Nuclear power plant three-dimensional reactor core operation support system based on digital twinning

Abstract

The invention particularly relates to a nuclear power plant three-dimensional reactor core operation support system based on digital twinning, and belongs to the technical field of digital twinning and nuclear power plant operation support. The system comprises a data acquisition module, a physical test module, a reactor core monitoring module, a reactor core prediction module and a database, the data acquisition module is used for acquiring real-time measurement data of the reactor core and storing the data into a database; the physical test module is used for acquiring regular measurement data of the reactor core flux diagram and storing the data into a database; the reactor core monitoring module is used for initiating a reactor core monitoring task by a user or a system and executing the reactor core monitoring task initiated by the user or the system; and the reactor core prediction module is used for initiating a reactor core prediction task by a user and executing the reactor core prediction task initiated by the user. According to the invention, real-time operation support is effectively provided for operators.

Description

Technical Field

[0001] This invention relates to the fields of digital twin and nuclear power plant operation support technology, and in particular to a three-dimensional core operation support system for nuclear power plants based on digital twin, applicable to three-dimensional core operation support for pressurized water reactor units without fixed in-core detectors. Background Technology

[0002] Currently operating pressurized water reactor units without fixed in-core detectors, despite being equipped with numerous monitoring devices, lack the ability to monitor some key physical and thermal parameters, such as the core hotspot factor. Enthalpy rise factor Deviation from the boiling ratio of the nucleus Physical quantities that can only be obtained through core program calculations are often missing. This results in operators having a limited understanding of the core's condition, often relying on their personal experience to operate control rods and adjust core boron concentration, which can easily lead to human error and uncertainty in core operation.

[0003] Currently, nuclear power plants have traditionally addressed these issues by deploying a core program on-site to periodically import the core power operating history into the program for core tracking calculations. However, this approach has the following problems: 1. Relying solely on the calculation results of the core program will inevitably result in a deviation from the actual core state, and this deviation may gradually accumulate as the core burns out; 2. In reality, this method can only perform core tracking calculations after accumulating core operation data for a period of time. This will lead to a significant lag between the calculated core state and the actual state, and will not effectively provide real-time operational support for operators. Summary of the Invention

[0004] The purpose of this invention is to provide a three-dimensional reactor core operation support system for nuclear power plants based on digital twins. This system imports real-time reactor core measurement data into the system to complete three-dimensional neutronics calculations. It corrects the three-dimensional neutronics calculation results based on periodic measurement data from the reactor core flux diagram and real-time reactor core measurement data. Using the real-time reactor core measurement data and the three-dimensional neutronics calculation results, a digital twin is constructed to reliably and in real-time display the three-dimensional reactor core status. This provides a calculation model closer to the real reactor core for reactivity control, load tracking, and reactivity prediction. It is suitable for three-dimensional reactor core operation support in pressurized water reactor units without fixed in-core detectors, providing nuclear power plant operators with reactor core physical and thermal parameters that are unavailable through traditional monitoring methods, thus reducing monitoring blind spots. Based on this digital twin, operators can predict the reactor core status for a future period, optimize reactor core operation plans, and improve reactor core operation safety.

[0005] To achieve the above objectives, the present invention provides a three-dimensional nuclear power plant core operation support system based on digital twins, including a data acquisition module, a physical testing module, a core monitoring module, a core prediction module, and a database; The data acquisition module is used to collect real-time measurement data from the reactor core and store it in the database; The physical testing module is used to acquire periodic measurement data of the core flux map and store it in the database; The core monitoring module is used for user-initiated core monitoring tasks and executing user-initiated core monitoring tasks; and for system-initiated core monitoring tasks and executing system-initiated core monitoring tasks. The core prediction module is used to initiate core prediction tasks by users and to execute user-initiated core prediction tasks. Core monitoring tasks include real-time monitoring of core physical and thermal parameters and correction of core physical and thermal parameters calculated by establishing a three-dimensional neutronics model; core prediction tasks include predicting reactivity management during core power variation processes.

[0006] As one possible approach, the real-time core measurement data includes the first real-time core measurement data; the first real-time core measurement data is time-series data, including the real-time measured values ​​of the core relative power, control rod position, upper core power, lower core power, power of each external measurement channel, and detector current of each external measurement channel. The data acquisition module collects the first real-time measurement data of the reactor core, verifies it, and then stores it in the database. The specific steps include the following: The data acquisition module communicates with the real-time database of the nuclear power plant and acquires the first real-time measurement data of the reactor core from the real-time database of the nuclear power plant. The data acquisition module determines whether the first real-time measurement data of the reactor core meets condition one, which is: the real-time measurement values ​​of the reactor core relative power and control rod position are both... 0; If the first real-time measurement data of the reactor core does not meet condition one, the data acquisition module marks the first real-time measurement data of the reactor core as category 0; if the first real-time measurement data of the reactor core meets condition one, the data acquisition module further determines whether the first real-time measurement data of the reactor core meets condition two, which is: the real-time measurement value of the relative power of the reactor core is greater than 3%, and the real-time measurement values ​​of the upper power and lower power of the reactor core are both... 0; If the first real-time measurement data of the reactor core does not meet condition two, the data acquisition module marks the first real-time measurement data of the reactor core as Class 1; if the first real-time measurement data of the reactor core meets condition two, the data acquisition module further determines whether the first real-time measurement data of the reactor core meets condition three, which is: the deviation of the real-time power measurement value of each external measurement channel from the real-time power measurement value of the reactor core is less than 1.5%, and the deviation of the real-time current measurement value of each external measurement channel detector from the real-time current measurement value of the entire reactor detector is less than 5%; the real-time power measurement value of the reactor core is equal to the arithmetic mean of the real-time power measurement values ​​of each external measurement channel, and the real-time current measurement value of the entire reactor detector is equal to the arithmetic mean of the real-time current measurement values ​​of each external measurement channel detector. If the first real-time measurement data of the reactor core does not meet condition three, the data acquisition module marks the first real-time measurement data of the reactor core as category 2; if the first real-time measurement data of the reactor core meets condition three, the data acquisition module marks the first real-time measurement data of the reactor core as category 3. If the first real-time measurement data of the reactor core is of type 0 or type 1, the data acquisition module determines that the quality of the first real-time measurement data of the reactor core is unreliable and fails the verification of the first real-time measurement data of the reactor core. When the first real-time measurement data of the reactor core is of category 2 or 3, the data acquisition module determines that the quality of the first real-time measurement data of the reactor core is reliable, verifies the first real-time measurement data of the reactor core, and stores the verified first real-time measurement data of the reactor core into the database. The first real-time measurement data of both Type 2 and Type 3 cores were used to establish a three-dimensional neutronics model for calculations; the first real-time measurement data of Type 3 cores were used to correct the three-dimensional neutronics model and the core physical and thermal parameters calculated by the three-dimensional neutronics model.

[0007] As one possible approach, the real-time core measurement data also includes a second real-time core measurement data; the second real-time core measurement data is time-series data, including real-time measurements of nuclear power unit power, boron concentration, and core outlet temperature distribution; the data acquisition module collects the second real-time core measurement data and stores it in a database; The core physical and thermal parameters include real-time measured values ​​of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution, as well as real-time calculated values ​​of core axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, three-dimensional power distribution, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value. The core monitoring module obtains real-time measurements of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution from the real-time core measurement data stored in the database. The core monitoring module establishes a three-dimensional neutronics model based on the real-time core measurement data stored in the database to calculate the real-time values ​​of the core's axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value.

[0008] As one possible approach, the core monitoring module corrects the core physical and thermal parameters calculated by the three-dimensional neutronics model, including correcting the real-time calculated values ​​of radial power distribution between the current and next flux map measurement times, and correcting the real-time calculated values ​​of axial power distribution between the current and next flux map measurement times.

[0009] As one feasible approach, the core monitoring module corrects the real-time calculated value of the radial power distribution between the current and next flux map measurement times using periodic core flux map measurement data and real-time core measurement data. This process includes the following steps: (1) The core monitoring module calculates the correction factor of the radial power distribution flux map on each axial layer of the core and the real-time correction factor of the radial power distribution of the core respectively; (2) The core monitoring module corrects the real-time calculated values ​​of radial power distribution in each axial layer of the core between the current and next flux map measurement times based on the correction factor of the radial power distribution flux map on each axial layer of the core and the real-time correction factor of the radial power distribution in the core. The real-time calculated values ​​of radial power distribution in each axial layer of the reactor core between the current and next flux map measurement times constitute the real-time calculated values ​​of radial power distribution between the current and next flux map measurement times of the reactor core. The real-time calculated value of the radial power distribution in the axial layer between the current and next flux map measurements of the reactor core is corrected according to the following formula: in, The axial direction between the current and next flux plot measurements of the corrected core. Real-time calculated values ​​of radial power distribution on the layer. The axial direction between the current and next flux plot measurement times of the reactor core Real-time calculated values ​​of radial power distribution on the layer. Core axial direction Radial power distribution flux map correction factor on the layer, This is a real-time correction factor for the radial power distribution of the reactor core.

[0010] As one feasible approach, the core flux map periodic measurement data includes core flux map measurement data from each iteration; the core monitoring module determines the radial power distribution flux map correction factor on each axial layer of the core according to the following steps: (1) The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement. The three-dimensional neutronics model calculation provides the real-time calculated value of the three-dimensional power distribution at the time of the current flux map measurement. (2) The real-time calculated value of the three-dimensional power distribution and the real-time measured value of the three-dimensional power distribution at the time of the current flux diagram measurement of the reactor core are normalized layer by layer along the axial direction to obtain the real-time calculated value of the radial power distribution and the real-time measured value of the radial power distribution on each axial layer at the time of the current flux diagram measurement of the reactor core. (3) Based on the relationship between the real-time calculated value of radial power distribution on each axial layer and the real-time measured value of radial power distribution at the time of this flux map measurement of the reactor core, determine the correction factor of the radial power distribution flux map on each axial layer of the reactor core; The relationship between the real-time calculated value and the real-time measured value of the radial power distribution on the axial layer at the time of this core flux diagram measurement is as follows: in, This represents the real-time measured value of the radial power distribution on the axial z-layer at the moment of this flux diagram measurement of the reactor core. This represents the real-time calculated value of the radial power distribution along the axial z-layer at the moment of this flux diagram measurement of the reactor core. Core Axial Radial power distribution flux map correction factor on the layer.

[0011] As one feasible approach, the core monitoring module determines the real-time correction factor for the core radial power distribution according to the following steps: (1) The core monitoring module calculates the real-time two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. Real-time optimal prediction of two-dimensional power distribution ; (2) The core monitoring module calculates the real-time value of the two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. Real-time optimal prediction of two-dimensional power distribution The real-time correction factor for the radial power distribution of the reactor core is calculated according to the following formula: in, This is a real-time correction factor for the radial power distribution of the reactor core.

[0012] As one possible approach, the core monitoring module calculates the real-time two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. It includes the following steps: (1) The three-dimensional neutronics model calculation provides the real-time calculated value of the three-dimensional power distribution between the current and next flux map measurement times of the reactor core; (2) The core monitoring module integrates the real-time calculated value of the three-dimensional power distribution of the core between the current and next flux map measurement times along each fuel channel along the axial direction to obtain the real-time calculated value of the two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. .

[0013] As one feasible approach, the core monitoring module calculates the real-time optimal estimate of the two-dimensional power distribution in each fuel channel of the core. It includes the following steps: (1) The core monitoring module obtains real-time measurement data between the current and next flux map measurement times from the database. The real-time measurement data between the current and next flux map measurement times provides the real-time measured value of the outlet temperature distribution between the current and next flux map measurement times. ; (2) The core monitoring module corrects the core radial power distribution sub-channel based on the core. Real-time measured values ​​of the outlet temperature distribution between the current and next flux plot measurements of the reactor core. The real-time calculated value of the outlet temperature distribution between the current and next flux map measurement times of the reactor core is calculated according to the following formula. : (3) Real-time calculation of the outlet temperature distribution between the current and next flux map measurement times of the reactor core by the core monitoring module. Water property calculations were performed to obtain real-time calculated values ​​of the enthalpy rise distribution in each fuel channel between the current and next flux map measurement times of the reactor core. ; (4) The core monitoring module calculates the real-time enthalpy rise distribution of each fuel channel between the current and next flux diagram measurement times based on the single-channel thermal calculation model. The corresponding real-time optimal estimate of the two-dimensional power distribution .

[0014] As one possible approach, the core monitoring module determines the core radial power distribution subchannel correction factor according to the following steps. : (1) The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement. (2) The core monitoring module integrates the real-time three-dimensional power distribution measurement value of the core at the time of this flux diagram measurement along each fuel channel along the axis to obtain the real-time two-dimensional power distribution measurement value of each fuel channel at the time of this flux diagram measurement. (3) The core monitoring module calculates the real-time enthalpy rise distribution corresponding to the real-time measured value of the two-dimensional power distribution of each fuel channel at the time of the current flux diagram measurement of the core based on the single-channel thermal calculation model. (4) The core monitoring module performs water property calculations on the real-time calculated values ​​of the enthalpy rise distribution of each fuel channel at the time of the current flux diagram measurement of the core, and obtains the real-time calculated value of the outlet temperature distribution at the time of the current flux diagram measurement of the core. (5) The core monitoring module determines the core radial power distribution sub-channel correction factor based on the relationship between the real-time measured value of the outlet temperature distribution and the real-time calculated value of the outlet temperature distribution at the time of the current flux diagram measurement. The relationship between the real-time measured value and the real-time calculated value of the outlet temperature distribution at the moment of this core flux diagram measurement is as follows: in, This is the real-time measured value of the outlet temperature distribution at the moment of this flux diagram measurement of the reactor core. This is the real-time calculated value of the outlet temperature distribution at the moment of this flux diagram measurement of the reactor core. This is the correction factor for the radial power distribution subchannel of the reactor core.

[0015] As one possible approach, the core monitoring module corrects the real-time calculated value of the axial power distribution between the current and next flux map measurement times of the core, including the following steps: (1) The core monitoring module obtains real-time measurement data between the current and next flux map measurement times of the core and the current flux map measurement data of the core from the database; (2) The core monitoring module determines the [TS] matrix, [C] matrix and [I] matrix based on the real-time measurement data between the current and next flux map measurement times of the core and the current flux map measurement data of the core; The [TS] matrix represents the correspondence between the current of the six axial sections of the external power range detector calibrated during this flux diagram measurement of the reactor core and the power of the six axial sections inside the reactor core; the [C] matrix represents the influence of the control rod insertion of the reactor core on the current of the external detector; the [I] matrix represents the current of the external detector of the reactor core. (3) The core monitoring module obtains the power of the six axial layers of the core based on the [TS] matrix, [C] matrix and [I] matrix. : (4) The core monitoring module obtains the power of each axial layer of the core after merging through numerical calculation, and uses it as the real-time measurement value of the core axial power distribution; (5) The core monitoring module integrates the deviation between the real-time calculated value and the real-time measured value of the core axial power distribution to obtain the error distribution of the core axial power distribution; (6) The core monitoring module superimposes the real-time calculated value of the core axial power distribution with the core axial power distribution error distribution to obtain the corrected real-time calculated value of the core axial power distribution.

[0016] As one feasible approach, the core physical and thermal parameters also include the real-time calculated values ​​of the core's DNBR. The core monitoring module calculates the real-time DNBR values ​​of the core using the DNBR calculation model based on the corrected real-time calculated values ​​of the core's radial power distribution and axial power distribution. The DNBR calculation model selects a four-equation homogeneous flow model with a slip ratio, and the calculation of the critical heat flux density adopts empirical formulas consistent with the core thermal design program. During the DNBR calculation, based on the corrected real-time calculated values ​​of the core's radial power distribution and axial power distribution, the key grid regions are refined, the edge grid regions are coarsened, and multiple grid regions are calculated in parallel, taking into account the uncertainties of the physical correction results and boundary conditions.

[0017] As one possible approach, the core prediction module predicts reactivity management during core power variation, specifically including: using a core moment selected by the user from the core monitoring module in real time as the starting point for core prediction calculation, calculating reactivity management during core power variation according to the user-defined future core state, and exporting the calculation results as a "reactivity management report" with one click.

[0018] As one feasible approach, core prediction tasks also include core load tracking, criticality prediction, minimum shutdown boron concentration, and lifetime prediction.

[0019] As one feasible approach, the core prediction module needs to modify the three-dimensional neutronics model using perturbation theory before performing the core prediction task. This involves the following steps: (1) The core prediction module uses perturbation theory to generate a sensitivity matrix. ; (2) The core prediction module determines the additional absorption cross section of each axial layer of the core by solving a system of linear equations: in, The absorption cross section added to each axial layer of the reactor core. The power of each axial layer of the reactor core; The core prediction module uses the additional absorption cross sections of each axial layer of the core in the three-dimensional neutronics model to form a modified three-dimensional neutronics model.

[0020] As one feasible approach, the core prediction module utilizes perturbation theory to generate a sensitivity matrix, including the following steps: (1) The core prediction module adds an absorption section disturbance to each axial layer of the core. The power variation of each axial layer in the reactor core was calculated using a three-dimensional neutronics model. ; (2) The core prediction module calculates the impact of a unit disturbance in each axial layer of the core on the power distribution of each axial layer, and forms a sensitivity matrix. in, Characterizing the axial layers of the reactor core The effect of a unit perturbation at a location on the power distribution of each axial layer.

[0021] As one feasible approach, the core prediction module predicts the reactive management during the core power transition process. Taking the core power increase process as an example, the specific steps include: (1) Under the given power increase rate and target power, simulate the power increase process starting from state point A and the transient changes in iodine and xenon concentrations after reaching the target power; This simulation process does not consider the action of the control rods or perform a critical search, but it needs to simulate the dynamic behavior of iodine and xenon to obtain the changes in iodine and xenon concentrations at several power points; considering the numerical xenon oscillation problem, the power feedback effect is appropriately increased during the simulation. (2) Perform static calculations at the power point in step 1: Under the condition of fixed iodine-xenon distribution, calculate the changes in reactivity and axial power deviation to obtain path AB; This process also does not perform a critical search; the iodine-xenon distribution is taken from the distribution at the initial state time, and the iodine-xenon concentration is taken from the calculated value in step 1. The path AB is generated under the hypothetical condition that the control rod does not move and the xenon distribution remains unchanged during the power increase process. It shows the change in axial power deviation under the hypothetical condition, while the change in reactivity indicates the reactivity that needs to be diluted under the hypothetical condition. (3) Simulate the power increase process along path AC; Power boosting along path AC with constant axial power offset. at this time, ,in, The axial power deviations at points A and C are respectively. These are the axial powers at points A and C, respectively. In order to increase power along path AC, the axial power deviation between state point B and state point C needs to be compensated by raising the control rod. Therefore, based on state point B, a series of target control rod positions corresponding to axial power deviations are obtained through three-dimensional neutronics calculations. Conversely, the reactivity changes caused by the changes in control rod positions are also obtained. Thus, the reactivity that needs to be introduced for dilution during the power increase process along path AC is calculated. That is, the reactivity of path AB calculated in step 2 is subtracted from the reactivity that the control rod needs to introduce during path AC, and then the dilution rate during the power increase process is calculated. At this dilution rate from state point A to state point C, the introduced positive reactivity will be insufficient, and the core will become subcooled. Once the subcooling exceeds the control rod dead zone, it will drive the control rods upward. Assuming the three-dimensional neutronics model is reliable, in an actual reactor core, if this dilution rate is followed, the control rods will also be intermittently and slowly raised during the dilution process. (4) When the core state reaches state point C, xenon poisoning will first decrease and then increase; During the xenon poison reduction phase, the axial power offset will change in the negative direction, requiring boronizing to maintain core criticality; During the phase of increased xenon toxicity, the axial power offset will change in the positive direction, requiring dilution to maintain the criticality.

[0022] As one feasible approach, the online operation support system for three-dimensional reactor cores of nuclear power plants based on digital twins also includes a user management module. The user management module adopts the OAuth2 protocol, which entrusts user authentication to the user authentication intermediate service and realizes single sign-on. User authentication is integrated into the backend service, which adds user permission requirements to the corresponding resources and restricts the resource boundaries that users at each level can access.

[0023] As one feasible approach, the digital twin-based three-dimensional reactor core online operation support system for nuclear power plants also includes a unit management module for setting unit operating condition parameter limits. The unit operating condition parameters include Class I operating condition parameter limits and Class II operating condition parameter limits. Class I operating condition parameter limits include operating ladder diagram limits, loss-of-coolant accident limits, and DNBR limits. Class II operating condition parameter limits include protection ladder diagram limits, DNBR limits, control rod insertion limits, boron-10 abundance limits, and soluble boron concentration limits.

[0024] As one feasible approach, the digital twin-based 3D nuclear power plant core online operation support system features a front-end human-machine interface. Developed using the Vue web framework, this interface is presented to users as a single-page application, including a function bar, a status bar, and a main monitoring page. The function bar provides entry points to data function modules; the status bar displays the core physical and thermal parameters monitored in real-time by the core monitoring module; and the main monitoring page allows users to customize the core physical and thermal parameters that the core monitoring module needs to monitor in real-time by dragging or selecting.

[0025] As one possible approach, the system adopts a distributed computing architecture, including backend services and multiple computing nodes; The backend service runs on the master server to execute core monitoring tasks initiated by users or the system; the compute nodes run on the slave servers to execute core prediction tasks initiated by users; each compute node is connected to the master server through network file storage to achieve shared storage; a reverse proxy server runs on the master server, which sends packaged static resource files to the user's browser when the user accesses the site. The data acquisition module collects real-time measurement data of the reactor core at a frequency of one point per minute and stores it in the database, then starts the backend service. The backend service performs three-dimensional neutronics calculations and corrects the results at a frequency of one point per ten minutes, and presents the real-time monitored physical and thermal parameters of the reactor core to the front-end human-machine interface.

[0026] As one possible approach, the backend service is written using the Django framework; a three-dimensional nodal method core calculation program, at the same level as the core design program, is used as the kernel for three-dimensional neutronics calculations.

[0027] Beneficial technical effects of the present invention: 1. The system provides a more accurate correction method for power distribution calculations: In the current LSS monitoring system equipped in pressurized water reactor units, the geometric matrix [G] is directly used for the reconstruction of fine axial power distribution, and the accuracy is difficult to guarantee. However, the system only applies the geometric matrix [G] to the reconstruction of fine axial power distribution deviations, and uses the constructed deviations to correct the axial power distribution calculations, thereby achieving higher online monitoring accuracy. In the correction of radial power distribution, the correction method implemented by the system not only uses flux charts regularly measured on-site at nuclear power plants to determine the calculation errors of each axial layer, but also calibrates the deviation of thermocouple temperature under the single-channel model used by the three-dimensional core calculation software, taking into account the influence of coolant lateral turbulence on thermocouple temperature. 2. The system provides operators with more comprehensive and reliable operational support: The system takes reactivity balance during power variation as its basic starting point. However, the three-dimensional neutronics model for reactivity calculation has been modified to ensure that the three-dimensional neutronics model is consistent with the actual core at the initial moment, thereby obtaining more accurate reactivity calculation results. At the same time, the system can also directly provide boron concentration, axial power deviation, and control rod position changes, intuitively showing the degree of agreement between the predicted results at the past and present moments and the actual core state, providing operators with a real-time judgment on the degree of agreement between the two in the future. 3. The system fully considers the existing hardware conditions of nuclear power plants and can be put into use without any technical modifications to the site; it adopts modern development technologies in the Web field and is compatible with the existing browsers of nuclear power plants, providing on-site users with a rich and beautiful interface and a modern human-computer interaction experience.

[0028] Through the aforementioned innovative methods, the system fully utilizes on-site monitoring data without requiring technical modifications to existing nuclear power plant facilities. Based on more accurate theoretical calculations, it corrects the theoretical database, achieves real-time data twinning, and expands the range of data that can be monitored in nuclear reactors. At the same time, it enables a method to predict changes in the reactor core state over a period of time based on the current core state, allowing operators to adopt more reliable and efficient operating procedures. The system is of great benefit to improving the safety and economy of pressurized water reactor unit operation. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of an embodiment of the online operation support system for a three-dimensional nuclear power plant core based on digital twins according to the present invention; Figure 2 This is a schematic diagram of the data flow in one embodiment of the digital twin-based nuclear power plant three-dimensional reactor core online operation support system of the present invention; Figure 3 This is a schematic diagram of reactivity management during a variable power process, representing an embodiment of the digital twin-based online operation support system for nuclear power plant cores. Detailed Implementation

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0031] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0032] The terms “include,” “comprising,” or any other variation thereof are intended to cover non-exclusive inclusion, which includes not only the elements listed but also other elements not expressly listed.

[0033] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments.

[0034] See Figure 1-2 This embodiment provides a three-dimensional nuclear power plant core online operation support system based on digital twin, including a data acquisition module, a physical test module, a core monitoring module, a core prediction module, and a database; The data acquisition module is used to collect real-time measurement data from the reactor core and store it in the database; The physical testing module is used to acquire periodic measurement data of the core flux map and store it in the database; The core monitoring module is used for user-initiated core monitoring tasks and executing user-initiated core monitoring tasks; and for system-initiated core monitoring tasks and executing system-initiated core monitoring tasks. The core prediction module is used to initiate core prediction tasks by users and to execute user-initiated core prediction tasks. Core monitoring tasks include real-time monitoring of core physical and thermal parameters and correction of core physical and thermal parameters calculated by establishing a three-dimensional neutronics model; core prediction tasks include predicting reactivity management during core power variation processes.

[0035] In this embodiment, as one possible approach, the real-time core measurement data includes the first real-time core measurement data; the first real-time core measurement data is time-series data, including the real-time measured values ​​of the core relative power, control rod position, upper core power, lower core power, power of each external measurement channel, and detector current of each external measurement channel; The data acquisition module collects the first real-time measurement data of the reactor core, verifies it, and then stores it in the database. The specific steps include the following: The data acquisition module communicates with the real-time database of the nuclear power plant and acquires the first real-time measurement data of the reactor core from the real-time database of the nuclear power plant. The data acquisition module determines whether the first real-time measurement data of the reactor core meets condition one, which is: the real-time measurement values ​​of the reactor core relative power and control rod position are both... 0; If the first real-time measurement data of the reactor core does not meet condition one, the data acquisition module marks the first real-time measurement data of the reactor core as category 0; if the first real-time measurement data of the reactor core meets condition one, the data acquisition module further determines whether the first real-time measurement data of the reactor core meets condition two, which is: the real-time measurement value of the relative power of the reactor core is greater than 3%, and the real-time measurement values ​​of the upper power and lower power of the reactor core are both... 0; If the first real-time measurement data of the reactor core does not meet condition two, the data acquisition module marks the first real-time measurement data of the reactor core as Class 1; if the first real-time measurement data of the reactor core meets condition two, the data acquisition module further determines whether the first real-time measurement data of the reactor core meets condition three, which is: the deviation of the real-time power measurement value of each external measurement channel from the real-time power measurement value of the reactor core is less than 1.5%, and the deviation of the real-time current measurement value of each external measurement channel detector from the real-time current measurement value of the entire reactor detector is less than 5%; the real-time power measurement value of the reactor core is equal to the arithmetic mean of the real-time power measurement values ​​of each external measurement channel, and the real-time current measurement value of the entire reactor detector is equal to the arithmetic mean of the real-time current measurement values ​​of each external measurement channel detector. If the first real-time measurement data of the reactor core does not meet condition three, the data acquisition module marks the first real-time measurement data of the reactor core as category 2; if the first real-time measurement data of the reactor core meets condition three, the data acquisition module marks the first real-time measurement data of the reactor core as category 3. When the first real-time measurement data of the reactor core is of type 0 or type 1, the data acquisition module determines that the quality of the first real-time measurement data of the reactor core is unreliable and fails the verification of the first real-time measurement data of the reactor core. When the first real-time measurement data of the reactor core is of category 2 or 3, the data acquisition module determines that the quality of the first real-time measurement data of the reactor core is reliable, verifies the first real-time measurement data of the reactor core, and stores the verified first real-time measurement data of the reactor core into the database. The first real-time measurement data of both Type 2 and Type 3 cores were used to establish a three-dimensional neutronics model for calculations; the first real-time measurement data of Type 3 cores were used to correct the three-dimensional neutronics model and the core physical and thermal parameters calculated by the three-dimensional neutronics model.

[0036] In this embodiment, as one possible approach, the real-time database of the nuclear power plant is a PI system.

[0037] In this embodiment, as one possible approach, the real-time core measurement data also includes second real-time core measurement data; the second real-time core measurement data is time-series data, including real-time measurements of nuclear power unit power, boron concentration, and core outlet temperature distribution; the data acquisition module acquires the second real-time core measurement data and stores it in a database; The core physical and thermal parameters include real-time measured values ​​of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution, as well as real-time calculated values ​​of core axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, three-dimensional power distribution, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value. The core monitoring module obtains real-time measurements of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution from the real-time core measurement data stored in the database. The core monitoring module establishes a three-dimensional neutronics model based on the real-time core measurement data stored in the database to calculate the real-time values ​​of the core's axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value.

[0038] Core axial power offset = Core axial power deviation = Core axial power offset .

[0039] Obtaining accurate three-dimensional power distribution of the reactor core is a prerequisite for realizing online monitoring of the reactor core's physical and thermal parameters. However, the three-dimensional power distribution of the reactor core calculated by the three-dimensional neutronics model inevitably deviates from the actual situation.

[0040] In this embodiment, as one possible approach, the core monitoring module corrects the core physical and thermal parameters calculated by the three-dimensional neutronics model, including correcting the real-time calculated value of the radial power distribution between the current and next flux map measurement times, and correcting the real-time calculated value of the axial power distribution between the current and next flux map measurement times.

[0041] The error in the real-time calculation of the radial power distribution of the reactor core is mainly caused by the error in the three-dimensional neutronics model. For a specific fuel cycle, the error in the real-time calculation of the radial power distribution of the reactor core is more stable than that in the real-time calculation of the axial power distribution of the reactor core. The error distribution of the real-time calculation of the radial power distribution of the reactor core changes less with the core power level and control rod position, and also changes more slowly with core burnup.

[0042] The real-time calculated value of the radial power distribution of the reactor core can be corrected using periodic measurement data of the core flux map and real-time measurement data of the core. The former is mainly used to correct the reference model error of the three-dimensional neutronics model under the reference state, while the latter is mainly used to correct the model error caused by the change of control rod position and the burnup effect in the time period between the current and next flux map measurement time.

[0043] In this embodiment, as one possible approach, the core monitoring module corrects the real-time calculated value of the radial power distribution between the current and next flux map measurement times using periodic core flux map measurement data and real-time core measurement data. Specifically, this includes the following steps: 1. The core monitoring module calculates the correction factor for the radial power distribution flux map on each axial layer of the core and the real-time correction factor for the radial power distribution of the core. 2. The core monitoring module corrects the real-time calculated values ​​of radial power distribution in each axial layer of the core between the current and next flux map measurement times based on the correction factor of the radial power distribution flux map on each axial layer of the core and the real-time correction factor of the radial power distribution in the core. The real-time calculated values ​​of radial power distribution in each axial layer of the reactor core between the current and next flux map measurement times constitute the real-time calculated values ​​of radial power distribution between the current and next flux map measurement times of the reactor core. The real-time calculated value of the radial power distribution in the axial layer between the current and next flux map measurements of the reactor core is corrected according to the following formula: in, The axial direction between the current and next flux plot measurements of the corrected core. Real-time calculated values ​​of radial power distribution on the layer. The axial direction between the current and next flux plot measurement times of the reactor core Real-time calculated values ​​of radial power distribution on the layer. Core axial direction Radial power distribution flux map correction factor on the layer, This is a real-time correction factor for the radial power distribution of the reactor core.

[0044] In the formula, the superscript 0 indicates the measurement time of the current flux map of the reactor core, and the superscript 1 indicates the time range between the current and next flux map measurement times (including the current flux map measurement time); at the current flux map measurement time of the reactor core, The value is 0.

[0045] In this embodiment, as one possible approach, the periodic core flux map measurement data includes core flux map measurement data from each iteration; the core monitoring module determines the radial power distribution flux map correction factor on each axial layer of the core according to the following steps: 1. The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement; the three-dimensional neutronics model calculation provides the real-time calculated value of the three-dimensional power distribution at the time of the current flux map measurement. 2. The real-time calculated value of the three-dimensional power distribution and the real-time measured value of the three-dimensional power distribution at the moment of the current flux diagram measurement of the reactor core are normalized layer by layer along the axial direction to obtain the real-time calculated value of the radial power distribution and the real-time measured value of the radial power distribution on each axial layer at the moment of the current flux diagram measurement of the reactor core. 3. Based on the relationship between the real-time calculated values ​​of radial power distribution on each axial layer and the real-time measured values ​​of radial power distribution at the time of this flux map measurement of the reactor core, determine the correction factor for the radial power distribution flux map on each axial layer of the reactor core; The relationship between the real-time calculated value and the real-time measured value of the radial power distribution on the axial layer at the time of this core flux diagram measurement is as follows: in, This represents the real-time measured value of the radial power distribution on the axial z-layer at the moment of this flux diagram measurement of the reactor core. This represents the real-time calculated value of the radial power distribution along the axial z-layer at the moment of this flux diagram measurement of the reactor core. Core Axial Radial power distribution flux map correction factor on the layer.

[0046] In this invention, when obtaining the radial power distribution flux map correction factor on each axial layer of the reactor core, the real-time calculated value and the real-time measured value of the three-dimensional power distribution at the time of reactor core flux map measurement are first normalized layer by layer along the axial direction to obtain the real-time calculated value and the real-time measured value of the radial power distribution on each axial layer at the time of reactor core flux map measurement. Then, based on the relationship between the real-time calculated value and the real-time measured value of the radial power distribution on each axial layer at the time of reactor core flux map measurement, the radial power distribution flux map correction factor on each axial layer of the reactor core is determined. Therefore, the flux map correction factor of the radial power distribution of the reactor core is not directly related to the deviation of the axial power distribution of the reactor core.

[0047] In this embodiment, as one possible approach, the core monitoring module determines the real-time correction factor for the core radial power distribution according to the following steps: 1. The core monitoring module calculates the real-time two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. Real-time optimal prediction of two-dimensional power distribution ; 2. The core monitoring module calculates the real-time values ​​based on the two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. Real-time optimal prediction of two-dimensional power distribution The real-time correction factor for the radial power distribution of the reactor core is calculated according to the following formula: in, This is a real-time correction factor for the radial power distribution of the reactor core.

[0048] During the operation between the current and next flux map measurements of the reactor core, the real-time calculated value of the three-dimensional power distribution of the reactor core can be obtained through three-dimensional neutronics calculations.

[0049] In this embodiment, as one possible approach, the core monitoring module calculates the real-time two-dimensional power distribution of each fuel channel between the current and next flux map measurement times. It includes the following steps: 1. The three-dimensional neutronics model calculation provides real-time calculation values ​​of the three-dimensional power distribution between the current and next flux map measurement times of the reactor core; 2. The core monitoring module integrates the real-time calculated three-dimensional power distribution values ​​of the core between the current and next flux map measurement times along each fuel channel along the axial direction to obtain the real-time calculated two-dimensional power distribution values ​​of each fuel channel between the current and next flux map measurement times. .

[0050] During the operation between the current and next flux mapping measurements of the core, real-time measurements of the core's three-dimensional power distribution cannot be obtained. However, real-time measurements of the core outlet temperature distribution can be obtained by storing the core's real-time measurement data in the database. The real-time optimal estimate of the two-dimensional power distribution of each fuel channel in the reactor core can be calculated based on the real-time measured value of the core outlet temperature distribution.

[0051] In this embodiment, as one possible approach, the core monitoring module calculates the real-time optimal estimate of the two-dimensional power distribution in each fuel channel of the core. It includes the following steps: 1. The core monitoring module retrieves real-time measurement data from the database between the current and next flux map measurement times. This real-time measurement data provides the real-time measured value of the outlet temperature distribution between the current and next flux map measurement times. ; 2. The core monitoring module uses the core radial power distribution sub-channel correction factor. Real-time measured values ​​of the outlet temperature distribution between the current and next flux plot measurements of the reactor core. The real-time calculated value of the outlet temperature distribution between the current and next flux map measurement times of the reactor core is calculated according to the following formula. : 3. The core monitoring module calculates the real-time outlet temperature distribution between the current and next flux map measurement times. Water property calculations were performed to obtain real-time calculated values ​​of the enthalpy rise distribution in each fuel channel between the current and next flux map measurement times of the reactor core. ; 4. Based on the single-channel thermal calculation model, the core monitoring module calculates the real-time enthalpy rise distribution of each fuel channel between the current and next flux diagram measurement times. The corresponding real-time optimal estimate of the two-dimensional power distribution .

[0052] In this embodiment, as one possible implementation method, the core monitoring module determines the core radial power distribution sub-channel correction factor according to the following steps. : 1. The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement. 2. The core monitoring module integrates the real-time three-dimensional power distribution measurement value of the core at the time of the current flux diagram measurement along each fuel channel along the axis to obtain the real-time two-dimensional power distribution measurement value of each fuel channel at the time of the current flux diagram measurement. 3. The core monitoring module calculates the real-time enthalpy rise distribution corresponding to the real-time measured value of the two-dimensional power distribution of each fuel channel at the moment of the current flux diagram measurement, based on the single-channel thermal calculation model. 4. The core monitoring module calculates the water properties of the enthalpy rise distribution of each fuel channel at the time of the current core flux diagram measurement, and obtains the real-time calculated value of the outlet temperature distribution at the time of the current core flux diagram measurement. 5. The core monitoring module determines the core radial power distribution sub-channel correction factor based on the relationship between the real-time measured value and the real-time calculated value of the outlet temperature distribution at the time of the current core flux diagram measurement. The relationship between the real-time measured value and the real-time calculated value of the outlet temperature distribution at the moment of this core flux diagram measurement is as follows: in, This is the real-time measured value of the outlet temperature distribution at the moment of this flux diagram measurement of the reactor core. This is the real-time calculated value of the outlet temperature distribution at the moment of this flux diagram measurement of the reactor core. This is the correction factor for the radial power distribution subchannel of the reactor core.

[0053] Under the assumption of the single-channel thermal calculation model, the real-time measured values ​​of the two-dimensional power distribution of each fuel channel in the core essentially correspond to the real-time calculated values ​​of the enthalpy rise distribution of each fuel channel in the core. A core radial power distribution sub-channel correction factor is introduced between the real-time measured values ​​and the real-time calculated values ​​of the core outlet temperature distribution because the sub-channel effect of the core's axial lateral flow objectively exists.

[0054] Compared to the radial power distribution of the core, the calculation error of the axial power distribution of the core is more affected by changes in the core state, especially when the core is in a xenon transient state.

[0055] In this embodiment, as one possible approach, the core monitoring module corrects the real-time calculated value of the axial power distribution between the current and next flux map measurement times of the core, including the following steps: 1. The core monitoring module obtains real-time measurement data between the current and next flux map measurement times of the core, as well as the current flux map measurement data of the core, from the database; 2. The core monitoring module determines the [TS] matrix, [C] matrix, and [I] matrix based on the real-time measurement data between the current and next flux map measurement times and the current flux map measurement data of the core. The [TS] matrix represents the correspondence between the current of the six axial sections of the external power range detector calibrated during this flux diagram measurement of the reactor core and the power of the six axial sections inside the reactor core; the [C] matrix represents the influence of the control rod insertion of the reactor core on the current of the external detector; the [I] matrix represents the current of the external detector of the reactor core. 3. The core monitoring module obtains the power of the six axial layers of the core based on the [TS] matrix, [C] matrix, and [I] matrix. : 4. The core monitoring module obtains the power of each axial layer of the core after merging through numerical calculation, which serves as the real-time measurement value of the core axial power distribution; 5. The core monitoring module integrates the deviation between the real-time calculated value and the real-time measured value of the core axial power distribution to obtain the error distribution of the core axial power distribution; 6. The core monitoring module superimposes the real-time calculated value of the core axial power distribution with the error distribution of the core axial power distribution to obtain the corrected real-time calculated value of the core axial power distribution.

[0056] In this embodiment, as one possible approach, the core physical and thermal parameters also include the real-time calculated value of the core's DNBR; the core monitoring module calculates the real-time calculated value of the core's DNBR in real time using the DNBR calculation model based on the corrected real-time calculated values ​​of the core's radial power distribution and axial power distribution; the DNBR calculation model selects a four-equation homogeneous flow model with a slip ratio, and the calculation of the critical heat flux density adopts an empirical formula consistent with the core thermal design program; During DNBR calculation, based on the real-time calculated values ​​of the corrected radial power distribution and axial power distribution of the core, the key grid regions with higher power are refined, while the edge grid regions with lower power are coarsened to reduce the number of grids. Parallel calculation of multiple grid regions is also adopted to improve the calculation speed. The uncertainties of physical correction results and boundary conditions are taken into account.

[0057] In this embodiment, as one possible approach, the core prediction module predicts the reactivity management during the core power change process, specifically including: taking a core moment selected by the user from the core moment monitored in real time by the core monitoring module as the starting point for the core prediction calculation, calculating the reactivity management during the core power change process according to the future core state set by the user, and exporting the calculation results as a "reactivity management report" with one click.

[0058] In this embodiment, as one possible approach, the core prediction task also includes core load tracking, criticality prediction, minimum shutdown boron concentration, and lifetime prediction.

[0059] During the real-time monitoring of the core's physical and thermal parameters, the deviation distribution between the real-time calculated value and the real-time measured value of the core's axial power distribution can be obtained.

[0060] In this embodiment, as one possible approach, the core prediction module needs to modify the three-dimensional neutronics model using perturbation theory before performing the core prediction task. Specifically, this includes the following steps: 1. The core prediction module uses perturbation theory to generate a sensitivity matrix. ; 2. The core prediction module determines the additional absorption cross-section of each axial layer of the core by solving a system of linear equations: in, The absorption cross section added to each axial layer of the reactor core. The power of each axial layer of the reactor core; 3. The core prediction module uses the additional absorption cross sections of each axial layer of the core in the three-dimensional neutronics model to form a modified three-dimensional neutronics model.

[0061] In this embodiment, as one possible approach, the core prediction module generates a sensitivity matrix using perturbation theory, including the following steps: 1. The core prediction module adds a disturbance of an absorption section to each axial layer of the core. The power variation of each axial layer in the reactor core was calculated using a three-dimensional neutronics model. ; 2. The core prediction module calculates the impact of a unit disturbance in each axial layer of the core on the power distribution of each axial layer, forming a sensitivity matrix. in, Characterizing the axial layers of the reactor core The effect of a unit perturbation at a location on the power distribution of each axial layer.

[0062] See Figure 3 In this embodiment, as one possible approach, the core prediction module predicts the reactivity management during the core power transition process. Taking the core power increase process as an example, the specific steps include: 1. Given the power increase rate and target power, simulate the power increase process starting from state point A and the transient changes in iodine and xenon concentrations after reaching the target power; This simulation process does not consider the action of the control rods or perform a critical search, but it needs to simulate the dynamic behavior of iodine and xenon to obtain the changes in iodine and xenon concentrations at several power points; considering the numerical xenon oscillation problem, the power feedback effect can be appropriately increased during the simulation. 2. Perform static calculations at the power point in step 1: Under the condition of fixed iodine-xenon distribution, calculate the changes in reactivity and axial power deviation to obtain path AB; This process also does not perform a critical search; the iodine-xenon distribution is taken from the distribution at the initial state time, and the iodine-xenon concentration is taken from the calculated value in step 1. The path AB is generated under the hypothetical condition that the control rod does not move and the xenon distribution remains unchanged during the power increase process. It shows the change in axial power deviation under the hypothetical condition, while the change in reactivity indicates the reactivity that needs to be diluted under the hypothetical condition. 3. Simulate the power increase process along path AC; Ideally, power is increased along a path AC where the axial power offset remains constant. at this time, ,in, The axial power deviations at points A and C are respectively. These are the axial powers at points A and C, respectively, which effectively prevents xenon oscillations. In order to increase power along path AC, the axial power deviation between state point B and state point C needs to be compensated by raising the control rod. Therefore, based on state point B, a series of target control rod positions corresponding to axial power deviations are obtained through three-dimensional neutronics calculations. Conversely, the reactivity changes caused by the changes in control rod positions are also obtained. Thus, the reactivity that needs to be introduced for dilution during the power increase process along path AC is calculated. That is, the reactivity of path AB calculated in step 2 is subtracted from the reactivity that the control rod needs to introduce during path AC, and then the dilution rate during the power increase process is calculated. At this dilution rate from state point A to state point C, the introduced positive reactivity will be insufficient, and the core will become subcooled. Once the subcooling exceeds the control rod dead zone, it will drive the control rods upward. Assuming the three-dimensional neutronics model is reliable, in an actual reactor core, if this dilution rate is followed, the control rods will also be intermittently and slowly raised during the dilution process. 4. When the core state reaches state point C, xenon poisoning will first decrease and then increase; During the xenon poison reduction phase, the axial power offset will change in the negative direction, but the change will not be too large because the change in axial power offset is very small throughout the process, and boronizing is required to maintain core criticality. During the phase of increased xenon toxicity, the axial power offset will change in the positive direction, requiring dilution to maintain the criticality.

[0063] The above uses the power increase process as an example to introduce the reactivity management during the prediction of core power change by the core prediction module. The power decrease process is essentially the reverse process of the power increase process. During the power decrease process, the changes in reactivity, iodine-xenon concentration, and control rods are also opposite to those during the power increase process. The specific steps for reactivity management will not be elaborated here.

[0064] In this embodiment, as one possible approach, the online operation support system for the three-dimensional reactor core of a nuclear power plant based on digital twins also includes a user management module. The user management module adopts the OAuth2 protocol, which entrusts user authentication to a user authentication intermediate service and enables single sign-on. User authentication is integrated into the backend service, which adds user permission requirements to the corresponding resources and restricts the resource boundaries that users at each level can access.

[0065] In this embodiment, as one possible approach, the digital twin-based nuclear power plant three-dimensional reactor core online operation support system also includes a unit management module for setting unit operating condition parameter limits. The unit operating condition parameters include unit Class I operating condition parameter limits and unit Class II operating condition parameter limits. The unit Class I operating condition parameter limits include operating ladder diagram limits, loss-of-coolant accident (LOCA) limits, and DNBR limits. The unit Class II operating condition parameter limits include protection ladder diagram limits, DNBR limits, control rod insertion limits, boron-10 abundance limits, and soluble boron concentration limits.

[0066] In this embodiment, as one possible approach, the digital twin-based nuclear power plant 3D core online operation support system is equipped with a front-end human-machine interface. The front-end human-machine interface is developed using the Vue front-end framework in the Web domain and presented to the user in the form of a single-page application, including a function bar, a status bar, and a main monitoring page. The function bar provides entry points for the data acquisition module, physical test module, core monitoring module, core prediction module, unit management module, and user management module. The status bar is used to display the core physical and thermal parameters monitored in real time by the core monitoring module. The main monitoring page allows users to customize the core physical and thermal parameters that the core monitoring module needs to monitor in real time by dragging or clicking.

[0067] In this embodiment, as one possible approach, the online operation support system for the three-dimensional reactor core of a nuclear power plant based on digital twins is a multi-user, multi-task system involving concurrent computation of multiple tasks. To ensure computational stability and improve computational performance, the system adopts a distributed computing structure, including backend services and multiple computing nodes. The backend service runs on the master server to execute core monitoring tasks initiated by users or the system; the compute nodes run on the slave servers to execute core prediction tasks initiated by users; each compute node is connected to the master server through network file storage to achieve shared storage; a reverse proxy server runs on the master server, which sends packaged static resource files to the user's browser when the user accesses the site. The data acquisition module collects real-time measurement data of the reactor core at a frequency of one point per minute and stores it in the database, then starts the backend service. The backend service performs three-dimensional neutronics calculations and corrects the results at a frequency of one point per ten minutes, and presents the real-time monitored physical and thermal parameters of the reactor core to the front-end human-machine interface.

[0068] In this embodiment, as one possible approach, the backend service is written using the Django framework; A three-dimensional nodal method core calculation program, which is at the same level as the core design program, is used as the kernel for three-dimensional neutronics calculations.

[0069] The following example, taken during the Nth cycle of an operating pressurized water reactor unit, illustrates how the system of this invention enables online operation support of the reactor core.

[0070] During the startup phase, backend services and compute nodes are started on the master server and slave server, respectively.

[0071] After logging into the system, the administrator user enters the unit management module to check whether the unit operating condition parameter limits in the unit management module need to be modified. After confirming that there are no errors, the data acquisition module stores the real-time core measurement data transmitted from the PI system into the database, and the backend service begins to execute the core monitoring task.

[0072] After startup, the unit enters a stable operation phase. During this period, users can access the core's physical and thermal parameters at any time via a web browser through the user interface.

[0073] During unit operation, when peak shaving requirements are encountered, the reactor core needs to reduce its power first, maintain the low power level for a certain period of time, and then increase the power back to the original power level. The reactor core prediction module needs to correct the three-dimensional neutronics model and predict the reactive management of the reactor core power change process based on the corrected three-dimensional neutronics model.

[0074] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A digital-twin-based three-dimensional core operational support system for a nuclear power plant, characterized in that, The system comprises a data acquisition module, a physical test module, a core monitoring module, a core prediction module and a database; The data acquisition module is used for acquiring core real-time measurement data and storing the data into the database; The physical test module is used for acquiring core flux map periodic measurement data and storing the data into the database; The core monitoring module is used for initiating a core monitoring task by a user, executing the core monitoring task initiated by the user, initiating a core monitoring task by the system and executing the core monitoring task initiated by the system; The core prediction module is used for initiating a core prediction task by the user and executing the core prediction task initiated by the user. The core monitoring task comprises monitoring core physical thermal parameters in real time and correcting core physical thermal parameters calculated by a three-dimensional neutron model.

2. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 1, characterized in that, The core real-time measurement data comprises core first real-time measurement data; the core first real-time measurement data is time series data, comprising real-time measurement values of core relative power, control rod position, core upper power, core lower power, each out-of-core measurement channel power and each out-of-core measurement channel detector current; The data acquisition module acquires the core first real-time measurement data and stores the data into the database after verification, specifically comprising the following steps: The data acquisition module is communicatively connected with a nuclear power plant real-time database and acquires the core first real-time measurement data from the nuclear power plant real-time database; The data acquisition module judges whether the first real-time measurement data of the core meets condition one, and condition one is that the real-time measurement values of the core relative power and the control rod position are both 0; When the first real-time measurement data of the reactor core does not satisfy condition one, the data acquisition module marks the first real-time measurement data of the reactor core as class 0; when the first real-time measurement data of the reactor core satisfies condition one, the data acquisition module further judges whether the first real-time measurement data of the reactor core satisfies condition two, condition two being: the real-time measurement value of the relative power of the reactor core is greater than 3%, and the real-time measurement values of the upper power and the lower power of the reactor core are both greater than 0 0; When the core first real-time measurement data does not satisfy condition two, the data acquisition module marks the core first real-time measurement data as type 1; when the core first real-time measurement data satisfies condition two, the data acquisition module further judges whether the core first real-time measurement data satisfies condition three, which is that the deviation of each out-of-core measurement channel power real-time measurement value relative to the core power real-time measurement value is less than 1.5%, and the deviation of each out-of-core measurement channel detector current real-time measurement value relative to the total core detector current real-time measurement value is less than 5%; the core power real-time measurement value is equal to the arithmetic mean of each out-of-core measurement channel power real-time measurement value, and the total core detector current real-time measurement value is equal to the arithmetic mean of each out-of-core measurement channel detector current real-time measurement value; When the core first real-time measurement data does not satisfy condition three, the data acquisition module marks the core first real-time measurement data as type 2; when the core first real-time measurement data satisfies condition three, the data acquisition module marks the core first real-time measurement data as type 3; When the core first real-time measurement data is type 0 or type 1, the data acquisition module determines that the quality of the core first real-time measurement data is not reliable, and the core first real-time measurement data is not verified; When the core first real-time measurement data is type 2 or type 3, the data acquisition module determines that the quality of the core first real-time measurement data is reliable, the core first real-time measurement data is verified, and the verified core first real-time measurement data is stored into the database; Both type 2 and type 3 core first real-time measurement data are used for calculating a three-dimensional neutron model; type 3 core first real-time measurement data is used for correcting the three-dimensional neutron model and core physical thermal parameters calculated by the three-dimensional neutron model.

3. The digital-twin-based nuclear power plant three-dimensional core operational support system of claim 2, wherein, The real-time core measurement data also includes the second real-time core measurement data; the second real-time core measurement data is time series data, including real-time measurements of nuclear power unit power, boron concentration and core outlet temperature distribution; the data acquisition module collects the second real-time core measurement data and stores it in the database; The core physical and thermal parameters include real-time measured values ​​of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution, as well as real-time calculated values ​​of core axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, three-dimensional power distribution, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value. The core monitoring module obtains real-time measurements of nuclear power unit electrical power, core relative power, boron concentration, control rod position, power of each external measurement channel, and core outlet temperature distribution from the real-time core measurement data stored in the database. The core monitoring module establishes a three-dimensional neutronics model based on the real-time core measurement data stored in the database to calculate the real-time values ​​of the core's axial power offset, axial power deviation, hot spot factor, enthalpy rise factor, radial power distribution, axial power distribution, quadrant power tilt, operating ladder diagram, burnup distribution, linear power density, shutdown margin, moderator temperature coefficient, boron differential value, and xenon toxicity value.

4. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 3, characterized in that, The core physical and thermal parameters also include the real-time calculated values ​​of the core's DNBR; The core monitoring module calculates the real-time DNBR value of the core based on the corrected real-time radial power distribution and the real-time axial power distribution of the core using the DNBR calculation model. The DNBR calculation model is a four-equation homogeneous flow model with a slip ratio. The calculation of the critical heat flux density adopts the empirical formula consistent with the core thermal design program. During DNBR calculation, based on the real-time calculated values ​​of the corrected radial power distribution and axial power distribution of the core, the key grid regions are refined and the edge grid regions are coarsened. Multiple grid regions are calculated in parallel, taking into account the uncertainties of the physical correction results and boundary conditions.

5. The digital-twin-based nuclear power plant three-dimensional core operational support system of claim 1, wherein, The core monitoring module corrects the core physical and thermal parameters calculated by the three-dimensional neutronics model, including correcting the real-time calculated values ​​of radial power distribution between the current and next flux map measurement times, and correcting the real-time calculated values ​​of axial power distribution between the current and next flux map measurement times.

6. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 5, characterized in that, The core monitoring module corrects the real-time calculated value of the radial power distribution between the current and next flux map measurement times using periodic core flux map measurement data and real-time core measurement data. The specific steps include the following: (1) The core monitoring module calculates the correction factor of the radial power distribution flux map on each axial layer of the core and the real-time correction factor of the radial power distribution of the core respectively; (2) The core monitoring module corrects the real-time calculated values ​​of radial power distribution in each axial layer of the core between the current and next flux map measurement times based on the correction factor of the radial power distribution flux map on each axial layer of the core and the real-time correction factor of the radial power distribution in the core. The real-time calculated values ​​of radial power distribution in each axial layer of the reactor core between the current and next flux map measurement times constitute the real-time calculated values ​​of radial power distribution between the current and next flux map measurement times of the reactor core. The real-time calculated value of the radial power distribution in the axial layer between the current and next flux map measurements of the reactor core is corrected according to the following formula: wherein, is the real-time calculated value of the radial power distribution on the axial layer between the core current and next flux map measurement times, is the real-time calculated value of the radial power distribution on the axial layer between the core current and next flux map measurement times, is the radial power distribution flux map correction factor on the axial layer of the core, is the real-time correction factor for the radial power distribution of the core.

7. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 6, characterized in that, The core flux map periodic measurement data includes flux map measurement data from each core operation; the core monitoring module determines the radial power distribution flux map correction factor on each axial layer of the core according to the following steps: (1) The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement. The three-dimensional neutronics model calculation provides the real-time calculated value of the three-dimensional power distribution at the time of the current flux map measurement. (2) The real-time calculated value of the three-dimensional power distribution and the real-time measured value of the three-dimensional power distribution at the time of the current flux diagram measurement of the reactor core are normalized layer by layer along the axial direction to obtain the real-time calculated value of the radial power distribution and the real-time measured value of the radial power distribution on each axial layer at the time of the current flux diagram measurement of the reactor core. (3) Based on the relationship between the real-time calculated value of radial power distribution on each axial layer and the real-time measured value of radial power distribution at the time of this flux map measurement of the reactor core, determine the correction factor of the radial power distribution flux map on each axial layer of the reactor core; The relationship between the real-time calculated value and the real-time measured value of the radial power distribution on the axial layer at the time of this core flux diagram measurement is as follows: wherein, is the real-time measured value of the radial power distribution on the axial z layer at the time of the current flux map measurement of the reactor core, is the real-time calculated value of the radial power distribution on the axial z layer at the time of the current flux map measurement of the reactor core, is the axial layer of the reactor core.

8. The digital-twin-based nuclear power plant three-dimensional core operational support system of claim 6, wherein, The core monitoring module determines the real-time correction factor for the core radial power distribution according to the following steps: (1) The core monitoring module calculates the two-dimensional power distribution real-time calculation value of each fuel channel between the current and next flux map measurement time of the core and the two-dimensional power distribution real-time optimal prediction value ; (2) The core monitoring module calculates the real-time value of the two-dimensional power distribution of each fuel channel between the flux map measurement time of the current core and the next core and the real-time optimal estimate value of the two-dimensional power distribution According to the following formula, the core radial power distribution real-time correction factor is calculated: wherein is the real-time correction factor for the core radial power distribution.

9. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 8, characterized in that, The core monitoring module calculates the real-time calculation value of the two-dimensional power distribution of each fuel channel between the current and next flux map measurement time of the reactor core comprising the steps of: (1) The three-dimensional neutronics model calculation provides the real-time calculated value of the three-dimensional power distribution between the current and next flux map measurement times of the reactor core; (2) The core monitoring module integrates the real-time calculated value of the three-dimensional power distribution between the measurement time of the current and next flux maps along the axial direction of each fuel channel to obtain the two-dimensional power distribution real-time calculated value of each fuel channel between the measurement time of the current and next flux maps .

10. The digital-twin-based nuclear power plant three-dimensional core operational support system of claim 8, wherein, The core monitoring module calculates a real-time optimal prediction value of a two-dimensional power distribution of each fuel channel in the core including the following steps: (1), the core monitoring module obtains the real-time measurement data between the current and next flux map measurement time from the database, and the real-time measurement data between the current and next flux map measurement time provides the outlet temperature distribution real-time measurement value between the current and next flux map measurement time ; (2) The core monitoring module calculates the outlet temperature distribution real-time measurement value between the core current and next flux map measurement time according to the core radial power distribution sub-channel correction factor and the outlet temperature distribution real-time measurement value between the core current and next flux map measurement time , and calculates the outlet temperature distribution real-time calculation value between the core current and next flux map measurement time according to the following formula : (3) The core monitoring module calculates the real-time value of the outlet temperature distribution between the measurement time of the current and next core flux maps The water property calculation is performed to obtain the real-time value of the enthalpy rise distribution of each fuel channel between the measurement time of the current and next core flux maps ; (4) The core monitoring module calculates the enthalpy rise distribution of each fuel channel between the measurement time of the current and next flux map according to the single-channel thermal calculation model The corresponding two-dimensional power distribution real-time optimal prediction value .

11. The digital-twin-based nuclear power plant three-dimensional core operational support system of claim 10, wherein, The core monitoring module determines the core radial power distribution subchannel correction factors in accordance with the following steps : (1) The core monitoring module obtains the current flux map measurement data of the core from the database. The current flux map measurement data of the core provides the real-time measurement value of the three-dimensional power distribution at the time of the current flux map measurement. (2) The core monitoring module integrates the real-time three-dimensional power distribution measurement value of the core at the time of this flux diagram measurement along each fuel channel along the axis to obtain the real-time two-dimensional power distribution measurement value of each fuel channel at the time of this flux diagram measurement. (3) The core monitoring module calculates the real-time enthalpy rise distribution corresponding to the real-time measured value of the two-dimensional power distribution of each fuel channel at the time of the current flux diagram measurement of the core based on the single-channel thermal calculation model. (4) The core monitoring module performs water property calculations on the real-time calculated values ​​of the enthalpy rise distribution of each fuel channel at the time of the current flux diagram measurement of the core, and obtains the real-time calculated value of the outlet temperature distribution at the time of the current flux diagram measurement of the core. (5) The core monitoring module determines the core radial power distribution sub-channel correction factor based on the relationship between the real-time measured value of the outlet temperature distribution and the real-time calculated value of the outlet temperature distribution at the time of the current flux diagram measurement. The relationship between the real-time measured value and the real-time calculated value of the outlet temperature distribution at the moment of this core flux diagram measurement is as follows: wherein, is the outlet temperature distribution real-time measurement value at the time of the measurement of the core current flux map is the outlet temperature distribution real-time calculation value at the time of the measurement of the core current flux map, is the core radial power distribution subchannel correction factor.

12. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 5, wherein, The core monitoring module corrects the real-time calculated value of the axial power distribution between the current and next flux map measurement times, including the following steps: (1) The core monitoring module obtains real-time measurement data between the current and next flux map measurement times of the core and the current flux map measurement data of the core from the database; (2) The core monitoring module determines the [TS] matrix, [C] matrix and [I] matrix based on the real-time measurement data between the current and next flux map measurement times of the core and the current flux map measurement data of the core; The [TS] matrix represents the correspondence between the current of the six axial sections of the external power range detector calibrated during this flux diagram measurement of the reactor core and the power of the six axial sections inside the reactor core; the [C] matrix represents the influence of the control rod insertion of the reactor core on the current of the external detector; the [I] matrix represents the current of the external detector of the reactor core. (3) The core monitoring module obtains the power of the six axial layers of the core according to the [TS] matrix, the [C] matrix and the [I] matrix : (4) The core monitoring module obtains the power of each axial layer of the core after merging through numerical calculation, and uses it as the real-time measurement value of the core axial power distribution; (5) The core monitoring module integrates the deviation between the real-time calculated value and the real-time measured value of the core axial power distribution to obtain the error distribution of the core axial power distribution; (6) The core monitoring module superimposes the real-time calculated value of the core axial power distribution with the core axial power distribution error distribution to obtain the corrected real-time calculated value of the core axial power distribution.

13. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, Before performing the core prediction task, the core prediction module needs to correct the three-dimensional neutronics model using perturbation theory, which includes the following steps: (1) The core prediction module uses the perturbation theory to generate the sensitivity matrix ; (2) The core prediction module determines the additional absorption cross section of each axial layer of the core by solving a system of linear equations: wherein, the absorption cross section added for each axial layer of the core, the power of each axial layer of the core; (3) The core prediction module uses the additional absorption cross sections of each axial layer of the core in the three-dimensional neutronics model to form a modified three-dimensional neutronics model.

14. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, The core prediction module predicts reactivity management during core power variation, specifically including: using a core moment selected by the user from the core monitoring module in real time as the starting point for core prediction calculation, calculating reactivity management during core power variation according to the user-defined future core state, and exporting the calculation results as a "reactivity management report" with one click.

15. The digital-twin-based nuclear power plant three-dimensional core operational support system according to claim 14, characterized in that, The reactivity management during the core power increase prediction process by the core prediction module includes the following steps: (1) Under the given power increase rate and target power, simulate the power increase process starting from state point A and the transient changes in iodine and xenon concentrations after reaching the target power; This simulation process does not consider the action of the control rods or perform a critical search, but it needs to simulate the dynamic behavior of iodine and xenon to obtain the changes in iodine and xenon concentrations at several power points; considering the numerical xenon oscillation problem, the power feedback effect is appropriately increased during the simulation. (2) Perform static calculations at the power point in step 1: Under the condition of fixed iodine-xenon distribution, calculate the changes in reactivity and axial power deviation to obtain path AB; This process also does not perform a critical search; the iodine-xenon distribution is taken from the distribution at the initial state time, and the iodine-xenon concentration is taken from the calculated value in step 1. The path AB is generated under the hypothetical condition that the control rod does not move and the xenon distribution remains unchanged during the power increase process. It shows the change in axial power deviation under the hypothetical condition, while the change in reactivity indicates the reactivity that needs to be diluted under the hypothetical condition. (3) Simulate the power increase process along path AC; The path AC along which the axial power offset remains constant is the path of increasing power At this time, wherein, respectively the axial power offset of point A and point C, respectively the axial power of point A and point C; In order to increase power along path AC, the axial power deviation between state point B and state point C needs to be compensated by raising the control rod. Therefore, based on state point B, a series of target control rod positions corresponding to axial power deviations are obtained through three-dimensional neutronics calculations. Conversely, the reactivity changes caused by the changes in control rod positions are also obtained. Thus, the reactivity that needs to be introduced for dilution during the power increase process along path AC is calculated. That is, the reactivity of path AB calculated in step 2 is subtracted from the reactivity that the control rod needs to introduce during path AC, and then the dilution rate during the power increase process is calculated. At this dilution rate from state point A to state point C, the introduced positive reactivity will be insufficient, and the core will become subcooled. Once the subcooling exceeds the control rod dead zone, it will drive the control rods upward. Assuming the three-dimensional neutronics model is reliable, in an actual reactor core, if this dilution rate is followed, the control rods will also be intermittently and slowly raised during the dilution process. (4) When the core state reaches state point C, xenon poisoning will first decrease and then increase; During the xenon poison reduction phase, the axial power offset will change in the negative direction, requiring boronizing to maintain core criticality; During the phase of increased xenon toxicity, the axial power offset will change in the positive direction, requiring dilution to maintain the criticality.

16. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, It also includes a user management module; the user management module adopts the OAuth2 protocol, which hosts user authentication in the user authentication intermediate service and implements single sign-on; user authentication is integrated into the backend service, which adds user permission requirements to the corresponding resources and restricts the resource boundaries that users at each level can access.

17. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, It also includes a unit management module for setting unit operating condition parameter limits; the unit operating condition parameters include unit Class I operating condition parameter limits and unit Class II operating condition parameter limits; the unit Class I operating condition parameter limits include operating ladder diagram limits, water loss accident limits, and DNBR limits; the unit Class II operating condition parameter limits include protection ladder diagram limits, DNBR limits, control rod insertion limits, boron-10 abundance limits, and soluble boron concentration limits.

18. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, The system features a front-end human-computer interaction interface. Developed using the Vue framework, this interface is presented to users as a single-page application and includes a function bar, a status bar, and a main monitoring page. The function bar provides entry points to functional modules. The status bar displays the real-time core physical and thermal parameters monitored by the core monitoring module. The main monitoring page allows users to customize the core physical and thermal parameters that the core monitoring module needs to monitor in real-time by dragging or selecting.

19. The digital-twin-based nuclear power plant 3D core operational support system, as claimed in claim 1, wherein, The system adopts a distributed computing architecture, including backend services and multiple computing nodes; The backend service runs on the main server and is used to execute core monitoring tasks initiated by users or the system. The compute nodes run on the slave server and are used to execute user-initiated core prediction tasks; Each computing node is connected to the main server through network file storage to achieve shared storage; a reverse proxy server runs on the main server, and when a user accesses the site, the packaged static resource files are sent to the user's browser. The data acquisition module collects real-time measurement data of the reactor core at a frequency of one point per minute and stores it in the database, then starts the backend service. The backend service performs three-dimensional neutronics calculations and corrects the results at a frequency of one point per ten minutes, and presents the real-time monitored physical and thermal parameters of the reactor core to the front-end human-machine interface.

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