High-temperature reactor transition stage HF fuel ball layered statistical method and system

Abstract

The invention relates to the technical field of nuclear reactor engineering, and discloses a high-temperature reactor transition stage HF fuel sphere layering statistical method and system, and the method comprises the steps: calculating a theoretical HF fuel sphere layering statistical result based on an ideal model and an accumulated circulating fuel sphere number; acquiring real-time axial temperature distribution data and unloaded fuel burnup data of the reactor; a thermal correction factor is obtained by comparing the theoretical power peak value position with an actually measured power peak value position determined by temperature distribution; comparing the theoretical average burnup with the actually measured average burnup to obtain a burnup correction factor; performing weighted fusion on the thermal correction factor and the burn-up correction factor to form a comprehensive correction factor; and finally, correcting the accumulated circulating fuel sphere number by using the comprehensive correction factor. According to the method, the ideal model is dynamically calibrated by using real-time physical measurement data, so that the problem of calculation deviation caused by factors such as a particle flow effect is solved, and the accuracy and the real-time performance of distribution statistics of the HF fuel balls are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of nuclear reactor engineering technology, specifically to a statistical method and system for the layering of HF fuel spheres during the transition phase of a high-temperature reactor. Background Technology

[0002] High-temperature gas-cooled reactors, especially pebble bed type high-temperature gas-cooled reactors, employ spherical fuel elements and achieve continuous refueling through an online refueling and unloading system. During specific phases of operation, such as the fuel transition phase C from initial loading to equilibrium, the reactor is loaded with new fuel elements of a different enrichment level than the existing fuel elements, such as high-enrichment (HF) fuel elements. Accurately determining the axial distribution of these newly loaded HF fuel elements within the core is crucial for monitoring core power distribution, ensuring thermal safety margins, and optimizing reactor operation.

[0003] Currently, a calculation method based on an ideal piston flow model is commonly used to estimate the axial distribution of HF fuel pellets. This method simplifies the movement of the pellet bed within the reactor core as a holistic, uniform downward translational process, the distribution of which is driven solely by the total number of pellets in the cumulative cycle.

[0004] However, this ideal model deviates from the actual motion of fuel spheres within the pebble bed. In a physical pebble bed, influenced by gravity, friction, and interactions between spheres, the flow velocity of fuel spheres at different radial positions within the core is not uniform, and complex particle flow effects exist. This deviation causes the HF fuel sphere leading edge position calculated based on the ideal model to deviate from its actual physical position within the core. Since existing methods typically rely solely on the cumulative number of circulating spheres as a single theoretical input, lacking a mechanism for feedback calibration using real-time reactor physical measurements, this deviation cannot be corrected. This inaccuracy directly affects the prediction of the core power peak location, potentially leading to biased assessments of the reactor's safety status and impacting subsequent operational decisions. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a statistical method and system for the layering of HF fuel balls during the transition phase of a high-temperature reactor, which solves the problem that existing statistical methods for the distribution of HF fuel balls based on ideal models are inaccurate due to the failure to consider actual physical effects.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of this invention provides a statistical method for the layering of HF fuel pellets during the transition phase of a high-temperature reactor. This method calibrates the calculation results of an ideal model by introducing a dynamic correction mechanism based on real-time physical measurements. The specific scheme is as follows: First, the initial distribution calculation step is performed. This step is based on the preset core axial stratification model and the number of cumulative cycle fuel balls tracked. The theoretical HF fuel ball stratification statistics are calculated using an ideal model.

[0007] Subsequently, a physical data acquisition step is performed to obtain real-time axial temperature distribution data and unloaded fuel burnup data from the reactor system.

[0008] Then, the dynamic correction factor calculation step is performed, which is the core of this method. Based on the theoretical HF fuel sphere stratification statistics and the collected real-time physical data, a comprehensive correction factor is calculated. This comprehensive correction factor calculation integrates two different physical dimension deviation calibrations: on the one hand, a thermal correction factor is calculated based on spatial position deviation. The theoretical power peak position is determined by analyzing the theoretical HF fuel sphere stratification statistics. Simultaneously, the location of the measured power peak was identified by analyzing the real-time acquired axial temperature distribution data. Thermal correction factor That is, the ratio of their positions: ; On the other hand, a fuel consumption correction factor is calculated based on the average flow velocity deviation. This is the theoretical average fuel consumption of the unloaded fuel spheres. Compared with the measured average fuel consumption calculated based on real-time collected unloaded fuel consumption data Comparison. Fuel consumption correction factor. That is, the ratio of the two is defined as: ; Finally, the aforementioned thermal correction factor and fuel consumption correction factor are weighted by a preset coefficient. and Perform a weighted average to obtain the comprehensive correction factor. : ; Finally, the corrected distribution calculation and output steps are performed. The comprehensive correction factor calculated in the previous step is applied to the initial cumulative cycle fuel spherical count. This yields a calibrated effective cumulative number of cyclic balls. : ; Based on this effective cumulative number of circulating balls, the calculation is recalculated using an ideal model to obtain and output a corrected statistical result of HF fuel ball stratification that is more consistent with the actual physical state.

[0009] A second aspect of the present invention provides a high-temperature reactor transition stage HF fuel ball stratification statistical system, the system comprising: The model initialization and parameter definition module is used to configure the core axial layered model and related physical parameters; The initial distribution calculation module, which is connected to the model initialization and parameter definition module, is used to calculate the theoretical HF fuel ball stratification statistics based on the cumulative number of cycle fuel balls using an ideal model. The physical data acquisition module is used to acquire real-time axial temperature distribution data and unloaded fuel burnup data from the reactor system. The dynamic correction factor calculation module, which is connected to the initial distribution calculation module and the physical data acquisition module, is used to calculate a comprehensive correction factor based on the deviation between theoretical results and measured data. The corrected distribution calculation and output module, which is connected to the dynamic correction factor calculation module, is used to apply the comprehensive correction factor to correct the cumulative cycle fuel ball number and recalculate to obtain and output the final corrected HF fuel ball stratification statistics.

[0010] This invention provides a method and system for statistical analysis of HF fuel sphere stratification during the transition phase of a high-temperature reactor. It offers the following advantages: 1. This method not only uses an ideal model for basic calculations, but more importantly, it introduces dynamic corrections based on two different physical measurements. By using real-time temperature distribution data to calibrate the spatial position deviation of the HF fuel sphere leading edge, and using unloaded fuel burnup data to calibrate the average flow velocity deviation of the sphere bed, the final output distribution results can reflect the complex physical processes within the reactor core, thus significantly outperforming calculation methods that rely solely on ideal models.

[0011] 2. The input data relied upon by this method, such as the cumulative number of circulating pellets, axial temperature, and burnup of discharged pellets, can all be obtained in real time through the reactor's existing instrumentation and control system and refueling system. The calculation logic mainly involves algebraic operations and does not involve complex iterative solutions, resulting in a low computational load. It can continuously output corrected distribution results at a frequency of seconds or minutes, providing reactor operators with immediate decision-making support.

[0012] 3. This method combines a weighted adjustment factor that reflects spatial location and average flow velocity with a fuel consumption adjustment factor to form a comprehensive adjustment factor. This design integrates two independent physical measurement information, avoiding the impact of large errors from a single measurement source on the final result, thereby improving the robustness of the entire statistical method. Attached Figure Description

[0013] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a system architecture diagram of the present invention.

[0014] The module consists of: 100, Model Initialization and Parameter Definition Module; 200, Initial Distribution Calculation Module; 300, Physical Data Acquisition Module; 400, Dynamic Correction Factor Calculation Module; and 500, Corrected Distribution Calculation and Output Module. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Example: See attached document Figure 1 This invention provides a method for statistical analysis of HF fuel sphere stratification during the transition phase of a high-temperature reactor, which may include the following steps: S1, Model Initialization: Establish a discretized mathematical model describing the core ball bed, and set basic calculation parameters including the total number of balls in the core and the number of axial layers.

[0017] S2, Theoretical Distribution Calculation: Based on the ideal piston flow model, the theoretical distribution of highly enriched fuel balls in each axial height layer of the reactor core is calculated according to the cumulative number of circulating fuel balls in the reactor.

[0018] S3, Physical Data Acquisition: Parallel to S2, it acquires physical measurement data in real time through the reactor instrumentation and control system, which reflects the actual distribution of fuel spheres. This data includes axial temperature distribution data and burnup measurement data of unloaded fuel spheres.

[0019] S4, Correction Factor Calculation: Compare the theoretical distribution prediction results obtained in S2 with the measured physical data collected in S3, and calculate the comprehensive correction factor used to calibrate the deviation of the theoretical model.

[0020] S5, Corrected Distribution Calculation: Apply the comprehensive correction factor calculated in S4 to calibrate the calculation baseline of the theoretical model, and recalculate the dynamically corrected statistical results of HF fuel sphere stratification, and finally output the results.

[0021] See attached document Figure 2 This invention provides a statistical system for the stratification of HF fuel pellets during the transition phase of a high-temperature reactor. The system may include: The model initialization and parameter definition module 100 is used to set basic parameters such as the total number of core pellets and the number of axial layers, and to establish a spatial discretization model of the core pellet bed.

[0022] The initial distribution calculation module 200 is used to connect to the reactor operation database, obtain the cumulative number of circulating fuel balls, and calculate the theoretical distribution of HF fuel balls in each axial layer based on the ideal piston flow model.

[0023] The physical data acquisition module 300 is used to acquire real-time axial temperature distribution data and burnup measurement data of unloaded fuel balls from the reactor instrumentation and control system.

[0024] The dynamic correction factor calculation module 400 receives the theoretical prediction results from the initial distribution calculation module 200 and the measured data from the physical data acquisition module 300. It calculates the thermal correction factor and the fuel consumption correction factor by comparing the differences between the two and integrates them into a comprehensive correction factor.

[0025] The corrected distribution calculation and output module 500 receives the comprehensive correction factor, uses it to calibrate the cumulative cycle fuel ball number, recalculates the HF fuel ball distribution based on the calibrated data, and finally outputs the corrected stratified statistical results.

[0026] In model initialization and parameter definition S1, a unified mathematical foundation is established for subsequent calculations, and the core parameters need to be defined. These parameters are the fundamental basis for the calculations performed by the method of this invention.

[0027] Defines the total number of spheres in the reactor core. This parameter represents the total design quantity of all spherical elements within the reactor core. This is a known design constant for a specific reactor, and its mathematical notation is: ; in, This represents the total number of spherical elements within the reactor core.

[0028] Define the axial layer number. This parameter is used to discretize the physically continuous core into several equivalent computational layers in the vertical direction to achieve layered statistics. This parameter is a preset integer, and its value determines the spatial resolution of the statistical model. Its mathematical notation is: ; in, The number of layers divided along the core axis. .

[0029] Define the number of spheres per layer. This parameter is the theoretical number of spheres contained in each discrete layer, calculated based on the uniform density assumption, using the total number of spheres in the core and the number of axial layers. The calculation formula is: ; in, The number of spherical elements contained in a single axial layer.

[0030] Define the HF fuel pellet addition ratio. This parameter characterizes the proportion of newly added high-enrichment (HF) fuel pellets relative to the total number of pellets in a cycle batch during the refueling operation in the fuel transition phase. This ratio is determined by the reactor's refueling scheme. Its mathematical notation is: ; in, This refers to the proportion of newly added HF fuel balls. Taking the HTR-PM demonstration project as an example, its Stage C refueling strategy involves replacing one HF ball with every 15 balls in a cycle. =1 / 15.

[0031] The model initialization and parameter definition S1 also includes spatial discretization of the core model to construct a mathematical representation that can be used for computation.

[0032] Establish a one-dimensional axial coordinate system. Simplify the three-dimensional physical space of the reactor core into a one-dimensional vertical coordinate system for analysis. The origin of this coordinate system can be set at the top of the reactor core, with its direction perpendicularly downwards along the direction of gravity.

[0033] The coordinate system is layered. This is based on the defined number of axial layers. The entire effective height of the reactor core is divided into There are three equivalent, non-overlapping computational layers. Each layer is treated as a computational unit with a uniform internal state in the model.

[0034] Create indexes and construct data structures for each level. Assign a unique integer index to each computational level. The index The value range is from 1 to Among them, the index =1 corresponds to the topmost level of the stack core, index = This corresponds to the bottommost layer of the reactor core. In computer implementation, this index structure corresponds to a one-dimensional data array or vector. Each element of this data structure stores the computational parameters for its corresponding physical layer, such as the number of HF fuel pellets. Through this step, the continuous physical pellet bed is transformed into a discrete data model that can be processed by a computer program.

[0035] In the initial distribution calculation S2 based on the ideal model, it is necessary to obtain the reactor's operating status data as the calculation input.

[0036] Tracking the cumulative number of refueling spheres is crucial, and this step involves tracking a key variable: the total number of spheres recycled by the reactor refueling system from the start of fuel transition phase C to the current moment. This variable can be obtained through a data interface established between the system of this invention and the reactor instrumentation and control system or an operational history database. Its mathematical notation is as follows: ; in, This represents the cumulative number of cycle fuel balls.

[0037] The number of circulating balls is accumulated. The counting function of the circulating balls in the loading and unloading system is well-known in the art and will not be described further here. This method periodically reads the count or receives its incremental data and accumulates it internally. The calculation can be expressed as: ; in, This refers to the increment in the number of circulating balls recorded and transmitted by the loading and unloading system within each preset time period. This cumulative value forms the basis for driving the state evolution of the ideal model.

[0038] In the initial distribution calculation S2 based on the ideal model, the theoretical distribution of HF fuel pellets at each axial level is calculated using an ideal piston flow model based on the tracked operational data. The physical basis of this model is that the core pellet bed moves smoothly from top to bottom as a whole during the cycle.

[0039] Calculate the theoretical frontier position. Based on the cumulative cycle fuel spherical count. and the number of single-layer spheres The number of layers that have theoretically been completely filled and pushed downwards by the newly added HF fuel balls is calculated. The formula is: ; in, This represents the theoretically fully filled number of layers. This is the floor function. This parameter defines the macroscopic position of the HF fuel ball leading edge in the reactor core.

[0040] The theoretical HF sphere count for each layer is calculated by region, based on the position of the theoretical frontier. The number of HF spheres in all layers of the reactor core is calculated in separate regions.

[0041] For the upper layers that have been completely swept by the leading edge of the HF fuel ball, i.e., the layer index The theoretical HF ball number for the region is calculated using the following formula: ; For the leading layer that is currently being filled, i.e., the layer index The theoretical number of HF balls in the region depends on the number of balls that have been cycled through in the current layer. This number uses... right Calculate the remainder: ; For the lower layers that the HF fuel ball front has not yet reached, i.e., the layer index In the region where the theoretical HF sphere number is zero: ; Generate theoretical distribution data. Calculate the theoretical HF sphere numbers for each layer. (in From 1 to The data is filled into the corresponding data structure to form a complete one-dimensional array. This array represents the theoretical distribution of HF fuel balls along the entire core axis and serves as the baseline input for subsequent correction calculations.

[0042] In the real-time physical measurement data acquisition S3, it is necessary to obtain the axial temperature distribution data of the reactor core, which provides a physical basis for subsequent thermal correction calculations.

[0043] Establish data communication. A communication connection is established between this system and the reactor instrumentation and control system or data acquisition system via a data interface to obtain real-time measurements from the temperature sensor.

[0044] Acquire raw temperature data. The placement of temperature sensors (such as thermocouples) at different axial heights in the reactor core or reflector and the reading of their measurements via the instrumentation and control system are well-known techniques in the field and will not be elaborated upon here. This step reads the measurement values ​​from these temperature sensors at preset locations from the instrumentation and control system.

[0045] Data mapping and processing maps the acquired temperature measurements, located at discrete physical locations, to the axial calculation levels defined in S1. For any given calculation level... The corresponding temperature value This can be calculated by averaging the sensor measurements from all physical locations falling within this layer's range. The calculation can be expressed as: ; in, For computational hierarchy Representative temperature value, All physical locations are at the computational level. A collection of temperature sensors within a certain range. It is the number of sensors in the set. It is a set The Middle The raw measurement values ​​of each sensor. For computational levels without any temperature sensors, their representative temperature values ​​can be obtained by linear interpolation or extrapolation of the temperatures of their adjacent upper and lower levels that have valid temperature values, in order to ensure the integrity of the temperature distribution data.

[0046] Temperature distribution data is generated. Through processing, a one-dimensional data array is ultimately produced. The array index is the layer number. Its elemental values ​​are representative temperature values ​​for the corresponding levels. This array fully describes the measured temperature distribution along the core axis and is passed to the dynamic correction factor calculation S4.

[0047] In the real-time physical measurement data acquisition S3, it is also necessary to acquire burnup measurement data of the fuel spheres being unloaded from the bottom of the reactor core. This data is used to characterize the actual average flow velocity of the fuel spheres within the reactor core, providing physical input for subsequent burnup correction calculations.

[0048] Establish data communication with the loading and unloading system. This method establishes a communication connection between the system and the control section of the high-temperature stack loading and unloading system, particularly the data server of the burnup measurement device.

[0049] Burnup measurements are collected. After each spherical element is unloaded from the bottom of the reactor core, the high-temperature reactor's refueling system typically measures its burnup using a burnup measurement device. This is well-known technology in the field and will not be elaborated upon here. This step uses an established data interface to obtain the burnup measurement values ​​for each unloaded low-enrichment fuel sphere. During the fuel transition phase C, only the burnup data of the LF fuel spheres are considered, as their burnup depth reflects their long-term residence history within the reactor core.

[0050] Storing and updating the fuel consumption dataset. Each acquired fuel consumption measurement is stored in a pre-defined dataset. This dataset stores fuel consumption measurements from all LF fuel balls unloaded within a recent period. As new measurements are generated, this dataset is dynamically updated to maintain a statistically representative pool of measured fuel consumption samples. This dataset can be represented as: ,in, This represents the set of collected fuel consumption measurements from the unloaded LF fuel balls. This dataset will be passed to the dynamic correction factor calculation S4 for subsequent analysis and calculations.

[0051] A core component of the dynamic correction factor calculation S4 is the calculation of the thermal correction factor. This factor, based on the measured temperature distribution in the reactor core, is used to calibrate the biases in the ideal model's prediction of the spatial position of the HF fuel ball leading edge.

[0052] Determine the theoretical power peak location. In the ideal model, the region with the highest HF fuel sphere concentration or the fastest growth is the theoretical power peak region. According to the calculation results of S2, this location corresponds to the frontier layer that is being filled. Its layer index is determined by the following formula: ; in, This is the layer index where the theoretical power peak value is located.

[0053] Identify the measured power peak location. The physical basis for this step is that HF ​​fuel spheres have a higher enrichment degree, and their aggregation region corresponds to the power peak region of the reactor core, which in turn manifests as a temperature peak region. Therefore, by finding the highest point in the measured temperature distribution, the actual physical aggregation location of the HF fuel spheres can be determined. The layer index of this location is obtained by finding the maximum value in the temperature distribution data collected in S3: ; in, This is the layer index where the measured temperature peak is located. The function returns the index at which the expression within the parentheses is maximized. .

[0054] Calculate the thermal correction factor. The thermal correction factor is calculated by comparing the theoretical peak position with the measured peak position. This factor is defined as the ratio of the measured peak position index to the theoretical peak position index: ; in, This is the thermal correction factor. This factor quantifies the degree of deviation of the macroscopic movement position of the fuel spheres within the reactor core from the ideal model, and serves as one of the inputs for subsequent comprehensive correction calculations.

[0055] Another core part of the dynamic correction factor calculation S4 is the calculation of the fuel consumption correction factor. This factor is used to calibrate the deviation caused by the inconsistency between the actual average flow velocity of the fuel bed and the ideal model by comparing the theoretical fuel consumption of the unloaded fuel balls with the measured fuel consumption.

[0056] Determine the theoretical average burnup. For a low-enrichment fuel sphere undergoing a complete residence cycle within the reactor core, the theoretical average burnup from loading to unloading is a known physical design parameter. This parameter can be predetermined by reactor physical design calculations. Its mathematical notation is: ; in, This represents the theoretical average fuel consumption value for unloading LF fuel balls.

[0057] Calculate the measured average fuel consumption. This involves analyzing the set of fuel consumption measurements of the unloaded LF fuel balls collected and stored in S3. A statistical average is calculated to obtain a statistically representative measured fuel consumption value. The calculation formula is as follows: ; in, This is the measured average fuel consumption value. This represents the number of samples in the set of fuel consumption measurements.

[0058] Calculate the burnup correction factor. This factor is defined as the ratio of theoretical average burnup to measured average burnup, used to quantify the deviation of the actual average flow velocity of fuel pellets within the reactor core from the ideal model. The calculation formula is as follows: ; in, This is the burnup correction factor. When this factor is greater than 1, it indicates that the measured burnup of the unloaded spheres is too low, corresponding to the actual average flow velocity of the fuel spheres in the reactor core being faster than the ideal model; when this factor is less than 1, it indicates that the measured burnup is too high, corresponding to the actual average flow velocity being slower than the ideal model.

[0059] In the dynamic correction factor calculation S4, in order to obtain a unified calibration basis that can simultaneously reflect spatial position deviation and average flow velocity deviation, the thermal correction factor and fuel consumption correction factor calculated above need to be fused to generate a comprehensive correction factor.

[0060] Calculate the comprehensive correction factor. This step will represent the thermal correction factor for macroscopic location information. and the fuel consumption correction factor representing average flow rate information The fusion is performed using a weighted average method. The calculation formula is as follows: ; in, This is the final comprehensive correction factor. and These are the weighting coefficients corresponding to the thermal correction factor and the fuel consumption correction factor, respectively.

[0061] Define the weighting coefficients. and These are preset parameters, and their sum is 1 ( + =1), and both are non-negative. The values ​​of these two coefficients are allocated based on the contribution and reliability of different physical measurements in characterizing the actual distribution of HF fuel spheres. For example, when the reactor operating conditions are stable and the signal-to-noise ratio of the temperature measurement signal is high, the thermal correction factor can be given a higher weight, such as setting... =0.7, =0.3. The comprehensive correction factor obtained through this step. This will be passed to subsequent steps for calibrating the theoretical model.

[0062] In applying the correction and outputting the final distribution result S5, the input benchmark driving the ideal model first needs to be calibrated.

[0063] Calculate the effective cumulative number of cyclic balls. This step applies the comprehensive correction factor calculated by S4. The number of original cumulative cycle fuel balls obtained The results are then corrected to obtain an effective cumulative number of cyclic balls that reflects the actual physical process. The calculation formula is as follows: ; in: To effectively accumulate the number of balls in a cycle; This represents the original cumulative number of cycle fuel balls; This is a comprehensive correction factor.

[0064] The essence of this calculation is to convert the comprehensive deviation of the physical ball-bed motion relative to the ideal model, quantified through measured data, into an equivalent adjustment of the input parameters of the ideal model. The resulting effective cumulative number of balls in circulation... This will serve as the sole input benchmark for the next step of recalculating the HF fuel sphere distribution, replacing the original... .

[0065] In the application correction and output of the final distribution result S5, the axial distribution of HF fuel balls in the core is recalculated using the effective cumulative number of circulating balls calculated in the previous step.

[0066] Calculate the corrected leading edge position. Then, calculate the effective cumulative number of balls. As input to the ideal piston flow model, the number of complete layers that have been fully filled and pushed downwards by the HF fuel balls is recalculated. The calculation formula is as follows: ; in, The corrected number of layers is the number of layers fully filled at the leading edge of the HF fuel ball.

[0067] The number of HF spheres in each layer is recalculated by dividing the region. However, its input is changed from the original... Replace with the corrected version .

[0068] For the upper layers that have been fully scanned by the corrected frontier, i.e., the layer index The corrected HF sphere count for the region is: ; For the corrected leading edge level that is currently being filled, i.e., the layer index The corrected HF sphere count for the region is: ; For the lower levels that the corrected frontier has not yet reached, i.e., the layer index In the region where the corrected HF sphere count is zero: 0 in, In the first The corrected number of HF fuel balls in the layer.

[0069] Generate and output the final distribution results. This includes calculating the distribution across all levels. As a result, the data is integrated into a one-dimensional data array. This array represents the final output of the method of this invention, which is a dynamically calibrated statistical result of the HF fuel sphere layering based on multi-physical dimension information. This result can be output to a human-computer interface and displayed as a numerical list or graphical curve to provide decision support for reactor operators; it can also be stored in a historical database for subsequent tracing and analysis.

Claims

1. A statistical method for the stratification of HF fuel pellets during the transition phase of a high-temperature reactor, characterized in that, Includes the following steps: S1: Based on the preset core axial stratification model and the tracked cumulative number of cycle fuel balls, the theoretical HF fuel ball stratification statistics are calculated using an ideal model; S2: Obtain real-time axial temperature distribution data and unloaded fuel burnup data from the reactor system; S3: Based on the theoretical HF fuel ball stratification statistical results, the axial temperature distribution data, and the unloaded fuel consumption data, a comprehensive correction factor is calculated; S4: Apply the comprehensive correction factor to correct the cumulative number of cycle fuel balls to obtain the effective cumulative number of cycle fuel balls; Based on the effective cumulative number of cycle fuel balls, the results are recalculated to obtain and output the corrected statistical results of HF fuel ball stratification.

2. The method according to claim 1, characterized in that, The dynamic correction factor calculation steps specifically include: Based on the theoretical HF fuel ball stratification statistics and the axial temperature distribution data, the thermal correction factor was calculated. Based on the unloaded fuel consumption data, the fuel consumption correction factor is calculated. The comprehensive correction factor is obtained by weighting the thermal correction factor and the fuel consumption correction factor.

3. The method according to claim 2, characterized in that, The calculation of the thermal correction factor specifically includes: The theoretical power peak location is determined based on the statistical results of the theoretical HF fuel ball stratification. The location of the measured power peak was identified based on the axial temperature distribution data. The ratio of the measured power peak position to the theoretical power peak position is used as the thermal correction factor.

4. The method according to claim 3, characterized in that, Before identifying the location of the measured power peak, the method further includes: The axial temperature distribution data is then smoothed and filtered.

5. The method according to claim 2, characterized in that, The calculation of the fuel consumption correction factor specifically includes: Determine the theoretical average fuel consumption after unloading the fuel spheres; The measured average fuel consumption was calculated based on the unloaded fuel consumption data. The ratio of the theoretical average fuel consumption to the measured average fuel consumption is used as the fuel consumption correction factor.

6. The method according to claim 2, characterized in that, The weighted average uses preset weighting coefficients, and the sum of the weighting coefficients is 1.

7. The method according to claim 1, characterized in that, The initial distribution calculation steps specifically include: The number of layers that are theoretically fully filled is calculated based on the cumulative number of cycle fuel balls. Based on the number of fully filled layers, the theoretical HF fuel spheres are calculated by region for the upper layers that have been swept by the front edge, the front edge layers that are in the filling process, and the lower layers that have not yet been reached by the front edge, thus forming the theoretical HF fuel sphere layering statistics.

8. The method according to claim 1, characterized in that, The process of recalculating based on the effective cumulative number of cycle fuel balls in the corrected distribution calculation and output step specifically includes: The corrected number of fully filled layers is calculated based on the effective cumulative number of cycle fuel balls. Based on the corrected number of fully filled layers, the number of HF fuel balls in the upper layers that have been swept by the front edge, the front edge layers that are in the filling process, and the lower layers that have not yet been reached by the front edge are calculated by region to form the corrected statistical results of HF fuel ball layering.

9. The method according to claim 1, characterized in that, In the physical data acquisition step, when there is no temperature sensor in a certain calculation layer of the axial layered model, the temperature value of that calculation layer is obtained by interpolation or extrapolation through the temperature data of its adjacent layers.

10. A high-temperature reactor transition stage HF fuel spherical stratification statistical system, the system according to any one of claims 1-9, characterized in that, include: The model initialization and parameter definition module is used to configure the core axial layered model and related physical parameters; The initial distribution calculation module is used to calculate the theoretical HF fuel ball stratification statistics based on the cumulative number of cycle fuel balls using an ideal model; The physical data acquisition module is used to acquire real-time axial temperature distribution data and unloaded fuel burnup data from the reactor system. The dynamic correction factor calculation module is used to calculate a comprehensive correction factor based on the deviation between theoretical results and measured data. The corrected distribution calculation and output module is used to apply the comprehensive correction factor to correct the cumulative number of cycle fuel balls and recalculate to obtain and output the final corrected HF fuel ball stratification statistics.

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