Core model correction based on data assimilation and quadrant power tilt calculation method

Abstract

The application discloses a core model correction method and device based on data assimilation, and equipment, the method can change the characteristics of the power level of each component in the core by adjusting the characteristic parameters, and the accuracy of the core theoretical model after correction in simulating the theoretical power level of the component can be improved by parameter assimilation of the parameter values of the characteristic parameters in the core theoretical model; and if at least one of the first characteristic parameters which do not change with the nuclear reactor unit operation is corrected in the first i-1 core theoretical model correction processes, it is proved that the first characteristic parameters at each component in the i-1 corrected core theoretical model have reached balance and solidification, interference of the parameters in the i correction process can be avoided, and the accuracy of the core theoretical model after the i correction in simulating the theoretical power level of the component can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear reactors, and particularly to a core model correction and quadrant power tilt calculation method based on data assimilation. BACKGROUND

[0002] In the field of nuclear reactor physics, the power level of each component of the core is mainly determined according to periodic measurement activities of the detector, but during the interval between two measurements, the change of the power level of each component of the core cannot be determined by this method, and only the power level of each component of the core can be simulated by a core theoretical model. However, since the core is always in a dynamic development process, the local and global state parameters of the core change at any time, and the power level of each component of the core also changes at any time. The prediction accuracy of the core theoretical model for the change trend of the power level of each component of the core is low. SUMMARY

[0003] The present application aims to at least solve the technical problems existing in the prior art. To this end, the present application provides a core model correction and quadrant power tilt calculation method based on data assimilation, which can improve the accuracy of the core theoretical model in simulating the power level of each component of the core and the calculation of the quadrant power tilt.

[0004] In a first aspect, an embodiment of the present application provides a core model correction method based on data assimilation, which comprises:

[0005] obtaining theoretical power levels of each component in the core simulated by a core theoretical model based on the i-th simulation, wherein the core theoretical model is constructed according to a corresponding nuclear reactor unit of the core; i is a positive integer greater than 1;

[0006] obtaining measured power levels corresponding to the theoretical power levels of each component, wherein the measured power levels are obtained by measuring the components in the core;

[0007] If there is at least one operation of parameter assimilation of the parameter value of the first characteristic parameter in the correction process of the core theoretical model in the previous i-1 times, then the parameter value of the second characteristic parameter in the core theoretical model is parameterized based on the theoretical power levels of each component obtained by the i-th simulation and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component obtained by the corrected core theoretical model and the measured power levels of each component is less than a target threshold;

[0008] The first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an influence on the power level of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reactor unit, and the second characteristic parameter is different from the first characteristic parameter.

[0009] The embodiments of the present application have at least the following beneficial effects by adopting the above technical solutions:

[0010] The method can change the characteristics of the power level of each component in the core by adjusting the characteristic parameters, and can improve the accuracy of the core theoretical model in simulating the theoretical power level of the component by correcting the parameter values of the characteristic parameters in the core theoretical model. If at least one of the first characteristic parameters is corrected in the previous i-1 times of correction of the core theoretical model, the first characteristic parameters of each component in the core theoretical model after the i-1 times of correction have reached a balance and are fixed, which can avoid interference of the parameters in the i times of correction, so that the i times of correction of the core theoretical model can be performed by correcting the characteristic parameters different from the first characteristic parameters in the core theoretical model, and the accuracy of the core theoretical model in simulating the theoretical power level of the component after the i times of correction can be improved.

[0011] In some embodiments of the present application, after the measured power levels corresponding to the theoretical power levels of each component are obtained, the method further comprises:

[0012] If there is no parameter assimilation operation of the parameter value of the first characteristic parameter in the previous i-1 times of correction of the characteristic parameters in the core theoretical model, the parameter value of the first characteristic parameter in the core theoretical model is corrected based on the theoretical power levels of each component obtained by the i times of simulation and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component obtained by the corrected core theoretical model and the measured power levels of each component is less than a target threshold.

[0013] In some embodiments of the present application, the parameter assimilation of the parameter value of the second characteristic parameter in the core theoretical model based on the theoretical power levels of each component obtained by the i times of simulation and the corresponding measured power levels comprises:

[0014] Determining the positive or negative correlation between the parameter value of the second characteristic parameter at the position of each component and the theoretical power level of each component;

[0015] Determining the size relationship between the theoretical power level of each component obtained by the core theoretical model and the measured power level of each component.

[0016] correcting a parameter value of the second characteristic parameter in the core theoretical model according to the positive or negative correlation and the size relationship.

[0017] In some embodiments of the present application, the parameter assimilation of the parameter value of the second characteristic parameter in the core theoretical model according to the positive or negative correlation and the size relationship comprises:

[0018] if the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, then increasing the parameter value of the second characteristic parameter in the core theoretical model; the target component is any one of the components;

[0019] if the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the second characteristic parameter is negatively correlated with the theoretical power level, then decreasing the parameter value of the second characteristic parameter in the core theoretical model;

[0020] if the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the second characteristic parameter is negatively correlated with the theoretical power level, then increasing the parameter value of the second characteristic parameter in the core theoretical model;

[0021] if the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, then decreasing the parameter value of the second characteristic parameter in the core theoretical model.

[0022] In some embodiments of the present application, before the obtaining of the theoretical power level of each component in the core simulated based on the core theoretical model after the i-1th correction, the method further comprises:

[0023] obtaining an initial theoretical power level of each component in the core simulated based on an initial core theoretical model;

[0024] obtaining an initial measured power level corresponding to the initial theoretical power level of each component;

[0025] correcting a parameter value of a first characteristic parameter in the initial core theoretical model based on the initial theoretical power level of each component and the corresponding initial measured power level, to obtain a core theoretical model after the first correction, and the deviation between the theoretical power level of each component simulated by the core theoretical model after the first correction and the initial measured power level of each component is less than a target threshold.

[0026] In some embodiments of the present application, the first characteristic parameter comprises a flow rate of the coolant / moderator at the reactor core inlet; and the second characteristic parameter comprises a water gap.

[0027] In a second aspect, the embodiments of the present application provide a method for calculating a quadrant power tilt of a reactor core, the method comprising:

[0028] simulating theoretical power levels of each component in the reactor core based on a target model, the target model being based on the corrected reactor core theoretical model in the method for correcting a reactor core model based on data assimilation according to the first aspect;

[0029] calculating a quadrant power tilt state of the reactor core according to the simulated theoretical power levels of each component in the reactor core based on the target model.

[0030] The embodiments of the present application have at least the following beneficial effects by adopting the above technical solutions:

[0031] The method simulates the theoretical power levels of each component in the reactor core based on the corrected reactor core theoretical model according to the first aspect, and then calculates the quadrant power tilt state of the reactor core using the simulated theoretical power levels of each component in the reactor core. Since the simulated theoretical power levels of each component in the reactor core are highly accurate, the calculated quadrant power tilt state of the reactor core is also highly accurate.

[0032] In a third aspect, the embodiments of the present application provide a device for correcting a reactor core model based on data assimilation, the device comprising:

[0033] a theoretical power level obtaining unit configured to obtain theoretical power levels of each component in the reactor core simulated based on the reactor core theoretical model corrected for the i-th time, the reactor core theoretical model being constructed according to a nuclear reaction unit corresponding to the reactor core; i is a positive integer greater than 1;

[0034] a measured power level obtaining unit configured to obtain measured power levels corresponding to the theoretical power levels of each component, the measured power levels being obtained by measuring the components in the reactor core;

[0035] a reactor core theoretical model correcting unit configured to, if there is at least one operation of parameter assimilation on a parameter value of a first characteristic parameter in a correction process of the reactor core theoretical model for the first i-1 times, perform parameter assimilation on a parameter value of a second characteristic parameter in the reactor core theoretical model based on the theoretical power levels of each component simulated for the i-th time and the corresponding measured power levels, so that a deviation between the theoretical power levels of each component simulated by the corrected reactor core theoretical model and the measured power levels of each component is less than a target threshold.

[0036] The first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an impact on the power level of each of the components, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reactor unit, and the second characteristic parameter is different from the first characteristic parameter.

[0037] In a fourth aspect, an embodiment of the present application provides an electronic device, including at least one control processor and a memory connected with the at least one control processor in communication; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor to enable the at least one control processor to execute the core model correction method based on data assimilation in the first aspect and the core quadrant power tilt calculation method in the second aspect.

[0038] In a fifth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions are used to make a computer execute the core model correction method based on data assimilation in the first aspect and the core quadrant power tilt calculation method in the second aspect.

[0039] It can be understood that the beneficial effects of the third aspect to the fifth aspect and related technologies compared with the first aspect and related technologies are the same, and can be referred to the related description in the first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0040] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, including the references to the figures, in which:

[0041] Figure 1 is a flowchart of an embodiment of the core model correction method based on data assimilation provided by the present application;

[0042] Figure 2 is a structural schematic diagram of an embodiment of the core model correction device based on data assimilation provided by the present application;

[0043] Figure 3 is a structural schematic diagram of an embodiment of the electronic device provided by the present application. DETAILED DESCRIPTION

[0044] Embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, in which the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation of the present application.

[0045] In the description of the present application, if there is a description to the first, second, etc. is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or implicitly indicating the order of the indicated technical features.

[0046] In the description of the present application, it is necessary to understand that the orientation description, such as the orientation or position relationship indicated by the upper, lower, etc. is based on the orientation or position relationship shown in the drawings, only for the purpose of describing the present application and simplifying the description, and is not indicative or implied that the indicated device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application.

[0047] Before introducing the specific embodiments, the technical concept of the present application is introduced:

[0048] The theoretical core model is a model constructed based on the existing three-dimensional core nuclear design program according to the core design parameters and core loading scheme of the nuclear power plant unit. The model can simulate the theoretical power level of each component in the nuclear reactor core after the preset parameters are obtained.

[0049] The core quadrant power tilt (TILT) refers to the asymmetry of the power of each quadrant during the operation of the core. It is a widespread phenomenon in the core of the pressurized water reactor, and is also a long-term problem left over in the field of core operation and fuel management. The factors causing the quadrant power tilt are numerous and complex, and involve the mutual coupling of neutron-thermal-fuel multi-physical fields in the core, and it is difficult to analyze the root cause in actual engineering. It mainly relies on regular measurement activities of the detector to determine the power tilt state of the current core.

[0050] Referring to Figure 1 An embodiment of the present application provides a core model correction method based on data assimilation, which comprises the following steps S110 to S130:

[0051] Step S110, obtaining the theoretical power level of each component in the core simulated at the i-th time based on the core theoretical model after the (i-1)-th correction, and the core theoretical model is constructed according to the corresponding nuclear reactor unit of the core.

[0052] Step S120, obtaining the measured power level corresponding to the theoretical power level of each component, and the measured power level is obtained by measuring the components in the core.

[0053] In step S130, if there is at least one operation of parameter assimilation of the parameter value of the first characteristic parameter in the previous i-1 times of the correction process of the theoretical model of the reactor core, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is assimilated based on the theoretical power level of each component obtained by the i-th simulation and the corresponding measured power level, so that the deviation between the theoretical power level of each component simulated by the corrected theoretical model of the reactor core and the measured power level of each component is less than the target threshold.

[0054] The first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an impact on the power level of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reactor unit, and the second characteristic parameter is different from the first characteristic parameter.

[0055] In step S110, the theoretical model of the reactor core can be designed by the reactor core block program SMART in the SCIENCE nuclear design package, or other core programs with equivalent functions. It should be noted that different types of nuclear power plant units need to have conventional core information, such as the number, type, size, arrangement of fuel assemblies, and the power, temperature, flow of the core design; the relevant design information of each unit may be slightly different.

[0056] Generally, the power level of each component in the core of the nuclear reactor unit is measured periodically to evaluate (such as quadrant tilt evaluation) according to the measurement, but during the two measurements, the power level of each component needs to be simulated and estimated by the model. In order to improve the accuracy of the simulated theoretical power level of the core theoretical model, the characteristic parameters in the model are adjusted to correct the model, so that the deviation between the theoretical power level of each component simulated by the corrected core theoretical model and the corresponding measured power level is less than the pre-set target threshold (the threshold can be set according to experience).

[0057] It should be noted that the modification process of the characteristic parameters in the theoretical model of the reactor core is the assimilation process of the characteristic parameters in the theoretical model of the reactor core. In the mainstream data assimilation algorithm, the measured value is fully trusted, that is, it is assumed that the true value is equal to the measured value. In this embodiment, the measured power level is fully trusted, that is, the measured power level is considered as the target value of the theoretical correction, and the influence of the measurement error is not considered.

[0058] Since there are many factors affecting the power distribution level of each component in the core, measurement error, reconstruction theory method, cross section database, reaction cross section, and core macroscopic operating state all have certain influences. However, in the correction process of the model, only a single adjustment of a certain characteristic parameter is considered each time to make the simulation theoretical result of the core theoretical model close to the measurement result. The single characteristic parameter is used to cover the comprehensive result of all other factors, and the unique characteristic parameter is used to represent the deviation between the measurement result and the theoretical calculation.

[0059] Therefore, when the power level of each component is measured each time, since there is a time interval between the previous measurement, the deviation of the core theoretical model will increase within the time interval. At this time, the core theoretical model needs to be corrected to reduce the deviation between the theoretical power level output by the core theoretical model and the measured power level. Step S110 assumes that the current is the i-th correction process, where i is a positive integer greater than 1. Before the i-th correction process, there are i-1 correction processes, and each correction process is based on the model after the last correction. For example, the i-th time uses the core theoretical model after the i-1-th correction. Through the cumulative correction of the model, the accuracy of the simulation theoretical power level of the model can be continuously improved.

[0060] In step S120, the measured power level corresponding to the theoretical power level of each component is obtained. For example, a core has 157 components, and the theoretical power level of the 157 components can be obtained through the model. The measured power level of the 157 components can be measured through flux map tests and other means. For example, the flux map measurement test is usually once a month. Here, in order to make the measured power level more real, the measured power level of each component after the flux map measurement test of the core measurement system is post-processed. The post-processing here can be filtering and other operations. Filtering removes interference factors to make the measured power level of the component more real, thereby improving the accuracy of subsequent correction.

[0061] In step S130, the first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an influence on the power level of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reactor unit. In this way, the first characteristic parameter can be adjusted first to achieve the assimilation of the first characteristic parameter in the model, so that the first characteristic parameter in the corrected core theoretical model reaches the optimal distribution, that is, the characteristic parameter can maintain a balanced state and be fixed in the subsequent correction process, and will not interfere with the subsequent operation.

[0062] Therefore, in step S130, when the i-th correction, firstly, it is judged whether the first characteristic parameter in the model has been adjusted at least once in the previous i-1 times, if the first characteristic parameter has been adjusted, it proves that the distribution level of the first characteristic parameter in the i-th corrected model reaches the theoretically optimal state (because the deviation of the theoretical power level of the output caused by the first characteristic parameter from the true value is small), at this time, because the first characteristic parameter in the model has been fixed, no interference is caused, and only the other characteristic parameters except the first characteristic parameter need to be considered, the second characteristic parameter is adjusted in the embodiment to make the theoretical power level simulated by the i-th corrected model close to the measured power level.

[0063] In some embodiments of the present application, the first characteristic parameter refers to a characteristic parameter that does not change with the operation of the nuclear reactor unit, for example, the first characteristic parameter is the flow rate of the coolant / moderator at the core inlet, in a pressurized water reactor, the coolant / moderator is light water containing boric acid, the flow rate distribution at the core inlet has different values or relative values (i.e. the flow rate distribution level) at the positions of each assembly, by adaptively adjusting the flow rate distribution level of the core inlet in the core theoretical model, the power distribution level of each assembly in the core theoretical model can be changed.

[0064] Because the difference between the theoretical power level and the measured power level of the nuclear reactor unit in the early life depends mainly on the flow rate distribution level, the flow rate distribution level of the core inlet in the model can be adjusted first to make the flow rate distribution level of the core inlet in the corrected model reach the theoretical optimum, and the flow rate distribution of each assembly reaches equilibrium and is fixed, for example, when the first correction, the flow rate distribution level of the core inlet in the core theoretical model is adjusted. It should be noted that the flow rate distribution level of the core inlet does not change with the operation of the reactor, the flow rate distribution level of the core inlet is caused by the flow rate distributor at the inlet of the reactor coolant, which is caused by the possible non-uniformity in manufacturing and assembly, and does not change after correction. However, the flow rate at each assembly inside the reactor will change, which is calculated according to various operating conditions of the reactor, which is not considered here.

[0065] The second characteristic parameter can be a characteristic parameter that does not change with the operation of the nuclear reactor unit, or a characteristic parameter that changes with the operation of the nuclear reactor unit, for example, the second characteristic parameter is the water gap. Because the fuel assembly deformation is an important influencing factor of TILT, the fuel assembly may be deformed or displaced in the reactor, which causes the change of the assembly gap (water gap), therefore, as the core continues to operate, the fuel assembly deformation will gradually accumulate, and the water gap distribution will gradually change.

[0066] The embodiment has at least the following beneficial effects:

[0067] The method can change the characteristics of the power levels of each component in the core by adjusting the characteristic parameters, and can improve the accuracy of the core theoretical model after correction in simulating the theoretical power levels of the components by correcting the parameter values of the characteristic parameters in the core theoretical model.

[0068] Moreover, if at least one of the previous i-1 core theoretical model correction processes is the correction of the parameter value of the first characteristic parameter that does not change with the operation of the nuclear reactor unit, it is proved that the first characteristic parameter at each component in the core theoretical model after the i-1 correction has reached equilibrium and solidification, which can avoid the interference of the parameter in the i correction process, so that when the core theoretical model is corrected for the i time, the accuracy of the core theoretical model after the i correction in simulating the theoretical power levels of the components can be improved by correcting the characteristic parameters different from the first characteristic parameter in the core theoretical model.

[0069] In some embodiments of the present application, after step S120, the method further comprises:

[0070] In step S120, if there is no parameter assimilation operation on the parameter value of the first characteristic parameter in the previous i-1 correction processes of the characteristic parameters in the core theoretical model, the parameter value of the first characteristic parameter in the core theoretical model is corrected based on the theoretical power levels of each component obtained by the i simulation and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component obtained by the simulation of the corrected core theoretical model and the measured power levels of each component is less than a target threshold.

[0071] Since the first characteristic parameter refers to a characteristic parameter that does not change with the operation of the nuclear reactor unit, if the parameter value of the first characteristic parameter is not corrected in the previous i-1 correction processes of the characteristic parameters in the core theoretical model, for example, the second characteristic parameter is corrected, then the parameter value of the first characteristic parameter in the model can be corrected when the model is corrected for the i time, so that the parameter value of the first characteristic parameter at each component in the model after correction reaches equilibrium and solidification, and the accuracy of the model in simulating the theoretical power levels is improved.

[0072] In some embodiments of the present application, the correction of the parameter value of the second characteristic parameter in the core theoretical model based on the theoretical power levels of each component obtained by the i simulation and the corresponding measured power levels in step S130 comprises:

[0073] In step S1310, the positive and negative correlation between the parameter value of the second characteristic parameter at the position of each component and the theoretical power level of each component is determined.

[0074] Step S1320, determine the magnitude relationship between the theoretical power level of each assembly simulated by the core theoretical model and the measured power level of each assembly.

[0075] Step S1330, correct the parameter value of the second characteristic parameter in the core theoretical model according to the positive and negative correlation and the magnitude relationship.

[0076] In step S1310, by adjusting the parameter value of the second characteristic parameter in the model, the theoretical power level of each assembly simulated by the model can be obtained, and by comparison, the positive and negative correlation between the parameter value of the second characteristic parameter of each assembly and the theoretical power level of each assembly can be determined, for example, the greater the flow distribution level, the better the moderation condition, and the higher the power level of the fuel assembly. Alternatively, a table is preset in advance, which records the positive and negative correlation between the flow distribution level of each assembly and the theoretical power level of each assembly (which can be obtained by experiment), and then the table is looked up to obtain.

[0077] In step S1320, the magnitude relationship can be determined by comparing the values of the two, for example, the theoretical power level of assembly 1 is greater than the measured power level, and the theoretical power level of assembly 2 is greater than the measured power level.

[0078] In step S1330, the parameter value of the second characteristic parameter in the core theoretical model is corrected according to the positive and negative correlation and the magnitude relationship. If the theoretical power level of each assembly simulated by the core theoretical model is higher than the measured power level of the assembly, and the second characteristic parameter (such as water gap) has a positive correlation with the theoretical power level, then the second characteristic parameter in the core theoretical model should be reduced, so that the theoretical power level of each assembly simulated by the corrected core theoretical model approximates the measured power level of the assembly.

[0079] It should be noted that the corresponding relationship between the preset theoretical power level and the corresponding measured power level and the parameter value of the second characteristic parameter can also be used, for example, according to the deviation between the theoretical power level and the measured power level, a corresponding adjustment value is set for the deviation, and this relationship is stored in the form of key value, and when used, only the table needs to be looked up to obtain the adjustment scheme.

[0080] It should be noted that if the first characteristic parameter is corrected, the correction process of the first characteristic parameter is also similar, for example,

[0081] (1) Determine the positive and negative correlation between the parameter value of the first characteristic parameter at the position of each assembly and the theoretical power level of each assembly.

[0082] (2) Determine the magnitude relationship between the theoretical power level of each assembly simulated by the core theoretical model and the measured power level of each assembly.

[0083] (3) According to the positive and negative correlation and the size relationship, the parameter value of the first characteristic parameter in the theoretical model of the reactor core is corrected.

[0084] Here is not described in detail.

[0085] The method can adjust the parameter value of the characteristic parameter through data comparison and positive and negative correlation, and the adjustment scheme is more accurate than the table lookup scheme.

[0086] In some embodiments of the present application, according to the positive and negative correlation and the size relationship, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is corrected, including the following:

[0087] (1) If the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is increased; the target component is any one of the components;

[0088] (2) If the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the second characteristic parameter is negatively correlated with the theoretical power level, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is decreased.

[0089] (3) If the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the second characteristic parameter is negatively correlated with the theoretical power level, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is increased.

[0090] (4) If the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, the parameter value of the second characteristic parameter in the theoretical model of the reactor core is decreased.

[0091] The present embodiment lists four cases of correcting the parameter value of the characteristic parameter in the theoretical model of the reactor core according to the positive and negative correlation and the size relationship. According to the above four cases, the parameter value of the second characteristic parameter in the theoretical model of the reactor core can be corrected, so that the corrected model can simulate the theoretical power level close to the measured power level, and the accuracy of the model simulated theoretical power level is improved.

[0092] It should be noted that the correction process of the first characteristic parameter is also similar, for example,

[0093] (1) If the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the first characteristic parameter is positively correlated with the theoretical power level, the parameter value of the first characteristic parameter in the theoretical model of the reactor core is increased; the target component is any one of the components.

[0094] (2) If the theoretical power level of the target component is less than the measured power level of the target component, and the parameter value of the first characteristic parameter is negatively correlated with the theoretical power level, the parameter value of the first characteristic parameter in the core theoretical model is reduced.

[0095] (3) If the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the first characteristic parameter is negatively correlated with the theoretical power level, the parameter value of the first characteristic parameter in the core theoretical model is increased.

[0096] (4) If the theoretical power level of the target component is greater than the measured power level of the target component, and the parameter value of the first characteristic parameter is positively correlated with the theoretical power level, the parameter value of the first characteristic parameter in the core theoretical model is reduced.

[0097] In some embodiments of the present application, the above-mentioned correction of the parameter value of the second characteristic parameter in the core theoretical model according to the positive and negative correlation and the size relationship includes the following process:

[0098] Step S1331, preset a proportionality coefficient.

[0099] Step S1332, multiply the parameter value of the second characteristic parameter in the core theoretical model by the proportionality coefficient, wherein the proportionality coefficient is associated with the positive and negative correlation and the size relationship.

[0100] In the present embodiment, each time the parameter value of the target characteristic parameter in the core theoretical model is corrected is to multiply the parameter value of the characteristic parameter in the core theoretical model by a proportionality coefficient, which can control the consistency of adjustment. Moreover, because the correction process of the model often needs multiple adjustments, when multiplying a proportionality coefficient, the adjustment process can be refined, and the efficiency of model correction can be improved. For example, if the flow distribution level is to be improved, a coefficient c (c>1) is multiplied, and the coefficient c can be 1.1, 1.2, 1.3. If it is to be reduced, a coefficient c (0<c<1) is multiplied, and the coefficient c can be 0.9, 0.8, 0.7. The value of the coefficient c is associated with the positive and negative correlation and the size relationship.

[0101] It should be noted that the proportionality coefficient can not be used, but fine-tuning can be performed according to experience.

[0102] In some embodiments of the present application, before the step S110 of acquiring the theoretical power level of each component in the core obtained by the i-th simulation based on the core theoretical model after the i-1-th correction, the method further comprises:

[0103] acquiring an initial theoretical power level of each component in the core obtained by simulation based on an initial core theoretical model;

[0104] obtaining initial measured power levels corresponding to the initial theoretical power levels of the components;

[0105] correcting the parameter values of the first characteristic parameters in the initial core theoretical model based on the initial theoretical power levels of the components and the corresponding initial measured power levels, to obtain a first corrected core theoretical model, and the deviation between the theoretical power levels of the components simulated by the first corrected core theoretical model and the initial measured power levels of the components is less than a target threshold.

[0106] The method provided by the embodiment can adjust the first characteristic parameters when the core theoretical model is initially corrected, and then the subsequent several times of correction do not need to consider the interference caused by the first characteristic parameters, but can consider the second characteristic parameters changed with the operation of the core and correct the second characteristic parameters. Moreover, because the first correction is performed at the first time, the interference caused by the first characteristic parameters in the subsequent correction of the core theoretical model can be avoided to the maximum extent, and the accuracy of the simulation of the subsequent core theoretical model is improved.

[0107] Two application scenarios of the application are provided as follows:

[0108] Scenario 1, safety monitoring of the components of the core.

[0109] Generally, the actual measurement of the power levels of the components in the core needs to be performed at an interval of 1 month, and thus the power levels of the components cannot be actually measured and detected between two periodic actual measurements. At this time, the theoretical power levels are simulated by the core theoretical model, the theoretical power levels of the components of the core are simulated by the simulated theoretical power levels, and the safety monitoring of the components is performed by the simulated data.

[0110] Through the processing of the above steps S110 to S130, the theoretical power levels simulated by the corrected core theoretical model can be maximally close to the actual levels of the components, and thus the simulation of the theoretical power levels of the components between two periodic actual measurements is realized, and the safety monitoring is realized.

[0111] Scenario 2, tilt monitoring of the components of the core.

[0112] The core quadrant power tilt value calculation formula is:

[0113]

[0114] wherein, P i (i=1, 2, 3, 4) represents the average power level in each quadrant; P (avg)represent the full core average power level; that is, the ratio of the maximum quadrant average power to the full core average power level.

[0115] Therefore, after obtaining the accurate simulated theoretical power level, the quadrant tilt state can be calculated by using the above formula.

[0116] Therefore, one embodiment of the present application provides a method for calculating the core quadrant power tilt, the method comprising:

[0117] In step S210, the theoretical power level of each component in the core is simulated based on a target model, which is based on the corrected core theoretical model in the data assimilation-based core model correction method.

[0118] In step S220, the core quadrant power tilt state is calculated according to the theoretical power level of each component simulated by the target model.

[0119] It should be noted that the core quadrant power tilt state is calculated by using the above core quadrant power tilt calculation formula, and a high-accuracy core quadrant power tilt state can be calculated by using the method. Details are not described here, and will be described in subsequent embodiments.

[0120] In order to facilitate the understanding of those skilled in the art, taking scenario 2 as an example, a method for calculating the core quadrant power tilt is provided, and the method flow is as follows:

[0121] In step S910, a core theoretical model is constructed based on the existing three-dimensional core nuclear design program according to the core design parameters and the core loading scheme of the nuclear power plant unit.

[0122] For example, taking a CPR1000 unit as an example, the core has 157 components, and 157 theoretical power levels can be obtained by theoretical calculation of the core theoretical model. Denoted as: Pa (i) where i = 1, 2,..., 157.

[0123] At the same time, the core quadrant power tilt value TILT(k) is obtained, k is four quadrants: 1, 2, 3, and 4 quadrants. It should be noted that in the general initial state, the reference symmetric design, TILT = 1.00, that is, the power of each quadrant of the full core is uniform. It should be noted that there are various ways to divide the quadrant, but it does not affect the present embodiment.

[0124] In step S920, the periodic measured data is obtained.

[0125] Based on the RIC (nuclear core measurement system) flux map measurement test work of the nuclear power plant carried out periodically (about once a month), the periodic measured power level and the core TILT value are obtained.

[0126] For example, taking the CPR1000 unit as an example, there are 157 assemblies in the core, i.e. 157 measured power levels are obtained after test measurement and post-processing. Denoted as: Pt (i) , i = 1, 2,..., 157.

[0127] Step S930, fuse the measured data and the theoretical model.

[0128] (1) the first correction process;

[0129] In this embodiment, the measured value is fully trusted. The measured power level is considered as the target value for theoretical correction, and subsequent technical means will be taken to correct the theoretical model so that the theoretical power level Pa (i) approaches the measured power level Pt (i) .

[0130] Obtain the measured power level of each assembly described above;

[0131] Adjust the flow distribution level at the core inlet in the core theoretical model to correct the theoretical power level of each assembly in the core theoretical model. Then, by repeatedly adjusting the inlet flow distribution parameters in the core theoretical model, an optimal inlet flow distribution level is finally obtained, so that the core theoretical power level Pa (i) approaches the first measured power level Pt (i) .

[0132] The specific correction process includes:

[0133] Analyze the influence of the selected flow distribution level increase / decrease on the power level of the assembly to determine its positive / negative correlation. Generally, the greater the flow level, the better the moderation condition, and the higher the power level of the fuel assembly.

[0134] First, give an initial level of flow distribution.

[0135] Then, solve the theoretical power level Pa (i) of the core theoretical model under the condition of the initial level of flow distribution.

[0136] Then, in order, compare the size of the theoretical power level Pa i and the measured power level Pt (i) in the order of the label (from assembly 1 to assembly 157), i = 1, 2,..., 157.

[0137] If Pt (i) > Pa (i) ; increase the flow distribution level at the assembly to increase Pa (i) ; if Pt (i) < Pa (i); then reduce the flow distribution level at the component, so that Pa (i) is reduced.

[0138] When adjusting (increasing, reducing), the adjustment can be proportional; assuming that the correction weight coefficient of the initial flow level is consistent, all are 1.0.

[0139] If the flow distribution level is increased, multiply by the coefficient c (c>1), such as 1.1, 1.2, 1.3. If the flow distribution level is reduced, multiply by the coefficient c (c<1), such as 0.9, 0.8, 0.7.

[0140] For the flow distribution level, only a small amplitude is adjusted each time, and the inlet flow level of each component in the core theoretical model needs to be adjusted repeatedly through multiple iterations, and finally a reasonable flow distribution level of the core theoretical model will be obtained, so that the core theoretical power distribution and the measured power level distribution are consistent, that is:

[0141] Pt (i) -Pa (i) <0.001, i = 1, 2,..., 157

[0142] Finally, the burnup calculation analysis is carried out by using the corrected core theoretical model to simulate the steady-state flux map test time of the actual operation of the core, so as to predict the change trend of TILT in this stage. It should be noted that the core quadrant power tilt is calculated based on the power distribution, and when the core power distribution is determined, the core quadrant power tilt will also be determined.

[0143] The first correction is to assimilate the core inlet flow parameters, ignoring other uncertain factors that cause TILT. It is assumed that the difference between theory and practice at the beginning of the life of the nuclear reactor unit depends on the flow difference, and the flow distribution is corrected to correct the core theoretical model, and this flow distribution is maintained unchanged during the subsequent operation of the unit. It can effectively describe the possible uneven flow distribution problem of the actual core.

[0144] (2) The second correction process;

[0145] Collect the measured power level of each component;

[0146] Based on the model of the first correction, adjust the water gap distribution in the core theoretical model (which covers all factors that may affect TILT), to correct the theoretical power level of each component in the core theoretical model. Then, by repeatedly adjusting the water gap distribution in the core theoretical model, the core theoretical power level Pa (i) approaches the measured power level Pt (i) .

[0147] The specific correction process is similar to the first correction process described above, and will not be described here.

[0148] Based on the core theoretical model after assimilating the water gap distribution parameters, the burnup calculation analysis is carried out, the core operation state and the quadrant power tilt state (TILT value) of the core in the subsequent stage (about a month) are simulated, and the short-term prediction of the TILT change trend is realized.

[0149] Since the fuel assembly deformation is an important factor affecting the TILT, and the fuel assembly may be deformed or displaced in the reactor, which changes the assembly gap (water gap), the flow distribution has been corrected and fixed after the first correction process. Therefore, the water gap distribution is used as the characteristic parameter for the second correction of the model in the present application, and the water gap is used as the main factor, which can not only approximately replace other comprehensive influences, but also effectively solve the problem of possible fuel assembly deformation in the actual core.

[0150] (3) The third to Nth correction processes are similar to the correction process of the previous step, which is to adjust the water gap distribution in the core theoretical model to realize the data assimilation-based core model correction. This is because the fuel assembly deformation will gradually accumulate with the operation of the nuclear reactor unit, so each subsequent correction process can only adjust the water gap distribution. Through regular correction, long-term prediction of the TILT change trend is realized.

[0151] As Figure 2 Some embodiments of the present application provide a data assimilation-based core model correction device, which comprises:

[0152] The theoretical power level acquisition unit 1100 is configured to acquire theoretical power levels of each component in the core simulated in the i-th time based on the core theoretical model corrected in the i-1-th time, and the core theoretical model is constructed according to the corresponding nuclear reactor unit of the core.

[0153] The measured power level acquisition unit 1200 is configured to acquire measured power levels corresponding to the theoretical power levels of each component, and the measured power levels are obtained by measuring the components in the core.

[0154] The core theoretical model correction unit 1300 is configured to, if there is at least one operation of parameter assimilation of the parameter value of the first characteristic parameter in the correction process of the core theoretical model in the previous i-1 times, perform parameter assimilation of the parameter value of the second characteristic parameter in the core theoretical model based on the theoretical power levels of each component simulated in the i-th time and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component simulated by the corrected core theoretical model and the measured power levels of each component is less than a target threshold.

[0155] The first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an influence on the power level of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reaction unit, and the second characteristic parameter is different from the first characteristic parameter.

[0156] It should be noted that the data assimilation-based core model correction device provided by the embodiment and the data assimilation-based core model correction method described above are based on the same inventive concept, and therefore the content of the data assimilation-based core model correction method described above is also applicable to the data assimilation-based core model correction method device, and therefore the content will not be described again here.

[0157] As Figure 3 The embodiment of the present application further provides an electronic device, and the electronic device comprises:

[0158] at least one hydrogen fuel cell;

[0159] at least one memory;

[0160] at least one processor;

[0161] at least one program;

[0162] The program is stored in the memory, and the processor executes the at least one program to implement the data assimilation-based core model correction method and the core quadrant power tilt calculation method provided in the present disclosure.

[0163] The electronic device can be any intelligent terminal, such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a vehicle-mounted computer, etc.

[0164] The electronic device of the embodiment of the present application will be described in detail below.

[0165] The processor 1600 can be implemented in a general central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute related programs to implement the technical solutions provided by the embodiments of the present disclosure.

[0166] The memory 1700 can be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM), etc. The memory 1700 can store an operating system and other application programs. When the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, the related program codes are stored in the memory 1700 and are invoked and executed by the processor 1600 to implement the data assimilation-based core model correction method and the core quadrant power tilt calculation method according to the embodiments of the present disclosure.

[0167] The input / output interface 1800 is configured to realize information input and output.

[0168] The communication interface 1900 is configured to realize the communication interaction between the device and other devices. The communication can be realized in a wired manner (for example, a USB, a network cable, etc.) or in a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.).

[0169] The bus 2000 is configured to transmit information between various components (for example, the processor 1600, the memory 1700, the input / output interface 1800, and the communication interface 1900) of the device.

[0170] The processor 1600, the memory 1700, the input / output interface 1800, and the communication interface 1900 are connected to each other through the bus 2000 to realize the communication connection between them within the device.

[0171] The present disclosure further provides a storage medium, which is a computer-readable storage medium and stores computer executable instructions for causing a computer to execute the data assimilation-based core model correction method and the core quadrant power tilt calculation method.

[0172] The memory is a non-transitory computer-readable storage medium and can be used to store a non-transitory software program and a non-transitory computer executable program. In addition, the memory can include a high-speed random access memory and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0173] The embodiments described in the present disclosure are to more clearly illustrate the technical solutions of the present disclosure, and do not constitute a limitation on the technical solutions provided by the present disclosure. Those skilled in the art can know that, as technology evolves and new application scenarios appear, the technical solutions provided by the present disclosure are also applicable to similar technical problems.

[0174] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the present disclosure, and can include more or fewer steps than shown in the figures, or combine certain steps, or different steps.

[0175] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment.

[0176] Those skilled in the art can understand that all or some steps in the above disclosed method, the function modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0177] The terms "first", "second", "third", "fourth" and the like (if any) in the specification of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0178] It should be understood that, in the application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases of only A, only B and A and B existing at the same time, wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b and c can be single or multiple.

[0179] In several embodiments provided in the application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0180] The units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0181] In addition, the functional units in each embodiment of the application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0182] If the integrated unit is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes multiple instructions for causing an electronic device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various program storage media.

[0183] The above is a specific description of the preferred implementation of the embodiments of the present application, but the embodiments of the present application are not limited to the above-mentioned implementation. Those skilled in the art can make various equivalent modifications or replacements without departing from the spirit of the embodiments of the present application, and these equivalent modifications or replacements are all included in the scope defined by the claims of the embodiments of the present application.

[0184] The embodiments of the present application are described in detail above in combination with the drawings, but the present application is not limited to the above-mentioned embodiments. Those skilled in the art can make various changes within the scope of knowledge possessed by those skilled in the art without departing from the purpose of the present application.

Claims

1. A method for core model updating based on data assimilation, characterized in that, The method comprises: obtaining theoretical power levels of each component in a core obtained by i-th simulation based on a core theoretical model after i-1-th correction, wherein the core theoretical model is constructed according to a nuclear reaction unit corresponding to the core; i is a positive integer greater than 1; obtaining measured power levels corresponding to the theoretical power levels of each component, wherein the measured power levels are obtained by measuring the components in the core; if there is at least one operation of parameter assimilation of a parameter value of a first characteristic parameter in a correction process of the core theoretical model in the previous i-1 times, then performing parameter assimilation of a parameter value of a second characteristic parameter in the core theoretical model based on the theoretical power levels of each component obtained by the i-th simulation and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component obtained by simulation of the corrected core theoretical model and the measured power levels of each component is less than a target threshold; wherein the first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an impact on the power levels of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reaction unit, and the second characteristic parameter is different from the first characteristic parameter.

2. The data assimilation based core model correction method of claim 1, wherein, After the obtaining of the measured power levels corresponding to the theoretical power levels of each component, the method further comprises: if there is no operation of parameter assimilation of the parameter value of the first characteristic parameter in the correction process of the characteristic parameter in the core theoretical model in the previous i-1 times, then correcting the parameter value of the first characteristic parameter in the core theoretical model based on the theoretical power levels of each component obtained by the i-th simulation and the corresponding measured power levels, so that the deviation between the theoretical power levels of each component obtained by simulation of the corrected core theoretical model and the measured power levels of each component is less than a target threshold.

3. The data assimilation based core model correction method of claim 1, wherein, The parameter assimilation of the parameter value of the second characteristic parameter in the core theoretical model based on the theoretical power levels of each component obtained by the i-th simulation and the corresponding measured power levels comprises: determining the positive and negative correlation between the parameter value of the second characteristic parameter at the position of each component and the theoretical power level of each component; determining the size relationship between the theoretical power levels of each component obtained by simulation of the core theoretical model and the measured power levels of each component; correcting the parameter value of the second characteristic parameter in the core theoretical model according to the positive and negative correlation and the size relationship.

4. The data assimilation based core model correction method of claim 3, wherein, The parameter assimilation of the parameter value of the second characteristic parameter in the core theoretical model according to the positive and negative correlation and the size relationship comprises: if the theoretical power level of a target component is less than the measured power level of the target component, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, then increasing the parameter value of the second characteristic parameter in the core theoretical model; the target component is any one of the components; if the theoretical power level of the target assembly is less than the measured power level of the target assembly, and the parameter value of the second characteristic parameter is negatively correlated with the theoretical power level, then the parameter value of the second characteristic parameter in the theoretical model of the reactor core is decreased; if the theoretical power level of the target assembly is greater than the measured power level of the target assembly, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, then the parameter value of the second characteristic parameter in the theoretical model of the reactor core is decreased. if the theoretical power level of the target assembly is greater than the measured power level of the target assembly, and the parameter value of the second characteristic parameter is positively correlated with the theoretical power level, then the parameter value of the second characteristic parameter in the theoretical model of the reactor core is decreased.

5. The data assimilation based core model correction method of claim 1, wherein, Before the theoretical power level of each assembly in the reactor core simulated based on the i-th modified theoretical model of the reactor core is obtained, the method further comprises: obtaining an initial theoretical power level of each assembly in the reactor core simulated based on an initial theoretical model of the reactor core; obtaining an initial measured power level corresponding to the initial theoretical power level of each assembly; based on the initial theoretical power level of each assembly and the corresponding initial measured power level, modifying the parameter value of the first characteristic parameter in the initial theoretical model of the reactor core to obtain a first modified theoretical model of the reactor core, and the deviation between the theoretical power level of each assembly simulated by the first modified theoretical model of the reactor core and the initial measured power level of each assembly is less than a target threshold.

6. The data assimilation based core model correction method of claim 1, wherein, The first characteristic parameter includes the flow rate of the coolant / moderator at the inlet of the reactor core; and the second characteristic parameter includes the water gap.

7. A method of calculating a core quadrant power tilt, characterized by, The method comprises: simulating the theoretical power level of each assembly in the reactor core based on a target model, the target model being based on the modified theoretical model of the reactor core in the method for modifying the reactor core model based on data assimilation according to any one of claims 1 to 6; calculating the quadrant power tilt state of the reactor core according to the theoretical power level of each assembly simulated by the target model.

8. A core model correction device based on data assimilation, characterized by, The apparatus comprises: a theoretical power level obtaining unit configured to obtain the theoretical power level of each assembly in the reactor core simulated based on the i-th modified theoretical model of the reactor core, the theoretical model of the reactor core being constructed according to the corresponding nuclear reaction unit of the reactor core; i is a positive integer greater than 1; a measured power level obtaining unit configured to obtain a measured power level corresponding to the theoretical power level of each assembly, the measured power level being obtained by measuring the assembly in the reactor core; and a modifying unit configured to modify the parameter value of the first characteristic parameter in the initial theoretical model of the reactor core based on the initial theoretical power level of each assembly and the corresponding initial measured power level. The core theoretical model correction unit is configured to, if there is at least one operation of parameter assimilation on the parameter value of the first characteristic parameter in the previous i-1 times of correction of the core theoretical model, perform parameter assimilation on the parameter value of a second characteristic parameter in the core theoretical model based on the theoretical power level of each component obtained by the i-th simulation and the corresponding measured power level, so that the deviation between the theoretical power level of each component obtained by the corrected core theoretical model and the measured power level of each component is less than a target threshold. The first characteristic parameter and the second characteristic parameter are both characteristic parameters that have an impact on the power level of each component, and the first characteristic parameter is a characteristic parameter that does not change with the operation of the nuclear reactor unit, and the second characteristic parameter is different from the first characteristic parameter.

9. An electronic device, comprising: The computer readable storage medium stores computer executable instructions for causing a computer to execute any one of the core model correction method based on data assimilation and the core quadrant power tilt calculation method of claim 7.

10. A computer-readable storage medium, characterized in that: The computer readable storage medium stores computer executable instructions for causing a computer to execute any one of the core model correction method based on data assimilation and the core quadrant power tilt calculation method of claim 7.

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