a specific direction, and therefore cannot be understood as a limitation to the present invention.
[0056] It should also be noted that, unless otherwise clearly specified and limited, the terms such as "installed", "connected", "connected", "fixed", "set" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral one; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. When an element is referred to as being "on" or "under" another element, the element can be "directly" or "indirectly" located on the other element, or there may be one or more intermediate elements. The terms "first", "second", "third", etc. are only for the convenience of describing the present technical solution, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first", "second", "third", etc. can explicitly or implicitly include one or more of the features. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.
[0057] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.
[0058] like Figure 1 As shown, in one embodiment of the neutron flux uncertainty quantification method of the present invention, the following steps are included:
[0059] S1: Obtaining uncertainty input parameters, and outputting calculation parameters of the target reactor under different states according to the uncertainty input parameters, wherein the calculation parameters include core neutron flux output parameters.
[0060] In this embodiment, an uncertainty input parameter library is first established, and the uncertainty input parameter library includes uncertain input parameters. According to the input method of the parameters, the uncertainty input parameter library can be divided into a random sampling input parameter library and a verification input parameter library. Correspondingly, the random sampling input parameter library includes a number of random sampling input parameters, and the verification input parameter library includes a number of verification input parameters.
[0061] By passing the uncertainty information of nuclear data at the source, the uncertainty information of nuclear fuel assembly manufacturing parameters, and the uncertainty information of thermal fluid parameters to the nuclear design software in the form of input parameters, the uncertainty input parameter library meets the requirements of sufficiency and authenticity.
[0062] In this embodiment, the randomly sampled input parameters include nuclear fuel assembly manufacturing parameters and thermal fluid parameters; correspondingly, the randomly sampled input parameter library includes a nuclear fuel assembly manufacturing parameter library and a thermal fluid parameter library.
[0063] When the uncertain input parameter library calls the uncertain input parameter, the random sampling input parameter library is randomly called to obtain the random sampling input parameter. For example: randomly calling several nuclear fuel assembly manufacturing parameters in the nuclear fuel assembly manufacturing parameter library to form the core neutron flux output parameter.
[0064] Several thermal fluid parameters in the thermal fluid parameter library are randomly called to form the core neutron flux output parameters.
[0065] The verification input parameters include nuclear data, such as nuclide cross-section parameters; correspondingly, the verification input parameter library includes a multi-group cross-section library composed of nuclide cross-section parameters. The nuclear data can be randomly sampled and input, and after verification, the verification input parameters can be obtained.
[0066] In this embodiment, the nuclide cross section parameter is a nuclide cross section parameter with covariance information, and its calling and verification process is as follows: Figure 2 As shown:
[0067] S21: Randomly call a number of nuclide cross-section parameters from a multi-group cross-section database. In this embodiment, a one-step multi-group cross-section database is established, and the multi-group cross-section database includes a number of nuclide cross-section parameters. Parallel statistical sampling can be performed as needed.
[0068] S22: Generate a cross-section disturbance factor based on the covariance information of the nuclide cross-section parameters.
[0069] S23: Perform multi-group microscopic cross-sectional perturbations based on cross-sectional perturbation factors.
[0070] S24: Make multi-group microscopic cross sections self-consistent.
[0071] S25: Reconstruction of multi-group microscopic cross sections.
[0072] S26: Performing full core neutronics calculation on the reconstructed core to obtain core neutron flux output parameters. For example, performing one-step neutronics calculation on the full core.
[0073] S27: Calculate the correspondence between the called nuclide cross section parameters and the core neutron flux output parameters. For example, according to the input nuclide cross section parameters, calculate the variance of the core neutron flux output parameters to obtain the confidence of the neutron flux uncertainty.
[0074] S28: Determine whether the confidence of the core neutron flux output parameter meets the set conditions, for example, determine whether the confidence reaches the set value; if yes, end and output the core neutron flux output parameter, otherwise execute step S22.
[0075] The above calculation parameters can be used to model the target reactor using nuclear design software, which outputs the calculation parameters of the target reactor under different states by calling uncertain input parameters.
[0076] Then, the power of the target reactor is fully utilized, which is a physical quantity that has been fully measured by uncertainty experiments. The calculation parameters and the power of the target reactor are used as response parameters to calculate the neutron flux uncertainty (step S2).
[0077] In this embodiment, the core neutron flux output parameter and the power of the target reactor are taken as response parameters to obtain the joint covariance matrix M of the neutron flux and the power and the correlation coefficient a of the neutron flux and the power.
[0078] The correlation coefficient a is calculated by the following formula:
[0079]
[0080] Among them, the power variance is Fpc, the neutron flux variance is Fnc, and the covariance of power-neutron flux is Xpn.
[0081] Then, the neutron flux uncertainty is obtained according to the correlation coefficient a. In this embodiment, the neutron flux uncertainty Unz is calculated by the following formula:
[0082]
[0083] Among them, the covariance of power-neutron flux Xpn, the total power uncertainty Upz, and the correlation coefficient a between neutron flux and power.
[0084] In this embodiment, while avoiding a large number of core measurement experiments, the uncertainty of neutron flux can still be fully considered. The main advantages are as follows:
[0085] It can simultaneously cover the uncertainty of nuclear data, uncertainty of nuclear fuel assembly manufacturing parameters, and uncertainty of neutron flux caused by thermal parameters;
[0086] It is possible to make full use of the existing power uncertainty data, and ultimately envelope the model uncertainty and measurement uncertainty related to the neutron flux by means of the power and neutron flux correlation coefficient.
[0087] like Figure 3 As shown, it is a schematic diagram of a specific application example of the neutron flux uncertainty quantification method of the present invention. In this embodiment, the uncertainty input parameter library includes a covariance multi-group cross-section library 31, a manufacturing parameter sample library 32, a core inlet temperature sample library 33, etc., and the nuclear design software PCM33 is used for modeling and calculation; the neutron flux output parameter and power are used as response parameters at the same time, and the joint covariance matrix M of the neutron flux and power and the correlation coefficient a (34) of the neutron flux and power are obtained, and finally the neutron flux uncertainty 35 is obtained.
[0088] First, the nuclide cross sections with covariance information are sampled to form 10,000 (of course, the number can be adjusted according to actual needs) new multi-group cross section libraries with covariance information.
[0089] The nuclear fuel assembly manufacturing parameter library is sampled to form 10,000 copies (the quantity can be adjusted according to actual needs) of manufacturing parameter tables; the core inlet temperature sample library is sampled to form 10,000 copies (the quantity can be adjusted according to actual needs) of core inlet temperature parameter tables.
[0090] The uncertainty caused by the manufacturing parameters of nuclear fuel assemblies and thermal fluid parameters only needs to be changed by random sampling, while the uncertainty caused by nuclear data is more complicated. The quantification process of the uncertainty of neutron flux caused by nuclear data based on the one-step calculation framework is as follows: Figure 4 shown.
[0091] S41: Establishing a one-step 69-group microscopic cross-section database. In this embodiment, a one-step multi-group cross-section database is established, and the multi-group cross-section database includes a number of nuclide cross-section parameters.
[0092] S42: Parallel statistical sampling based on efficient sampling techniques.
[0093] S43: Generate cross-section perturbation factors for the covariance information of the nuclide cross-section parameters, such as the covariance information of important nuclides such as Fe and U.
[0094] S44: Perform 69 groups of microscopic cross-sectional perturbations based on the cross-sectional perturbation factor.
[0095] S45: Make the 69-group microscopic cross section self-consistent.
[0096] S46: Reconstruction of the microscopic cross section of group 69.
[0097] S47: Performing full core neutronics calculation on the reconstructed core to obtain core neutron flux output parameters. For example, performing one-step neutronics calculation on the full core.
[0098] S48: Calculate the correspondence between the called nuclide cross section parameters and the core neutron flux output parameters. For example, according to the input nuclide cross section parameters, calculate the variance of the core neutron flux output parameters to obtain the confidence of the neutron flux uncertainty.
[0099] S49: Determine whether the confidence of the core neutron flux output parameter meets the set conditions, for example, determine whether the confidence reaches the set value, for example, whether the confidence reaches 95% (of course, this value can be adjusted as needed); if so, end and output the core neutron flux output parameter, otherwise execute step S43.
[0100] Then, the nuclear design software PCM is used to call 10,000 multi-group cross-section libraries to form 10,000 neutron flux output parameters. The nuclear design software PCM is used to call 10,000 manufacturing parameter tables to form 10,000 neutron flux output parameters. The nuclear design software PCM is used to call 10,000 core inlet thermal fluid parameter tables to form 10,000 neutron flux output parameters.
[0101] Then, we make full use of power, a physical quantity that has been fully measured by uncertainty experiments, and take the neutron flux output parameter and power as response parameters at the same time to obtain the joint covariance matrix M of neutron flux and power and the correlation coefficient a of neutron flux and power; the joint covariance matrix M is obtained by calculating the power variance Fpcpcm and the neutron flux variance Fncpcm by the nuclear design software PCM, and calculating the covariance Xpnpcm of power-neutron flux by the nuclear design software PCM. The correlation coefficient a of neutron flux and power is obtained by the following formula:
[0102]
[0103] Finally, the total neutron flux uncertainty Unzpcm is determined by the power-neutron flux covariance Xpnpcm, the total power uncertainty Upzpcm, and the correlation coefficient a between neutron flux and power. The total neutron flux uncertainty is obtained by the following formula:
[0104]
[0105] like Figure 5, which is a schematic block diagram of an embodiment of a neutron flux uncertainty quantification system of the present invention, and the system can execute the neutron flux uncertainty quantification method of any of the above embodiments. The system includes an acquisition module 51, which is used to acquire uncertainty input parameters;
[0106] An output calculation module 52, used to output calculation parameters of the target reactor under different states according to the uncertain input parameters; the calculation parameters include core neutron flux output parameters; and
[0107] The neutron flux uncertainty calculation module 53 is used to calculate the neutron flux uncertainty by taking the calculation parameters and the power of the target reactor as response parameters.
[0108] Furthermore, the system also includes an uncertainty input parameter library 54, which contains uncertain input parameters for the acquisition module to call to acquire the uncertain input parameters;
[0109] The uncertainty input parameter library includes a random sampling input parameter library and a verification input parameter library.
[0110] An embodiment of the present invention also provides a computer device, which includes a memory, a processor, and computer instructions stored in the memory and executable on the processor; when the processor executes the instructions, the steps of the neutron flux uncertainty quantification method are implemented.
[0111] In some embodiments, the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus random access memory (DRRAM). The memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.
[0112] The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware.
[0113] In some embodiments, the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), general purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions of the present application, or a combination thereof.
[0114] For software implementation, the technology of this article can be implemented by modules (such as procedures, functions, etc.) that perform the functions of this article. The software code can be stored in a memory and executed by a processor. The memory can be implemented in the processor or outside the processor.
[0115] Yet another embodiment of the present invention provides a computer storage medium, wherein the computer-readable storage medium stores an executable program, and when the executable program is executed by a processor, the steps of the neutron flux uncertainty quantification method can be implemented.
[0116] In some embodiments, computer storage media may include: USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks, and other media that can store program codes.
[0117] It can be understood that the above embodiments only express the preferred implementation modes of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the patent scope of the present invention. It should be pointed out that, for ordinary technicians in this field, the above technical features can be freely combined without departing from the concept of the present invention, and several deformations and improvements can be made, which all belong to the protection scope of the present invention. Therefore, all equivalent changes and modifications made to the scope of the claims of the present invention should belong to the coverage of the claims of the present invention.
Claims
1. A method for quantifying neutron flux uncertainty, characterized in that: The following steps are involved: S1: Acquire uncertainty input parameters; output calculation parameters of the target reactor under different states according to the uncertainty input parameters; the calculation parameters include core neutron flux output parameters; S2: taking the calculation parameter and the power of the target reactor as response parameters, calculating the neutron flux uncertainty, wherein the step S2 comprises: S2-1: taking the core neutron flux output parameter and the power of the target reactor as response parameters, obtaining a joint covariance matrix M of neutron flux and power and a correlation coefficient a of neutron flux and power; S2-2: Obtain the neutron flux uncertainty according to the correlation coefficient a; wherein, The correlation coefficient a is calculated by the following formula: Power variance Fpc, neutron flux variance Fnc, power-neutron flux covariance Xpn; The neutron flux uncertainty Unz is calculated by the following formula: Among them, the covariance of power-neutron flux Xpn, the total power uncertainty Upz, and the correlation coefficient a between neutron flux and power.
2. The neutron flux uncertainty quantification method according to claim 1, characterized in that: In step S1, it includes: S1-1: Establishing an uncertain input parameter library, wherein the uncertain input parameter library includes the uncertain input parameters; S1-2: Calling the uncertain input parameter in the uncertain input parameter library.
3. The neutron flux uncertainty quantification method according to claim 2, characterized in that: The uncertainty input parameter library includes a random sampling input parameter library and a verification input parameter library; correspondingly, the random sampling input parameter library includes a number of random sampling input parameters, and the verification input parameter library includes a number of verification input parameters; In the step S1-2, it includes: S1-2-1: randomly call the random sampling input parameter library to obtain the random sampling input parameter; S1-2-2: randomly retrieve the verification input parameter from the verification input parameter library, and obtain the verification input parameter after verification.
4. The method for quantifying neutron flux uncertainty according to claim 3, characterized in that: The random sampling input parameters include nuclear fuel assembly manufacturing parameters and thermal fluid parameters; correspondingly, the random sampling input parameter library includes a nuclear fuel assembly manufacturing parameter library and a thermal fluid parameter library; The verification input parameters include nuclide cross-section parameters; correspondingly, the verification input parameter library includes a multi-group cross-section library composed of the nuclide cross-section parameters.
5. The method for quantifying neutron flux uncertainty according to claim 4, characterized in that: In the step S1-2-1, a plurality of the nuclear fuel assembly manufacturing parameters in the nuclear fuel assembly manufacturing parameter library are randomly called to obtain the core neutron flux output parameter; A plurality of the thermal fluid parameters in the thermal fluid parameter library are randomly called to obtain the core neutron flux output parameter.
6. The method for quantifying neutron flux uncertainty according to claim 5, characterized in that: The nuclide cross section parameter is a nuclide cross section parameter with covariance information; In the step S1-2-2, it includes: S1-2-2-1: randomly calling a number of nuclide cross-section parameters from the multi-group cross-section library; S1-2-2-2: Generate a cross-section disturbance factor for the covariance information of the nuclide cross-section parameter; S1-2-2-3: Perform multi-group microscopic cross-sectional perturbations according to the cross-sectional perturbation factors; S1-2-2-4: making the multi-group microscopic cross sections self-consistent; S1-2-2-5: reconstructing the plurality of groups of microscopic cross sections; S1-2-2-6: Perform full core neutronics calculation on the reconstructed core to obtain the core neutron flux output parameters; S1-2-2-7: Calculate the correspondence between the nuclide cross-section parameter and the core neutron flux output parameter; S1-2-2-8: Determine whether the confidence level of the core neutron flux output parameter meets the set conditions; if so, terminate and output the core neutron flux output parameter; otherwise, execute step S1-2-2-2.
7. A neutron flux uncertainty quantification system, applying the neutron flux uncertainty quantification method according to any one of claims 1 to 6, characterized in that: include: An acquisition module, used to obtain uncertain input parameters; An output calculation module, used for outputting calculation parameters of the target reactor under different states according to the uncertainty input parameters; the calculation parameters include core neutron flux output parameters; as well as The neutron flux uncertainty calculation module is used to calculate the neutron flux uncertainty by taking the calculation parameter and the power of the target reactor as response parameters.
8. The neutron flux uncertainty quantification system according to claim 7, characterized in that: It also includes an uncertain input parameter library, which contains the uncertain input parameters and is used by the acquisition module to call and acquire the uncertain input parameters; The uncertainty input parameter library includes a random sampling input parameter library and a verification input parameter library.
9. A computer device, characterized in that: include: A processor and a memory for storing a computer program that can be run on the processor, wherein the processor is used to implement the neutron flux uncertainty quantification method described in any one of claims 1 to 6 when running the computer program.
10. A computer storage medium, characterized in that: An executable program is stored, and when the executable program is executed by a processor, the neutron flux uncertainty quantification method according to any one of claims 1 to 6 is implemented.