Method for monitoring and analyzing reactor thermal-hydraulic simulation output data in real time under multiple conditions

Abstract

This invention discloses a method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data, comprising: establishing a correspondence between simulation output files and components to be monitored; parsing the variable names in the output file header according to a variable name rule base, identifying component information and physical parameters, and establishing a data mapping relationship; reading output data incrementally by time step during simulation operation, and updating parameter tables, key indicators, and trend curves in real time; loading historical operating condition data, comparing trends of the same components and physical parameters under multiple operating conditions, and supporting trend data export. This invention can reduce the manual variable lookup and plotting analysis process, improve the efficiency of reading, monitoring, and multi-condition analysis of reactor thermal-hydraulic simulation results, and is applicable to the processing of engineering calculation results of reactor thermal-hydraulic simulation.

Description

Technical Field

[0001] This invention belongs to the technical field of nuclear reactor thermal-hydraulic simulation data processing and engineering monitoring software, specifically relating to a method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data. Background Technology

[0002] Reactor thermal-hydraulic simulation programs are important tools in reactor system design, operation analysis, accident analysis, and engineering optimization. Taking ERAC and other reactor thermal-hydraulic simulation programs as examples, their calculation results are usually saved in the form of multiple text output files. Different output files correspond to different components or systems such as the reactor core, piping, pumps, heat exchangers, residual heat removal systems, air cooling systems, inter-cell flow, chambers, and hot pools.

[0003] In traditional results analysis, engineers typically need to manually open the output files, locate the corresponding variable names and data columns, and then organize and analyze them using spreadsheet or graphing software. Because reactor thermal-hydraulic simulation output files are numerous, have complex variable names, and contain large amounts of data, and because the variable organization formats differ between output files from different components, manual processing is prone to problems such as variable correspondence errors, unit conversion errors, and low efficiency in comparing operating conditions.

[0004] Meanwhile, during simulation program operation, traditional methods mainly rely on console output or final result files to determine the calculation status, making it difficult to observe in a timely and intuitive manner the changes of key parameters such as inlet and outlet pressure, temperature, mass flow rate, pressure drop, power, liquid level, and reactivity of critical components over time. When the simulation time is long or the output data volume is large, the time required for manual reading, processing, and plotting further increases, affecting the efficiency of engineering analysis.

[0005] Furthermore, comparative analysis between different historical operating conditions typically requires manually importing output files from multiple operating conditions, manually filtering for identical components and physical quantities, and then plotting and comparing curves. This process is cumbersome and makes it difficult to ensure consistency in variable sources, display units, and curve definitions across different operating conditions.

[0006] In summary, existing methods for processing reactor thermal-hydraulic simulation results suffer from problems such as difficulty in finding output variables, insufficient real-time monitoring capabilities, low efficiency in comparing multiple operating conditions, and cumbersome data export and secondary plotting processes. These issues make it difficult to meet the needs for fast, accurate, and traceable data analysis in reactor thermal-hydraulic engineering calculations. Summary of the Invention

[0007] To address the problems existing in the prior art, the present invention aims to provide a method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data. This method can automatically establish a mapping relationship between components and physical parameters based on the variable names in the output file header, read new time step data in real time during simulation operation, and perform unified comparative analysis of multiple historical conditions, thereby improving the efficiency of reading, monitoring, comparing, and exporting reactor thermal-hydraulic simulation results.

[0008] To achieve the above objectives, the present invention adopts the following technical solution: A method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data includes the following steps: Step 1: Establish the correspondence between the output file of the reactor thermal-hydraulic simulation program and the components to be monitored. The components to be monitored include one or more calculation components in the reactor thermal-hydraulic simulation model. The calculation components include core components, flow components, power components, heat exchange components, and safety system components. Step 2: Read the header variable names of the output files corresponding to each monitored component, parse the header variable names according to the pre-established variable name rule base, identify the time column, component number, system number, and physical parameter column, and establish the mapping relationship between component name, variable column name, physical parameter name, and display unit; let the first step be... c The set of header variable names in the class component output file for: (1) in, c Indicates the component type. Vm This indicates the first [number]th [item] in the output file of this component. m Variable names; establish variable mapping relationships by grouping according to physical parameter names, variable names, display units, and trend curves: (2) in, M k This represents the variable mapping relationship for the k-th physical parameter. P k Indicates the first k A physical parameter name, V k This indicates the output file variable name corresponding to this physical parameter. U k Indicates the unit of display. G k This indicates the grouping of the trend curve to which the physical parameter belongs; This method does not rely on the variable order or fixed column positions in the output file, enabling it to adapt to different component output files and variable order adjustments. It avoids parameter misalignment or data misreading caused by column position changes, improving the accuracy, adaptability, and reliability of data identification. The header variable names are parsed using a pre-established variable name rule base. Based on the component identifier, parameter identifier, and unit identifier fields in the variable names, the corresponding data columns are determined, and a correspondence is established between variable names, physical parameter names, and display units.

[0009] Step 3: Generate parameter tables, key indicators and trend curve configurations for each component to be monitored based on the mapping relationship established in Step 2. The parameter tables are used to display the numerical results of each component at the current time step, the key indicators are used to display the main physical quantities of the currently selected component, and the trend curves are used to display the historical data of the corresponding physical quantities changing over time. Each type of monitored component has an independent parameter table, key indicators, and trend curve configuration. When the user selects different components, the parameter table fields, key indicator fields, and trend curve fields of the corresponding component are automatically switched. This ensures that the displayed content matches the parameter characteristics of the currently selected component, avoiding irrelevant parameter mixing and manual repetitive configuration, and improving the switching efficiency of monitoring interfaces for different components, the relevance of information display, and the accuracy of operational status interpretation.

[0010] Step 4: During the reactor thermal-hydraulic simulation program, the output files corresponding to each monitored component are polled and read in a round-robin fashion. New output data is acquired at each time step and appended to the historical data cache. The data read by component c at the nth time step... Represented as: (3) in, t n Indicates the first n Each time step x m ( t n ) indicates the first (input) in the output file. m The values ​​of each variable at this time step; The polling read is an incremental read method, which only reads the newly added time step data in the output file and does not change the original data in the reactor thermal-hydraulic simulation program output file. This avoids repeated reading of historical data, reduces data reading volume and system resource consumption, and improves real-time monitoring efficiency; at the same time, it ensures the integrity of simulation output data and realizes non-intrusive monitoring of the simulation process.

[0011] Step 5: Based on the parameter table, key indicators, and trend curve configuration generated in Step 3, and the historical data cache obtained in Step 4, update the parameter table, key indicators, and trend curve of the current component in real time. When the user selects different components, the system automatically switches the parameter table, key indicators, and trend curve according to the mapping relationship corresponding to the current component. For temperature parameters, the system supports switching between Kelvin and Celsius temperature displays. When the user selects Celsius temperature display, the displayed temperature value is obtained by the following formula: (4) in, T k The output file contains the raw Kelvin temperature values. T c The temperature value displayed on the interface is in Celsius. The temperature unit display switching process only applies to the display layer and does not change the original temperature data in the output file or the original temperature data in the historical data cache.

[0012] Step 6: Load one or more historical operating condition output directories. Based on component type identifiers, component object identifiers, and variable mapping relationships, perform consistency matching on the same physical parameter across multiple historical operating conditions, and extract the corresponding time series data for trend comparison analysis. N The set of comparative data for the same components and physical parameters under different historical operating conditions is represented as follows: (5) in, p Indicates the selected physical parameters, Y N ,p ( t ) indicates the first N Sequence data of how the physical parameter changes over time under a specific working condition; The historical operating condition output directory is only referenced as a data reading source; it is not copied, modified, or overwritten. This reduces the storage space occupied by copying historical data, ensures the integrity and traceability of the original historical operating condition data, and avoids distortion of analysis results due to data modification or overwriting.

[0013] Step 7: Based on the user's selection, export the current trend curve data or the trend curve data of all current components, generate a data file for subsequent plotting and engineering analysis. The exported data file includes physical parameter names, original variable names, units, and time series data. The exported trend data matrix is ​​represented as follows: (6) Using the method of this invention, the correspondence between output data and component physical parameters can be automatically established based on the variable names in the header of the simulation output file, avoiding data reading errors caused by fixed column numbers or manual variable lookup; the change process of key component parameters can be displayed in real time during simulation, improving the monitoring capability of the calculation process; multiple historical working conditions can be loaded uniformly and the trends of the same components and the same physical quantities can be compared, improving the efficiency of multi-working-condition analysis; and data files containing physical quantity names, original variable names, units, and time series data can be exported, facilitating subsequent plotting and engineering analysis.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention establishes a data mapping relationship based on the variable names in the output file header, without relying on fixed row numbers or fixed column numbers, and can adapt to changes in input card adjustment, component numbering, and output file variable order. 2. This invention allows for independent configuration of parameter tables, key indicators, and trend curves for different components, enabling the display of key thermal-hydraulic parameters for components such as the reactor core, pipelines, pumps, heat exchangers, waste heat removal systems, air cooling systems, inter-cell flow, chambers, and hot pools. 3. During the simulation program's operation, this invention can read the output file incrementally according to time steps, enabling real-time updates of parameter tables, key indicators, and trend curves, thereby improving the observability of the simulation calculation process; 4. This invention also supports switching between Kelvin and Celsius temperatures on the display layer without changing the original output file and historical data cache, thereby ensuring the consistency and traceability of the data source; 5. This invention supports unified loading and trend comparison analysis of multiple historical working conditions, which can reduce the workload of manual import, filtering and drawing, and improve the efficiency of engineering analysis; 6. This invention can export the current trend curve or all trend curve data of the current component, which facilitates further analysis in Origin or Excel post-processing plotting software. Attached Figure Description

[0015] Figure 1 This is a diagram of the overall functional structure of the platform.

[0016] Figure 2 This is a flowchart of the real-time monitoring module.

[0017] Figure 3 A flowchart for comparing multiple operating conditions of the analysis module. Detailed Implementation

[0018] like Figure 1As shown, this invention provides a method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data. The platform of this method uses the input cards and output files of the ERAC thermal-hydraulic simulation program as data sources. By reading the variable names in the output file header, it establishes the correspondence between variable columns and engineering physical parameters, and maps them to parameter tables, key indicators, and trend curves of different components. The platform mainly includes a data reading and parsing layer, a component parameter mapping layer, a real-time monitoring module, an analysis module, a temperature unit display and conversion module, and a data export module.

[0019] In this embodiment, after the ERAC simulation program runs, it generates multiple component output files, such as output files corresponding to components like the reactor core, piping, main pump, pump support, heat exchanger, waste heat removal system, air cooling system, inter-cell flow, chambers, and hot pools. The platform does not read data using fixed row or column numbers; instead, it first reads the header variable names from the output files and forms a variable set. : (1) in, c Indicates the component type. Vm This indicates the first [number]th [item] in the output file of this component. m Each variable name is matched with a pre-configured component parameter definition by the platform to determine the actual column position of a physical quantity in the output file. For a given component parameter, the platform establishes the following mapping relationship: (2) in, M k This represents the variable mapping relationship for the k-th physical parameter. P k Indicates the first k A physical parameter name, V k This indicates the output file variable name corresponding to this physical parameter. U k Indicates the unit of display. G k This indicates the group of trend curves to which the physical parameter belongs; through this mapping relationship, when the component number in the input card changes, or the variable order in the output file is adjusted, the platform can still read the correct data according to the variable name, avoiding parameter misalignment caused by reading fixed column numbers.

[0020] like Figure 2 As shown, the real-time monitoring module's operation includes the following steps: Step 1: The user starts the ERAC simulation program or connects to an existing output directory. The platform records the current output directory path and checks whether the output files of each component exist.

[0021] Step two: The platform polls the output file at set time intervals. When a new data line is detected in the output file, only the data for the newly added time step is read, and the new data is appended to the historical data cache. For a given time step... t n The data read by the platform can be represented as: (3) in, t n Indicates the first n Each time step x m ( t n ) indicates the first (input) in the output file. m The values ​​of each variable at this time step; Step three: Based on the mapping relationship between variable names in the output file header and component parameters, the platform extracts the required physical parameters for each component. For example, for the core module, the platform can read parameters such as core inlet and outlet pressure, non-heavy pressure drop, inlet and outlet temperature, channel mass flow rate, maximum fuel temperature, maximum cladding temperature, maximum coolant temperature, total core power, and total core mass flow rate; for the piping module, the platform can read parameters such as pipe inlet and outlet pressure, non-heavy pressure drop, and mass flow rate; for the heat exchanger module, the platform can read parameters such as primary and secondary flow rates, inlet and outlet temperatures, inlet and outlet pressures, non-heavy pressure drop, and heat removal power.

[0022] Step four: The platform will synchronously display the latest data read in the parameter table and update the key indicator display area of ​​the corresponding component. Key indicators only display the latest values ​​of variables already present in the output file; no additional physical calculations are performed on the original data.

[0023] Step five: Based on the chart definition of the currently selected component, the platform extracts the time series from the historical data cache and refreshes the trend curve. The trend curves for different components are configured independently, thus allowing the display of different physical quantities according to the analysis needs of each component. For example, the core module can display trend curves for total power, total reactivity, maximum temperature, and the corresponding temperatures for each reactivity level; the piping module can display trend curves for mass flow rate, non-heavy pressure drop, and inlet / outlet pressure; and the waste heat removal system module can display trend curves for mass flow rate, pressure drop, liquid level, and heat removal power.

[0024] Step six: When the user switches the temperature unit, the platform only performs the temperature conversion on the display layer. If the original temperature is in Kelvin... T K The temperature is displayed in Celsius. T C Used at that time: (4) This conversion only applies to table displays, key indicator displays, trend curve vertical axis displays, and hover reading displays. It does not change the original data in the output file, nor does it change the original values ​​in the historical data cache.

[0025] Step 7: The platform refreshes the parameter table based on the current time step data and the parameter mapping relationship of the currently selected component, displaying the variable names and latest values ​​of the corresponding physical parameters.

[0026] Step 8: The platform refreshes the key indicators of the currently selected component and displays the latest values ​​of the corresponding physical parameters in the key indicator display area without performing any additional physical calculations on the original data.

[0027] Step 9: Based on the trend curve configuration of the currently selected component, the platform extracts the time series of the corresponding physical parameters from the historical data cache and refreshes the trend curve.

[0028] After completing steps seven through nine, the platform continues to poll the output files of each component and determine if a new time step has been added. If a new time step has been added, it returns to step two and sequentially performs data reading, variable identification, component matching, historical data updating, and display refresh. If no new time step has been added, it maintains the current display content and waits for the next polling. During real-time monitoring, users can also view the time and physical quantity values ​​corresponding to the floating position of the trend curve, and export the trend curve data. The exported data file retains the variable names, display names, and unit information, which is convenient for subsequent import into software such as Origin for plotting and analysis.

[0029] like Figure 3 As shown, the multi-condition comparison process of the analysis module includes the following steps: Step 1: In the working condition management interface, the user adds one or more historical working conditions, sets the working condition name, and selects the corresponding historical working condition output directory; the platform only saves the working condition name and the output directory path.

[0030] Step two: The user selects the historical operating conditions to be analyzed, and the platform reads the output files of each component in the output directory of the selected operating conditions one by one.

[0031] Step 3: The platform reads the header variable names of the output files for each working condition and performs consistency matching according to the actual variable names and the pre-established variable mapping relationship to determine the data columns with the same physical meaning in different working conditions.

[0032] Step four: The user selects multiple operating conditions to be compared and specifies the component type, specific component, and physical parameters to be compared in sequence.

[0033] Step 5: The platform extracts the time series corresponding to the selected physical parameters from the output files of each working condition, forming a multi-working condition comparison data set as shown in Equation (5).

[0034] (5) Step six: The platform processes the display unit of the comparison data according to the current temperature unit setting; when the user switches between Kelvin and Celsius temperatures, only the curve display value, vertical axis unit and floating reading are converted, without modifying the original data in the output files of each historical operating condition.

[0035] Step 7: The platform plots the time series of the same component and the same physical parameters under different working conditions onto the same trend chart, generating a multi-working-condition comparison curve; the same trend chart can display curves for up to 10 working conditions.

[0036] Step 8: When the user hovers the cursor over the comparison curve, the platform reads and displays the corresponding time point and the physical parameter values ​​of each working condition curve at that time point.

[0037] Step nine: Users can export the current multi-condition comparison data. The exported file includes the condition name, the actual variable name, the physical parameter name, the display unit, the time series, and the corresponding values, so that post-processing software such as Origin can continue to plot and analyze it.

[0038] During the above process, the historical operating condition output directory is only used as a data reading source. The platform does not copy, modify, or overwrite the original output files. When the actual variable name corresponding to the selected physical parameter does not exist in a certain operating condition, the platform prompts that the operating condition is missing the corresponding variable and does not use other variables to replace it, thereby avoiding the mixing and comparison of data with different physical meanings.

[0039] Users can compare the variation range, peak value, steady-state value and variation trend of physical parameters under different working conditions based on the multi-condition comparison curves and exported data, obtain the parameter variation law between each working condition, and form corresponding engineering analysis conclusions, providing a basis for simulation result evaluation and engineering decision-making.

[0040] In one specific embodiment of real-time monitoring, the platform loads the corresponding variable mapping relationship based on the currently selected component type and specific component, and generates parameter tables, key indicators, and trend curve configurations accordingly. The parameter table fields include component name, physical parameter name, output file variable name, display unit, and current time step value; the key indicators display the latest values ​​of the main physical parameters of the currently selected component; the trend curves are grouped according to trend curves, extracting the time series of corresponding physical parameters from the historical data cache. When the user switches the component type or specific component, the platform reloads the corresponding variable mapping relationship and synchronously switches the parameter table fields, key indicator fields, and trend curve fields.

[0041] In one specific embodiment of multi-condition comparison, the user selects one or more historical conditions and sequentially specifies the component type, specific component, and physical parameters to be compared. The platform searches for data columns with the same physical meaning in the output files of each condition based on the actual variable names, extracts the corresponding time series, and plots the time series of each condition on the same trend chart. The user can view the parameter values ​​corresponding to each condition at the same time point through a hover reading and can export the current multi-condition comparison data.

[0042] In one specific embodiment of historical operating condition management, users add operating conditions by selecting a historical operating condition output directory. The platform saves the operating condition name and its output directory path, and checks whether the corresponding component output files exist in the directory. When loading an operating condition, the platform directly reads the original output files in the output directory; when removing an operating condition, only the directory reference saved by the platform is deleted; when reloading an operating condition, the data in the output directory is read again. All of the above operations do not copy, modify, or overwrite the original historical operating condition output files.

[0043] In this embodiment, the trend data export file can be represented as follows: (6) in, t n Indicates the first n At a certain point in time, y n,r Indicates the first r The trend curve at the 1st n The exported file also includes the numerical values ​​corresponding to each time point. It further includes variable names, physical parameter names, and unit information, enabling users to clearly identify the physical meaning of each column of data in the post-processing software.

[0044] Through the above implementation methods, the present invention can realize real-time reading of ERAC thermal-hydraulic simulation results, component-based display, historical operating condition loading, multi-operating condition trend comparison, temperature unit display switching, and trend data export, reducing the workload of manually searching for variables, organizing data, and repeatedly drawing plots, and improving the efficiency of reactor thermal-hydraulic simulation result analysis.

Claims

1. A method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data, characterized in that, Includes the following steps: Step 1: Establish the correspondence between the output file of the reactor thermal-hydraulic simulation program and the components to be monitored. The components to be monitored include one or more calculation components in the reactor thermal-hydraulic simulation model. The calculation components include core components, flow components, power components, heat exchange components, and safety system components. Step 2: Read the header variable names of the output files corresponding to each monitored component, parse the header variable names according to the pre-established variable name rule base, identify the time column, component number, system number, and physical parameter column, and establish the mapping relationship between component name, variable name, physical parameter name, and display unit; let the first step be... c The set of header variable names in the class component output file for: (1) in, c Indicates the component type. Vm This indicates the first [number]th [item] in the output file of this component. m Variable names; establish variable mapping relationships by grouping according to physical parameter names, variable names, display units, and trend curves: (2) in, M k Indicates the first k The mapping relationship of variables for each physical parameter. P k Indicates the first k A physical parameter name, V k This indicates the output file variable name corresponding to this physical parameter. U k Indicates the unit of display. G k This indicates the grouping of the trend curve to which the physical parameter belongs; Step 3: Generate parameter tables, key indicators and trend curve configurations for each component to be monitored based on the mapping relationship established in Step 2. The parameter tables are used to display the numerical results of each component at the current time step, the key indicators are used to display the main physical quantities of the currently selected component, and the trend curves are used to display the historical data of the corresponding physical quantities changing over time. Step 4: During the operation of the reactor thermal-hydraulic simulation program, the output files corresponding to each monitored component are polled and read in a round-robin fashion. New output data is acquired according to time steps and appended to the historical data cache. c Class of components in the first n Data read at each time step Represented as: (3) in, t n Indicates the first n Each time step x m ( t n ) indicates the first (input) in the output file. m The values ​​of each variable at this time step; Step 5: Based on the parameter table, key indicators, and trend curve configuration generated in Step 3, and the historical data cache obtained in Step 4, update the parameter table, key indicators, and trend curve of the current component in real time; Step 6: Load one or more historical operating condition output directories. Based on component type identifiers, component object identifiers, and variable mapping relationships, perform consistency matching on the same physical parameter across multiple historical operating conditions, and extract the corresponding time series data for trend comparison analysis; for N Comparative datasets of identical components and physical parameters under historical operating conditions. Represented as: (4) in, p Indicates the selected physical parameters, Y N ,p ( t ) indicates the first N Sequence data of how the physical parameter changes over time under a specific working condition; Step 7: Based on the user's selection, export the current trend curve data or the trend curve data of all current components to generate a data file for subsequent plotting and engineering analysis.

2. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, In step 2, when identifying the physical parameter column based on the header variable name, fixed row numbers or fixed column numbers are not used. Instead, the header variable name is parsed through a pre-established variable name rule base. The corresponding data column is determined based on the component identifier field, parameter identifier field, and unit identifier field in the header variable name, and the correspondence between component name, variable name, physical parameter name, and display unit is established.

3. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, In step 3, each type of monitored component has an independent parameter table, key indicator, and trend curve configuration. When the user selects different components, the parameter table fields, key indicator fields, and trend curve fields of the corresponding component are automatically switched.

4. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, The polling read described in step 4 is an incremental read method, which only reads the newly added time step data in the output file and does not change the original data in the output file of the reactor thermal-hydraulic simulation program.

5. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, Step 5 also includes a temperature unit display switching process. When the user selects Celsius temperature display, the displayed temperature value is obtained by the following formula: (5) in, T k The output file contains the raw Kelvin temperature values. T c The temperature value displayed on the interface is in Celsius. The temperature unit display switching process only applies to the display layer and does not change the original temperature data in the output file or the original temperature data in the historical data cache.

6. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, The historical operating condition output directory loaded in step 6 is only referenced as a data reading source and is not copied, modified, or overwritten from the original historical operating condition output file.

7. The method for real-time monitoring and multi-condition analysis of reactor thermal-hydraulic simulation output data as described in claim 1, characterized in that, The data file in step 7 includes physical parameter names, original variable names, units, and time series data. The exported trend curve data matrix is ​​represented as follows: (6) in, t n Indicates the first n At a certain point in time, y n,r Indicates the first r The trend curve at the 1st n Data corresponding to each time point.

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