Groundwater environment risk evolution simulation and early warning system for thermal power plant based on digital twinning

Abstract

This invention discloses a digital twin-based simulation and early warning system for the environmental risk evolution of groundwater in thermal power plants, comprising a data acquisition module, a digital twin model construction module, a risk evolution simulation module, a risk assessment module, an early warning module, and a visualization module. By constructing an integrated digital twin model encompassing geological structure, groundwater flow, and pollutant migration, this invention achieves real-time dynamic simulation of the spatiotemporal evolution of pollution plumes in groundwater. The system utilizes real-time data from the data acquisition module to drive continuous model operation, enabling early prediction of pollution diffusion trends and impact ranges, transforming passive post-event monitoring into proactive early warning, and significantly shortening risk response time. This invention improves the accuracy of pollution risk assessment under complex hydrogeological conditions, and the 3D visualization module provides managers with an intuitive decision support interface, effectively reducing the blind spots and overall costs of groundwater pollution control in thermal power plants.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and risk early warning technology, specifically to a digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants. Background Technology

[0002] During the production and operation of thermal power plants, there is a risk of leakage in areas such as ash fields, oil storage tanks, and desulfurization wastewater ponds. This could lead to pollutants such as heavy metals, sulfides, and oils entering the groundwater environment, causing long-term and difficult-to-remediate pollution.

[0003] Traditional groundwater environmental monitoring methods mainly rely on periodic water sample collection and laboratory analysis. This method has a long sampling cycle, discrete data, and is difficult to capture the dynamic migration process of pollutants, let alone predict the spatiotemporal evolution trend of pollution plumes. With the development of digital twin technology, it has become possible to realize real-time state simulation by constructing virtual mappings of physical entities.

[0004] However, existing digital twin systems mostly focus on equipment operation status or surface environment, making it difficult to effectively simulate the risk evolution of pollutant transport patterns in groundwater, a hidden and heterogeneous medium. In particular, they cannot dynamically assimilate real-time monitoring data with complex hydrogeological models, resulting in early warning responses lagging behind the actual pollution diffusion process. Summary of the Invention

[0005] To address this issue, the present invention provides a digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants, in order to solve the problem in existing technologies that cannot dynamically assimilate real-time monitoring data with complex hydrogeological models, resulting in early warning responses lagging behind the actual pollution diffusion process.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants includes:

[0008] The data acquisition module is used to collect groundwater level, water quality parameters, soil parameters, and emission source data of the thermal power plant area;

[0009] The digital twin model construction module connects to the data acquisition module and constructs a digital twin model of the groundwater environment of the thermal power plant based on the acquired data. The digital twin model includes a geological structure sub-model, a groundwater flow sub-model, and a pollutant migration sub-model.

[0010] The risk evolution simulation module connects to the digital twin model building module, receives real-time collected data to drive the digital twin model to run, simulates the spatiotemporal distribution evolution of groundwater pollutants, and generates pollution plume diffusion prediction data.

[0011] The risk assessment module connects to the risk evolution simulation module and calculates the risk level and impact range based on pollution plume diffusion prediction data.

[0012] The early warning module is connected to the risk assessment module. It compares the risk level with a preset threshold and generates an early warning message when the risk level exceeds the preset threshold.

[0013] The visualization module connects the digital twin model building module, the risk evolution simulation module, and the early warning module, and is used to display the digital twin model, the dynamic process of pollution plume diffusion, and the early warning location in three dimensions.

[0014] Preferably, the data acquisition module includes an online monitoring submodule and a manual input submodule. The online monitoring submodule consists of a water level sensor, a conductivity sensor, a pH sensor, a heavy metal ion selective electrode, and a distributed fiber optic temperature sensor deployed in the groundwater monitoring well of the thermal power plant. The online monitoring submodule transmits the collected data to the digital twin model construction module in real time via a wireless sensor network. The manual input submodule is used to input soil adsorption coefficient, dispersion, and historical emission records of the thermal power plant obtained from laboratory analysis.

[0015] Preferably, the digital twin model construction module includes a model initialization unit and a real-time correction unit. The model initialization unit establishes a geological structure sub-model containing stratigraphic information, porosity distribution, and permeability coefficient field based on geological survey data, and establishes a groundwater flow sub-model and a pollutant migration sub-model based on the initial water level and initial water quality concentration field. The real-time correction unit uses a data assimilation algorithm to use the groundwater level and water quality parameters acquired in real time by the data acquisition module as observation data to dynamically adjust the permeability coefficient, dispersion, and reaction rate parameters, so as to minimize the error between the state variables of the digital twin model and the actual monitoring data.

[0016] Preferably, the risk evolution simulation module includes a pollution source inversion unit and a scenario simulation unit. The pollution source inversion unit estimates the release location, release time, and release intensity of the upstream pollution source based on the time series data of pollutant concentration in the downstream monitoring well and the flow field information calculated by the groundwater flow sub-model. The scenario simulation unit simulates the diffusion path, concentration decay trend, and arrival time of the pollution plume within a set future time window based on the parameter field of the current digital twin model and the output results of the pollution source inversion unit.

[0017] Preferably, the risk assessment module includes an exposure assessment unit and a hazard characterization unit. The exposure assessment unit receives pollution plume diffusion prediction data generated by the risk evolution simulation module, overlays the pollutant concentration distribution in the prediction data with the groundwater flow field grid, and calculates the average concentration of each pollutant in each grid cell during the exposure duration. The hazard characterization unit pre-stores reference doses or reference concentrations obtained from the toxicity database for each pollutant, divides the average concentration of each pollutant by the corresponding reference dose or reference concentration to obtain a single risk index for each pollutant in each grid cell, and then weights and sums the single risk indices of all pollutants according to the toxicity weighting factor of each pollutant. The toxicity weighting factor is jointly determined by the carcinogenicity level of the pollutant and the environmental standard limit. The result of the weighted sum is used as the comprehensive risk index. Grid cells with a comprehensive risk index exceeding 1.0 are marked as risk areas. The comprehensive risk index is divided into four levels according to the numerical value: low-risk area, medium-risk area, high-risk area, and extremely high-risk area.

[0018] Preferably, the early warning module includes a threshold management submodule and an early warning release submodule. The threshold management submodule stores multi-level early warning thresholds preset for different receptor types of thermal power plants. Receptor types include plant boundaries, groundwater intakes, and surface water bodies. The early warning release submodule receives the comprehensive risk index and spatial distribution of risk areas output by the risk assessment module, compares the comprehensive risk index with the multi-level early warning thresholds level by level, and generates early warning information containing risk level, risk area boundary coordinates, and arrival time when the comprehensive risk index exceeds the lowest level early warning threshold. The early warning information is released in three different ways according to the risk level: SMS push, central control room pop-up alarm, and audible and visual alarm.

[0019] Preferably, the visualization module includes a 3D scene rendering unit and a dynamic evolution playback unit. The 3D scene rendering unit establishes a 3D scene containing surface buildings, monitoring well locations, and groundwater levels based on the geological structure sub-model output by the digital twin model construction module. The risk areas marked by the risk assessment module are superimposed on the 3D scene in the form of semi-transparent colored isosurfaces. The dynamic evolution playback unit stores the pollution plume diffusion prediction data sequence generated by the risk evolution simulation module at different time steps. It supports users to select any start and end time to perform accelerated playback or frame-by-frame playback of the pollution plume diffusion process, and displays the risk level and the number of affected grid cells corresponding to the current frame in real time during the playback process.

[0020] Preferably, the visualization module also integrates an interactive correction submodule. The interactive correction submodule allows users to manually edit the layer interface positions and permeability coefficient values ​​of the geological structure submodel in the 3D scene. The interactive correction submodule passes the edited parameters to the real-time correction unit of the digital twin model construction module. The real-time correction unit reruns the data assimilation process with the edited parameters as the initial conditions to generate an updated digital twin model. The visualization module then refreshes the display results of the risk area in the 3D scene.

[0021] This invention offers the following advantages: By constructing an integrated digital twin model encompassing geological structure, groundwater flow, and pollutant migration, it achieves real-time dynamic simulation of the spatiotemporal evolution of pollution plumes in groundwater. The system utilizes real-time data from the data acquisition module to drive continuous model operation, enabling early prediction of pollution diffusion trends and impact ranges. This transforms passive post-event monitoring into proactive early warning, significantly shortening risk response time. Furthermore, through multi-source data fusion and automatic model correction, this invention improves the accuracy of pollution risk assessment under complex hydrogeological conditions. The visualization module's 3D display function provides managers with an intuitive decision support interface, effectively reducing the blind spots and overall costs of groundwater pollution control in thermal power plants. Attached Figure Description

[0022] To more intuitively illustrate the prior art and this application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be regarded as limiting conditions for implementing this application; for example, based on the technical concept disclosed in this application and the exemplary drawings, those skilled in the art are able to easily make conventional adjustments or further optimizations to the addition / reduction / classification, specific shapes, positional relationships, connection methods, size ratios, etc. of certain units (components).

[0023] Figure 1 A block diagram of a digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants, provided in an embodiment of this application. Detailed Implementation

[0024] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these embodiments are merely for further explanation of the present invention and should not be construed as limiting the scope of protection of the present invention. Technical engineers in the field can make some non-essential improvements and adjustments to the present invention based on the above-described content. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Please see Figure 1 A digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants, including:

[0026] The data acquisition module is used to collect groundwater level, water quality parameters, soil parameters, and emission source data of the thermal power plant area;

[0027] The digital twin model construction module connects to the data acquisition module and constructs a digital twin model of the groundwater environment of the thermal power plant based on the acquired data. The digital twin model includes a geological structure sub-model, a groundwater flow sub-model, and a pollutant migration sub-model.

[0028] The risk evolution simulation module connects to the digital twin model building module, receives real-time collected data to drive the digital twin model to run, simulates the spatiotemporal distribution evolution of groundwater pollutants, and generates pollution plume diffusion prediction data.

[0029] The risk assessment module connects to the risk evolution simulation module and calculates the risk level and impact range based on pollution plume diffusion prediction data.

[0030] The early warning module is connected to the risk assessment module. It compares the risk level with a preset threshold and generates an early warning message when the risk level exceeds the preset threshold.

[0031] The visualization module connects the digital twin model building module, the risk evolution simulation module, and the early warning module, and is used to display the digital twin model, the dynamic process of pollution plume diffusion, and the early warning location in three dimensions.

[0032] This embodiment provides a digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants. The system is applied to a coal-fired power plant in northern my country. The power plant has an ash field, a desulfurization wastewater pond and three oil storage tanks. Quaternary loose porous aquifers are distributed in and around the plant area. The groundwater flows from northwest to southeast. There is a village drinking water source well 1.5 kilometers downstream.

[0033] First, a data acquisition module was deployed within the power plant area. This module includes an online monitoring submodule and a manual input submodule. The online monitoring submodule deployed eight groundwater monitoring wells at locations including the upstream background area, 10 meters, 50 meters, and 100 meters downstream of the pollution source, and at the water source well. Each well was equipped with a water level sensor, conductivity sensor, pH sensor, and heavy metal ion selective electrode (for lead, cadmium, and arsenic). Distributed fiber optic temperature sensors were embedded in the foundation layer at the bottom of the ash field and desulfurization wastewater pond to detect temperature anomalies caused by leakage. All sensors transmitted the collected data in real time to a digital twin server located in the power plant's central control room via a ZigBee wireless sensor network. The manual input submodule was used to input soil adsorption coefficients obtained from laboratory analysis (e.g., the adsorption distribution coefficient for lead in the cohesive soil layer at the bottom of the ash field is 120 L / kg), longitudinal dispersion (5.2 m), and emission records from the power plant over the past five years.

[0034] Secondly, the digital twin model construction module runs on the server. The model initialization unit establishes a three-dimensional geological structure sub-model based on geological survey data. This model contains four layers: topsoil, silty clay, fine sand, and clay. The porosity (0.32–0.45) and permeability coefficient (vertical permeability coefficient of silty clay is 0.05 m / d, and horizontal permeability coefficient of fine sand is 8.5 m / d) of each layer are stored in the form of a spatial distribution field.

[0035] The groundwater flow sub-model was solved using the finite element method, with boundary conditions set as a constant head boundary (water level 55.2 m) on the northwest side and an outflow boundary on the southeast side. The initial settings for the pollutant migration sub-model were 0 mg / L for lead and 0 mg / L for all grid cells. The real-time correction unit employed an ensemble Kalman filter algorithm, using real-time water level and lead / arsenic concentration data from eight monitoring wells weekly as observations to dynamically adjust the permeability and dispersion fields. This reduced the root mean square error between the model predictions and measured values ​​from an initial 0.23 mg / L to 0.07 mg / L.

[0036] Then, the risk evolution simulation module was activated. The pollution source inversion unit read time-series data of lead concentration in a monitoring well 50 meters downstream, showing a decrease from 0.01 mg / L on day 30 to 0.08 mg / L on day 60. Combined with flow field information calculated from the groundwater flow sub-model with an average flow velocity of 0.12 m / d, it deduced that the pollution source was located 5 meters east of the center of the bottom of the ash field, with an initial release time of day 25 and a total release mass of 12.5 kg. The scenario simulation unit, based on the current corrected digital twin model, set a time window of 180 days and simulated the pollution plume diffusion path in a forward direction. The simulation results showed that the lead pollution plume front reached a location 210 meters downstream of the ash field after 120 days, with a maximum concentration of 0.32 mg / L. After 165 days, the front reached the water source well, where the concentration was expected to be 0.015 mg / L.

[0037] The exposure assessment unit overlays the lead concentration distribution from the pollution plume diffusion prediction data onto a groundwater flow field grid (grid size 10 m × 10 m) to calculate the average lead concentration in each grid cell during the exposure duration. The hazard characterization unit uses a pre-stored reference dose of 0.01 mg / L for lead, obtained from a toxicity database. The single risk index for lead in each grid cell is the average concentration divided by 0.01 mg / L. Since lead is the only major pollutant detected at this site, the hazard characterization unit sets the lead toxicity weighting factor to 1, and the overall risk index equals the lead single risk index. If multiple pollutants are present, the hazard characterization unit determines the toxicity weighting factor for each pollutant based on its carcinogenicity level and environmental standard limits, and the weighted sum of the single risk indices of all pollutants is used as the overall risk index. For example, the average lead concentration in the grid cell containing the water source well is 0.012 mg / L, the single risk index is 1.2, and the overall risk index is 1.2. Grid cells with a comprehensive risk index exceeding 1.0 are marked as risk areas, with 1.0–2.0 being medium-risk areas, 2.0–5.0 being high-risk areas, and greater than 5.0 being extremely high-risk areas. The grid containing the water source well, with a comprehensive risk index of 1.2, is classified as a medium-risk area.

[0038] The threshold management submodule of the early warning module stores multi-level early warning thresholds for three receptor types: plant boundary, water source well, and downstream surface water. The first-level early warning threshold for water source wells is a comprehensive risk index of 0.8 (indicating attention), the second-level threshold is 1.0 (warning of potential exceedance), and the third-level threshold is 1.5 (severe exceedance warning). The early warning release submodule receives the comprehensive risk index at the water source well from the risk assessment module (this index is calculated by the hazard characterization unit using a weighted summation method; since only lead was detected at this site, the weighted summation result equals the lead single risk index of 1.2). This index is compared with the second-level early warning threshold of 1.0 and the third-level early warning threshold of 1.5. If the index exceeds the second-level threshold but not the third-level threshold, a second-level early warning is generated. This information includes a risk level of "medium risk," the boundary coordinates of the risk area (extending from 120 meters to 220 meters downstream of the ash field), and the estimated time of arrival at the water source well (165 days later). The Level 2 warning information is displayed in the power plant's environmental management system via a pop-up alarm in the central control room, and at the same time, SMS notifications are sent to the power plant's environmental protection specialists and management.

[0039] The visualization module runs on the server and outputs to the large screen in the central control room. The 3D scene rendering unit builds a 3D scene based on the geological structure sub-model. Surface buildings and monitoring well locations are displayed as 3D icons, and the groundwater level is presented as a semi-transparent blue curved surface. The medium-risk area marked by the risk assessment module is superimposed on the 3D scene as an orange semi-transparent isosurface, displayed as a narrow plume extending from downstream of the ash field to in front of the water source well. The dynamic evolution playback unit stores the pollution plume concentration distribution data sequences generated by the risk evolution simulation module at six time steps: 30 days, 60 days, 90 days, 120 days, 150 days, and 180 days. Managers select the start time (day 30) and end time (day 180) on the touchscreen. The system accelerates the playback of the pollution plume diffusion process at a rate of one time step per second, while simultaneously displaying the risk level (gradually changing from low risk to medium risk) and the number of affected grid cells (increasing from 12 to 58) in real time in the upper left corner of the playback interface.

[0040] Considering the uncertainties in geological parameters, the visualization module also integrates an interactive correction submodule. Geological engineers discovered that the actual clay layer thickness at the bottom of the ash field was 0.8 meters thicker than in the initial geological survey data. Therefore, they manually edited the layer interface position of the geological structure submodel in the 3D scene, increasing the clay layer thickness by 0.8 meters and modifying the lead adsorption coefficient of this layer from 120 L / kg to 180 L / kg. The interactive correction submodule passed the edited parameters to the real-time correction unit of the digital twin model construction module. The real-time correction unit re-runs the ensemble Kalman filter data assimilation process using the edited parameters as initial conditions. After recalculation, the updated digital twin model showed that the time for the pollution plume front to reach the water source well was delayed from 165 days to 198 days, and the comprehensive risk index at the water source well decreased from 1.2 to 0.9, downgrading it to a low-risk area. The visualization module then refreshed the 3D scene, the orange isosurface of the risk area shrank, and the early warning module canceled the level two warning and downgraded it to a level one attention alert. This demonstrates that the system has good user interactivity and model adaptability, supporting the scientific adjustment of management decisions.

[0041] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A digital twin-based simulation and early warning system for the evolution of groundwater environmental risks in thermal power plants, characterized in that, include: The data acquisition module is used to collect groundwater level, water quality parameters, soil parameters, and emission source data of the thermal power plant area; The digital twin model construction module constructs a digital twin model of the groundwater environment of a thermal power plant based on the collected data. The digital twin model includes a geological structure sub-model, a groundwater flow sub-model, and a pollutant migration sub-model. The risk evolution simulation module receives real-time data to drive the operation of the digital twin model, simulates the spatiotemporal distribution evolution of groundwater pollutants, and generates pollution plume diffusion prediction data. The risk assessment module calculates the risk level and impact range based on pollution plume diffusion prediction data; The early warning module compares the risk level with a preset threshold and generates an early warning message when the risk level exceeds the preset threshold. The visualization module is used to display the digital twin model, the dynamic process of pollution plume diffusion, and the early warning location in three dimensions.

2. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 1, characterized in that, The data acquisition module includes an online monitoring submodule and a manual input submodule. The online monitoring submodule consists of a water level sensor, a conductivity sensor, a pH sensor, a heavy metal ion selective electrode, and a distributed fiber optic temperature sensor deployed in the groundwater monitoring wells of the thermal power plant. The online monitoring submodule transmits the collected data to the digital twin model construction module in real time via a wireless sensor network. The manual input submodule is used to input soil adsorption coefficient, dispersion, and historical emission records of the thermal power plant obtained from laboratory analysis.

3. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 2, characterized in that, The digital twin model construction module includes a model initialization unit and a real-time correction unit. The model initialization unit establishes a geological structure sub-model based on geological survey data, which includes stratigraphic information, porosity distribution, and permeability coefficient field. It also establishes a groundwater flow sub-model and a pollutant migration sub-model based on the initial water level and initial water quality concentration field. The real-time correction unit uses a data assimilation algorithm to use the groundwater level and water quality parameters acquired in real time by the data acquisition module as observation data to dynamically adjust the permeability coefficient, dispersion, and reaction rate parameters, so as to minimize the error between the state variables of the digital twin model and the actual monitoring data.

4. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 3, characterized in that, The risk evolution simulation module includes a pollution source inversion unit and a scenario simulation unit. The pollution source inversion unit estimates the release location, release time, and release intensity of the upstream pollution source based on the time series data of pollutant concentration in the downstream monitoring well and the flow field information calculated by the groundwater flow sub-model. The scenario simulation unit simulates the diffusion path, concentration decay trend, and arrival time of the pollution plume within a set future time window based on the parameter field of the current digital twin model and the output results of the pollution source inversion unit.

5. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 4, characterized in that, The risk assessment module includes an exposure assessment unit and a hazard characterization unit. The exposure assessment unit receives pollution plume diffusion prediction data generated by the risk evolution simulation module, overlays the pollutant concentration distribution in the prediction data with the groundwater flow field grid, and calculates the average concentration of each pollutant in each grid cell during the exposure duration. The hazard characterization unit pre-stores reference doses or reference concentrations obtained from the toxicity database for each pollutant, divides the average concentration of each pollutant by the corresponding reference dose or reference concentration, and obtains a single risk index for each pollutant in each grid cell. The hazard characterization unit then performs a weighted summation of the single risk indices of all pollutants according to the toxicity weighting factor of each pollutant. The toxicity weighting factor is jointly determined by the carcinogenicity level of the pollutant and the environmental standard limit. The result of the weighted summation is used as the comprehensive risk index. Grid cells with a comprehensive risk index exceeding 1.0 are marked as risk areas. The comprehensive risk index is divided into four levels according to its numerical value: low-risk area, medium-risk area, high-risk area, and extremely high-risk area.

6. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 5, characterized in that, The early warning module includes a threshold management submodule and an early warning release submodule. The threshold management submodule stores multi-level early warning thresholds preset for different receptor types of thermal power plants. Receptor types include plant boundaries, groundwater intakes, and surface water bodies. The early warning release submodule receives the comprehensive risk index and spatial distribution of risk areas output by the risk assessment module, and compares the comprehensive risk index with the multi-level early warning thresholds step by step. When the comprehensive risk index exceeds the lowest level early warning threshold, an early warning message containing the risk level, risk area boundary coordinates, and arrival time is generated. The early warning message is released in three different ways according to the risk level: SMS push, central control room pop-up alarm, and audible and visual alarm.

7. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 6, characterized in that, The visualization module includes a 3D scene rendering unit and a dynamic evolution playback unit. The 3D scene rendering unit establishes a 3D scene containing surface buildings, monitoring well locations, and groundwater levels based on the geological structure sub-model output by the digital twin model construction module. The risk areas marked by the risk assessment module are superimposed on the 3D scene in the form of semi-transparent colored isosurfaces. The dynamic evolution playback unit stores the pollution plume diffusion prediction data sequence generated by the risk evolution simulation module at different time steps. It supports users to select any start and end time to perform accelerated playback or frame-by-frame playback of the pollution plume diffusion process, and displays the risk level and the number of affected grid cells corresponding to the current frame in real time during playback.

8. The digital twin-based groundwater environmental risk evolution simulation and early warning system for thermal power plants according to claim 7, characterized in that, The visualization module also integrates an interactive correction submodule, which allows users to manually edit the layer interface positions and permeability coefficient values ​​of the geological structure submodel in the 3D scene. The interactive correction submodule passes the edited parameters to the real-time correction unit of the digital twin model construction module. The real-time correction unit uses the edited parameters as initial conditions to rerun the data assimilation process and generate an updated digital twin model. The visualization module then refreshes the display results of the risk areas in the 3D scene.

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