Nuclear emergency rescue commander-oriented training system and application thereof

Abstract

The invention belongs to the technical field of nuclear emergency rescue training, and relates to a nuclear emergency rescue commander-oriented training system and application thereof, the training system is a B / S architecture-based nuclear emergency command training information visualization system, and comprises a user layer, a control layer, a service layer and a base layer, wherein the user layer comprises a state monitoring system, a director scheduling system, a deduction simulation system, an assessment system and a geographic information system, and is used for processing front-end data and visually displaying situation data in a nuclear emergency situation map; the control layer is used for processing interface data; the service layer adopts a deduction engine and a data engine to perform read-write and authority control on back-end data; the basic layer comprises a database and a file server which are used for managing geographic information data, drilling data and other data respectively; according to the invention, the whole process of rescue can be displayed, and the ability of drilling scheme and evaluation, historical data backtracking, simulation drilling and the like can be designed.

Description

Technical Field

[0001] The present invention belongs to the technical field of nuclear emergency response, and in particular relates to a training system for nuclear emergency rescue commanders and its application. Background Art

[0002] Nuclear emergency response systems are generally categorized into two types: decision support systems and command information management systems. Within the decision support field, system research focuses on consequence assessment and emergency response. Representative consequence assessment and decision support systems include ARAC / NARAC developed by Lawrence Livermore National Laboratory (LLNL) in the United States, the European Union's Real-Time Online Nuclear Accident Decision Support System (RODOS), and Japan's Environmental Emergency Dose Prediction Information System (SPEEDI / WAPEEDI). Emergency response systems include the on-site automated emergency control system (A-EOS) for emergency operations and response. The nuclear emergency evacuation system, based on India's nuclear power plant accident response, focuses on contaminated area simulations to provide risk assessment and decision support for off-site rescue and evacuation. In addition to system research, related databases are also being developed, such as databases for basic radionuclide data, geographic information systems, and radionuclide diffusion models. Some scholars have also designed simulation training systems for frontline rescue personnel.

[0003] Currently, research in China on command and information management is limited. This research primarily focuses on power plant information management systems and information query and management. Research on command and control systems for external nuclear emergency rescue teams is still lacking in China. However, nuclear emergency rescue inevitably requires the support of external rescue teams. The accuracy and timeliness of accident, command, and situational information in the command and control of external rescue teams directly impact the effectiveness of nuclear emergency rescue. Furthermore, the command and control personnel's mastery of rescue processes and familiarity with emergency response plans at all levels also impact rescue effectiveness. Therefore, based on external nuclear emergency rescue drills, and drawing on actual nuclear emergency rescue processes and drill procedures, this paper develops a nuclear emergency rescue command and control system. This system can be incorporated as a command module into an integrated emergency rescue platform for decision support and emergency command, or it can be used as a standalone command center for command and control of nuclear emergency rescue and rescue drills. It also includes a simulation system, allowing command personnel to practice rescue plans, familiarize themselves with the plan development process, and optimize rescue plans. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and to provide a training system for nuclear emergency rescue commanders and its application.

[0005] In order to achieve the purpose of the present invention, the present invention is implemented by adopting the following technical solutions.

[0006] A training system for nuclear emergency rescue commanders adopts a B / S architecture, which includes a user layer, a control layer, a service layer, and a basic layer arranged in sequence, wherein:

[0007] At the user level, the status monitoring system, director and dispatch system, simulation system, and evaluation and assessment system are combined with the geographic information system to process front-end data and visualize the situation data in a nuclear emergency situation map;

[0008] The state monitoring system includes a situation display module and an information fusion module; wherein:

[0009] The situation display module uses the GIS engine to establish a map management function, supporting the import, loading and display of maps;

[0010] The information fusion module has an information management function and can enable hiding and displaying modes for displayed information. The situation display module displays a nuclear emergency situation map and can be combined with the simulation system to visualize and dynamically review historical drill records. The nuclear emergency situation map is formed by superimposing all information related to monitoring, personnel and equipment, terminals, and supplies that needs to be displayed on the situation map.

[0011] The director scheduling system includes exercise planning, command scheduling, data management and auxiliary decision-making modules, among which:

[0012] The drill planning module has the functions of data training, scenario preparation, and program planning, and supports scenario preparation and program planning for simulation exercises, which are used for preparation of rescue drills;

[0013] The command and dispatch module has the functions of document transmission, process monitoring, and director adjustment, and supports intervention in the process during simulation and deduction, and is used for command and dispatch of rescue drills;

[0014] The data management module is used for recording and storing data during the preparation and exercise process of nuclear emergency rescue drills, and supports the recording and storage of simulation deductions;

[0015] The auxiliary decision-making module runs through the entire process of nuclear emergency rescue drills and provides decision-making suggestions to operators;

[0016] The simulation system includes a model library and a simulation engine for rescue simulation and solution optimization, allowing command personnel to master the accident rescue process in different scenarios. The module library includes a method model, a task scheduling model, a rescue team model, a command model, and a special situation model.

[0017] The evaluation and assessment system includes a recording module, an indicator library, an expert library, an evaluation and assessment training module, wherein: the evaluation and assessment module is used to evaluate and assess the exercise records in the recording module; the indicator library is used to automatically evaluate quantitative indicators and generate evaluation questionnaires for expert scoring based on qualitative indicators; the expert library is used to manage evaluation experts, identify evaluation results, and generate evaluation reports; the assessment and training module is used to evaluate the theoretical level of trainees;

[0018] The control layer is used to process interface data and transmit JSON format data through the https interface;

[0019] The service layer uses a deduction engine and a data engine to read and write backend data and perform permission control. The deduction and simulation engine simulates different accident scenes and emergency rescue processes through scenario models based on on-site monitoring data, drill data, or simulation data, combined with input data from the method model, task scheduling model, and special situation model. The GIS engine is used to read and write GIS data.

[0020] The basic layer includes a nuclear emergency database composed of a database and a file server, which respectively manage geographic information data, exercise data and other data;

[0021] in:

[0022] The front-end data includes front-end interface data, user input and interaction data, cached data obtained based on API, and user permission data;

[0023] The situation data includes geographic information data, meteorological data, pollution simulation data, on-site personnel and equipment monitoring data, on-site pollution monitoring data, and path data;

[0024] The backend data includes logs, user entity data, personnel and equipment entity data, configuration data, metadata, and model deduction data;

[0025] The other data include basic data, monitoring data, management data, evaluation data, command data and model library.

[0026] As a preferred solution of the present invention, the control layer can be extended to access real devices, third-party simulation systems, and upper and lower level command systems.

[0027] As a preferred solution of the present invention, the specific functions of the drill planning module are as follows:

[0028] (1) By setting the accident scenario, exercise environment, and source parameter information to describe the accident situation, the simulation system can be combined to generate a visual initial situation, and the parameters can be dynamically modified and updated during the exercise;

[0029] (2) It has the function of program planning and can complete the nuclear emergency drill program planning based on the initial situation. The drill program includes training process and action plan;

[0030] (3) It has the function of task scheduling and can complete the specific rescue drill steps of training and exercise scheduling, task formulation and planning, and site location planning according to the nuclear emergency drill plan;

[0031] (4) Built-in template plans, which can preset template plans for scenarios, schemes, and tasks; when planning exercises, you can directly import the complete plan template or import the corresponding sub-plan templates separately;

[0032] (5) It has the function of setting special situations, which can be combined with the simulation system to preset special situations for simulating sudden dangerous situations. Special situations will be automatically triggered according to time;

[0033] (6) Virtualization support: The module supports simulation and can load simulation models to simulate training teams, accident scenarios, accident hazards, and sudden hazards. It can also seamlessly convert actual exercise plans into simulation plans for demonstration and optimization of the plans.

[0034] As a preferred solution of the present invention, the specific functions of the command and dispatch module are as follows:

[0035] (1) It has the function of command and dispatch document, and can generate command and dispatch plan according to the assumptions, plans and command and dispatch plans formulated in the exercise planning module;

[0036] (2) It has a process monitoring function, which can monitor the task progress through voice, video, and documents, and support the display of the task progress through the Gantt chart;

[0037] (3) It has the function of task adjustment and can issue guidance and adjustment instructions to adjust the task plan according to the task progress;

[0038] (4) Support directing and regulating the training team through voice and video;

[0039] (5) It has a message delivery system that can deliver documents, tasks, instructions, and messages to terminals; it supports sending documents, tasks, instructions, and messages to designated terminals and supports terminal message feedback;

[0040] (6) Built-in dispatching instructions. The system presets dispatching instructions and can generate dispatching documents in standard format for operators to send quickly.

[0041] (7) It has a command and control plan function, which can preset command and control documents, command and control instructions, and command and control timing; during the exercise, it can retrieve the plan and quickly issue command and control information, or automatically trigger it according to time.

[0042] As a preferred solution of the present invention, the specific functions of the data management module are as follows:

[0043] (1) It has basic data management and maintenance functions, stores and maintains site, personnel, equipment, and material data, classifies and saves data, supports data retrieval, maintenance, viewing, batch import and export, and supports data display in the form of analytical charts and tables;

[0044] (2) It has the function of storing exercise preparation data, storing all the data in the exercise preparation stage, including the data of scenarios, program planning, and task scheduling;

[0045] (3) It has the function of storing data during the exercise, storing all data during the exercise, including on-site monitoring data, training personnel and equipment monitoring data, geographic marking and plotting data, meteorological data, and guidance and coordination document data;

[0046] (4) It has the function of classifying and maintaining drill data. The data of the preparation and process stages of a single drill are classified and managed according to the timeline, and supports retrieval by time, keyword, and accident type;

[0047] (5) It has the function of backtracking the drill data and supports visual backtracking of the drill data. By reading the drill records, the historical situation can be reviewed and the situation can be updated as the drill records change, dynamically displaying the entire drill process;

[0048] (6) It has virtualization support functions, supports the management and maintenance of simulation data, classifies and manages the data of simulation preparation and simulation process according to the timeline, supports retrieval by time, keyword, and accident type, and supports visualization of simulation data;

[0049] (7) Supports importing real data into the model library and making simulation models based on real data.

[0050] As a preferred solution of the present invention, the specific functions of the auxiliary decision module are as follows:

[0051] (1) It has the auxiliary function of hazardous substance pollution area, which can calculate the spread direction, speed and range of the pollution area based on accident information and meteorological information to generate pollution area situation, and deduce pollution data at different locations in the pollution area;

[0052] (2) It has the function of assisting team formation, collecting and analyzing the status information of on-site equipment, personnel, and material data, and analyzing and visualizing the charts;

[0053] (3) It has the function of auxiliary operation scheduling, updating the status of trainees and equipment in real time, providing information on personnel and equipment that can be dispatched, and providing information on the quantity and storage location of emergency supplies;

[0054] (4) It has a route planning auxiliary function. Based on the route navigation and distance measurement functions provided by the status monitoring system, it can plan a variety of route plans for command decision-making;

[0055] (5) It has the function of supporting information warning, real-time monitoring of personnel, equipment, and on-site monitoring data, and issues early warnings for abnormal data. It supports the formation of different levels of annotation, pop-up windows, and flashing alarms according to the severity, and displays them in the situation;

[0056] (6) Support scalability, reserve an auxiliary suggestion interface, and operators can enter protection, task steps, and scheduling experience suggestions. It supports dynamic binding of auxiliary suggestions, can provide suggestions for specific task types and protection targets, and display suggestions when performing related operations.

[0057] As a preferred solution of the present invention, the specific functions of the status monitoring system are as follows:

[0058] (1) Management and display functions for monitoring data: analyzing on-site monitoring data, classifying the data and displaying it in real time, dynamically updating the situation, and supporting the separate display or hiding of certain types of monitoring data, supporting data early warning, marking abnormal data and issuing real-time alerts;

[0059] (2) The trend display function of monitoring data records data history information and can display data change trends in the form of lists, linear graphs, and trend graphs for each type of data;

[0060] (3) Management and display of rescue team personnel and equipment data, obtaining real-time display of rescue team personnel and equipment monitoring data, and dynamically updating the situation, supporting abnormal data annotation, display and early warning;

[0061] (4) Trend display function for personnel and equipment data, record data history information, and display data change trends for each personnel and equipment data in the form of lists, linear graphs, and trend graphs;

[0062] (5) Management and display functions for geographic data, supporting the marking, adding information and display of key locations of key areas, buildings, roads and accident points;

[0063] (6) Management and display functions for weather, exercise documents, and message data, supporting the overlay display of weather, exercise documents, and message data, and dynamic updates;

[0064] (7) Management and display of pollution area data: record data according to the coordinate area, display the pollution area in the form of heat map and pollution model, and update it dynamically, supporting the display and hiding switching of pollution areas;

[0065] (8) The function of situation review during the exercise can review the historical situation according to the timeline by reading the exercise records, and can cooperate with the simulation system to dynamically display the entire exercise process; it can review and replay the situation, actions, monitoring videos, command documents, command instructions, and information transmission of the participating teams during the exercise; and support the control of the display process, including fast forward, step, pause, and jump to a specified time;

[0066] (9) It has virtualization support function. The module supports simulation and can form a virtual situation based on the simulation data generated by the model. It supports dynamic update of the situation based on the model data. The display, data management and display, and interface operation of the virtual situation are consistent with the real situation.

[0067] As a preferred embodiment of the present invention, the deduction simulation system is composed of a model library and a deduction engine, wherein the model library includes a scenario model, a scheme model, a special situation model and a task scheduling model; the scenario model includes a radiation model, a weather model, a reactor model and a plurality of accident models, which are used to simulate the on-site situation and the situation change process; the scheme model is composed of a plurality of task models, each task model is composed of a plurality of instruction models, a rescue team model and a route model, which are used to simulate the execution of the entire rescue plan; the special situation model is composed of a plurality of accident models and a plurality of rescue team models, which are used to simulate sudden dangerous situations; the task scheduling model is composed of a plurality of task models, which simulates the scheduling task when an alarm is triggered; the radiation model is used to simulate on-site source item data; the reactor model is used to simulate reactor monitoring data; the accident model is used to simulate non-reactor accidents; the rescue team model is used to simulate the personnel and equipment data of the rescue team; the route model is used to simulate the movement route of the rescue team; the instruction model is used to simulate the task execution status; the weather model is used to simulate on-site meteorological data, and the meteorological data is used by the pollution model to calculate the contaminated area.

[0068] As a preferred solution of the present invention, the nuclear emergency database includes a database and a file server; wherein: the database is deployed using a Galera architecture cluster, and is used to store external monitoring data and read the monitoring data of the nuclear emergency rescue commander training system, and synchronize it to the cloud database; the database reads the map data and road network data of the nuclear emergency rescue commander training system, and stores them in the map server; the file server is used to store other data of the nuclear emergency rescue commander training system, and record file information and paths to the database; wherein: the map server stores tile images; the file server stores video and audio files.

[0069] As a preferred solution of the present invention, the Galera architecture is composed of N servers that are mutually master-slave. Users can obtain data from any server, and when writing data, the data can be synchronized to all servers.

[0070] As a preferred solution of the present invention, the assessment and training module is used to assess the theoretical level of trainees;

[0071] The specific functions of the recording module are as follows:

[0072] (1) Evaluation plan planning, supporting the customization of training evaluation plans based on exercise plans and exercise records, and determining the evaluation elements, evaluation indicators, evaluation standards, evaluation items, evaluation content and scoring rules;

[0073] (2) Support issuing information collection forms and assessment and evaluation forms to terminals, and support receiving collection records and assessment and evaluation feedback reported by terminals;

[0074] (3) Support virtualization and generate evaluation tables for simulation records to conduct rapid and comprehensive evaluations;

[0075] The indicator library contains a three-level indicator system that supports the evaluation of the entire exercise phase, loads an exercise evaluation model based on AHP analysis, and can be managed and maintained by operators; it is extensible and can be added and modified by operators;

[0076] The expert database manages and maintains the evaluation expert information, weights, permissions, historical evaluation records, etc.

[0077] The specific functions of the evaluation module are as follows:

[0078] (1) It has an automatic evaluation function, and the quantitative indicators in the drill records are analyzed and evaluated by the system;

[0079] (2) It has an online evaluation function, which generates an evaluation form for the qualitative indicators in the exercise records and is scored by experts;

[0080] (3) It has an evaluation and calculation function, which supports the use of a multi-attribute index nuclear emergency rescue drill evaluation method based on interval preference distribution based on system evaluation records and expert evaluation records, and converts the scoring records into expert selection preferences for intervals;

[0081] (4) It has a variable weighting function that can manually assign expert weights and automatically downgrade extreme scores;

[0082] (5) It has the functions of visual display and historical trend comparison;

[0083] The assessment and training module allows operators to input training materials for training personnel to learn; the training materials support graphic, text, audio and video formats; it has an assessment function, supports logged-in users to assess and record assessment results.

[0084] The invention discloses an application of a training system for nuclear emergency rescue commanders in training nuclear emergency rescue team commanders.

[0085] As a preferred embodiment of the present invention, the training method for the commander of the nuclear emergency rescue team comprises the following steps:

[0086] S21. The commander formulates a scenario based on the initial situation transmitted from the directorate or the accident site; the scenario includes source parameters, weather conditions, and accident information; the initial situation includes geographic information, markings, and map images;

[0087] S22. The command and guidance system generates a simulated nuclear contaminated area on the nuclear emergency situation map based on the scenario developed in step S21 and the on-site monitoring data, and overlays the on-site situation to generate an accident scenario.

[0088] S23. The commander formulates a rescue plan based on the accident scenario generated in step S22, the nuclear emergency plan and auxiliary suggestions;

[0089] S24, optimizing the rescue plan developed in step S23 through virtual simulation, generating a command document, and uploading and issuing it in the form of a command document;

[0090] S25. The commander monitors the progress of the mission and the situation by marking and mapping the situation, and adjusts the mission and communicates when special situations arise;

[0091] S26. During the nuclear emergency rescue process, all data shall be saved in the nuclear emergency database for experts to review and evaluate the drill process, and the records shall be archived.

[0092] Beneficial effects

[0093] The nuclear emergency rescue commander training system described in the present invention is used to train command personnel of emergency rescue teams. The training system has the following features: 1. It can display the entire rescue process; 2. It designs drill plans based on standard rescue process plans; 3. It has the ability to evaluate based on drill results; 4. It supports historical data backtracking and simulation drills. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 This is an architectural diagram of the system of the present invention;

[0095] Figure 2 is a data flow diagram of the present invention;

[0096] Figure 3 This is a workflow diagram of the deduction and simulation platform of the present invention;

[0097] Figure 4 This is the database structure diagram of the present invention;

[0098] Figure 5 This is a flow chart of the evaluation of the training system of the present invention;

[0099] Figure 6 This is a flow chart of the evaluation and assessment system of the present invention;

[0100] Figure 7 This is an interface diagram of the virtual deduction process table in the present invention;

[0101] Figure 8 Schematic diagram of the scaling interval and triangular whitening weight function;

[0102] Figure 9 A histogram of the model evaluation results. DETAILED DESCRIPTION

[0103] The present invention will be further described with reference to the embodiments and the accompanying drawings.

[0104] As an embodiment of the present invention, Figures 1 to 9 As shown, nuclear emergencies are characterized by widespread contamination and the difficulty of coordinated rescue efforts. Therefore, specialized nuclear emergency rescue teams are essential. The development of nuclear emergency rescue teams also relies on experienced rescue personnel, particularly command and coordination personnel. Currently, domestic training for rescue personnel primarily focuses on frontline personnel, leaving a gap in training for command and operational personnel. Therefore, we have designed and deployed a dedicated training system for emergency command and coordination.

[0105] A training system for nuclear emergency rescue commanders, using B / S architecture, such as Figure 1 As shown, the B / S architecture includes a user layer, a control layer, a service layer, and a basic layer arranged in sequence, wherein:

[0106] At the user level, the status monitoring system, director and dispatch system, simulation system, and evaluation and assessment system are combined with the geographic information system to process front-end data and visualize the situation data in a nuclear emergency situation map;

[0107] The state monitoring system includes a situation display module and an information fusion module; wherein:

[0108] The situation display module uses the GIS engine to establish a map management function, supporting the import, loading and display of maps;

[0109] The information fusion module has an information management function and can enable hiding and displaying modes for displayed information. The situation display module displays a nuclear emergency situation map and can combine with the simulation system to visualize and dynamically review historical drill records. The nuclear emergency situation map is formed by superimposing all information related to monitoring, personnel and equipment, terminals, and supplies that need to be displayed on the situation map. Utilizing the characteristics of the B / S architecture, it fully displays various types of information through overlays, pop-ups, sidebars, split screens, etc., supporting multi-user collaborative operations.

[0110] The director scheduling system includes exercise planning, command scheduling, data management and auxiliary decision-making modules, among which:

[0111] The drill planning module has the functions of data training, scenario preparation, and program planning, and supports scenario preparation and program planning for simulation exercises, which are used for preparation of rescue drills;

[0112] The command and dispatch module has the functions of document transmission, process monitoring, and director adjustment, and supports intervention in the process during simulation and deduction, and is used for command and dispatch of rescue drills;

[0113] The data management module is used for recording and storing data during the preparation and exercise process of nuclear emergency rescue drills, and supports the recording and storage of simulation deductions;

[0114] The auxiliary decision-making module runs through the entire process of nuclear emergency rescue drills and provides decision-making suggestions to operators;

[0115] The simulation system includes a model library and a simulation engine for rescue simulation and solution optimization, allowing command personnel to master the accident rescue process in different scenarios. The module library includes a method model, a task scheduling model, a rescue team model, a command model, and a special situation model.

[0116] The evaluation and assessment system includes a recording module, an indicator library, an expert library, an evaluation and assessment training module, wherein: the evaluation and assessment module is used to evaluate and assess the exercise records in the recording module; the indicator library is used to automatically evaluate quantitative indicators and generate evaluation questionnaires for expert scoring based on qualitative indicators; the expert library is used to manage evaluation experts, identify evaluation results, and generate evaluation reports; the assessment and training module is used to evaluate the theoretical level of trainees;

[0117] The control layer is used to process interface data and transmit JSON format data through the https interface;

[0118] The service layer uses a deduction engine and a data engine to read and write backend data and perform permission control. The deduction and simulation engine simulates different accident scenes and emergency rescue processes through scenario models based on on-site monitoring data, drill data, or simulation data, combined with input data from the method model, task scheduling model, and special situation model. The GIS engine is used to read and write GIS data.

[0119] The basic layer includes a nuclear emergency database composed of a database and a file server, which respectively manage geographic information data, exercise data and other data;

[0120] in:

[0121] The front-end data includes front-end interface data, user input and interaction data, cached data obtained based on API, and user permission data;

[0122] The situation data includes geographic information data, meteorological data, pollution simulation data, on-site personnel and equipment monitoring data, on-site pollution monitoring data, and path data;

[0123] The backend data includes logs, user entity data, personnel and equipment entity data, configuration data, metadata, and model deduction data;

[0124] The other data include basic data, monitoring data, management data, evaluation data, command data and model library.

[0125] As an embodiment of the present invention, Figure 1 As shown, the control layer can be extended to access real devices, third-party simulation systems, and upper and lower level command systems.

[0126] System architecture design

[0127] The system adopts B / S architecture and is developed based on SSM, which can give full play to the flexibility and compatibility of browsers. It also adopts modular and micro-service design, which has extremely high scalability.

[0128] System architecture such as Figure 1As shown. The user layer processes front-end information. Command and guidance are the key functions of this system. For this purpose, four platforms are designed: status monitoring platform, director and dispatch platform, deduction and simulation platform, and evaluation system. The platform combines geographic information systems and visualizes situation data based on the concept of "one map for emergency situations". It also utilizes the characteristics of the B / S architecture to fully display various types of information through overlays, pop-ups, sidebars, split screens, etc., and supports multi-user collaborative operations. The control layer processes interface data and transmits JSON format data through the https interface. It can be expanded to connect to real devices, other simulation systems, and superior command systems. The service layer is used for reading and writing back-end data and GIS data. At the same time, a deduction engine with a timing function is designed to simulate a variety of different accident scenes and emergency rescue processes. The basic layer performs general data management and spatial data management.

[0129] This system is used for emergency rescue drills and needs to support real-life drills using real equipment. To achieve this, it requires: 1. Visual display of the on-site accident situation. 2. Continuous monitoring of the rescue process, as well as storage, management, and backtracking of process data. 3. Information transmission according to standard command procedures. 4. Scalability and the need to connect to other devices and systems. Platform workflow, such as Figure 5 As shown, blue arrows represent data reading and writing, while red arrows represent interface communication. The entire process is divided into four parts: plan, situation, command, and data. Of these four parts, the situation and data parts are relatively independent. Situation data (geographic information, marking plots, etc.) is isolated from exercise data and independently deployed and stored. This avoids data reading and writing bottlenecks in information display. The data process is used for post-exercise review and evaluation.

[0130] In the situation flow, the entire drill process is presented by overlaying process information with situation data, with detailed information displayed through split-screen and pop-up windows. Process data is divided into planning data such as plans and commands, and process data such as monitoring. Monitoring data is primarily displayed in the situation flow. Process data is read and pushed from the database by the status monitoring system. Based on actual research with rescue teams, the monitoring data query frequency was set at 5 seconds, ensuring data timeliness while reducing hardware read and write performance requirements.

[0131] During the planning process, the integrated drill subsystem within the director's dispatch platform develops a rescue / rescue drill plan. The steps are as follows: 1. Develop a scenario. The system generates an initial situation based on the scenario, operator identification plots, and on-site information. If this is a drill, a scenario model can be included during the scenario development process to generate the initial situation. 2. Develop a rescue plan based on the initial situation and the emergency plan. 3. Determine material reserves based on information from the decision support system and dispatch rescue personnel and equipment. 4. Develop detailed information such as the mission route. 5. After the drill, evaluate the drill process and review the drill progress based on the saved drill data.

[0132] During the command process, the command operations subsystem within the director scheduling platform is responsible for all communication and interface transfers. The system generates a timeline table based on time and associates all monitoring data, documented command data, and other command data with this table. This timeline table creates traceable and retrospective process data and archives it. Loading this timeline table allows the system to track all data from the exercise in the database, enabling the tracking and retrospection of exercise data.

[0133] During the data flow, the integrated management system will categorize and store rescue team and drill process data. To this end, we use an indirect dump method to save all process data, thereby generating a traceable drill record and greatly improving data reading and writing efficiency. After the drill, the drill is reviewed through an evaluation system. The evaluation system is divided into two parts: automatic evaluation and expert evaluation. The automatic evaluation targets quantifiable parameters in the drill, such as the radiation level in the main control room and the temperature inside the containment. After the drill, the parameters are scored according to the index system based on the range they fall into. For non-quantifiable parameters in the drill, experts can evaluate them. The system uses an expert database and weighted method for expert scoring, with different scoring weights set according to the expert level and professional field to reflect different emphases. This system has a specially designed index database and evaluation model for this purpose.

[0134] As an embodiment of the present invention, the specific functions of the drill planning module are as follows:

[0135] (1) By setting the accident scenario, exercise environment, and source parameter information to describe the accident situation, the simulation system can be combined to generate a visual initial situation, and the parameters can be dynamically modified and updated during the exercise;

[0136] (2) It has the function of program planning and can complete the nuclear emergency drill program planning based on the initial situation. The drill program includes training process and action plan;

[0137] (3) It has the function of task scheduling and can complete the specific rescue drill steps of training and exercise scheduling, task formulation and planning, and site location planning according to the nuclear emergency drill plan;

[0138] (4) Built-in template plans, which can preset template plans for scenarios, schemes, and tasks; when planning exercises, you can directly import the complete plan template or import the corresponding sub-plan templates separately;

[0139] (5) It has the function of setting special situations, which can be combined with the simulation system to preset special situations for simulating sudden dangerous situations. Special situations will be automatically triggered according to time;

[0140] (6) Virtualization support: The module supports simulation and can load simulation models to simulate training teams, accident scenarios, accident hazards, and sudden hazards. It can also seamlessly convert actual exercise plans into simulation plans for demonstration and optimization of the plans.

[0141] As an embodiment of the present invention, the specific functions of the command and dispatch module are as follows:

[0142] (1) It has the function of command and dispatch document, and can generate command and dispatch plan according to the assumptions, plans and command and dispatch plans formulated in the exercise planning module;

[0143] (2) It has a process monitoring function, which can monitor the task progress through voice, video, and documents, and support the display of the task progress through the Gantt chart;

[0144] (3) It has the function of task adjustment and can issue guidance and adjustment instructions to adjust the task plan according to the task progress;

[0145] (4) Support directing and regulating the training team through voice and video;

[0146] (5) It has a message delivery system that can deliver documents, tasks, instructions, and messages to terminals; it supports sending documents, tasks, instructions, and messages to designated terminals and supports terminal message feedback;

[0147] (6) Built-in dispatching instructions. The system presets dispatching instructions and can generate dispatching documents in standard format for operators to send quickly.

[0148] (7) It has a command and control plan function, which can preset command and control documents, command and control instructions, and command and control timing; during the exercise, it can retrieve the plan and quickly issue command and control information, or automatically trigger it according to time.

[0149] As an embodiment of the present invention, the specific functions of the data management module are as follows:

[0150] (1) It has basic data management and maintenance functions, stores and maintains site, personnel, equipment, and material data, classifies and saves data, supports data retrieval, maintenance, viewing, batch import and export, and supports data display in the form of analytical charts and tables;

[0151] (2) It has the function of storing exercise preparation data, storing all the data in the exercise preparation stage, including the data of scenarios, program planning, and task scheduling;

[0152] (3) It has the function of storing data during the exercise, storing all data during the exercise, including on-site monitoring data, training personnel and equipment monitoring data, geographic marking and plotting data, meteorological data, and guidance and coordination document data;

[0153] (4) It has the function of classifying and maintaining drill data. The data of the preparation and process stages of a single drill are classified and managed according to the timeline, and supports retrieval by time, keyword, and accident type;

[0154] (5) It has the function of backtracking the drill data and supports visual backtracking of the drill data. By reading the drill records, the historical situation can be reviewed and the situation can be updated as the drill records change, dynamically displaying the entire drill process;

[0155] (6) It has virtualization support functions, supports the management and maintenance of simulation data, classifies and manages the data of simulation preparation and simulation process according to the timeline, supports retrieval by time, keyword, and accident type, and supports visualization of simulation data;

[0156] (7) Supports importing real data into the model library and making simulation models based on real data.

[0157] As an embodiment of the present invention, the specific functions of the auxiliary decision module are as follows:

[0158] (1) It has the auxiliary function of hazardous substance pollution area, which can calculate the spread direction, speed and range of the pollution area based on accident information and meteorological information to generate pollution area situation, and deduce pollution data at different locations in the pollution area;

[0159] (2) It has the function of assisting team formation, collecting and analyzing the status information of on-site equipment, personnel, and material data, and presenting it in analytical charts such as bar charts and pie charts;

[0160] (3) It has the function of auxiliary operation scheduling, updating the status of trainees and equipment in real time, providing information on personnel and equipment that can be dispatched, and providing information on the quantity and storage location of emergency supplies;

[0161] (4) It has a route planning auxiliary function. Based on the route navigation and distance measurement functions provided by the status monitoring system, it can plan a variety of route plans for command decision-making;

[0162] (5) It has the function of supporting information warning, real-time monitoring of personnel, equipment, and on-site monitoring data, and issues early warnings for abnormal data. It supports the formation of different levels of annotation, pop-up windows, and flashing alarms according to the severity, and displays them in the situation;

[0163] (6) Support scalability, reserve an auxiliary suggestion interface, and operators can enter protection, task steps, and scheduling experience suggestions based on actual experience. It supports dynamic binding of auxiliary suggestions, can provide suggestions for specific task types and protection targets, and display suggestions when performing related operations.

[0164] As an embodiment of the present invention, the specific functions of the status monitoring system are as follows:

[0165] (1) Management and display functions for monitoring data: analyzing on-site monitoring data, classifying the data and displaying it in real time, dynamically updating the situation, and supporting the separate display or hiding of certain types of monitoring data, supporting data early warning, marking abnormal data and issuing real-time alerts;

[0166] (2) The trend display function of monitoring data records data history information and can display data change trends in the form of lists, linear graphs, and trend graphs for each type of data;

[0167] (3) Management and display of rescue team personnel and equipment data, obtaining real-time display of rescue team personnel and equipment monitoring data, and dynamically updating the situation, supporting abnormal data annotation, display and early warning;

[0168] (4) Trend display function for personnel and equipment data, record data history information, and display data change trends for each personnel and equipment data in the form of lists, linear graphs, and trend graphs;

[0169] (5) Management and display functions for geographic data, supporting the marking, adding information and display of key locations of key areas, buildings, roads and accident points;

[0170] (6) Management and display functions for weather, exercise documents, and message data, supporting the overlay display of weather, exercise documents, and message data, and dynamic updates;

[0171] (7) Management and display of pollution area data: record data according to the coordinate area, display the pollution area in the form of heat map and pollution model, and update it dynamically, supporting the display and hiding switching of pollution areas;

[0172] (8) The function of situation review during the exercise can review the historical situation according to the timeline by reading the exercise records, and can cooperate with the simulation system to dynamically display the entire exercise process; it can review and replay the situation, actions, monitoring videos, command documents, command instructions, and information transmission of the participating teams during the exercise; and support the control of the display process, including fast forward, step, pause, and jump to a specified time;

[0173] (9) It has virtualization support function. The module supports simulation and can form a virtual situation based on the simulation data generated by the model. It supports dynamic update of the situation based on the model data. The display, data management and display, and interface operation of the virtual situation are consistent with the real situation.

[0174] As an embodiment of the present invention, live-fire drills cannot meet the daily teaching and training needs of command personnel. Therefore, a stand-alone simulation platform is used for training, using the same operational procedures as the command and control platform. This allows command personnel to familiarize themselves with emergency plans and master rescue procedures. This platform is highly customizable, allowing command personnel to convert real-world rescue drill data into simulation models for virtual simulations. Command personnel can use simulations to review deficiencies in actual rescue and rescue drill processes, and can also optimize rescue plans through virtual simulations before rescue and drills.

[0175] The platform consists of a model library and a deduction engine. The workflow and main models are as follows: Figure 3 As shown. The simulation model adopts a framework structure and modular design, and is composed of multiple basic models. The situation model mainly simulates the on-site situation and the process of situation change, and is composed of scenario models. The solution model simulates the execution of the entire rescue plan and is composed of task models. The task model, scenario model, and special situation model are composed of different basic models. In the basic model, the radiation model is used to simulate on-site source information, the reactor model mainly simulates reactor monitoring data, and the accident model is used to simulate other non-reactor accidents. In the task model, the rescue team model is used to simulate the personnel and equipment information of the rescue team, the route model is used to simulate the movement route of the rescue team, and the instruction model is used to simulate the task execution status.

[0176] When saving drill data, the platform divides the information into basic information and state information. Basic information defines data attributes, while state information defines data changes. For example, information such as a rescue vehicle's license plate and display model constitutes basic information, while monitoring data such as the vehicle's location during the drill constitutes state information. Models are similarly composed of basic information and process models. Basic information defines model attributes, allowing the use of real-world basic information to simulate personnel, equipment, and accident scenes. Model changes are reflected through process models, which utilize a value table and a rule table. The value table represents the thresholds for state changes, while the rule table represents the conditions for state changes. This combination of basic information and process models maximizes the simulation of real-world scenarios. For example, a vehicle model can directly utilize the basic information of an actual rescue vehicle, while data such as vehicle movement trajectory is simulated using the process model. In addition to simulating the vehicle's state model, the process model also includes a route model and a command model. The route model periodically generates vehicle location information based on the set route to simulate movement. The command model simulates the progress of the rescue vehicle's mission execution through icons, text, and modifications to monitoring value tables.

[0177] As an embodiment of the present invention, the deduction simulation system is composed of a model library and a deduction engine, wherein the model library includes a simulation model; the simulation model includes a situation model, a scenario model, a special situation model and a task conditioning model; the situation model is composed of a scenario model, which is used to simulate the on-site situation and the situation change process, and the scenario model is composed of a radiation model, a weather model, a reactor model and a multiple accident model; the scenario model is used to simulate the execution of the entire rescue plan, and is composed of multiple task models, and the task model is composed of multiple instruction models, a rescue team model and a route model; the special situation model is composed of multiple accident models and multiple rescue team models; the task conditioning model is composed of multiple task models; the radiation model is used to simulate on-site source item data; the reactor model is used to simulate reactor monitoring data; the accident model is used to simulate non-reactor accidents; the rescue team model is used to simulate the personnel and equipment data of the rescue team; the route model is used to simulate the movement route of the rescue team; the instruction model is used to simulate the task execution status; the weather model is used to simulate on-site meteorological data, and the meteorological data can be used by the pollution model to calculate the contaminated area.

[0178] As an embodiment of the present invention, Figure 4 As shown in the figure, we designed a nuclear emergency response database and optimized its storage for the specific characteristics of external rescue data. We used an indirect storage method to divide process data into time segments based on the drill timeline. These time segments are separated by 5 seconds, but the time spans are based on the drill timeframe, not the actual timeframe. This allows for fast-forwarding during simulations, where 5 seconds in real time equals several minutes in the simulation. Furthermore, each drill data is uniquely labeled, eliminating interference between different drills, especially those for the same accident.

[0179] The system database uses a relational database with high stability and reliability as its carrier. Geographic information data and drill data are deployed separately, using a database with better spatial data performance as its carrier. Video, audio, and map tiles are stored in the file server, and only file information and addresses are recorded in the database. The drill data database is deployed using a mature and efficient Galera architecture cluster. The architecture consists of several servers that are mutually master-slave. Users can obtain data from any server, and when writing, the data will be synchronized to all servers. This architecture ensures that when a node server fails, it can seamlessly switch to other servers, and the data will be backed up at the same time. This highly redundant architecture can maximize data security and system stability.

[0180] To address I / O bottlenecks that are prone to occur in the database, such as reading and writing monitoring data, we use a combination of main memory and in-memory database caching.

[0181] As an embodiment of the present invention, the nuclear emergency database is composed of a database for storing drill data, a database for storing geographic information data, and a file server for storing other data; wherein: the database is deployed using a Galera architecture cluster;.

[0182] As an embodiment of the present invention, the Galera architecture is composed of N servers that are mutually master-slave. Users can obtain data from any server, and when writing data, the data can be synchronized to all servers.

[0183] As a preferred solution of the present invention, the assessment and training module is used to assess the theoretical level of trainees;

[0184] The specific functions of the recording module are as follows:

[0185] (1) Evaluation plan planning, supporting the customization of training evaluation plans based on exercise plans and exercise records, and determining the evaluation elements, evaluation indicators, evaluation standards, evaluation items, evaluation content and scoring rules;

[0186] (2) Support issuing information collection forms and assessment and evaluation forms to terminals, and support receiving collection records and assessment and evaluation feedback reported by terminals;

[0187] (3) Support virtualization and generate evaluation tables for simulation records to conduct rapid and comprehensive evaluations;

[0188] The indicator library contains a three-level indicator system that supports the evaluation of the entire exercise phase, loads an exercise evaluation model based on AHP analysis, and can be managed and maintained by operators; it is extensible and can be added and modified by operators;

[0189] The expert database manages and maintains the evaluation expert information, weights, permissions, historical evaluation records, etc.

[0190] The specific functions of the evaluation module are as follows:

[0191] (1) It has an automatic evaluation function, and the quantitative indicators in the drill records are analyzed and evaluated by the system;

[0192] (6) It has an online evaluation function, which generates an evaluation form for the qualitative indicators in the exercise records and is scored by experts;

[0193] (7) It has an evaluation and calculation function, which supports the use of a multi-attribute index nuclear emergency rescue drill evaluation method based on interval preference distribution based on system evaluation records and expert evaluation records, and converts the scoring records into expert selection preferences for intervals;

[0194] (8) It has a variable weight function that can manually assign expert weights and automatically downgrade extreme scores;

[0195] (9) It has the functions of visual display and historical trend comparison;

[0196] The assessment and training module allows operators to input training materials for training personnel to learn; the training materials support formats such as graphics, text, audio and video; and has an assessment function that supports logged-in users to assess and record assessment results.

[0197] The invention discloses an application of a training system for nuclear emergency rescue commanders in training nuclear emergency rescue team commanders.

[0198] As a preferred embodiment of the present invention, the training method for the commander of the nuclear emergency rescue team comprises the following steps:

[0199] S21. The commander formulates a scenario based on the initial situation transmitted from the directorate or the accident site; the scenario includes source parameters, weather conditions, and accident information; the initial situation includes geographic information, markings, and map images;

[0200] S22. The command and guidance system generates a simulated nuclear contaminated area on the nuclear emergency situation map based on the scenario developed in step S21 and the on-site monitoring data, and overlays the on-site situation to generate an accident scenario.

[0201] S23. The commander formulates a rescue plan based on the accident scenario generated in step S22, the nuclear emergency plan and auxiliary suggestions;

[0202] S24, optimizing the rescue plan developed in step S23 through virtual simulation, generating a command document, and uploading and issuing it in the form of a command document;

[0203] S25. The commander monitors the progress of the mission and the situation by marking and mapping the situation, and adjusts the mission and communicates when special situations arise;

[0204] S26. During the nuclear emergency rescue process, all data shall be saved in the nuclear emergency database for experts to review and evaluate the drill process, and the records shall be archived.

[0205] The system is mainly used for training command personnel of emergency rescue teams, and for commanding and directing emergency drills. The system has the following features: 1. It can display the entire process of the drill; 2. It designs drill plans around standard rescue process plans; 3. It has the ability to evaluate based on the results of the drill; 4. It supports historical data backtracking and simulation drills. The system features of nuclear emergency rescue drills are shown in Table 1. Compared with information systems that collect nuclear emergency data and assist in emergency evacuation decisions, nuclear emergency rescue drill systems that focus on command and direction involve more complex data types, have higher requirements for data fusion and display, and need to follow actual emergency processes to design data flows, such as Figure 2 shown.

[0206]

[0207]

[0208] Commanders formulate scenarios based on accident parameters transmitted from the directorate or the scene, including source, weather, and accident information. Based on these scenarios and combined with on-site monitoring information, the system generates a simulated contaminated area on a situation map and overlays the on-site situation to create an accident scenario. Based on the accident scenario, command personnel develop a rescue plan based on the emergency plan and supporting recommendations. The plan determines task scheduling and details such as the selection of personnel and equipment, and the route. The plan is optimized through virtual simulations and ultimately uploaded and issued in the form of a command document. Commanders monitor the rescue process through monitoring and situation analysis, and adjust tasks and communicate them when special circumstances arise. All data from the drill is stored in a database for experts to review and evaluate the drill process, and records are archived.

[0209] All data and icons on the system situation interface are test data. This interface displays the status of a virtual simulation. The geographic information system can switch between satellite and civilian map modes and provides auxiliary functions such as contour lines and latitude and longitude grids. The situation is displayed on the map using an overlay, and the interface displays information such as vehicles, routes, and contaminated areas. All information in the interface is simulated by the simulation engine based on the model.

[0210] Other information that can be overlaid includes markings and other identification information. Markings and icons such as vehicle power stations can be customized.

[0211] Figure 7 This diagram shows the mission progress chart for a virtual game, along with the editing of mission models. The mission, route, and vehicle are all models. Commands are used to simulate the mission execution process, and their content, timing, and effects can all be customized.

[0212] In order to effectively identify deficiencies in the drill and make targeted improvements, the evaluation work should run through the entire drill process. The evaluation process designed by the present invention starts with the preparation stage. The preparation group is mainly responsible for setting up accident scenarios and formulating drill plans based on the plan. The evaluation experts mainly undertake two tasks at this stage: one is to participate in the formulation of the drill plan and formulate the evaluation benchmark; the second is to participate in the setting of sudden dangerous situations to improve the authenticity of the drill and strengthen the assessment of emergency response capabilities. After completing the formulation of the drill plan and the evaluation standards, you can move on to the implementation stage of the drill.

[0213] During actual emergency response, commanders use decision-support systems to obtain key information, including geographic information, decision-making recommendations, and emergency response plans, to support the development of emergency plans. To ensure the authenticity and practicality of the drills, some drills allow participants to utilize the decision-support systems. Therefore, during the drill preparation phase, assessment experts conduct a systematic evaluation of the decision-support functions to ensure the integrity and accuracy of the information and prevent biased decisions from impacting the drill.

[0214] The evaluation phase of the drill focused on three key areas: command and dispatch, on-site execution, and effectiveness evaluation. See Table 1 for details. The command and dispatch phase focused on two key aspects: first, the commander's scenario awareness, such as map creation and site selection; and second, their understanding of the emergency plan and overall planning and dispatch capabilities. The evaluation criteria for command and dispatch were primarily based on expert judgment. Furthermore, the commander's emergency response capabilities and time-limited decision-making were assessed through the handling of sudden emergencies. Finally, an intuitionistic fuzzy multi-expert voting method was used to comprehensively evaluate the emergency response plans.

[0215] The on-site execution phase includes the most evaluation indicators, primarily assessing frontline personnel's professional and technical skills, their proficiency in operating procedures and equipment, and their coordination and communication skills during emergency response. This phase has broad evaluation criteria, with experts scoring personnel's actual performance using a 100-point scale.

[0216] The effectiveness evaluation phase primarily relies on quantitative indicators, objectively assessing the effectiveness of emergency response through on-site monitoring data collected by the system. Finally, experts comprehensively assess whether the effectiveness meets expectations based on the compliance and changing trends of various monitoring data.

[0217] The result evaluation stage mainly includes two steps: expert scoring and model conversion. Figure 6 As shown in the figure, the evaluation process is based on a three-level indicator system: first, multiple experts judge the three-level indicators, then use the evaluation model to standardize the evaluation results of different types of indicators into interval selection tendencies, and finally, combine the weights of each indicator to summarize the evaluation results of the three-level indicators step by step into the comprehensive evaluation results of the second-level indicators.

[0218] Relevant indicators for evaluation of nuclear emergency rescue drills

[0219] Building on the previously established three-level indicator evaluation system, this paper categorizes indicators into three categories: quantitative, qualitative, and comprehensive. Table 1 lists the core evaluation indicators and their corresponding three-level evaluation criteria. The evaluation results of each indicator are ultimately converted into a five-level interval quantitative evaluation standard to facilitate the presentation of the results.

[0220] 1. Quantitative indicators refer to evaluation indicators with clear quantitative standards and benchmark values, which are mainly used to measure execution quality and can be divided into the following three categories:

[0221] 1) Interval-type indicators: For example, task execution time and monitoring data, it is normal for these indicators to fluctuate within a specific range, and this range is used as the evaluation benchmark.

[0222] 2) Extremely large indicators, such as on-site sign coverage, are graded based on how close the actual value is to the upper limit. If the value falls below the lower limit, it is considered unqualified.

[0223] 3) Extremely small indicators, such as casualty rate, are graded based on how close the actual value is to the lower limit. If the value exceeds the upper limit, the system is deemed unqualified.

[0224] 2. Qualitative indicators are primarily evaluated based on expert experience, including assessments of plotting accuracy, rationality of planned area division, and selection of assembly point locations. While these indicators lack clear standards, they can be evaluated through collective analysis by the expert group.

[0225] 3. Comprehensive evaluation indicators have a broad scoring standard, as shown in Table 2. Experts first determine the preliminary scoring range based on established standards and then accurately determine the indicator score based on actual on-site conditions, thus achieving an organic combination of objective evaluation and professional judgment.

[0226] Comprehensive evaluation metrics: Traditional evaluation methods have limitations. The five-point scoring system fails to capture the experts' hesitation and can amplify their pessimistic and optimistic tendencies. While fuzzy set evaluation methods can address these issues, their complexity hinders real-time expert scoring and tracking of exercise progress.

[0227] The present invention proposes an evaluation model based on a percentage system, which reflects the degree of hesitation of the expert's judgment through the scoring value. The survey results show that experts usually determine the score range first and then determine the specific score value during the scoring process. According to this scoring characteristic, the percentage system is divided into the following five intervals: 1. Excellent 90-100; 2. Excellent 80-90; 3. Good 70-80; 4. Pass 60-70; 5. Unqualified 60-0. The expert's score can reflect the degree of certainty of his judgment: the score close to the upper limit of the interval indicates that the expert's judgment is relatively clear, and the score close to the lower limit of the interval reflects that the expert has a certain hesitation. Taking the excellent interval as an example, when the expert's judgment is relatively certain, a score of 95 points or more is usually given; otherwise, the score is close to 90 points. The specific content of the hesitation quantification method and the interference factor elimination mechanism will be systematically discussed in subsequent chapters.

[0228] Quantitative indicator processing: Quantitative indicator evaluation uses two judgment methods: real number benchmark and interval benchmark. The real number benchmark is based on the actual value x ij and the reference value D ijThe real number benchmark is unique and is evaluated by the following steps: first, the deviation value is calculated according to formula (1) and converted into a score, and then the trigonometric whitening function formulas (6) to (10) in Chapter 3 are used to convert the score into the selection tendency of the scale interval. Among them, the maximum index d1 ij , the degree of proximity between the assessment value and the benchmark value is positively correlated. ij , the degree of deviation between the assessment value and the benchmark value is positively correlated.

[0229]

[0230] Interval-based indicator assessments use multiple preset scale intervals and determine the interval to which the indicator belongs based on the monitored value. Quantitative indicators can be directly calculated by the model without the need for expert judgment.

[0231] Qualitative indicator processing: Due to the lack of detailed scoring standards, qualitative indicators usually rely on expert experience for evaluation and are easily affected by personal scoring tendencies. In order to improve the objectivity of the evaluation, the present invention adopts a method of converting language evaluation into an intuitive fuzzy function. Based on the correspondence between language variables and intuitive fuzzy functions established in the literature, the present invention further expands the evaluation system and establishes a correspondence between language variables and interval score tendencies. The evaluation coefficient matrix γ_ij of k experts is calculated by formula (2), where f(d_ij^k) represents the interval tendency corresponding to the selected language variable of the kth expert, and the average tendency value of the expert group is finally calculated. In view of the particularity of the qualitative indicator scoring standard, the original weight of the individual judgment of the experts is retained.

[0232]

[0233] Rescue plan evaluation: In the evaluation of rescue plans, a special qualitative indicator, this invention improves the traditional scoring method and establishes a set of weighted standards. During the evaluation process, experts make judgments on five dimensions based on the degree of indicator completion: a. Compliant (μ = 1); b. Basically compliant (μ = 0.7); c. Uncertain (μ = 0); d. Basically non-compliant (v = 0.7); e. Non-compliant (v = 1). Based on the expert evaluation results, the intuitive fuzzy number of the plan refinement indicator is generated, and then the final scoring function is constructed. Among them, μ represents the expert's degree of affirmative tendency, and ν represents the degree of negative tendency.

[0234] This method adopts a simplified intuitive model group decision-making method, and the steps are as follows:

[0235] (1) k experts evaluate the refined indicators.

[0236] (2) The comprehensive evaluation results form the intuitive fuzzy number of the refined index α=(μ α ,v α ). where μα is the proportion μ / k of items that are satisfied among k experts. α is the proportion v / k of unsatisfied items selected by k experts.

[0237] (3) According to the weight of the refined index ω i , aggregate k refined indicators.

[0238]

[0239] (4) Determine the solution score according to formula (5), and then determine the scale interval to which the solution belongs based on the score. Because this model does not involve the ranking of multiple solutions, a simplified score function L(α) is used.

[0240]

[0241] (5) According to the score function of the intuitionistic fuzzy set corresponding to the scaling interval, select the interval that is closest to the scoring function of the scheme. This interval is the scaling interval selection tendency of the scheme.

[0242] Improved hybrid center point triangle whitening weight function

[0243] The three-level model for nuclear emergency rescue drill evaluation has a total of first-level indicators U, second-level indicators U i and the third-level indicator U ij . The model uses a percentage system to evaluate the three-level indicators. Experts first determine the score range of the indicator and then give its score in the range. The score range is divided into ten intervals according to the percentage system, and scores below 60 are considered unqualified. When the model is whitening, the interval of the triangular whitening weight function is expanded. Compared with the traditional score interval, the indicator domain of the model is expanded by five points to the left and right, and adjacent intervals overlap by five points. The scores for each interval are: excellent, [85-100); excellent, [75-95); good, [65-85); qualified, [55-75); unqualified, [65-0).

[0244] like Figure 8 As shown, the dotted lines divide the score ranges, but in the model, each range extends outward by five points and overlaps with other ranges. This overlap represents the experts' hesitation in scoring. When experts score, they usually first determine the approximate range of the indicator and then determine the specific score. In this case, high or low scores within the range often reflect the experts' hesitation when deciding the scale level of the indicator. For example, indicator U ij The expert rated it as excellent, but the score was only 81. This shows that the expert hesitated between the excellent and good ranges when assigning the indicator a score that was lower than the excellent range.

[0245] The expression of the mixed triangular whitening weight function based on the five-scale interval is as follows:

[0246]

[0247]

[0248] In the formula Give the kth expert the three-level indicator U ij Score, let the evaluation level e=(1,2,3,4,5), Corresponding to five scales respectively. For example, the Kth expert gives the index U ij The score is 81 points, which indicates that the score falls into the excellent interval represented by formula (7), with a score tendency of 0.6, and the good interval represented by formula (8), with a score tendency of 0.4.

[0249] Variable Weighting of Specific Scores: Considering the high authority of the assessment experts, their familiarity with the scoring criteria, and their ability to score rationally and objectively, and the fact that expert scores are reviewed after nuclear emergency drills to eliminate errors, extreme scores reflect controversial aspects of the assessment and need to be retained to maintain record accuracy. However, extreme scores can also affect the indicator's scale range and overall score, so the model uses variable weighting to smooth the curve.

[0250] After analyzing the evaluation records, we can summarize the following characteristics: 1) The overall scores of expert evaluations tend to be consistent; 2) Experts have scoring tendencies, some experts are more strict and give lower overall scores, while others give higher scores; 3) There are large differences in the scores of individual indicators, which is a reflection of the controversial nature of expert evaluations. Therefore, the model will weight the extreme scores of each indicator to smooth the score curve. The model determines the extreme scores through the formula deviation between the score and the benchmark value, and the benchmark value is the average score of all experts on the indicator. The weighting is only for indicators with extreme scores and does not affect

[0251] Other indicators. The Kth expert, after giving the indicator U ij Score When , the weight change formula is as follows:

[0252]

[0253] Through our expert survey, we concluded that a score difference of 5 points is acceptable, mainly due to the expert's scoring tendency. However, a difference of more than 5 points reflects the divergence of expert opinions. However, based on historical statistics and research, such differences generally do not exceed 10 points. Taking into account the scoring tendency, the formula limits the range of disagreement to 15 points. Only when the indicator score and the average score of K experts are different, the difference between the two scores will be considered. Disagreements between 5 and 15 points are weighted accordingly. Disagreements exceeding 15 points are discussed during the review process, and if experts insist, the dispute remains undisputed but is given a lower weight.

[0254] Comprehensive evaluation: After the evaluation, the model calculates the scores of each indicator based on the grey weight clustering algorithm. First, the weights are changed according to the expert scores to eliminate the influence of extreme scores. Then, the expert weights are summed and normalized according to formula (12), where ω k is the K-th expert pair index U ij The scoring weight of .

[0255]

[0256] Then according to the triangular whitening weight function of formula (6)-(10) The expert weights of formulas (11) to (12) are used to calculate the index U according to formula (13) ij Gray evaluation coefficient belonging to e.

[0257]

[0258] The gray evaluation weight matrix γ of the three-level indicators is generated by integrating the gray evaluation coefficients ij , matrix γ ij Including all evaluation experts on indicator U ij The five-level evaluation coefficient γ ij Based on γ ij Generated second-level indicator U i The grey evaluation weight matrix γ i As shown in formula (14):

[0259]

[0260] Combined with the weights of the three-level indicators, the matrix is comprehensively weighted to generate a scoring matrix.

[0261]

[0262] As an example of the present invention, this exercise sets a scenario for a prolonged overpressure accident in the containment vessel of a nuclear power plant. The accident occurred at an old pressurized water reactor nuclear power plant and was caused by a serious failure in the control system, resulting in a loss of core power control. The accident sequence is as follows:

[0263] T+0 hours: The accident began. A control system malfunctioned, causing unstable reactor power control and a slow increase in primary coolant pressure. Simultaneously, a safety valve failed, limiting the safety system's pressure relief efficiency.

[0264] T+16 hours: The primary circuit pressure reached the design upper limit, and the pressure inside the containment vessel began to rise slowly. Although a manual emergency shutdown was subsequently implemented, the residual heat effect kept the primary circuit pressure high.

[0265] T+24 hours: The pressure inside the containment exceeds the design value, and the emergency pressure reduction measures within the plant are ineffective, so the emergency response procedure is initiated.

[0266] T+32 hours: The containment pressure continued to rise to 1.5 times the design value, causing cracks to appear and expand in weak areas, and radioactive materials began to leak.

[0267] T+36 hours: Due to high radiation levels, the plant's emergency response team is unable to approach. The plant requests external assistance from regulators and local authorities.

[0268] T+40 hours: The pressure inside the containment reached 1.8 times the design pressure, and the leak intensified. The off-site emergency rescue team arrived at the scene and began setting up the emergency area, assessing the situation, and developing an emergency plan. According to the emergency plan, controlled venting was followed by sealing the breach.

[0269] T+52 hours: After controlled venting, the pressure inside the containment vessel dropped to 1.3 times the design value. An off-site rescue team used a robot to enter the containment vessel, detect leaks, and assess damage.

[0270] T+60 hours: During the preparation for the initial blockade, an operating robot malfunctioned and got stuck in a narrow passage, causing congestion.

[0271] T+62 hours: The commanding personnel made a quick decision and used another robot to clear the passageway obstruction. However, this resulted in the delay of subsequent tasks and the damage of one operating robot.

[0272] T+66 hours: The off-site rescue team continued to implement the sealing plan, using high-altitude spraying to reduce the radiation level at the breach. They then used specialized sealing materials to initially seal the breach.

[0273] T+72 hours: After initial sealing, the rescue team continued to reinforce the breach. The containment leak was ultimately effectively controlled. Radiation monitoring systems inside and outside the plant indicated a gradual decrease in radiation levels.

[0274] T+100 hours: The pressure and radiation levels within the containment vessel were under control and stabilized. The on-site command center continued to monitor the containment and confirmed that the leak had been eliminated. The off-site emergency rescue team began to evacuate in batches, leaving some personnel behind to continue monitoring and supporting follow-up operations.

[0275] Table 1 shows some examples of multi-attribute index evaluation. The evaluation steps are as follows:

[0276] Step 1. Quantitative indicator processing: Table 1 shows the conversion of three types of indicators: maximum, minimum, and interval.

[0277] Step 2. Qualitative Index Processing: For example, in the map evaluation, six experts gave very high ratings (Excellent 0.7, Excellent 0.3), and four experts gave high ratings (Excellent 0.4, Excellent 0.6). The average values for Excellent are calculated as (0.7*0.6+0.4*4) / 10=0.58, and (0.3*6+0.6*4) / 10=0.42.

[0278] Step 3. The evaluation attributes of the execution plan are 1. Route planning U1; 2. Task scheduling U2; 3. Time planning U3; 4. Resource scheduling U4; 5. Location planning U5. A total of 10 experts formed an intuitionistic fuzzy set α = [(0.7, 0.2), (0.8, 0.1), (0.9, 0.1), (0.7, 0.1), (1, 0)], and each detailed evaluation attribute weight ω i Both are 0.2. According to formulas (3) and (4), the intuitive fuzzy number α=(0.82,0.08) is generated, and according to formula (5), the score L(α)=0.8364 is generated. According to Table 2, the score function L(α)=0.8571 of the intuitive fuzzy number (0.85,0.1,0.05) is closest, so the score range is excellent (0.7), good (0.3), as shown in the following example. Figure 9 shown.

[0279] Table 1 Examples of some preprocessed data

[0280]

[0281] Step 4. The score is generated according to the whitening function of formulas (1) to (5) to generate the evaluation coefficient e = (1, 2, 3, 4, 5), and then the evaluation weight matrix table 2 is generated according to formulas (6) to (8). Finally, the final evaluation result table 3 is generated according to formulas (9) and (10).

[0282] Tables 2 and 3 show the experts' preferences for scaled ranges. For example, in the overall exercise performance, U, the experts tended to score "Excellent" at approximately 0.31, "Excellent" at 0.56, and "Good" at 0.2. This indicates that the exercise was generally good, with experts preferring the "Excellent" range. However, they also noted a small number of "Good" and "Qualifying" scores. The details of the secondary indicators reveal details such as the relatively low score for U4.

[0283] Table 2 Evaluation weight matrix

[0284]

[0285]

[0286] Table 3 Evaluation results

[0287] Special excellent good qualified Unqualified index 0.235947 0.590629 0.173423 0 0 U1 0.059134 0.59141 0.321431 0.028026 0 U2 0.523839 0.47428 0.001881 0 0 U3 0.1855 0.71725 0.48125 0.016 0 U4 0.556 0.41 0.034 0 0 U5 0.312084 0.556714 0.202397 0.008805 0 U

[0288] Results and Discussion: Traditional assessments utilize expert follow-up drills and questionnaires. Experts rate indicators on a five-point scale, and the final score is calculated using weighted calculations. Case data shows that indicator U1 scored 3.89, U2 scored 3.55, U3 scored 4.245, U4 scored 3.77, and U5 scored 4.34. Traditional assessment methods have limitations in both indicator system design and result presentation. The assessment lacks a detailed breakdown of the drill phases, and the uniform five-point scale makes it difficult to reflect the differentiated characteristics of indicators across different phases.

[0289] The evaluation method proposed in this paper has two key features: First, it implements differentiated assessments of different indicator types based on the rehearsal phase, thereby improving assessment accuracy; second, it converts scores into expert range selection preferences, providing more detailed assessment information. According to the evaluation results in Table 3, indicator U1 exhibits the highest tendency toward exceptional performance, reflecting the overall excellent performance of its three subordinate indicators. Indicator U4 exhibits a higher tendency toward good and acceptable ranges, indicating that its overall performance still has room for improvement. Combined with the evaluation weight matrix (see Table 2), the specific performance of the three subordinate indicators can be further analyzed as follows: 1. Although indicator U41 is in the excellent range, its tendency distribution (excellent 0.58, good 0.42) reflects a high degree of hesitation in expert scoring, and the scores may be higher than the actual level. Therefore, further improvements are needed for this indicator. The scoring results for indicator U46 are similar. 2. The scores for indicators U43 and U45 show that the evaluation results are generally consistent with the actual level. 3. Indicator U42 has the lowest overall performance, with relatively consistent expert judgments, indicating that this capability requires significant improvement. 4. The U44 indicator shows a polarized scoring phenomenon. A few high scores indicate that there are some bright spots, but the overall level still needs to be improved.

Claims

1. A training system for nuclear emergency rescue commanders, using a B / S architecture, characterized by: The B / S architecture includes a user layer, a control layer, a service layer, and a basic layer arranged in sequence, wherein: At the user level, the status monitoring system, director and dispatch system, simulation system, and evaluation and assessment system are combined with the geographic information system to process front-end data and visualize the situation data in a nuclear emergency situation map; The state monitoring system includes a situation display module and an information fusion module; wherein: The situation display module uses the GIS engine to establish a map management function, supporting the import, loading and display of maps; The information fusion module has an information management function and can enable hiding and display modes for each displayable information. The situation display module displays a nuclear emergency situation map and can combine with the simulation system to visualize and dynamically review historical exercise records. The nuclear emergency situation map is formed by superimposing all the information that needs to be displayed related to monitoring, personnel and equipment, terminals, and supplies on the situation map. The director scheduling system includes exercise planning, command scheduling, data management and auxiliary decision-making modules, among which: The drill planning module has the functions of data training, scenario preparation, and program planning, and supports scenario preparation and program planning for simulation exercises, which are used for preparation of rescue drills; The command and dispatch module has the functions of document transmission, process monitoring, and director adjustment, and supports intervention in the process during simulation and deduction, and is used for command and dispatch of rescue drills; The data management module is used for recording and storing data during the preparation and exercise process of nuclear emergency rescue drills, and supports the recording and storage of simulation deductions; The auxiliary decision-making module runs through the entire process of nuclear emergency rescue drills and provides decision-making suggestions to operators; The simulation system includes a model library and a simulation engine for rescue simulation and solution optimization, allowing command personnel to master the accident rescue process in different scenarios. The module library includes scenario models, method models, task scheduling models, and special situation models. The evaluation and assessment system includes a recording module, an indicator library, an expert library, an evaluation and assessment training module, wherein: the evaluation and assessment module is used to evaluate and assess the exercise records in the recording module; the indicator library is used to automatically evaluate quantitative indicators and generate evaluation questionnaires for expert scoring based on qualitative indicators; the expert library is used to manage evaluation experts, identify evaluation results, and generate evaluation reports; the assessment and training module is used to evaluate the theoretical level of trainees; The control layer is used to process interface data and transmit JSON format data through the https interface; The service layer uses a simulation engine and a data engine to read and write backend data and control permissions. The simulation engine simulates different accident scenes and emergency rescue processes through scenario models based on on-site monitoring data, drill data, or simulation data, combined with input data from the method model, task scheduling model, and special situation model. The GIS engine is used to read and write GIS data. The basic layer includes a nuclear emergency database composed of a database and a file server, which respectively manage geographic information data, exercise data and other data; in: The front-end data includes front-end interface data, user input and interaction data, cached data obtained based on API, and user permission data; The situation data includes geographic information data, meteorological data, pollution simulation data, on-site personnel and equipment monitoring data, on-site pollution monitoring data, and path data; The backend data includes logs, user entity data, personnel and equipment entity data, configuration data, metadata, and model deduction data; The other data include basic data, monitoring data, management data, evaluation data, command data and model library.

2. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The control layer can be extended to access real equipment, third-party simulation systems, and upper and lower level command systems.

3. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The specific functions of the drill planning module are as follows: (1) By setting the accident scenario, exercise environment, and source parameter information to describe the accident situation, the simulation system can be combined to generate a visual initial situation, and the parameters can be dynamically modified and updated during the exercise; (2) Ability to complete the planning of nuclear emergency drills based on the initial situation, including training process and action plan; (3) Ability to complete specific rescue drill steps including participant scheduling, task formulation and planning, and site location planning according to the nuclear emergency drill plan; (4) Built-in template plans, which can preset template plans for scenarios, schemes, and tasks; when planning exercises, you can directly import the complete plan template or import the corresponding sub-plan templates separately; (5) It can be combined with the simulation system to preset special situations to simulate sudden dangerous situations, and the special situations will be automatically triggered according to the time; (6) It has virtualization support functions and supports simulation. It can load simulation models to simulate training teams, accident scenarios, accident hazards, and sudden hazards, and can seamlessly convert actual exercise plans into simulation plans for demonstration and optimization of plans.

4. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The specific functions of the command and dispatch module are as follows: (1) Ability to generate a command and control plan based on the scenarios, plans, and command and control plans developed in the exercise planning module; (2) It can monitor the progress of tasks through voice, video, and documents, and support displaying the progress of tasks through Gantt charts; (3) Ability to issue guidance and control instructions to adjust mission plans according to mission progress; (4) Support directing and regulating the training team through voice and video; (5) Ability to deliver documents, tasks, instructions, and messages to terminals; support sending documents, tasks, instructions, and messages to designated terminals, and support terminal message feedback; (6) Built-in dispatching instructions. The system presets dispatching instructions and can generate dispatching documents in standard format for operators to send quickly. (7) It can preset command documents, command instructions, and command timing; during the drill, it can retrieve the plan and quickly issue command information, or automatically trigger it according to time.

5. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The specific functions of the data management module are as follows: (1) It has basic data management and maintenance functions, stores and maintains site, personnel, equipment, and material data, classifies and saves data, supports data retrieval, maintenance, viewing, batch import and export operations, and supports displaying data in the form of analytical charts and tables; (2) It has the function of storing exercise preparation data, storing all the data in the exercise preparation stage, including the data of scenarios, program planning, and task scheduling; (3) It has the function of storing data during the exercise, storing all data during the exercise, including on-site monitoring data, training personnel and equipment monitoring data, geographic marking and plotting data, meteorological data, and guidance and coordination document data; (4) It has the function of classifying and maintaining drill data. The data of the preparation and process stages of a single drill are classified and managed according to the timeline, and supports retrieval by time, keyword, and accident type; (5) It has the function of backtracking the drill data and supports visual backtracking of the drill data. By reading the drill records, the historical situation can be reviewed and the situation can be updated as the drill records change, dynamically displaying the entire drill process; (6) It has virtualization support functions, supports the management and maintenance of simulation data, classifies and manages the data of simulation preparation and simulation process according to the timeline, supports retrieval by time, keyword, and accident type, and supports visualization of simulation data; (7) Supports importing real data into the model library and making simulation models based on real data.

6. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The specific functions of the auxiliary decision module are as follows: (1) It has the auxiliary function of hazardous substance pollution area, which can calculate the spread direction, speed and range of the pollution area based on accident information and meteorological information to generate pollution area situation, and deduce pollution data at different locations in the pollution area; (2) It has the function of assisting team formation, collecting and analyzing the status information of on-site equipment, personnel, and material data, and presenting it in analytical charts such as bar charts and pie charts; (3) It has the function of auxiliary operation scheduling, updating the status of trainees and equipment in real time, providing information on personnel and equipment that can be dispatched, and providing information on the quantity and storage location of emergency supplies; (4) It has a route planning auxiliary function. Based on the route navigation and distance measurement functions provided by the status monitoring system, it can plan a variety of route plans for command decision-making; (5) It has the function of supporting information warning, real-time monitoring of personnel, equipment, and on-site monitoring data, and issues early warnings for abnormal data. It supports the formation of different levels of annotation, pop-up windows, and flashing alarms according to the severity, and displays them in the situation; (6) Support scalability, reserve an auxiliary suggestion interface, and operators can enter protection, task steps, and scheduling experience suggestions based on actual experience. It supports dynamic binding of auxiliary suggestions, can provide suggestions for specific task types and protection targets, and display suggestions when performing related operations.

7. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The specific functions of the condition monitoring system are as follows: (1) Management and display functions for monitoring data: analyzing on-site monitoring data, classifying the data and displaying it in real time, dynamically updating the situation, and supporting the separate display or hiding of certain types of monitoring data, supporting data early warning, marking abnormal data and issuing real-time alerts; (2) The trend display function of monitoring data records data history information and can display data change trends in the form of lists, linear graphs, and trend graphs for each type of data; (3) Management and display of rescue team personnel and equipment data, obtaining real-time display of rescue team personnel and equipment monitoring data, and dynamically updating the situation, supporting abnormal data annotation, display and early warning; (4) Trend display function for personnel and equipment data, record data history information, and display data change trends for each personnel and equipment data in the form of lists, linear graphs, and trend graphs; (5) Management and display functions for geographic data, supporting the marking, adding information and display of key locations of key areas, buildings, roads and accident points; (6) Management and display functions for weather, exercise documents, and message data, supporting the overlay display of weather, exercise documents, and message data, and dynamic updates; (7) Management and display of pollution area data: record data according to the coordinate area, display the pollution area in the form of heat map and pollution model, and update it dynamically, supporting the display and hiding switching of pollution areas; (8) The function of situation review during the exercise can review the historical situation according to the timeline by reading the exercise records, and can cooperate with the simulation system to dynamically display the entire exercise process; it can review and replay the situation, actions, monitoring videos, command documents, command instructions, and information transmission of the participating teams during the exercise; and support the control of the display process, including fast forward, step, pause, and jump to a specified time; (9) It has virtualization support function. The module supports simulation and can form a virtual situation based on the simulation data generated by the model. It supports dynamic update of the situation based on the model data. The display, data management and display, and interface operation of the virtual situation are consistent with the real situation.

8. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The deduction and simulation system is composed of a model library and a deduction engine. The model library includes scenario models, solution models, special situation models, and task scheduling models. The scenario models include radiation models, weather models, reactor models, and complex accident models, which are used to simulate on-site situations and situation change processes. The scheme model is composed of multiple task models, each of which is composed of multiple instruction models, rescue team models and route models, and is used to simulate the execution of the entire rescue plan; the special situation model is composed of multiple accident models and multiple rescue team models, and is used to simulate sudden dangerous situations; the task conditioning model is composed of multiple task models, and simulates the conditioning task when an alarm is triggered; the radiation model is used to simulate on-site source item data; the reactor model is used to simulate reactor monitoring data; the accident model is used to simulate non-reactor accidents; the rescue team model is used to simulate the personnel and equipment data of the rescue team; the route model is used to simulate the movement route of the rescue team; the instruction model is used to simulate the task execution status; the weather model is used to simulate on-site meteorological data, and the meteorological data is used by the pollution model to estimate the contaminated area.

9. The training system for nuclear emergency rescue commanders according to claim 1, characterized in that: The nuclear emergency database includes a database and a file server; wherein: the database adopts the Galera architecture cluster deployment, is used to store external monitoring data and read the monitoring data of the nuclear emergency rescue commander training system, and synchronize it to the cloud database; the database reads the map data and road network data of the nuclear emergency rescue commander training system, and stores them in the map server; the file server is used to store other data of the nuclear emergency rescue commander training system, and record file information and paths in the database; wherein: the map server stores tile images; the file server stores video and audio files.

10. Application of a training system for nuclear emergency rescue commanders in training nuclear emergency rescue team commanders, characterized by: The training method for the commander of the nuclear emergency rescue team comprises the following steps: S21. The commander formulates a scenario based on the initial situation transmitted from the directorate or the accident site; the scenario includes source parameters, weather conditions, and accident information; the initial situation includes geographic information, markings, and map images; S22. The command and guidance system generates a simulated nuclear contaminated area on the nuclear emergency situation map based on the scenario developed in step S21 and the on-site monitoring data, and overlays the on-site situation to generate an accident scenario. S23. The commander formulates a rescue plan based on the accident scenario generated in step S22, the nuclear emergency rescue plan and auxiliary suggestions; S24, optimizing the rescue plan developed in step S23 through virtual simulation, generating a command document, and uploading and issuing it in the form of a command document; S25. The commander monitors the progress of the mission and the situation by marking and mapping the situation, and adjusts the mission and communicates when special situations arise; S26. During the nuclear emergency rescue process, all data shall be saved in the nuclear emergency database for experts to review and evaluate the drill process, and the records shall be archived.

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