A monitoring device and system for monitoring the reactor core of a nuclear power plant.

Abstract

This application provides a monitoring device and system for nuclear power plant core monitoring. The monitoring device includes a data preprocessing module, a model update module, a monitoring module, a shared data pool, and a monitoring interface module. On the one hand, it tracks actual reactor operating data to achieve online core monitoring, improving the accuracy of monitoring results; on the other hand, because the core's three-dimensional power distribution is reconstructed by combining actual measured current, the monitoring results obtained based on the reconstructed core three-dimensional power distribution (such as second core physical parameters) are more closely matched to the actual core operating conditions, resulting in higher accuracy.

Description

Technical Field

[0001] This application relates to the field of nuclear power plant monitoring technology, and in particular to a monitoring device and a system for monitoring nuclear power plant cores. Background Technology

[0002] Pressurized water reactor (PWR) nuclear power plants require regular monitoring of core physical parameters during operation to ensure that reactor operation remains within design limits and to prevent unacceptable accident consequences. Traditional PWR plants lack a device for continuous online monitoring of core physical parameters, relying instead on mobile neutron detectors for periodic monitoring at low frequencies, such as once a month, resulting in high uncertainty in the measured parameters. In such cases, the plant must increase the limits for reactor operating safety parameters to ensure core safety, thereby reducing operational flexibility and economic efficiency. Summary of the Invention

[0003] To alleviate, reduce or eliminate the above-mentioned technical problems, this application provides a monitoring device for monitoring the reactor core of a nuclear power plant.

[0004] In a first aspect, this application provides a monitoring device for nuclear power plant core monitoring, the monitoring device comprising a data preprocessing module, a model update module, a monitoring module, a shared data pool, and a monitoring interface module, wherein:

[0005] The data preprocessing module is used to perform a first preprocessing on reactor operation data from the data processing equipment and store the preprocessed reactor operation data in the shared data pool; the reactor operation data includes reactor operation measurement data and design data associated with the reactor core; wherein the first preprocessing includes any one or more of the following: filtering out outliers and averaging, and the reactor operation measurement data includes the measurement current of the reactor core neutron detector;

[0006] The model update module is used to perform three-dimensional neutronics calculations of the reactor core based on the first preprocessed reactor operating data, generate a reactor core neutronics model file, and store the reactor core neutronics model file in the shared data pool; wherein the reactor core neutronics model file contains the first reactor core physical parameters;

[0007] The monitoring module is used to acquire the target measurement current, perform core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measurement current to obtain the core measurement three-dimensional power distribution; and obtain the second core physical parameters based on the core measurement three-dimensional power distribution, and store the second core physical parameters in a shared data pool; wherein, the target measurement current is the measurement current of the latest core neutron detector.

[0008] The monitoring interface module is used to obtain and output the first core physical parameters and the second core physical parameters from the shared data pool.

[0009] In one embodiment, the core neutronics model file further includes a predicted three-dimensional power distribution of the core and a predicted current of the core neutron detector. The monitoring module is used to perform a core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measured current, including:

[0010] The predicted three-dimensional power distribution of the reactor core is corrected by the ratio between the target measured current and the predicted current of the neutron detector in the reactor core, thus obtaining the measured three-dimensional power distribution of the reactor core.

[0011] In one embodiment, the model update module periodically performs the three-dimensional neutronics calculation of the reactor core according to a first period T1 to obtain the first reactor core physical parameters; the monitoring module periodically performs the three-dimensional power distribution reconstruction calculation of the reactor core according to a second period T2 to obtain the second reactor core physical parameters; wherein, T1 is greater than T2.

[0012] In one embodiment, the reactor operation measurement data further includes any one or more of the following: reactor power level, coolant inlet temperature, coolant flow rate, and control rod position; the core-associated design data includes any one or more of the following: core neutron detector model file and core initial neutronics model file corresponding to each fuel change.

[0013] In one embodiment, the monitoring device further includes a predictive analysis module and an analysis interface module, wherein:

[0014] The analysis interface module is used to output an analysis interface including a function selection area and a calculation parameter configuration area. The function selection area is used to determine the target analysis function to be executed, and the calculation parameter configuration area is used to obtain the calculation parameters associated with the target analysis function. The calculation parameter configuration area includes a core condition configuration area for configuring core operating conditions and an input model file configuration area for determining a target core neutronics model file from multiple core neutronics model files. The calculation parameters include the target core neutronics model file and the core operating conditions.

[0015] The predictive analysis module is used to perform calculations based on the target analysis function and the calculation parameters from the analysis interface module, and output the calculation results to the analysis interface module for display.

[0016] In one embodiment, the target analysis function includes single-step burnup analysis, load tracking simulation, or critical condition prediction. The calculation parameter configuration area further includes one or more of the following: search option configuration area, calculation model configuration area, and control rod position configuration area. The calculation parameters also include one or more of the following data obtained through the calculation parameter configuration area: search options, calculation model, control rod position, power scheme characterizing time and core average relative power, and analysis type.

[0017] In one embodiment, the monitoring device further includes a predictive analysis module, which is used to obtain a first flux map snapshot file from the shared data pool, perform core three-dimensional neutronics calculations according to the first flux map snapshot file to obtain a first core predicted three-dimensional power distribution, and use the measured current of the core neutron detector in the first flux map snapshot file to correct the first core predicted three-dimensional power distribution to generate a first core measured three-dimensional power distribution.

[0018] In one embodiment, the predictive analysis module is further configured to, within a predetermined time period after fuel replacement, compare the measured three-dimensional power distribution of the first core with the predicted three-dimensional power distribution of the first core, and trigger an output prompt indicating incorrect core loading based on the comparison result.

[0019] In one embodiment, the monitoring device further includes a predictive analysis module. This module is configured to acquire a second flux map snapshot file from the shared data pool, continuously acquire different control rod hypothetical positions, modify the control rod position in the second flux map snapshot file based on the acquired hypothetical position each time a control rod is acquired, calculate the second core measured three-dimensional power distribution based on the modified second flux map snapshot file, compare the second core measured three-dimensional power distribution with the second core predicted three-dimensional power distribution in the modified second flux map snapshot file to obtain a power difference, and continue acquiring new control rod hypothetical positions until the acquired power difference meets the conditions. The module then outputs the control rod hypothetical position that meets the conditions, completing the control rod out-of-synchronization diagnosis.

[0020] In one embodiment, the monitoring device further includes a predictive analysis module, which is used to obtain a third flux map snapshot file containing the measured current of the external detector from the shared data pool, calculate the third core measurement three-dimensional power distribution according to the third flux map snapshot file, and solve and output the core peripheral weight axial offset based on the third core measurement three-dimensional power distribution and the peripheral weight factor corresponding to the external detector.

[0021] Secondly, this application provides a system for monitoring the reactor core of a nuclear power plant, including a core neutron detector, a data processing device, and the monitoring device described in the first aspect, wherein:

[0022] The core neutron detector is located inside the core and is used to measure the neutron flux density at different locations within the core.

[0023] A data processing device is used to perform a second preprocessing on the acquired initial reactor operating data to obtain reactor operating data, and output the reactor operating data to the monitoring device; wherein the second preprocessing includes any one or more of the following: deviation correction, averaging and logical operation processing, and the initial reactor operating data includes the measured current of the core neutron detector.

[0024] Thirdly, this application provides a method for monitoring the reactor core of a nuclear power plant, which can be executed by the monitoring equipment described in the first aspect, the monitoring equipment including a shared data pool, and the method comprising:

[0025] The reactor operation data from the data processing equipment undergoes a first preprocessing, and the preprocessed reactor operation data is stored in the shared data pool; the reactor operation data includes reactor operation measurement data and design data associated with the reactor core; the reactor operation measurement data includes the measurement current of the reactor core neutron detector;

[0026] Based on the first preprocessed reactor operating data, perform three-dimensional neutronics calculations on the reactor core to generate a reactor core neutronics model file, and store the reactor core neutronics model file in the shared data pool; wherein the reactor core neutronics model file contains the first reactor core physical parameters;

[0027] The target measurement current is obtained, and a core three-dimensional power distribution reconstruction calculation is performed based on the core neutronics model file and the target measurement current to obtain the core measurement three-dimensional power distribution; and a second core physical parameter is obtained based on the core measurement three-dimensional power distribution, and the second core physical parameter is stored in a shared data pool; wherein, the target measurement current is the measurement current of the latest core neutron detector;

[0028] Obtain and output the first core physical parameters and the second core physical parameters.

[0029] Compared with the prior art, this application has the following advantages:

[0030] On the one hand, tracking the actual operating data of the reactor enables online monitoring of the reactor core, improving the accuracy of the monitoring results; on the other hand, because the three-dimensional power distribution of the reactor core is reconstructed by combining the actual measured current, the monitoring results obtained based on the reconstructed three-dimensional power distribution of the reactor core (such as the second core physical parameters) are more in line with the actual operating conditions of the reactor core, and the accuracy is higher. Attached Figure Description

[0031] 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. In the drawings:

[0032] Figure 1 This is a schematic diagram of the structure of a nuclear power plant core monitoring system provided in an embodiment of this application.

[0033] Figure 2 This is a schematic diagram of a monitoring device for monitoring the reactor core of a nuclear power plant, provided in an embodiment of this application.

[0034] Figure 3 This is a schematic diagram of the visual interface provided in the embodiments of this application.

[0035] Figure 4 This is a schematic diagram of another visual interface provided in an embodiment of this application.

[0036] Figure 5 This is a schematic diagram of another visual interface provided in the embodiments of this application.

[0037] Figure 6 This is a schematic flowchart of a method for monitoring the reactor core of a nuclear power plant provided in an embodiment of this application. Detailed Implementation

[0038] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are merely some examples or embodiments of this application. For those skilled in the art, these drawings can be applied to other similar scenarios without creative effort. Unless obvious from the context or otherwise specified, the same reference numerals in the drawings represent the same structures or operations.

[0039] As indicated in this application, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0040] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0041] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0042] Furthermore, 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 the description herein. Moreover, this application is to be understood not only by the actual terms used, but also by the meaning implied by each term.

[0043] This application uses flowcharts to illustrate the operations performed by an apparatus or device according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. 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.

[0044] See Figure 1 This application proposes a system for monitoring the reactor core of a nuclear power plant. The system includes a core neutron detector 100, a data processing device 110, a monitoring device 120, a terminal device 130, a reactor core 140, and a reactor pressure vessel 150. This system allows for continuous online monitoring of the reactor core's operation.

[0045] As a feasible implementation method, a core neutron detector 100 has been installed during the nuclear power plant construction and fuel loading phases. The core neutron detector 100 can be an in-core neutron detector, located at different positions within the reactor core, used to measure the neutron flux density at different locations within the reactor core, serving as a crucial input for calculating core physical parameters. The core neutron detector 100 is connected to the data processing equipment 110 via a core neutron detector signal cable.

[0046] Alternatively, as another feasible implementation, the core neutron detector 100 can be a core outlet thermocouple and an external detector, replacing the function of the internal neutron detector, but the monitoring accuracy will be reduced accordingly.

[0047] Before the reactor is first started for each fuel cycle, the user will create a core monitoring model file, which includes a list of reactor operation measurement data, a list of monitoring parameters, a list of reactor operation safety limits, a core neutron detector model file, and a core initial neutronics model file.

[0048] The reactor operation measurement data list is equivalent to the input signal list for online core monitoring. It mainly includes measurement data such as the core neutron detector measurement current, reactor power level, coolant inlet temperature, coolant flow rate, control rod position, volume of added boric acid solvent, and volume of added demineralized water. The subsequent data processing equipment 110 can collect the corresponding data according to the reactor operation measurement data list.

[0049] The monitoring parameter list is equivalent to the output signal list of the reactor core online monitoring, mainly including core physical parameters such as burnup, boron concentration, core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, deviation from bubble-nucleus boiling ratio, xenon value, samarium value, boron differential value, and shutdown margin. Monitoring equipment 120 can calculate and output the corresponding data based on this list.

[0050] The reactor operation safety limit list includes operating limits for parameters such as peak line power density, nuclear enthalpy rise heat pipe factor, deviation from bubble-nuclear boiling ratio, and shutdown margin. When monitoring equipment 120 calculates any core physical parameters, it compares them with the corresponding operating limits in the reactor operation safety limit list. If the corresponding limit is exceeded, an alarm is triggered. For example, if the peak line power density exceeds the operating limit, it indicates that the core is in an unsafe state, and an alarm will be triggered.

[0051] The core neutron detector model file contains information such as the number, distribution location, material composition, and length of the core neutron detectors 100. It is used by the subsequent monitoring equipment 120 to perform three-dimensional neutronics calculations of the core to obtain the predicted current of the core neutron detectors 100.

[0052] The initial neutronics model file for the reactor core contains information such as the quantity, arrangement, material composition, and neutronics cross-section of the reactor nuclear fuel after this fuel replacement. This information is used by monitoring equipment 120 to perform three-dimensional neutronics calculations of the core, obtaining the predicted three-dimensional power distribution. The initial neutronics model file is updated with each fuel replacement.

[0053] Data processing equipment 110 is used to acquire initial reactor operating data according to a list of monitoring parameters. This initial reactor operating data includes the measurement current of the core neutron detector 100 and other reactor operating measurement data (such as reactor power level, coolant inlet temperature, coolant flow rate, control rod position, etc.) generated in real time by other reactor system equipment. Further, data processing equipment 110 performs a second preprocessing on the initial reactor operating data to obtain reactor operating data that is acceptable to monitoring equipment 120, and then outputs the reactor operating data to monitoring equipment 120.

[0054] The second preprocessing described above includes any one or more of the following: deviation correction, averaging, processing into signals that do not exceed upper and lower limits, and logical operation processing. For example, deviation correction can be performed using the following formula:

[0055]

[0056] in, The original measurement signal is represented by G, where G is the signal gain and O is the signal bias. The measurement signal is after deviation correction processing, where G and O are both constants.

[0057] For example, the average can be calculated using the following formula:

[0058]

[0059] in, For time point t i The original measurement signal, For the recent period of time The measurement signal after averaging.

[0060] For example, a measurement signal that does not exceed the upper and lower limits of the signal can be processed by the following formula:

[0061]

[0062] in, For the original measurement signal, L low L is the lower limit of the signal. high The upper limit of the signal, For a measurement signal that, after processing, does not exceed the upper and lower limits of the signal, L low and L high All of these are pre-set known values.

[0063] For example, logical operations can be performed using the following formula:

[0064]

[0065] Among them, V A V B V C These are three raw measurement signals. This is the measurement signal after logical operations.

[0066] The monitoring device 120 continuously tracks the reactor burnup history and updates the core neutronics model file based on reactor operation data from the data processing equipment (input signals such as the measured current of the core neutron detector, reactor power level, coolant inlet temperature, coolant flow rate, and control rod position). It also monitors core physical parameters in real time, such as critical boron concentration, core axial power offset, peak linear power density, nuclear enthalpy rise heat pipe factor, and deviation from the bubble-nucleus boiling ratio, thus achieving online monitoring of the core.

[0067] In some implementations, the monitoring device 120 continuously updates the core neutronics model file and, through predictive analysis calculations, can obtain the core operating status of the reactor over a future period, thereby achieving core reactivity predictive analysis. In other embodiments, the monitoring device 120, based on reactor operating data from a data processing device, further calculates and analyzes the differences between measured and calculated values, thereby achieving functions such as misloading detection and control rod out-of-synchronization diagnosis.

[0068] For example, the monitoring device 120 includes functional modules such as Figure 2 As shown, it includes a data preprocessing module 1200, a model update module 1201, a monitoring module 1202, a shared data pool 1203 and a monitoring interface module 1204, a predictive analysis module 1205, a reactivity calculation module 1206, a management interface module 1207 and an analysis interface module 1208.

[0069] The monitoring interface module 1204, management interface module 1207, and analysis interface module 1208 of the monitoring device 120 provide a user-oriented graphical human-computer interaction interface. The monitoring interface module 1204 displays real-time monitored core physical parameters such as critical boron concentration, core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, and deviation from the bubble-nucleus boiling ratio. The management interface module 1207 manages and controls the startup and shutdown of underlying modules such as the data preprocessing module 1200, model update module 1201, monitoring module 1202, and reactivity calculation module 1206. The analysis interface module 1208 performs predictive analysis calculations for various purposes and types and displays the calculation results. Alternatively, in some embodiments, the monitoring interface module 1204, management interface module 1207, and analysis interface module 1208 may be omitted, and interaction may be performed through methods other than graphical human-computer interaction; this is not limited.

[0070] The data preprocessing module 1200 of the monitoring device 120 periodically receives input signals from the data processing device, performs the first preprocessing, generates data that meets the subsequent calculation requirements, and stores it in a shared data pool for use by the model update module 1201, the monitoring module 1202, and the reactivity calculation module 1206.

[0071] The first preprocessing step includes one or more of the following: filtering outliers and averaging. For example, the data preprocessing module receives measurement currents from several core neutron detectors. In some cases, due to signal fluctuations, detector malfunctions, or other reasons, the currents of some detectors may significantly deviate from the normal range (i.e., the average current of all detectors). When processing the measurement currents of the core detectors, the data preprocessing module will filter them according to the degree of deviation from the normal value, eliminating significant outliers and retaining only reasonable and valid measurement currents, thus completing the first preprocessing step of filtering outliers. As another example, the data preprocessing module receives four core inlet temperatures, corresponding to the four inlet temperature sensors of the reactor core. During post-processing, the data preprocessing module will calculate the average of the four temperatures to obtain an average inlet temperature, completing the first preprocessing step of averaging.

[0072] In some embodiments, the data processed by the data preprocessing module 1200 includes reactor operation measurement data such as reactor power level, system pressure, inlet temperature, control rod position, core neutron detector measurement current, thermocouple measurement current, and external detector measurement current. Taking the first preprocessing of the reactor power level as an example, the reactor power level includes thermal equilibrium power, ΔT power, power range detector power, and intermediate range detector power, where ΔT power typically refers to the power change caused by the change in core coolant temperature. During the reactor power level processing, the data preprocessing module 1200 receives four power level signals based on different measurement methods: thermal equilibrium power, ΔT power, power range detector power, and intermediate range detector power. It then selects the power level signal with higher confidence based on the quality of the four signals and the current power range. As a feasible approach, a signal with higher accuracy (corresponding to higher confidence) can be used to correct a signal with lower accuracy, ensuring that the data output by the data preprocessing module 1200 after the first preprocessing is as accurate and reliable as possible.

[0073] It should be noted that the accuracy of thermal equilibrium power is higher at higher power levels, while the accuracy of ΔT power is higher at lower power levels. When processing the power signal, the data preprocessing module 1200 will automatically select a signal source with higher accuracy (corresponding to higher confidence) based on the current power level range, and finally output a single power signal. If neither the current thermal equilibrium power nor ΔT power is available, it will use the power range detector power (or intermediate range detector power) as a fallback, and will add a correction amount to it. This correction amount is equal to the average deviation between the thermal equilibrium power and the power range detector power (or intermediate range detector power) within a preset time period (this preset time period can be the same as or different from the calculation period T1 of the model update module 1201, such as 15 minutes). As the data preprocessing module 1200 periodically processes the reactor operation data of the nuclear power plant, the reactor operation data after the first preprocessing is stored in the shared data pool 1203 and updated periodically for use by the model update module 1201, monitoring module 1202, and reactivity calculation module 1206. Although the data reading cycles of the model update module 1201, monitoring module 1202, and reactivity calculation module 1206 may not be the same, they can all read the latest set of data. The data accessed by the model update module 1201, monitoring module 1202, and reactivity calculation module 1206 are all internal interface data. This type of data is stored in the shared data pool 1203 in the form of interface files with fixed names and formats. By reading the required interface file, the module can find the data it needs. Furthermore, the interface files are updated periodically, overwriting expired files. Therefore, as long as the model update module 1201, monitoring module 1202, and reactivity calculation module 1206 read their corresponding interface file, they can access the latest set of data.

[0074] The model update module 1201 of the monitoring server periodically performs three-dimensional neutronics calculations on the reactor core based on reactor operation data (including reactor power level, system pressure, inlet temperature, control rod position, in-core fixed detector measurement current, thermocouple measurement current, and external detector measurement current) from the data processing equipment. This generates a core neutronics model file, which contains core physical parameters such as the current three-dimensional power distribution, burnup, boron concentration, core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, and detector predicted current. The core neutronics model file is stored in the shared data pool 1203 for use by the monitoring module 1202, the reactivity calculation module 1206, and the predictive analysis module 1205.

[0075] In some embodiments, the model update module 1201 can track the boron concentration in the main coolant loop of the power plant in real time, providing a more timely reference value for boron concentration for power plant operation. During reactor criticality, the model update module 1201 performs a three-dimensional neutronics criticality search calculation of the core to obtain the critical boron concentration; during reactor shutdown, the model update module 1201 calculates the current boron concentration based on the cumulative flow of borylation and dilution during upflow and downflow. Furthermore, as a feasible approach, the model update module 1201 can also perform burnup calculations for B-10 nuclides in boric acid, consider B-10 abundance correction based on B-10 burnup, and then provide boron concentrations based on nominal B-10 abundance and boron concentrations considering B-10 burnup, respectively.

[0076] In a pressurized water reactor, boric acid Dissolved in the primary coolant, Boron-10 ( 10 B) Isotopes can absorb neutrons and reduce neutron flux, thus playing a triple role in reactivity control, power distribution regulation, and safety protection. Monitoring boron concentration and B-10 abundance is of great significance for reactor operation.

[0077] In some embodiments, after receiving reactor operating data from the data processing device, if the reactor operating data does not include the three-dimensional power distribution of the core, the model update module 1201 determines that the reactor is shut down. It then obtains the volume of boric acid solvent added (corresponding to boration) or the volume of demineralized water added (corresponding to dilution) from the reactor operating data and calculates the current boron concentration according to the known boration or dilution formula. If the reactor operating data includes the three-dimensional power distribution of the core, the reactor is confirmed not to be shut down. The model update module 1201 performs three-dimensional neutronics calculations of the core to obtain the critical boron concentration. Specifically, the critical boron concentration can be obtained by solving the known neutron diffusion equation. The neutron diffusion equation describes the spatial distribution and energy balance of neutron flux in the reactor. When the reactor is in a critical state, the neutron production rate and loss rate are equal. At this time, the steady-state equilibrium condition of neutron flux must be satisfied. The model update module 1201 can iteratively adjust the reactivity control parameters (such as boron concentration) and solve the neutron diffusion equation. The boron concentration that makes the left and right sides of the neutron diffusion equation equal is determined as the critical boron concentration.

[0078] Conventional methods for measuring boron concentration in pressurized water reactor nuclear power plants involve chemical titration, which typically takes about 30 minutes from sampling to obtaining results and requires significant manpower and resources. In this embodiment, the boron concentration of the power plant can be tracked in real time. Compared to chemical measurement methods, this provides nuclear power plant operators with a more timely real-time reference value for the boron concentration in the reactor's main coolant loop. Furthermore, the tracked boron concentration can be corrected for B-10 abundance based on the burnup of B-10 in boric acid, providing both a boron concentration based on nominal B-10 abundance and a boron concentration considering B-10 burnup, offering valuable reference information for operational decisions.

[0079] The monitoring module 1202 is used to periodically perform core three-dimensional power distribution reconstruction calculations to obtain the core measured three-dimensional power distribution. It then further calculates the core axial power offset, peak line power density, core enthalpy rise heat pipe factor, and deviation from bubble-nucleus boiling ratio, generating monitoring result data, which is stored in a shared data pool for output by the monitoring interface module 1204.

[0080] The calculation results of monitoring module 1202 are similar to those of model update module 1201. However, monitoring module 1202 does not perform core three-dimensional neutronics calculations. Instead, based on the latest core neutronics model file already calculated by model update module 1201 and the measured current of the core neutron detector (i.e., the target measured current), it performs core three-dimensional power distribution reconstruction calculations to obtain second core physical parameters such as core axial power offset, peak line power density, and nuclear enthalpy rise heat pipe factor. The calculation cycle of model update module is typically 15 minutes, while the calculation cycle of real-time monitoring module is only 1 minute. In this way, on the one hand, monitoring module 1202 can obtain the current core three-dimensional power distribution more quickly; on the other hand, by reconstructing the core three-dimensional power distribution using the measured current during actual core operation, the reconstructed core three-dimensional power distribution better matches the actual core operation, resulting in higher accuracy.

[0081] The reactivity calculation module 1206 is used to periodically calculate the core reactivity coefficients, such as xenon value, samarium value, boron differential value, and shutdown margin. The calculation results are stored in a shared data pool for access by the monitoring interface. The xenon value, samarium value, and boron differential value are calculated using perturbation theory. Neutron perturbation theory refers to the theory that, under the condition that small or local changes in reactor parameters do not cause significant distortion of the neutron flux, directly obtains the reactivity increment after the perturbation from the perturbation of the neutron flux and related parameters before the perturbation. This method is more accurate than calculating the reactivity before and after the perturbation separately and then calculating the difference.

[0082] Shutdown margin is a core parameter in nuclear reactor safety analysis, referring to the negative reactivity the reactor can achieve when all control rods are inserted into the core (assuming the most valuable control rod is stuck outside the core). Assuming all control rods are inserted into the core (and the most valuable control rod is stuck outside), and maintaining the current core boron concentration constant, performing three-dimensional neutronics calculations of the core yields the negative reactivity achieved by the reactor, i.e., the shutdown margin.

[0083] Traditional nuclear power plant reactivity coefficient calculations primarily rely on table lookup methods. Based on current operating parameters such as burnup, power level, and rod position, the closest value to the corresponding condition is found in a pre-calculated table of reactivity coefficients for typical operating conditions of the current fuel cycle. Clearly, the reactivity coefficients obtained by table lookup cannot accurately reflect the reactor's actual operating history and current conditions over a recent period, resulting in high uncertainty. The system proposed in this application can calculate the reactivity coefficient for the current operating condition based on real-time tracking of neutronics model files, providing calculation results that more closely approximate actual operating conditions and thus better guiding operation.

[0084] The predictive analysis module 1205 of the monitoring device 120 can predict the reactor's operating status over a future period based on a user-selected core neutronics model file, thereby assessing its safety and feasibility. The predictive analysis module 1205 can perform various types of predictive analysis calculations to support diverse operational needs, including reactivity coefficient calculation, reactivity management plan development, misloading detection, control rod out-of-synchronization diagnosis, and external detector calibration, among others.

[0085] The shared data pool 1203 is used to store the data required for the operation of all functional modules of the monitoring device 120, and can support multiple modules to read and write at the same time without file conflicts.

[0086] Terminal device 130 is used to remotely connect to monitoring device 120. After accessing monitoring device 120 through terminal device 130, users can view core physical parameters such as boron concentration, core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, and deviation from bubble-nucleus boiling ratio through the monitoring interface provided by monitoring interface module 1204. They can control the start and stop of online core monitoring through management interface module 1207, and use various types of predictive analysis calculation functions (such as single-step burnup analysis, load tracking simulation, critical condition prediction, misloading detection, control rod out-of-step diagnosis, external detector calibration, etc.) through analysis interface module 1208.

[0087] The system proposed in this application can, on the one hand, continuously monitor core physical parameters such as boron concentration, core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, and deviation from the bubble-nuclear boiling ratio online, reducing the uncertainty in core physical parameter measurements. This allows nuclear power plants to release operational margins while ensuring core operation safety, improving operational flexibility and economy. On the other hand, its ability to accurately track reactor operating history provides a core neutronics model file at the end of the current fuel cycle's life that is more consistent with actual operating history for the refueling design of the next fuel cycle, thereby improving the accuracy of the design analysis and calculation for the next fuel cycle.

[0088] It should be noted that, Figure 1 The number of the reactor core neutron detector 100, data processing equipment 110, monitoring equipment 120, terminal equipment 130, reactor core 140, and reactor pressure vessel 150 can all be multiple. The data processing equipment 110 and monitoring equipment 120 can both be servers or server clusters, installed in racks in the nuclear power plant's computer room, or they can be cloud servers or other electronic devices capable of performing the same functions. The aforementioned terminal equipment 130 can be personal computers, tablets, smart wearable devices, smartphones, and other electronic devices. When the hardware and software of the terminal equipment 130 itself are sufficient to support it in performing all the functions of the monitoring equipment 120, the monitoring equipment 120 in the above system can be deleted. Alternatively, the data processing equipment 110 and monitoring equipment 120 can also be integrated into a single device; this application does not limit this, as long as the corresponding functions of each device can be achieved.

[0089] This application proposes a monitoring device for nuclear power plant core monitoring (such as monitoring device 120 in the above system). The monitoring device includes a data preprocessing module, a model update module, a monitoring module, a shared data pool, and a monitoring interface module, wherein:

[0090] The data preprocessing module is used to perform a first preprocessing on the reactor operation data from the data processing equipment, and store the preprocessed reactor operation data in the shared data pool. The reactor operation data includes reactor operation measurement data and design data associated with the reactor core. The reactor operation measurement data includes the measured current of the core neutron detector.

[0091] As a feasible implementation, reactor operation measurement data may also include any one or more of the following: reactor power level, coolant inlet temperature, coolant flow rate, and control rod position; design data associated with the core may include any one or more of the following: core neutron detector model file and core initial neutronics model file corresponding to each fuel replacement.

[0092] In some embodiments, reactor operation measurement data includes reactor power level, which includes multiple power level signals and the signal quality of each power level signal. The data preprocessing module is used to perform a first preprocessing on the reactor operation data from the data processing device, including: determining the output reactor power level based on the signal quality of each power level signal, the multiple power level signals, and a preset confidence rule.

[0093] In some embodiments, the multiple power level signals include thermal equilibrium power, ΔT power, power range detector power, and intermediate range detector power. A pre-set confidence rule states that the confidence level is ordered from highest to lowest as ΔT power → thermal equilibrium power → power range detector power or intermediate range detector power, and the power level signal with the highest confidence level is preferentially selected as the final output reactor power level. The data preprocessing module is used to determine the output reactor power level based on the signal quality of each power level signal, the multiple power level signals, and the pre-set confidence rule, including:

[0094] When the signal quality of ΔT power meets the quality condition, and ΔT power is less than or equal to the first power threshold (e.g., 25%), ΔT power is determined as the output reactor power level from multiple power level signals according to a preset confidence rule; or,

[0095] If the signal quality of the ΔT power does not meet the quality condition or the ΔT power is greater than the first power threshold, then if the signal quality of the thermal balance power meets the quality condition, the thermal balance power is determined as the output reactor power level; or...

[0096] When the signal quality of ΔT power and the signal quality of thermal balance power do not meet the quality conditions, the power of the power range detector or the power of the intermediate range detector is corrected based on the correction amount, and the corrected power range detector power or the corrected intermediate range detector power is determined as the output reactor power level; wherein, the correction amount is the average deviation between the historical thermal balance power and the historical power range detector power that meet the quality conditions within a preset time period, or the average deviation between the historical thermal balance power and the historical intermediate range detector power that meet the quality conditions within a preset time period, or the historical correction amount obtained in the previous calculation.

[0097] For example, assuming a preset duration of 10 minutes, if the quality of the historical thermal balance power changed from good to bad (i.e., from meeting the quality conditions to not meeting them) 1 minute ago, the correction is made based on the average deviation between the historical thermal balance power and the historical power range detector power / historical intermediate range detector power within the 9 minutes from 10 minutes ago to 1 minute ago. If the quality of the historical thermal balance power was bad in several discontinuous time periods within the first 10 minutes (i.e., the corresponding signal quality did not meet the quality conditions), these time periods are all removed and the average deviation is calculated. If the quality of the historical thermal balance power was bad for the first 10 minutes, the correction amount cannot be calculated normally at this time, and the historical correction amount obtained from the previous normal calculation is used directly.

[0098] The quality conditions are preset based on experimental data and can be adjusted later according to actual needs. The process of correcting the power of the power range detector or the intermediate range detector based on the correction amount can be as follows: add the power of the power range detector or the intermediate range detector to the correction amount.

[0099] In some embodiments, the data preprocessing module periodically and continuously performs first preprocessing on multiple power level signals, ultimately outputting a single power signal as the reactor power level. When the reactor starts up, if the signal quality of both the current ΔT power and the current thermal equilibrium power meets the requirements, the default initial state of the data preprocessing module, according to preset confidence rules, is to determine the current ΔT power as the output reactor power level. As time progresses, if the current ΔT power exceeds a first power threshold (e.g., 25%), the current thermal equilibrium power will be used as the current output reactor power level; subsequently, if the obtained current thermal equilibrium power is less than a second power threshold (e.g., 20%), the current ΔT power will be used as the current output reactor power level. Here, the first and second power thresholds are set to avoid frequent switching of the power level signal source.

[0100] The model update module is used to perform three-dimensional neutronics calculations on the reactor core based on the first preprocessed reactor operating data, generate a core neutronics model file, and store the core neutronics model file in a shared data pool. The core neutronics model file contains the first core physical parameters.

[0101] The monitoring module acquires the target measurement current and performs a three-dimensional power distribution reconstruction calculation of the core based on the core neutronics model file and the target measurement current to obtain the core measurement three-dimensional power distribution. Further, it statistically analyzes the core measurement three-dimensional power distribution to obtain second core physical parameters, which are then stored in a shared data pool. The target measurement current is the measurement current of the latest core neutron detector.

[0102] The monitoring interface module is used to obtain and output the physical parameters of the first and second cores from the shared data pool.

[0103] In some embodiments, the core neutronics model file also includes a core predicted three-dimensional power distribution and a predicted current of the core neutron detector. The monitoring module is used to perform a core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measured current, including: correcting the core predicted three-dimensional power distribution by the ratio between the target measured current and the predicted current of the core neutron detector to obtain the core measured three-dimensional power distribution.

[0104] For example, the predicted three-dimensional power distribution of the reactor core can be corrected using the following formula to obtain the measured three-dimensional power distribution of the reactor core. In the formula, P... M The three-dimensional power distribution measurement of the reactor core is the result of the core three-dimensional power distribution reconstruction calculation output; P P To predict the three-dimensional power distribution of the reactor core, the core neutronics model file was read; I M The measured current (i.e., the target measured current) of the neutron detector in the reactor core is obtained from the shared data pool, or directly input after the first preprocessing by the data preprocessing module; I P The predicted current for the core neutron detector is obtained by reading the core neutronics model file; Indicate I M / I P The value is a fitted interpolation at various positions throughout the entire heap.

[0105]

[0106] The predicted three-dimensional power distribution of the reactor core is corrected by measuring the current during actual core operation, making the obtained measured three-dimensional power distribution of the core more closely match the actual core operation and thus more accurate. Both the measured and predicted three-dimensional power distributions can characterize the power distribution of each fuel assembly in the core.

[0107] In some embodiments, the model update module periodically performs core three-dimensional neutronics calculations according to a first period T1 to obtain first core physical parameters, and the monitoring module periodically performs core three-dimensional power distribution reconstruction calculations according to a second period T2 to obtain second core physical parameters. Here, T1 is greater than T2, for example, T1 is 15 minutes and T2 is 1 minute. Core three-dimensional neutronics calculations are time-consuming; if the first core physical parameters obtained from the model update module are directly displayed to the user, the data update speed is slow. However, since the monitoring module 1202 does not perform core three-dimensional neutronics calculations, it can directly utilize the latest core neutronics model file already calculated by the model update module 1201 and the measured current of the core neutron detector (i.e., the target measured current) to quickly calculate the second core physical parameters for user viewing, resulting in better real-time performance.

[0108] In some embodiments, the first core physical parameters include burnup, boron concentration, etc., and the second core physical parameters include core axial power offset, peak line power density, nuclear enthalpy rise heat pipe factor, deviation from bubble-nucleation ratio, etc.

[0109] For example, the calculation process of core axial power offset can be as follows: normalize the volume weight of the three-dimensional power distribution measured in the core, then calculate the average power of the upper half and the lower half of the core by applying volume weights respectively, and finally calculate the power by dividing the difference between the power of the upper half and the power of the lower half of the core by the sum of the power of the upper half and the power of the lower half of the core.

[0110] For example, the calculation process of peak line power density can be as follows: perform statistical analysis on the three-dimensional power distribution of the reactor core, and statistically obtain the maximum power value per unit length among all fuel rods in the reactor core.

[0111] For example, the calculation process of the deviation from the nucleus boiling ratio can be as follows: using the sub-channel method, the flow and heat transfer process of the core coolant is simulated in a refined manner to locate the point where the local thermal parameters are most severe, and the ratio of the critical heat flux density to the heat flux density at that local location is evaluated. This ratio is the deviation from the nucleus boiling ratio.

[0112] In some embodiments, the monitoring device further includes a predictive analysis module and an analysis interface module, wherein:

[0113] The analysis interface module outputs an analysis interface including a function selection area and a calculation parameter configuration area. The function selection area determines the target analysis function to be executed, and the calculation parameter configuration area retrieves the calculation parameters associated with the target analysis function. The calculation parameter configuration area includes a core condition configuration area for configuring core operating conditions and an input model file configuration area for determining the target core neutronics model file from multiple core neutronics model files (generated periodically by the model update module performing core 3D neutronics calculations). The calculation parameters include the target core neutronics model file and the core operating conditions.

[0114] The predictive analysis module is used to perform calculations based on the target analysis functions and calculation parameters from the analysis interface module, and output the calculation results to the analysis interface module for display.

[0115] In some embodiments, the target analysis function mentioned above includes single-step burnup analysis, load tracking simulation, or critical condition prediction, etc. The calculation parameter configuration area also includes any one or more of the following: search option configuration area, calculation model configuration area, and control rod position configuration area. The calculation parameters also include any one or more of the following data obtained through the calculation parameter configuration area: search options, calculation model, control rod position, power scheme characterizing time and core average relative power, and analysis type.

[0116] For example, assuming the user selects single-step fuel consumption analysis as the target analysis function, the analysis interface is as follows: Figure 3 As shown, it includes a function selection area 300 and a calculation parameter configuration area 301. The calculation parameter configuration area 301 includes an input model file configuration area ( Figure 3 The area corresponding to the "Input Model File" and the core operating condition configuration area ( Figure 3 The corresponding area for "core operating conditions" in the middle), and the search option configuration area ( Figure 3 The corresponding area for "Search Options" and the calculation model configuration area ( Figure 3 The area corresponding to the "computation model" and the control rod position configuration area ( Figure 3 (The area corresponding to "Control Rod Positions"). Users can complete the target core neutronics model file, search options, calculation model, core operating conditions, and control rod positions settings through the analysis interface. Clicking the "Calculate" button starts the calculation. The predictive analysis module performs three-dimensional neutronics calculations of the core based on the user-provided target core neutronics model file, search options, calculation model, core operating conditions, and control rod positions, completing a single-step burnup analysis. After the calculation is completed, the calculation results are output through the analysis interface module.

[0117] For example, assuming the user selects load tracking simulation as the target analysis function, the analysis interface is as follows: Figure 4As shown, the calculation parameter configuration area 301 includes an input model file configuration area ( Figure 4 The area corresponding to the "Input Model File" and the core operating condition configuration area ( Figure 4 The corresponding area for "Core Operating Conditions" and the control option configuration area ( Figure 4 The corresponding area for "Control Options" and the calculation model configuration area ( Figure 4 The area corresponding to the "Computational Model" and the configuration area for newly created solution files ( Figure 4 (The corresponding area is "New Scheme"). Users input a power scheme representing the time and average core power in the new scheme file configuration area, complete the settings for the target core neutronics model file, calculation model, core operating conditions, and control options, and click the "Calculate" button to begin calculation. The predictive analysis module performs a series of burnup calculations based on the user-provided power scheme to calculate changes in parameters such as core inlet temperature, control rod position, critical boron concentration, and corresponding core power peak factor during core operation. After calculation, users can view the results and compile a reactivity management report to support reactor operation, providing guidance and reference to reactor operators. The load tracking simulation function can simulate operating conditions such as ramp power variation, weekend load tracking, and daily load tracking, supporting operators in selecting ideal operating strategies.

[0118] For example, assuming the user selects the critical condition prediction function as the target analysis function, the analysis interface is as follows: Figure 5 As shown, the calculation parameter configuration area 301 includes an input model file configuration area ( Figure 5 The area corresponding to the "Input Model File" and the core operating condition configuration area ( Figure 5 The corresponding area for "Core Operating Conditions" and the power option configuration area ( Figure 5 The corresponding area for "Power Options" and the analysis type configuration area ( Figure 5 The corresponding area for "analysis type" and the search range configuration area ( Figure 5 The area corresponding to the "search interval" in the middle) and the control rod position configuration area ( Figure 5 The corresponding area is the "Control Rod Position". Users can complete the settings for the target core neutronics model file, analysis type, search interval, core operating conditions, control rod position, and power options through the analysis interface. Clicking the "Calculate" button starts the calculation. The predictive analysis module, based on the user-provided target core neutronics model file, analysis type, search interval, core operating conditions, control rod position, and power options, uses the target core neutronics model file as the starting point and continuously calculates the target time range at preset time intervals (e.g., one hour). Figure 5The selected time range shows the changing trends of critical rod sites and critical boron concentration over time. The calculation method for a single critical rod site or critical boron concentration is the same as the core three-dimensional neutronics calculation performed by the single-step burnup analysis function described above. The critical condition prediction function is equivalent to automatically performing multiple single-step burnup analysis calculations for critical rod site searches or critical boron concentration searches.

[0119] The predictive analysis module can also collect flux map snapshot files and perform analysis and calculations on them, enabling functions such as core misloading detection, control rod out-of-synchronization diagnosis, and external detector calibration. The flux map snapshot files originate from data processed by the data preprocessing module and stored in a shared data pool. This data includes reactor operation measurement data such as the measured current of the core neutron detector, the measured current of the external detector, reactor power level, system pressure, coolant inlet temperature, and control rod position.

[0120] In some embodiments, the predictive analysis module is further configured to obtain a first flux map snapshot file from a shared data pool, perform core three-dimensional neutronics calculations according to the first flux map snapshot file to obtain a first core predicted three-dimensional power distribution, and correct the first core predicted three-dimensional power distribution using the measured current of the core neutron detector in the first flux map snapshot file to generate a first core measured three-dimensional power distribution. The first flux map snapshot file is the flux map snapshot file corresponding to the current time, obtained in response to a user's trigger command, such as the flux map snapshot file corresponding to time t1.

[0121] Understandably, the predictive analysis module uses the measured current of the core neutron detector in the first flux map snapshot file to correct the predicted three-dimensional power distribution of the first core. The specific calculation method for generating the measured three-dimensional power distribution of the first core is the same as the method used by the monitoring module to correct the predicted three-dimensional power distribution of the core using the ratio between the target measured current and the predicted current of the core neutron detector. This will not be elaborated upon here. Essentially, the predictive analysis module performs another offline calculation to reconstruct the three-dimensional power distribution of the core, based on user requirements.

[0122] In some embodiments, the predictive analysis module is further configured to compare the measured three-dimensional power distribution of the first core with the predicted three-dimensional power distribution of the first core within a predetermined time period after fuel replacement, and trigger an output of a core loading error warning based on the comparison result. This allows for core loading error detection in the early stages of the fuel cycle.

[0123] The measured and predicted three-dimensional power distributions of the first core can both characterize the radial and axial power of each fuel assembly in the core. The predictive analysis module compares the measured and predicted three-dimensional power distributions of the first core and triggers a core loading error warning based on the comparison results. This process involves comparing the percentage deviation between the measured and predicted radial power of each fuel assembly. If the comparison results indicate that the absolute value of the radial power deviation for any fuel assembly is greater than a deviation threshold (e.g., 10%), it indicates a possible fuel loading error for that fuel assembly, and a core loading error warning is then output.

[0124] Alternatively, as a feasible approach, if the absolute value of the radial power deviation of any fuel assembly is greater than the first deviation threshold (e.g., 10%), a comprehensive judgment can be made by combining the deviation of the surrounding fuel assemblies or the fuel assemblies at the quarter-symmetrical position. If the comparison results indicate that the power deviation of the surrounding fuel assemblies (the power deviation between the radial measured power and the radial predicted power) of any fuel assembly is generally large (e.g., all greater than the second deviation threshold), and the power deviation of the fuel assemblies at the quarter-symmetrical position is generally small (e.g., all less than the third deviation threshold), it indicates that there is a high probability of a fuel loading error, and the output core loading error prompt is triggered based on the comparison results.

[0125] Alternatively, as another feasible approach, based on the above comparison results indicating that the power deviation of the surrounding fuel assemblies of any given fuel assembly is generally large, while the deviation of the assemblies at the quarter-symmetric positions is generally small, it is possible to further examine the deviation between the measured power and the predicted power of the axial power distribution of that fuel assembly to determine whether this deviation is caused by control rod malfunction. If it is confirmed that it is unrelated to the control rod, then there is a high probability that a fuel loading error has occurred.

[0126] The process of confirming whether the deviation is caused by control rod loss of synchronization includes: using the control rod position system to confirm whether the control rod near any fuel assembly has lost synchronization. If no control rod loss of synchronization has occurred, it is confirmed that the issue is unrelated to the control rod, indicating that there is a high probability of a fuel loading error.

[0127] Alternatively, if the control rod position system confirms that a control rod near any fuel assembly has indeed lost synchronization, and the deviation disappears after the control rod loss of synchronization is restored, then the deviation is indeed caused by the control rod loss of synchronization. Otherwise, it is still confirmed that the deviation is unrelated to the control rod.

[0128] In some embodiments, the predictive analysis module is used to obtain a second flux map snapshot file from a shared data pool, continuously acquire different control rod hypothesis positions, and modify the control rod position in the second flux map snapshot file according to the currently acquired control rod hypothesis position each time it acquires a control rod hypothesis position. Based on the modified second flux map snapshot file, it calculates the second core measurement three-dimensional power distribution and compares the second core measurement three-dimensional power distribution with the second core prediction three-dimensional power distribution in the modified second flux map snapshot file to obtain a power difference. This process continues until the acquired power difference meets a condition (e.g., the power difference is minimized, or less than a certain value), at which point it stops acquiring new control rod hypothesis positions and outputs the control rod hypothesis position that meets the condition, completing the control rod out-of-synchronization diagnosis. The second flux map snapshot file is the flux map snapshot file corresponding to the current time moment, acquired in response to a user's trigger command, such as the flux map snapshot file corresponding to time t2. The specific calculation method of the predictive analysis module for calculating the second core measurement three-dimensional power distribution based on the modified second flux map snapshot file is the same as the method of the monitoring module for obtaining the core measurement three-dimensional power distribution, and will not be repeated here.

[0129] In some embodiments, the predictive analysis module is configured to obtain a third flux map snapshot file containing the measured current of the external detectors from a shared data pool, calculate the third core measurement three-dimensional power distribution based on the third flux map snapshot file, and solve for and output the core peripheral weight axial offset based on the third core measurement three-dimensional power distribution and the corresponding peripheral weight factors of the external detectors, facilitating subsequent calibration of the corresponding external detectors based on this core peripheral weight axial offset. The third flux map snapshot file is the flux map snapshot file corresponding to the current time, obtained in response to a user trigger command, such as the flux map snapshot file corresponding to time t3. The specific calculation method by which the predictive analysis module calculates the third core measurement three-dimensional power distribution based on the third flux map snapshot file is the same as the method used by the monitoring module to obtain the core measurement three-dimensional power distribution, and will not be repeated here.

[0130] The third core measurement of the three-dimensional power distribution includes the power of each fuel assembly in the core. Each external detector is pre-assigned an external weighting factor. When calibrating any external detector, the predictive analysis module can obtain the external weighting factor of that external detector, multiply the power of each fuel assembly in the third core measurement of the three-dimensional power distribution by the external weighting factor, and then calculate the average power of the upper half of the core in the third core measurement of the three-dimensional power distribution to obtain the weighted power of the upper core. The weighted power of the lower part of the reactor core is obtained by averaging the power of the lower part of the core. Then, the axial offset AO of the core periphery weight of any external detector is obtained by solving the following formula. wp .

[0131]

[0132] In some embodiments, the predictive analysis module can also provide the function of calculating the reactivity coefficient and shutdown margin under arbitrary operating conditions, which can be used to predict the reactivity coefficient and shutdown margin over a future period. The relevant calculations take a core neutronics model file as input and are implemented through three-dimensional core neutronics calculations. The calculation process may include:

[0133] Step 1: Perform one or more single-step burnup analysis calculations based on the core neutronics model file selected by the user (refer to the relevant content of single-step burnup analysis above) to calculate the core neutronics model file that predicts a certain time in the future.

[0134] Step 2: Using the core neutronics model file at a future time obtained in Step 1 as the new input model file, continue to perform three-dimensional neutronics calculations of the core with different calculation objectives to obtain the calculation results.

[0135] Assume the calculation targets include four types of reactivity coefficients: isothermal temperature coefficient, total power coefficient, boron differential value, and control rod value. For example, if the calculation target is the isothermal temperature coefficient, and the inlet temperature of the current core state is 280℃, then add a positive and a negative perturbation (refer to the recommended adjustment range in Table 1), setting it to 277℃ and 283℃ respectively. Perform two single-step burnup analysis calculations to obtain two eigenvalues ​​keff(277) and keff(283). Then, the isothermal temperature coefficient can be calculated using the following formula:

[0136] Isothermal temperature coefficient = ln(keff(283) / keff(277))×100000÷(283-277)=ln(keff(283) / keff(277))×100000÷6.

[0137] Table 1:

[0138]

[0139] Accordingly, when it is necessary to calculate the total power factor, boron differential value, and control rod value, the current power level, boron concentration, and control rod position of the reactor core can be obtained. Then, a positive or negative disturbance is added respectively (refer to the recommended adjustment range in Table 1) to complete two single-step burnup analysis calculations. Using the same calculation principle as the isothermal temperature coefficient, the total power factor, boron differential value, and control rod value are obtained.

[0140] Alternatively, when the calculation target is shutdown margin, the shutdown margin calculation method described above can be used for calculation.

[0141] See Figure 6This application also proposes a method for monitoring the reactor core of a nuclear power plant, which can be executed by the aforementioned monitoring equipment and achieve all the functions that the monitoring equipment described above can perform. The method includes:

[0142] S600: Performs first preprocessing on reactor operation data from the data processing equipment and stores the preprocessed reactor operation data in a shared data pool; the reactor operation data includes reactor operation measurement data and design data associated with the reactor core; the reactor operation measurement data includes the measured current of the reactor core neutron detector.

[0143] S601: Perform three-dimensional neutronics calculations on the reactor core based on the first preprocessed reactor operating data, generate a core neutronics model file, and store the core neutronics model file in a shared data pool; wherein the core neutronics model file contains the first core physical parameters.

[0144] S602: Obtain the target measurement current, perform a core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measurement current to obtain the core measurement three-dimensional power distribution; and obtain the second core physical parameters based on the core measurement three-dimensional power distribution, and store the second core physical parameters in a shared data pool; wherein, the target measurement current is the measurement current of the latest core neutron detector. In some implementations, the core three-dimensional neutronics calculation can be performed periodically according to a first period T1 to obtain the first core physical parameters; the core three-dimensional power distribution reconstruction calculation can be performed periodically according to a second period T2 to obtain the second core physical parameters; wherein, T1 is greater than T2.

[0145] S603: Obtain and output the physical parameters of the first core and the physical parameters of the second core.

[0146] In some embodiments, the core neutronics model file also includes a core predicted three-dimensional power distribution and a predicted current of the core neutron detector. The core three-dimensional power distribution reconstruction calculation is performed based on the core neutronics model file and the target measured current, including: correcting the core predicted three-dimensional power distribution by using the ratio between the target measured current and the predicted current of the core neutron detector to obtain the core measured three-dimensional power distribution.

[0147] In some embodiments, the method further includes outputting an analysis interface comprising a function selection area and a calculation parameter configuration area. The function selection area determines the target analysis function to be executed, and the calculation parameter configuration area obtains the calculation parameters associated with the target analysis function. The calculation parameter configuration area includes a core condition configuration area for configuring core operating conditions and an input model file configuration area for determining a target core neutronics model file from multiple core neutronics model files. The calculation parameters include the target core neutronics model file and the core operating conditions. Further, calculations are performed according to the target analysis function and the calculation parameters, and the calculation results are output.

[0148] In some embodiments, the method further includes obtaining a first flux map snapshot file from a shared data pool, performing core three-dimensional neutronics calculations according to the first flux map snapshot file to obtain a first core predicted three-dimensional power distribution, and correcting the first core predicted three-dimensional power distribution using the measured current of the core neutron detector in the first flux map snapshot file to generate a first core measured three-dimensional power distribution.

[0149] In some embodiments, the method further includes comparing the measured three-dimensional power distribution of the first core with the predicted three-dimensional power distribution of the first core within a predetermined time after fuel replacement, and triggering an output core loading error prompt based on the comparison result.

[0150] In some embodiments, the method further includes obtaining a second flux map snapshot file from a shared data pool, continuously obtaining different control rod hypothesis positions, modifying the control rod position in the second flux map snapshot file according to the currently obtained control rod hypothesis position each time a control rod hypothesis position is obtained, calculating the second core measured three-dimensional power distribution based on the modified second flux map snapshot file, comparing the second core measured three-dimensional power distribution with the second core predicted three-dimensional power distribution in the modified second flux map snapshot file to obtain a power difference, until the obtained power difference meets the condition, stopping the acquisition of new control rod hypothesis positions, outputting the control rod hypothesis position that meets the condition this time, and completing the control rod out-of-synchronization diagnosis.

[0151] In some embodiments, the method further includes obtaining a third flux map snapshot file containing the measured current of the external detector from a shared data pool, calculating the third core measurement three-dimensional power distribution according to the third flux map snapshot file, and solving and outputting the core peripheral weight axial offset based on the third core measurement three-dimensional power distribution and the peripheral weight factor corresponding to the external detector.

[0152] In some embodiments, the method further includes reactor operation measurement data including reactor power levels, the reactor power levels including multiple power level signals and the signal quality of each power level signal, and performing a first preprocessing on the reactor operation data from the data processing device, including:

[0153] The output reactor power level is determined based on the signal quality of each power level signal, multiple power level signals, and preset confidence rules.

[0154] The multiple power level signals include thermal balance power, ΔT power, power range detector power, and intermediate range detector power. Based on the signal quality of each power level signal, the multiple power level signals, and preset reliability rules, the output reactor power level is determined. This includes: when the signal quality of ΔT power meets the quality condition and ΔT power is less than or equal to a first power threshold, ΔT power is determined as the output reactor power level from the multiple power level signals according to preset reliability rules; or, when the signal quality of ΔT power does not meet the quality condition or ΔT power is greater than the first power threshold, if the signal quality of thermal balance power meets the quality condition, then the thermal balance power is determined as the output reactor power level. The output reactor power level is determined as follows: Alternatively, when the signal quality of both the ΔT power and the thermal balance power does not meet the quality conditions, the power of the power range detector or the intermediate range detector is corrected based on the correction amount, and the corrected power range detector power or the corrected intermediate range detector power is determined as the output reactor power level. The correction amount is the average deviation between the historical thermal balance power and the historical power range detector power that meet the quality conditions within a preset time period, or the average deviation between the historical thermal balance power and the historical intermediate range detector power that meet the quality conditions within a preset time period, or the historical correction amount obtained from the previous calculation.

[0155] As indicated in this application, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0156] Furthermore, this application uses specific terms to describe embodiments of the application. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of the application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this specification do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of the application can be appropriately combined.

[0157] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0158] Furthermore, 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 the description herein. Moreover, this application is to be understood not only by the actual terms used, but also by the meaning implied by each term.

[0159] Furthermore, although the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order or sequence shown, or to perform all of the shown operations to obtain the desired result. In some cases, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are addressed in the foregoing discussion, these details should not be construed as limiting the scope of this application, but rather as descriptions of features specific to particular embodiments. Certain features described in the context of a single embodiment may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0160] Although this application has been described with reference to specific embodiments, those skilled in the art should recognize that the above embodiments are only used to illustrate this application, and various equivalent changes or substitutions can be made without departing from the spirit of this application. Therefore, any changes or modifications to the above embodiments within the scope of the essential spirit of this application will fall within the scope of this application.

Claims

1. A monitoring device for monitoring the reactor core of a nuclear power plant, characterized in that, The monitoring equipment includes a data preprocessing module, a model update module, a monitoring module, a shared data pool, a predictive analysis module, and a monitoring interface module, wherein: The data preprocessing module is used to perform a first preprocessing on the reactor operation data from the data processing equipment, and store the first preprocessed reactor operation data in the shared data pool; the reactor operation data includes reactor operation measurement data and design data associated with the reactor core; the reactor operation measurement data includes the measurement current of the reactor core neutron detector; The model update module is used to perform three-dimensional neutronics calculations of the reactor core based on the first preprocessed reactor operating data, generate a reactor core neutronics model file, and store the reactor core neutronics model file in the shared data pool; wherein the reactor core neutronics model file contains the first reactor core physical parameters; The monitoring module is used to acquire the target measurement current, perform core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measurement current to obtain the core measurement three-dimensional power distribution; and obtain the second core physical parameters based on the core measurement three-dimensional power distribution, and store the second core physical parameters in the shared data pool; wherein, the target measurement current is the measurement current of the latest core neutron detector; The monitoring interface module is used to obtain and output the first core physical parameters and the second core physical parameters from the shared data pool; The predictive analysis module is used to obtain a third flux map snapshot file containing the measured current of the external detector from the shared data pool, calculate the third core measurement three-dimensional power distribution according to the third flux map snapshot file, and solve and output the core peripheral weight axial offset based on the third core measurement three-dimensional power distribution and the peripheral weight factor corresponding to the external detector.

2. The monitoring device as described in claim 1, characterized in that, The core neutronics model file also includes a predicted three-dimensional power distribution of the core and a predicted current for the core neutron detector. The monitoring module is used to perform a core three-dimensional power distribution reconstruction calculation based on the core neutronics model file and the target measured current, including: The predicted three-dimensional power distribution of the reactor core is corrected by the ratio between the target measured current and the predicted current of the neutron detector in the reactor core, thus obtaining the measured three-dimensional power distribution of the reactor core.

3. The monitoring device as described in claim 1, characterized in that, The model update module periodically performs the three-dimensional neutronics calculation of the reactor core according to the first period T1 to obtain the first reactor core physical parameters; the monitoring module periodically performs the three-dimensional power distribution reconstruction calculation of the reactor core according to the second period T2 to obtain the second reactor core physical parameters; wherein, T1 is greater than T2.

4. The monitoring device as described in claim 1, characterized in that, The reactor operation measurement data also includes any one or more of the following: reactor power level, coolant inlet temperature, coolant flow rate, and control rod position; the design data associated with the reactor core includes any one or more of the following: core neutron detector model file and core initial neutronics model file corresponding to each fuel change.

5. The monitoring device as described in claim 1, characterized in that, The monitoring device also includes an analysis interface module, wherein: The analysis interface module is used to output an analysis interface including a function selection area and a calculation parameter configuration area. The function selection area is used to determine the target analysis function to be executed, and the calculation parameter configuration area is used to obtain the calculation parameters associated with the target analysis function. The calculation parameter configuration area includes a core condition configuration area for configuring core operating conditions and an input model file configuration area for determining a target core neutronics model file from multiple core neutronics model files. The calculation parameters include the target core neutronics model file and the core operating conditions. The predictive analysis module is used to perform calculations based on the target analysis function and the calculation parameters from the analysis interface module, and output the calculation results to the analysis interface module for display.

6. The monitoring device as described in claim 5, characterized in that, The target analysis function includes single-step burnup analysis, load tracking simulation, or critical condition prediction. The calculation parameter configuration area also includes one or more of the following: search option configuration area, calculation model configuration area, and control rod position configuration area. The calculation parameters also include one or more of the following data obtained through the calculation parameter configuration area: search options, calculation model, control rod position, power scheme representing time and average core power, and analysis type.

7. The monitoring device as described in any one of claims 1-6, characterized in that, The predictive analysis module is further configured to obtain a first flux map snapshot file from the shared data pool, perform core three-dimensional neutronics calculations according to the first flux map snapshot file to obtain a first core predicted three-dimensional power distribution, and use the measured current of the core neutron detector in the first flux map snapshot file to correct the first core predicted three-dimensional power distribution to generate a first core measured three-dimensional power distribution.

8. The monitoring device as described in claim 7, characterized in that, The predictive analysis module is also used to compare the measured three-dimensional power distribution of the first core with the predicted three-dimensional power distribution of the first core within a predetermined time after fuel replacement, and trigger the output of a core loading error prompt based on the comparison result.

9. The monitoring device as described in any one of claims 1-6, characterized in that, The predictive analysis module is further configured to obtain a second flux map snapshot file from the shared data pool, continuously obtain different control rod hypothesis positions, modify the control rod position in the second flux map snapshot file based on the currently obtained control rod hypothesis position each time a control rod hypothesis position is obtained, calculate the second core measured three-dimensional power distribution based on the modified second flux map snapshot file, and compare the second core measured three-dimensional power distribution with the second core predicted three-dimensional power distribution in the modified second flux map snapshot file to obtain a power difference value, until the obtained power difference value meets the condition, stop obtaining new control rod hypothesis positions, output the control rod hypothesis position that meets the condition this time, and complete the control rod out-of-synchronization diagnosis.

10. The monitoring device as described in claim 4, characterized in that, The reactor operation measurement data includes the reactor power level, which includes multiple power level signals and the signal quality of each power level signal. The data preprocessing module is used to perform a first preprocessing on the reactor operation data from the data processing equipment, including: The output reactor power level is determined based on the signal quality of each power level signal, the multiple power level signals, and the preset confidence rules.

11. The monitoring device as described in claim 10, characterized in that, The multiple power level signals include thermal equilibrium power, ΔT power, power range detector power, and intermediate range detector power. The data preprocessing module is used to determine the output reactor power level based on the signal quality of each power level signal, the multiple power level signals, and preset confidence rules, including: When the signal quality of the ΔT power meets the quality condition, and the ΔT power is less than or equal to a first power threshold, the ΔT power is determined as the output reactor power level from the multiple power level signals according to a preset confidence rule; or, when the signal quality of the ΔT power does not meet the quality condition or the ΔT power is greater than the first power threshold, if the signal quality of the thermal balance power meets the quality condition, then the thermal balance power is determined as the output reactor power level; or... When the signal quality of the ΔT power and the signal quality of the thermal balance power do not meet the quality conditions, the power of the power range detector or the power of the intermediate range detector is corrected based on the correction amount, and the corrected power of the power range detector or the corrected power of the intermediate range detector is determined as the output reactor power level; wherein, the correction amount is the average deviation between the historical thermal balance power and the historical power range detector power that meet the quality conditions within a preset time period, or the average deviation between the historical thermal balance power and the historical intermediate range detector power that meet the quality conditions within a preset time period, or the historical correction amount obtained in the previous calculation.

12. A system for monitoring the reactor core of a nuclear power plant, characterized in that, It includes a core neutron detector, a data processing device, and a monitoring device according to any one of claims 1-11, wherein: The core neutron detector is located inside the core and is used to measure the neutron flux density at different locations within the core. A data processing device is used to perform a second preprocessing on the acquired initial reactor operating data to obtain reactor operating data, and output the reactor operating data to the monitoring device; wherein the second preprocessing includes any one or more of the following: deviation correction, averaging and logical operation processing, and the initial reactor operating data includes the measured current of the core neutron detector.

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