Method and device for diagnosing a reactor neutron probe, readable storage medium

Abstract

The application provides a reactor neutron detector diagnosis method and device, readable storage medium, the method comprises: according to the burnup calculation of reactor operation data, and the core model is updated according to the calculation result;Based on the updated core model, the whole core pin-by-pin neutron transport calculation is executed, and the whole core three-dimensional cell level neutron flux distribution is obtained;According to the cell level neutron flux distribution, the predicted current value of the position of each neutron detector is calculated;The measured current value of each neutron detector is obtained, and the measured current value, the predicted current value and the reactor operation parameter are periodically saved as historical data;From the saved historical data, the data set meeting the preset condition is screened out, based on the screened data set, the characteristic parameters of the ratio of the measured current value and the predicted current value of each neutron detector are counted, and the state of the corresponding neutron detector is diagnosed according to the characteristic parameters.

Description

Technical Field

[0001] This application relates primarily to the field of nuclear reactor technology, and in particular to a diagnostic method, apparatus, and readable storage medium for a reactor neutron detector. Background Technology

[0002] Real-time and accurate monitoring of neutron flux distribution in the reactor core is a core guarantee for the safe operation of nuclear power plants. The in-core neutron detector, acting as the "nerve endings" of core measurements, directly reflects the neutron flux distribution in the core, and thus can reveal potential abnormal states during reactor operation. However, in-core neutron detectors operate under high temperature, high pressure, and strong radiation environments for extended periods, making them prone to signal drift, cable insulation failure, and other malfunctions. This can lead to measurement distortion, and in severe cases, may mask localized power anomalies in the core, threatening nuclear safety.

[0003] When a neutron detector malfunctions, it is crucial to diagnose and accurately determine the failure status promptly. Inaccurate diagnosis and continued use of the failure signal will significantly reduce measurement accuracy; in severe cases, it may lead to operators misjudging the core status, impacting operational safety. Therefore, the accuracy of neutron detector diagnosis directly determines the accuracy and reliability of core measurements.

[0004] Existing detector diagnostic techniques include the measurement-prediction deviation threshold method. This method uses reactor operating data to construct a theoretical model to predict the detector current value (I_p, usually derived from neutron flux calculations), while simultaneously acquiring and measuring the current value (I_m) in real time. The ratio of I_m to I_p is calculated (R = I_m / I_p), and a fixed threshold range is set based on engineering experience (typically 0.6-1.4). The main problem with this method is that the predicted current generally has low calculation accuracy and significant uncertainty; the threshold range for the I_m / I_p ratio used for screening is too large, making it difficult to reliably screen detectors with non-significant deviations but already showing some difference from the average level. In other words, the accuracy of existing neutron detector diagnostic methods is low. Summary of the Invention

[0005] The technical problem to be solved by this application is to provide a diagnostic method, apparatus, and readable storage medium for reactor neutron detectors, thereby improving diagnostic accuracy.

[0006] To address the aforementioned technical problems, this application provides a diagnostic method for reactor neutron detectors, comprising: performing burnup calculations based on reactor operating data to obtain an updated core model; performing full-core pin-by-pin neutron transport calculations based on the updated core model to obtain a three-dimensional grid-level neutron flux distribution across the entire core; calculating the predicted current value at the location of each neutron detector based on the grid-level neutron flux distribution; obtaining the actual measured current value of each neutron detector and periodically saving the measured current value, predicted current value, and reactor operating parameters as historical data; selecting datasets that meet preset conditions from the saved historical data; statistically analyzing the characteristic parameters of the ratio of the measured current value to the predicted current value for each neutron detector based on the selected datasets; and diagnosing the state of the corresponding neutron detector based on the characteristic parameters.

[0007] Optionally, the pin-by-pin neutron transport calculation is solved using the block response matrix method, and an accelerated method based on matrix block inversion is used to calculate the block response matrix during the solution process.

[0008] Optionally, the accelerated calculation of the nodal response matrix using a matrix block inversion method during the solution process includes: constructing a matrix X representing the transport relationship of neutrons between different energy groups, wherein, based on the physical properties of neutron scattering, the matrix blocks corresponding to energy groups without upscattering effects are constructed into lower triangular matrices L, and the matrix blocks corresponding to hot energy groups with upscattering effects are constructed into matrix R, so that matrix X has a block-based lower triangular structure; based on the principle of matrix block inversion, the inversion operation of matrix X is transformed into the inversion operation of the lower triangular matrix L and the inversion operation of matrix R; and the nodal response matrix is ​​calculated using the transformed inversion operation results.

[0009] Optionally, the full-core pin-by-pin neutron transport calculation is solved through a source iteration process, which includes the following steps:

[0010] a. Initialize neutron flux, deflection current, and effective multiplication coefficient k eff ;

[0011] b. Set the source iteration counter;

[0012] c. Calculate or update the fission source term;

[0013] d. Calculate the nodal outflow deflection based on the nodal incident deflection and fission source term;

[0014] e. Update the nodal incident deflection based on the outer boundary conditions and the continuity conditions between nodules;

[0015] f. Calculate the nodal response matrix from the nodal incident deflection flow and fission source term to update the nodal flux;

[0016] g. Update the effective multiplication coefficient k eff ;

[0017] h. Calculate the flux deviation between the two iterations and k. eff deviation;

[0018] i. Determine the flux deviation relative to k eff Check whether the deviation meets the convergence criterion or whether the number of iterations has reached the upper limit; if it meets the criterion, output the result; otherwise, return to step c for the next iteration.

[0019] Optionally, the predicted current value is calculated using the following formula:

[0020]

[0021] in, Indicates slow-release current. Indicates instantaneous current;

[0022] ε is the electron escape probability, which characterizes the probability that electrons generated during the decay process of the neutron detector emitter will form an effective current; λ is the decay constant of the neutron detector emitter; N is the nucleon density of the neutron detector emitter; S is the transient sensitivity coefficient of the neutron detector; ϕ1 is the thermal neutron flux at the location of the neutron detector.

[0023] Optionally, statistically analyzing the characteristic parameters of the ratio of the measured current value to the predicted current value for each neutron detector, and diagnosing the state of the corresponding neutron detector based on the characteristic parameters, includes: for each neutron detector, calculating the average and standard deviation of the ratio of the measured current value to the predicted current value in its filtered dataset; diagnosing the state of the neutron detector based on the average and standard deviation, wherein the state of the neutron detector includes good, needing correction, and abnormal.

[0024] Optionally, diagnosing the state of the neutron detector based on the average value and standard deviation includes: when the average value is within a first preset range and the standard deviation is less than a first preset threshold, the state of the neutron detector is determined to be good; when the "good" condition is not met, but the average value is within a second preset range wider than the first preset range and the standard deviation is less than the first preset threshold, the state of the neutron detector is determined to be in need of correction; when the average value exceeds the second preset range, or the standard deviation is greater than the first preset threshold, the state of the neutron detector is determined to be abnormal.

[0025] Optionally, the first preset range is (0.95, 1.05), the second preset range is (0.9, 1.1), and the first preset threshold is 1.5%.

[0026] Optionally, it further includes: setting a response sensitivity correction factor for each neutron detector based on the diagnosed state of the neutron detector; and correcting the subsequent measured current value of the neutron detector based on the response sensitivity correction factor.

[0027] Optionally, setting a response sensitivity correction factor for each neutron detector based on the diagnosed state of the neutron detector includes: setting the response sensitivity correction factor of the neutron detector to 1.0 when the state of the neutron detector is determined to be good; setting the response sensitivity correction factor of the neutron detector to the reciprocal of the average value when the state of the neutron detector is determined to be to be corrected; and setting the response sensitivity correction factor of the neutron detector to 0.0 when the state of the neutron detector is determined to be abnormal.

[0028] To address the aforementioned technical problems, this application provides a diagnostic device for a reactor neutron detector, comprising a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to cause the device to perform the method described above.

[0029] To address the aforementioned technical problems, this application provides a computer-readable storage medium including computer program instructions, which, when executed by a processor, cause the processor to perform the method described above.

[0030] Compared with the prior art, this application has the following advantages:

[0031] The reactor neutron detector diagnostic method, apparatus, and readable storage medium of this application employ higher-precision whole-core pin-by-pin transport calculations, thereby improving the accuracy of neutron flux calculation, which in turn improves the accuracy of detector signal prediction and ultimately enhances the detector status diagnosis accuracy. Secondly, this application comprehensively considers the statistical quantities of a large amount of historical detector data for detector status diagnosis. Based on this, the method narrows the screening range of the ratio of measured current to predicted current of abnormal detectors from the traditional (0.6, 1.4) to (0.9, 1.1) without worrying about misjudgment, further improving the detector status diagnosis accuracy. Attached Figure Description

[0032] The accompanying drawings are included to provide a further understanding of this application. They are incorporated into and constitute a part of this application. The drawings illustrate embodiments of this application and, together with this specification, serve to explain the principles of this application.

[0033] Figure 1 This is a flowchart of a diagnostic method for a reactor neutron detector according to an embodiment of this application.

[0034] Figure 2This is a flowchart of pin-by-pin transport calculation according to an embodiment of this application.

[0035] Figure 3 This is a schematic diagram of a diagnostic system for a reactor neutron detector according to an embodiment of this application.

[0036] Figure 4 This is a diagram of the operation interface of a detector status diagnosis program according to an embodiment of this application.

[0037] Figure 5 This is a diagram of the operation interface of the detector status setting program according to an embodiment of this application.

[0038] Figure 6 This is a schematic diagram of a diagnostic device for a reactor neutron detector according to an embodiment of this application. Detailed Implementation

[0039] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0040] The purpose of this application is to provide a diagnostic method for reactor neutron detectors. This method can achieve high-precision neutron flux simulation calculation at the three-dimensional grid level of the entire reactor core, high-precision prediction of detector signals, and detector status diagnosis. It can accurately determine detector signal deviation and failure status, correct detector signals with deviations, and bypass (shield) failed detector signals to avoid their participation in subsequent core measurements, thereby improving the accuracy and reliability of core measurements.

[0041] The implementation of this method can be divided into key steps such as in-core neutron detector signal acquisition, core model update, core neutron flux calculation, detector signal prediction, detector historical data storage, detector status diagnosis, and detector signal correction.

[0042] Figure 1 This is a flowchart of a diagnostic method for a reactor neutron detector according to an embodiment of this application. Figure 1 As shown, the diagnostic method 100 for reactor neutron detectors includes:

[0043] Step S1: Calculate the burnup based on the reactor operating data and update the core model based on the calculation results.

[0044] The burnup history effect in neutronics calculations refers to the nonlinear influence of the fuel burnup process in the reactor core on neutronics parameters such as neutron flux, reactivity, and power distribution. This effect stems from the evolution of fuel composition with burnup depth (e.g., consumption of fissile nuclides, accumulation of fission products, and proliferation of actinides), resulting in significant differences in neutron behavior under the same instantaneous operating conditions due to different historical burnup paths.

[0045] To account for the burnup history effect in reactor neutronics calculations, burnup calculations must be performed based on recent reactor operating data before calculating core neutron flux, and the core model must be updated (an initial update is not required). The core model primarily contains the three-dimensional distribution of nucleon densities for various nuclides in the core. The updated core model should be consistent with the current state of the reactor. This calculation is automatically and periodically completed by the core model update program.

[0046] Neutron burnup calculation methods are common knowledge in this field. Based on the core neutron flux distribution (the program automatically and periodically calculates the core neutron flux, using the value from the previous calculation), the burnup equation is solved according to the reactor's power level and operating time to obtain an updated core model. This calculation step can be completed within 1 minute.

[0047] Step S2: Based on the updated core model, perform full-core pin-by-pin neutron transport calculations to obtain the three-dimensional cell-level neutron flux distribution of the entire core.

[0048] Calculating neutron flux in a reactor core requires solving the neutron transport equation, also known as the Boltzmann equation. The Boltzmann equation is a partial differential equation describing the transport behavior of particles (such as neutrons) in a medium, and it forms the theoretical basis for nuclear reactor physics analysis and radiation shielding design. This equation cannot be solved analytically and can only be solved numerically.

[0049] Traditional neutron science procedures (such as ANC and SCIENCE) are limited by computational resources and typically employ component homogenization or coarse-mesh block methods, achieving resolution only at the component level (approximately 20 cm scale). However, the detector's sensitive area is only a few millimeters, and the lack of grid-level (millimeter-centimeter scale) flux distribution leads to systematic biases in theoretical current predictions. In other words, existing neutron detector diagnostic methods lack sufficient accuracy, but currently, there is no publicly available solution capable of completing three-dimensional grid-level neutron flux simulation of the entire reactor core within an engineering-applicable timescale (<15 minutes). The lack of a real-time diagnostic framework that integrates high-fidelity physical models and detector response mechanisms results in a persistently high probability of unplanned reactor shutdowns due to neutron detector misdiagnosis at nuclear power plants worldwide.

[0050] To achieve high-precision current prediction for the detector, this method requires obtaining the neutron flux distribution at the grid cell level (millimeter-centimeter scale) at the detector location. This necessitates performing a full-core pin-by-pin transport calculation (where pin refers to the fuel grid cell, and pin-by-pin indicates that the geometric mesh of the transport calculation reaches the grid cell level). The computational cost of pin-by-pin transport calculation is substantial, requiring the application of acceleration and parallel techniques to improve efficiency. The parallel techniques employed in this application include, but are not limited to, a hybrid parallel technique based on message passing parallel programming (MPI) and shared memory parallel programming (OpenMP). The full-core pin-by-pin neutron transport calculation in this application employs the block response matrix method, and during the solution process, an acceleration method based on matrix block inversion is used to calculate the block response matrix.

[0051] Figure 2 This is a flowchart illustrating the pin-by-pin transport calculation according to an embodiment of this application. Figure 2 As shown, the full-core pin-by-pin neutron transport calculation is solved through a source iteration process, which includes the following steps:

[0052] Step a. Initialize neutron flux, deflection current, and effective multiplication factor k eff .

[0053] Neutron flux is the number of neutrons passing through a unit cross-sectional area per unit time. In actual reactors, the direction of neutron motion is not isotropic, especially near dielectric boundaries or strong absorbers, where the distribution of neutron flux exhibits strong directionality. To accurately describe this direction dependence, the neutron flux is expanded in the neutron transport equations, with the expansion terms including 0th-order flux, 1st-order flux, 2nd-order flux, and higher-order fluxes.

[0054] In nuclear reactor physics and neutron transport theory, deflection flow is a crucial vector quantity. Deflection flow is the net number of neutrons passing through a unit cross-sectional area per unit time. Flux is the total number of neutrons passing through the cross-section in all directions, regardless of orientation. Deflection flow, however, is a vector quantity calculated as the net number of neutrons in a given direction minus the number in the opposite direction. Similarly, deflection flow is expanded in the neutron transport equations, resulting in deflection flow expansion terms including 0th-order, 1st-order, 2nd-order, and higher-order deflection flows.

[0055] Effective proliferation coefficient k eff It is the ratio of the number of new neutrons produced by the current generation of neutron fission to the number of neutrons lost due to absorption and leakage in the previous generation.

[0056] In some embodiments, the 0th-order flux is initialized to 1.0, the 2nd-order flux to 0.0, and the expansion coefficients of higher-order fluxes are all 0.0. The effective multiplication coefficient k is then calculated. effReset the 0th-order flux to 1.0 / k eff ; Set k eff Set to 1.0; initialize the 0th-order bias flow to k. eff / 4, the second-order bias is 0.0.

[0057] Step b. Set the source iteration counter niter to 1;

[0058] Step c. Calculate or update the fission source term;

[0059] The fission source term refers to the neutron source produced by nuclear fission reactions, usually denoted by S_f. It is typically determined based on flux and the effective multiplication factor k. eff To calculate the fission source term. The fission source term S_f is usually given by the following formula:

[0060]

[0061] in:

[0062] χ represents the fission neutron energy spectrum (i.e., the distribution of neutrons produced in each fission in different energy groups);

[0063] Σ_f is the macroscopic fission cross section;

[0064] φ is the neutron flux.

[0065] Step d. Calculate the nodal outflow deflection based on the nodal incident deflection and fission source term;

[0066] In the nodal method, the reactor is typically divided into several nodules, and the global flux distribution is solved through the deflection current coupling between the nodules. For each nodal, the deflection current at the boundary is divided into nodal incident deflection current and nodal exit deflection current. Nodal incident deflection current refers to the current flowing from the outside of the nodal into the inside of the nodal, while nodal exit deflection current is the current flowing from the inside of the nodal to the outside.

[0067] Given the incident deflection current and fission source term within the nodal block, the steps to calculate the outgoing deflection current include: solving for the flux distribution within the nodal block based on the diffusion equations and boundary conditions (given the incident deflection current); calculating the net current at the boundary based on the flux distribution; and finally, calculating the outgoing deflection current based on the net current and the boundary flux.

[0068] Step e. Update the nodal incident deflection flow based on the outer boundary conditions and the continuity conditions between nodules;

[0069] In the nodal method, the reactor is divided into many nodules, and the neutron flux is solved within each nodal. Coupling between nodules is achieved through deflection flow and flux continuity conditions at the nodal interfaces. External boundary conditions typically refer to the reactor boundaries, such as vacuum boundary or reflection boundary conditions. The nodal continuity condition requires flux and deflection flow continuity between adjacent nodules at the interface.

[0070] The process of updating the incident bias flow in each node typically follows this procedure: First, we have the flux distribution within each node (usually represented by expansion coefficients, such as polynomial expansion) and the bias flow on the node surface (serving as the incident and outgoing flows). For each node, we calculate the outgoing bias flow on the node surface based on the flux distribution and diffusion coefficient within the node. For internal node interfaces, the outgoing bias flow of one node is the incident bias flow of the adjacent node. Therefore, the incident bias flow can be updated using the bias flow continuity condition between nodes. For outer boundaries, the bias flow on the boundary is updated based on the boundary conditions. For example: Vacuum boundary: No incident neutrons, so the incident bias flow is 0. Reflection boundary: The incident bias flow equals the outgoing bias flow (but in opposite directions). During the iteration process, the outgoing bias flow on the node surface is calculated using the flux within the current node step. Then, the incident bias flow is updated based on the relationship between adjacent nodes and the boundary conditions, and then substituted into the flux calculation within the node to solve for the flux in the next iteration step. Step f. Calculate the nodal response matrix from the nodal incident deflection flow and fission source term to update the nodal flux;

[0071] The nodal response matrix relates the neutron flux distribution within a nodal to the deflection flow at the nodal boundary. For each nodal, a local problem is solved (typically assuming the fission source terms are homogeneous or simply distributed within the nodal) to obtain the flux distribution within the nodal and the boundary deflection flow. The nodal response matrix can be calculated using the following formula:

[0072] .

[0073] Then, the flux distribution within the nodal is updated using the nodal response matrix and the nodal incident bias.

[0074] Step g. Update the effective multiplication coefficient k eff ;

[0075] After obtaining the updated nodal flux distribution, the ratio of the number of new neutrons produced by the current generation of neutron fission to the number of neutrons lost due to absorption and leakage in the previous generation can be calculated, thereby updating k. eff .

[0076] Step h. Calculate the flux deviation between the two iterations and k. eff deviation;

[0077] Step i. If the number of iterations exceeds the maximum, or the throughput deviation, k effIf the deviation meets the convergence criterion, exit the source iteration process and output the result; otherwise, increment the source iteration count niter by 1 and return to step c for the next iteration.

[0078] In step f of the pin-by-pin transport calculation, it is necessary to calculate the multi-group block response matrix. The main time consumption of this calculation occurs in the matrix inversion process. The following will focus on the implementation scheme for accelerating the calculation of the block response matrix.

[0079] In the solution process, this application employs an accelerated method based on matrix block inversion to calculate the block response matrix, including: constructing a matrix X representing the transport relationship of neutrons between different energy groups, wherein, based on the physical characteristics of neutron scattering, the matrix blocks corresponding to energy groups without upscattering effects are constructed into lower triangular matrices L, and the matrix blocks corresponding to thermal energy groups with upscattering effects are constructed into matrix R, so that matrix X has a block-based lower triangular structure; based on the principle of matrix block inversion, the inversion operation of matrix X is transformed into the inversion operation of the lower triangular matrix L and the inversion operation of matrix R.

[0080] For example, for a 17×17 fuel assembly problem with an energy group of 19 after grid homogenization, matrix X is a 133×133 matrix. If the LU decomposition direct inversion method is used, the total time of the block response matrix calculation module is 1.24 seconds, which accounts for about 23% of the total program running time (without source iteration acceleration).

[0081] Further analysis revealed that, due to the characteristics of the scattering matrix (no upscattering in the high-energy region, but significant upscattering in the thermal group), the X matrix has the following form:

[0082] (1)

[0083] in:

[0084] (2)

[0085] (3)

[0086] (4)

[0087] in, It is a lower triangular matrix, corresponding to an energy group without upward scattering effects; and It is essentially a full matrix, corresponding to the thermal group cross section with upscattering effect.

[0088] Based on the properties of matrix inversion:

[0089] (5)

[0090] X can-1 Large matrix transformation and Inverting two smaller matrices improves computational efficiency; and It is a lower triangular matrix with diagonal elements of a 7×7 identity matrix. The lower triangular matrix can be inverted multiple times using formula (5).

[0091] After adopting the above method, for the aforementioned problem of 17×17 fuel assembly with 19 energy groups after grid homogenization, the total time of the block response matrix calculation module is reduced from 1.24 seconds to 0.78 seconds, and the calculation time is reduced by about 40%.

[0092] Solving the neutron transport equations using a full-core pin-by-pin transport procedure yields the three-dimensional grid-level neutron flux distribution across the entire core. Based on the aforementioned acceleration and parallelization techniques, this calculation step can be completed within 15 minutes.

[0093] This method employs higher-precision whole-core pin-by-pin transport calculations in neutron flux calculations within the reactor core, while maintaining computational efficiency acceptable for engineering applications. It can complete calculations in a short time, thereby improving the accuracy of neutron flux calculations, which in turn improves the accuracy of detector signal prediction and ultimately enhances the accuracy of detector status diagnosis. This beneficial effect stems from the implementation of whole-core pin-by-pin transport calculations and their acceleration and parallelization techniques. Traditional methods use the coarse-mesh segmentation method for neutron flux calculations within the reactor core, resulting in lower accuracy.

[0094] Step S3: Calculate the predicted current value at the location of each neutron detector based on the neutron flux distribution at the gate level.

[0095] After completing the calculation of the neutron flux distribution in the reactor core, the predicted current of the neutron detector is calculated using the following formula:

[0096]

[0097] in, Indicates slow-release current. This indicates instantaneous current.

[0098] The electron escape probability is the probability that electrons generated during the decay process of the detector emitter will form an effective current. It is calculated theoretically using the Monte Carlo method.

[0099] The decay constant of the detector emitter was obtained experimentally.

[0100] The nucleon density of the detector emitter was obtained through an updated core model;

[0101] The transient sensitivity coefficient, which characterizes the relationship between the transient response current and the neutron flux, is obtained through theoretical calculation using the Monte Carlo method.

[0102] The thermal neutron flux at the detector location is obtained through the neutron flux distribution at the gate level.

[0103] This method can predict detector current by considering both delayed and instantaneous currents separately, thereby improving the prediction accuracy of the detector, rather than the traditional method that only considers instantaneous current. This beneficial effect comes from the delayed current term in the detector prediction current calculation formula; at the same time, this method has the parameters required for calculating delayed current, including the detector emitter nucleon density calculated through core model updates, the detector emitter decay constant, and the electron escape probability calculated by the Monte Carlo method.

[0104] Step S4: Obtain the actual measured current value of each neutron detector, and periodically save the measured current value, predicted current value, and reactor operating parameters as historical data.

[0105] Figure 3 This is a schematic diagram of a diagnostic system for a reactor neutron detector according to an embodiment of this application. Figure 3 As shown, several in-core neutron detectors 32 are deployed inside the reactor core 31. The signal cables 33 of these detectors are connected to the detector signal acquisition cabinet 34 outside the pressure vessel 30 via a through-hole in the upper part of the pressure vessel. During reactor startup and operation, the core neutron flux level increases, and the in-core neutron detectors 32 generate current signals. These signals are acquired and stored by the detector signal acquisition cabinet 34 and transmitted to the detector diagnostic cabinet 35. The function of the detector signal acquisition cabinet 34 is to amplify and filter the raw current signals from the in-core neutron detectors, converting them into reliable and usable data to provide a basis for subsequent calculations and analysis.

[0106] The high-performance computing server in detector diagnostic cabinet 35 will periodically and repeatedly perform detector signal acquisition, prediction, and historical data storage. Reactor operating parameters include, but are not limited to, time, reactor burnup, reactor power level, and control rod position. For example, if this is performed once per hour, the following data will be saved every hour: time, reactor burnup, reactor power level, control rod position, actual measured current value of all in-core neutron detectors, predicted current value, and the ratio of actual measured current value to predicted current value.

[0107] Step S5: Select datasets that meet the preset conditions from the saved historical data. Based on the selected datasets, calculate the characteristic parameters of the ratio of the measured current value to the predicted current value of each neutron detector, and diagnose the state of the corresponding neutron detector based on the characteristic parameters.

[0108] On the high-performance computing server in the detector diagnostic cabinet, start the detector status diagnostic program. The user interface is as follows: Figure 4 As shown. First, data filtering is performed. On the interface, select the most recent data from the saved historical detector data, for example, from July 1, 2025 to July 31, 2025. On the interface, select a power level range and delete data exceeding that range, for example, data with reactor power levels below 20% or above 120%. Based on the filtered data, click the "Diagnose" button on the interface. The program will then calculate the average and standard deviation of the ratio of measured current to predicted current for each detector, classify it according to the following criteria, and display it on the interface:

[0109] Good: The average value of the ratio of the detector's measured current to the predicted current is very close to 1.0, for example, in the range of (0.95, 1.05), and the standard deviation is less than 1.5%; the detector's response sensitivity correction factor is 1.0.

[0110] To be corrected: Not within the good range, the average value of the ratio of the detector's measured current to the predicted current is close to 1.0, for example, in the range of (0.9, 1.1), and the standard deviation is less than 1.5%; take the reciprocal of the average value of the ratio of the detector's measured current to the predicted current and use it as the response sensitivity correction factor for the detector.

[0111] Anomaly: The average value of the ratio of the detector's measured current to the predicted current deviates significantly from 1.0, for example, less than 0.9 or greater than 1.1, or the standard deviation is greater than 1.5%; the detector's response sensitivity correction factor is 0.0.

[0112] This method achieves higher accuracy in detector diagnosis than traditional methods. This is because the method boasts high precision in neutron flux calculation and detector signal prediction, and comprehensively considers statistical data from a large amount of historical detector data for detector status diagnosis. Furthermore, this method narrows the selection range for the ratio of measured current to predicted current of abnormal detectors from the traditional (0.6, 1.4) to (0.9, 1.1) without concern for misjudgment. Traditional detector diagnosis cannot simultaneously consider a large amount of historical detector data, relying solely on current measurement data for diagnosis. Moreover, due to inherent measurement uncertainties and low prediction current accuracy, the selection range for abnormal detectors should not be too narrow; it only proves effective when the deviation between the detector's measurement results and predicted values ​​is very significant.

[0113] In some embodiments, the diagnostic method for reactor neutron detectors further includes: setting a response sensitivity correction factor for each neutron detector based on the diagnosed state of the neutron detector; and correcting the subsequent measured current value of the neutron detector based on the response sensitivity correction factor.

[0114] On the signal acquisition server in the detector signal acquisition cabinet, start the detector status setting program. The operation interface is as follows: Figure 5 As shown in the image. The data displayed under "Before Modification" is only for displaying the current settings and cannot be edited; the data displayed under "After Modification" is editable.

[0115] On the interface, set the status of detectors diagnosed as abnormal to "Unavailable" and the status of detectors diagnosed as needing correction to "Correct," while also setting their response sensitivity correction factor. After confirming, click the "Save" button to apply the settings; the data corresponding to "After Modification" will automatically replace the data corresponding to "Before Modification." If you wish to discard the changes, click the "Restore" button, and the data corresponding to "After Modification" will be restored to its original state before editing.

[0116] Once the setting takes effect, measurement signals from unavailable detectors will not be used for subsequent core measurements. The original measurement signals from corrected detectors will be multiplied by a correction factor, and the corrected measurement signals from those detectors will be used for subsequent core measurements.

[0117]

[0118] in, , The current of the detector before and after correction was measured respectively. This is the response sensitivity correction factor.

[0119] This method corrects the response sensitivity of neutron detectors, thereby improving the accuracy of core measurements. Currently, no nuclear power plant can correct for manufacturing discrepancies in the response sensitivity of self-sufficient neutron detectors. This beneficial effect stems from the high-precision detector condition diagnosis and response sensitivity correction factor calculation in this method.

[0120] This application also provides a diagnostic device for a reactor neutron detector. The diagnostic device for a reactor neutron detector can be... Figure 3 The detector diagnostic cabinet 35 in the middle.

[0121] like Figure 6 As shown, the diagnostic device 600 for a reactor neutron detector includes a bus 601, a processor 602, a memory 604, and a communication interface 603. The processor 602, memory 604, and communication interface 603 communicate via the bus 601. The diagnostic device 600 for the reactor neutron detector can be a server or a terminal device. It should be understood that this application does not limit the number of processors and memories in the diagnostic device 600 for the reactor neutron detector.

[0122] Bus 601 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 6 The bus 601 is represented by a single line, but this does not mean that there is only one bus or one type of bus. The bus 601 may include a path for transmitting information between various components (e.g., memory 604, processor 602, communication interface 603) of the reactor neutron detector diagnostic device 600.

[0123] Processor 602 may include any one or more processors such as a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0124] Memory 604 may include volatile memory, such as random access memory (RAM). Processor 602 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0125] The memory 604 stores executable program code, which the processor 602 executes to implement the aforementioned diagnostic methods for the reactor neutron detector. That is, the memory 604 stores instructions for executing the diagnostic methods for the reactor neutron detector.

[0126] The communication interface 603 uses transceiver modules such as, but not limited to, network interface cards and transceivers to enable communication between the reactor neutron detector diagnostic device 600 and other devices or communication networks. This application also provides a computer program product containing instructions. The computer program product can be software or program products containing instructions that can run on a network device or be stored on any available medium. When the computer program product runs on at least one network device, it causes the at least one network device to perform a reactor neutron detector diagnostic method.

[0127] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium that a network device can store, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct the network device to perform a diagnostic method for a reactor neutron detector.

[0128] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, these terms have no special meaning and therefore should not be construed as limiting the scope of protection of this application. In addition, although the terminology used in this application is selected from commonly known and used terms, some terms mentioned in this application's specification may have been chosen by the applicant according to his or her judgment, and their detailed meanings are explained in the relevant sections of this description. Moreover, this application should be understood not only through the actual terms used, but also through the meaning implied by each term.

[0129] Flowcharts are used in this application to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0130] To make the objectives, technical solutions, and advantages of this application clearer, the application will be described in further detail below with reference to the accompanying drawings. The specific operating methods and functional descriptions in the method embodiments can also be applied to the device embodiments or system embodiments.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

[0132] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0133] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A diagnostic method for a reactor neutron detector, characterized in that, include: Burnup is calculated based on reactor operating data, and the core model is updated based on the calculation results; Based on the updated core model, a full-core pin-by-pin neutron transport calculation is performed to obtain the three-dimensional cell-level neutron flux distribution of the entire core. Based on the neutron flux distribution at the gate level, the predicted current value at the location of each neutron detector is calculated; The measured current value of each neutron detector is acquired, and the measured current value, predicted current value, and reactor operating parameters are periodically saved as historical data. Data sets that meet preset conditions are selected from the saved historical data. Based on the selected data sets, characteristic parameters of the ratio of the measured current value to the predicted current value of each neutron detector are statistically analyzed, and the state of the corresponding neutron detector is diagnosed according to the characteristic parameters. The predicted current value is calculated using the following formula: in, Indicates slow-release current. Indicates instantaneous current; The electron escape probability is the probability that electrons generated during the decay process of the neutron detector emitter will form an effective current. The decay constant of the neutron detector emitter; The nucleon density of the neutron detector emitter; This represents the transient sensitivity coefficient of the neutron detector. This represents the thermal neutron flux at the location of the neutron detector.

2. The method as described in claim 1, characterized in that, The pin-by-pin neutron transport calculation is solved using the block response matrix method, and an accelerated method based on matrix block inversion is used to calculate the block response matrix during the solution process.

3. The method as described in claim 2, characterized in that, The solution process employs an accelerated method based on matrix block inversion to calculate the block response matrix, including: A matrix X representing the transport relationship of neutrons between different energy groups is constructed. Based on the physical properties of neutron scattering, the matrix blocks corresponding to energy groups without upscattering effects are constructed into a lower triangular matrix L, and the matrix blocks corresponding to thermal energy groups with upscattering effects are constructed into a matrix R, so that the matrix X has a block-based lower triangular structure. Based on the principle of matrix block inversion, the inversion operation of the matrix X is transformed into the inversion operation of the lower triangular matrix L and the inversion operation of the matrix R. The block response matrix is ​​calculated using the result of the inverse operation after transformation.

4. The method as described in claim 3, characterized in that, The full-core pin-by-pin neutron transport calculation is solved through a source iteration process, which includes the following steps: a. Initialize neutron flux, deflection current, and effective multiplication coefficient k eff ; b. Set the source iteration counter; c. Calculate or update the fission source term; d. Calculate the nodal outflow deflection based on the nodal incident deflection and fission source term; e. Update the nodal incident deflection based on the outer boundary conditions and the continuity conditions between nodules; f. Calculate the nodal response matrix from the nodal incident deflection flow and fission source term to update the nodal flux; g. Update the effective multiplication coefficient k eff ; h. Calculate the flux deviation between the two iterations and k. eff deviation; i. Determine the flux deviation relative to k eff Check if the deviation meets the convergence criterion, or if the number of iterations has reached the upper limit; if it meets the criterion, output the result; otherwise, return to step c for the next iteration.

5. The method as described in claim 1, characterized in that, The characteristic parameter that calculates the ratio of the measured current value to the predicted current value for each neutron detector, and the diagnosis of the state of the corresponding neutron detector based on the characteristic parameter, includes: For each neutron detector, calculate the mean and standard deviation of the ratio of the centrally measured current value to the predicted current value in its filtered dataset; The state of the neutron detector is diagnosed based on the average value and standard deviation, and the state of the neutron detector includes good, needing correction, and abnormal.

6. The method as described in claim 5, characterized in that, The state of the neutron detector is diagnosed based on the average value and standard deviation, including: When the average value is within a first preset range and the standard deviation is less than a first preset threshold, the state of the neutron detector is determined to be good. When the "good" condition is not met, but the average value is in a second preset range that is wider than the first preset range and the standard deviation is less than the first preset threshold, the state of the neutron detector is determined to be in need of correction. When the average value exceeds the second preset range, or the standard deviation is greater than the first preset threshold, the state of the neutron detector is determined to be abnormal.

7. The method as described in claim 6, characterized in that, The first preset range is (0.95, 1.05), the second preset range is (0.9, 1.1), and the first preset threshold is 1.5%.

8. The method as described in claim 5, characterized in that, Also includes: A response sensitivity correction factor is set for each neutron detector based on the diagnosed state of the neutron detector; The subsequent measured current value of the neutron detector is corrected based on the response sensitivity correction factor.

9. The method as described in claim 8, characterized in that, Based on the diagnosed state of the neutron detector, a response sensitivity correction factor is set for each neutron detector, including: When the neutron detector is determined to be in good condition, the response sensitivity correction factor of the neutron detector is set to 1.0; When the state of the neutron detector is determined to be in need of correction, the response sensitivity correction factor of the neutron detector is set to the reciprocal of the average value; When the state of the neutron detector is determined to be abnormal, the response sensitivity correction factor of the neutron detector is set to 0.

0.

10. A diagnostic device for a reactor neutron detector, characterized in that, The device includes a processor and a memory; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to cause the device to perform the method as described in any one of claims 1-9.

11. A computer-readable storage medium, characterized in that, Includes computer program instructions, which, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-9.

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