TWI466052B - An integrated cross-scaled consequence analysis system for toxic/chemical disaster - Google Patents

Description

Integrated cross-scale poisoning disaster analysis system

The present invention relates to an analytical system, and more particularly to an integrated cross-scale poisoning disaster consequence analysis system for simulating and analyzing the hazards posed by industrial accidents involving chemical spills.

In recent years, as the demand for energy and electronic products continues to rise, the scale of the petrochemical and semiconductor industries continues to expand. This trend has led some new factories to store a greater amount of hazardous substances than ever before in order to meet the needs of the process. In the event of a serious chemical spill in the above-mentioned factories, the wide area affected by the damage will not only cause work safety problems, but also may involve public health and environmental problems. However, there is no better method or suitable tool. Risk assessment of such hazards.

At present, most studies on atmospheric diffusion are usually based on the Gaussian diffusion model or the convection-diffusion equation. This model can simulate the diffusion and sedimentation behavior of pollutants in the mid-scale range of 2 to 2000 km, and The computer requires low specification and short simulation time. However, the Gaussian diffusion model does not consider the obstacle effect, and cannot simulate the influence of local eddy currents generated by wind and obstacles on the flow of pollutants in a local area of several meters to 2 kilometers, resulting in poor simulation resolution. .

Computational Fluid Dynamics (CFD) mode usually analyzes Navier-Stokes partial differential equations by finite volume method, which can simultaneously consider the heat transfer, mass transfer, dynamic transmission and building of hazardous materials flowing in the fluid. Airflow vortex effect caused by obstacles and terrain (Eddy Effect) and other problems, so compared with the aforementioned Gaussian diffusion mode, the calculation of the change in the concentration of pollutants in the local region of the computational fluid dynamics mode within a few tens of meters is more accurate. However, computational fluid dynamics consumes a lot of computer resources and takes longer to simulate, plus the size of the grid affects its resolution and is not suitable for a wide range of simulations.

Accordingly, it is an object of the present invention to provide an integrated cross-scale poisoning disaster consequence analysis system that can improve the accuracy of the simulation area and the accuracy of the simulation, and save the resources and time required for the simulation operation.

Therefore, the integrated cross-scale poisoning disaster consequence analysis system of the present invention can simulate and analyze a micro-scale range of the plant area in the occurrence of a chemical leakage accident through a computer device, and the wind located below the plant area. The risk caused by the mesoscale range. The integrated cross-scale poisoning disaster consequence analysis system includes: an accident plant area consequence analysis module, and a mesoscale consequence analysis module.

The accident site analysis module includes a situational simulation mode and a lethal analysis mode. The scenario simulation mode includes a model construction simulation unit and an animation output analysis unit. The model construction simulation unit can input the construction equipment data, grid setting parameters and simulation situation parameters of the plant area, and output a three-dimensional model of the plant area and a flow field concentration data of a plant. The animation output analysis unit can input the flow field concentration data of the plant and output an animated map of the flow field concentration of the plant in which the concentration of the chemical in each grid changes with time. The lethal analysis mode can be used to input the flow field concentration data of the plant and output a dead rate map of the plant.

The mesoscale consequence analysis module includes a gas cloud numerical interception mode, a context simulation mode, and a lethal analysis mode. The gas cloud numerical interception mode can input the flow field concentration data of the plant area and output a gas cloud discharge amount. The situation simulation mode is configured to input grid setting parameters, emission source setting parameters, environment setting parameters and output setting parameters, and output a mesoscale simulation area map and a concentration distribution plan according to the gas cloud emission amount. The lethal analysis mode is available for inputting the concentration distribution plan and outputting a mesoscale lethal probability map. The grid setting parameters include the origin coordinates, the grid size, and the number of grids. The source setting parameters include emission source coordinates. The environmental setting parameters include wind speed, wind direction probability, atmospheric stability probability, surface type and ambient temperature. The output setting parameters include simulation execution time, time interval, and type of leaked substance.

The effect of the invention is that the micro-scale range analysis of the accident plant area is performed by the accident plant analysis component module to output a plant flow field concentration data, and the gas cloud numerical interception mode of the mesoscale consequence analysis module can directly accept the The gas flow concentration of the plant is output and a gas cloud discharge is output to facilitate the mesoscale consequence analysis module to perform the mid-scale analysis of the downwind of the plant. By integrating the advantages of the microscale mode and the mesoscale mode, the limitation of the simulation area and the accuracy of the simulation can be improved, and the resources and time required for the operation can be saved.

The above and other technical contents, features and advantages of the present invention will be apparent from the following detailed description of the preferred embodiments.

Referring to FIG. 1, a preferred embodiment of the integrated cross-scale poisoning disaster consequence analysis system of the present invention is suitable for use in a computer device, such as a computer, and executed by the computer device. The integrated cross-scale poisoning disaster analysis system analyzes a chemical spill in a plant area. The accident is for a micro-scale of several hundred meters around the plant and 20 kilometers around the wind below the plant. The mesoscale range and the hazards and risks of a micro-scale range of a few hundred meters around a selected target town.

The user can transfer the required data or settings into the integrated cross-scale poisoning disaster analysis system via a keyboard or a transmission line, and through a display or a display not shown. An output device such as a printer not shown, outputs the data produced by the integrated cross-scale poisoning disaster consequence analysis system.

The integrated cross-scale poisoning disaster consequence analysis system of the embodiment comprises an accident plant area consequence analysis module, a mesoscale consequence analysis module 2, a target town consequence analysis module 3, and a risk quantification module 4.

The accident plant area consequence analysis module 1 of the present embodiment includes a situation simulation mode 11 and a lethal analysis mode 12. The scenario simulation mode 11 includes a model construction simulation unit 111, and an animation output analysis unit 112.

The model construction simulation unit 111 can be used by the user to set the construction equipment data, the grid setting parameters and the simulation situation parameters of the plant, and calculate a plant flow field concentration data and a three-dimensional model of the plant area as shown in FIG. 2 . its The flow field concentration data of the plant contains information on the chemical concentration values in each grid at each time point. Since the establishment of the model is not the focus of the improvement of the present invention, it will not be described in detail.

In this embodiment, the construction equipment parameters include the length, width, height of the building and the coordinate position of the building in the grid. The grid setting parameters include the origin coordinates, the grid size, and the number of grids. The simulated context parameters include initial conditions and boundary conditions. The initial conditions include simulation time, gas type, gas leakage and concentration, monitoring point location, and ignition location. The boundary conditions include wind speed, wind direction, and the behavior of the fluid to freely enter and exit the various boundary layers of the simulation range. Among them, the initial conditions and boundary conditions are all relevant initial values and boundary values needed to solve the partial differential simultaneous equations. In addition, this embodiment is an example of simulating the leakage of a chlorine gas storage tank.

The animation output analysis unit 112 can construct the flow field concentration data of the plant generated by the simulation unit 111 according to the model, and calculate an animation of the flow field concentration of the plant in which the concentration of the chemical in each grid changes with time. Figure. It should be noted that the flow field concentration animated map of the plant area is in the form of a three-dimensional animated map, and can directly observe the impact range and process of the accident with the time axis, and can cut the three-dimensional animated map to analyze and hide in the surrounding of the building. Or the concentration change process of the internal chemical gas cloud, and the figure (b) of the figure (a) of Fig. 3 is the interception of the flow field concentration animation of the plant in the case of the simulation time of 1 second and 12 seconds, respectively. Instantaneous plant flow field concentration map, wherein each grid has a chemical concentration, and the concentration of the chemical concentration can be observed by the right concentration scale according to different colors. In this embodiment, the simulated chlorine storage tank is leaked, and the red color represents The concentration of the chemical in this place exceeds the highest concentration of chlorine. The TLV-Ceiling is 1000 parts per million (ppm), which is 0.00100 moles per unit. The boundary of the chemical gas cloud is blue, and the average limit of chlorine is used. TLV-TWA) is 0.5 parts per million (ppm), which is the 0.000005 mole fraction in the figure. The results simulated in Figure 3 show that the chemical gas cloud gradually diffuses toward the downwind due to the wind direction.

The lethal analysis mode 12 includes a toxic gas effect unit 121, a lethal probability conversion unit 122, and a plot output unit 123.

The toxic gas effect unit 121 can input the first toxic gas parameter ( K ₁ ), the second toxic gas parameter ( K ₂ ) and the toxicity index value ( n ), and cooperate with the model to construct the plant flow field concentration data calculated by the simulation unit 111. By means of equation (1), a hazard probability unit value ( Y _{x, y, z} ) can be calculated. See Table 1 for the first toxic gas parameter ( K ₁ ), the second toxic gas parameter ( K ₂ ), and the toxicity index value ( n ).

Where: Y _{x, y, z} = hazard probability unit value; K ₁ = first toxic gas parameter; K ₂ = second toxic gas parameter; Δ t = effective exposure time in different positions (minutes, min); n = toxicity Index value; F _{x, y, z} = toxic gas concentration value at different positions (parts per million, ppm); it should be noted that the unit of the concentration of the flow field concentration data after the output of the plant is the molar fraction, therefore Multiply by 10 ^{6 to} convert the unit of concentration into parts per million, and obtain the toxic gas concentration value F _{x, y, z} at the different positions, and then the effective exposure time (Δ t ) in the different position After the toxic gas concentration values ( F _{x, y, z} ) at different positions are multiplied, the sum is obtained, and the obtained value is substituted into the formula (1), and then the first toxic gas parameter and the second toxic gas parameter are substituted. Hazard probability unit value ( Y _{x, y, z} ). A specific location of personnel exposure time in which the different positions of the effective exposure time (△ t) is defined as the amount of the chemical concentration is greater than the average value Shu.

The lethal probability conversion unit 122 can input the hazard probability unit value ( Y _{y, y, z} ) produced by the toxic gas effect unit 121, and calculate a person lethality rate ( P ) by the formula (2).

Where: P = person death rate (%); Y _{x, y, z} = hazard probability unit value; u = integral variable.

Wherein, the integral variable ( u ) is an integral dummy variable, which exists in the integral formula and does not need to be input separately.

The drawing output unit 123 can input the death rate of the person, and cooperate with the three-dimensional model of the plant to fold the death rate of the person to the three-dimensional model of the plant, and output a plant death rate diagram as shown in FIG. 4. In the part of the model nesting, the drawing output unit 123 is completed by a drawing software (Matfor), as follows: Firstly, the model construction of the accident plant area consequence analysis module 1 is constructed in the simulation unit 111. The system converts the building construction system of the drawing output unit 123 into a one-to-one size. Then, the personnel lethality rate of each grid in the three-dimensional model of the plant is imported into the array of the drawing output unit 123 according to the corresponding grid, and the drawing output unit 123 can individually target the difference of the values. Color rendering. As shown in Fig. 4, the probability of death of personnel can be clearly determined by the right scale according to the color of the right scale. The probability of death of the personnel in the plant is 15 meters on the ground and the x-axis. The projection of the profile shows its distribution, and the simulation results show that the lethal range is limited to the central extent of the accident field.

The mesoscale consequence analysis module 2 of the present embodiment includes a gas cloud numerical interception mode 21, a context simulation mode 22, and a lethal analysis mode 23.

The gas cloud numerical interception mode 21 can be based on the analysis of the accident plant area consequences model. The model of Group 1 constructs the flow field concentration data generated by the simulation unit 111, and calculates a gas cloud discharge amount, wherein the flow field concentration data of the plant contains the chemical concentration in each grid at each time point. Numerical information, and the amount of gas cloud emissions represents the amount of change in chemical concentration over each time interval.

The calculation process of the gas cloud numerical interception mode 21 is as follows: the flow field concentration data generated by the model construction simulation unit 111 is brought into the corresponding grid matrix, wherein the value in the grid is greater than zero is the chemical The concentration of the cloud of the product, because each grid size is known, the weight of the cloud in the grid can be calculated. The sum of the weights of the gas clouds in each of the above grids is the total amount of gas clouds in the simulation range at that time. Because the total amount of gas clouds in the simulation range will gradually flow out of the simulated boundary as the gas cloud diffuses and decreases continuously, the total amount of gas clouds in the simulated range will be subtracted in the adjacent two time periods, that is, within the time interval. The amount of gas cloud flowing out of the simulated boundary, which is the amount of gas cloud emissions described in this embodiment.

The situation simulation mode 22 can input the grid setting parameter, the emission source setting parameter, the environment setting parameter and the output setting parameter, and cooperate with the gas cloud discharge amount outputted by the gas cloud numerical interception mode 21, and calculate a figure as shown in FIG. 5. The mesoscale simulation area map is a plan view of the concentration distribution as shown in FIG. It should be noted that the concentration distribution plan of FIG. 6 is a mesh size and number required to simulate the gas cloud emission according to the mesoscale simulation area map, and the three-dimensional grid of the simulation area is first calculated through the situation simulation mode 22. The concentration matrix of the flow field, and then the chemical concentration values of the (X, Y) two-dimensional array of the desired height are obtained, and are individually colored according to the chemical concentration values, and the concentration distribution is flat. Surface map. In this embodiment, the height is set at 1 meter because the toxic chemical gas cloud is more harmful to personnel when approaching the ground. In addition, the number of meshes of the simulated area of the present embodiment is 2000, 2000, and 5, respectively, for a total of 20,000,000.

As shown in Fig. 6, each of the separated color agglomerates and their color distributions represent the instantaneous position and concentration distribution state of the same gas cloud at different times, wherein the chemical concentration can be observed by the right concentration scale according to different colors. Learned. The simulation results in Figure 6 show that the gas cloud of the chemical is gradually diffused to the downwind by the influence of the natural wind direction, and the farther away from the source of the leak, the core concentration of the gas cloud will gradually decrease, and the distribution range will be more The larger the distance, the time interval between the gas clouds in each of the above transient states is 5 minutes.

In this embodiment, the grid setting parameters include an origin coordinate, a grid size, and a grid number. The source setting parameters include source source coordinates, gas bleed rate, bleed port diameter, and storage temperature. The environmental setting parameters include wind speed, wind direction probability, atmospheric stability probability, surface type and ambient temperature. The output setting parameters include simulation execution time, time interval, and type of leaked substance. In this embodiment, the storage temperature is the temperature in the chlorine storage tank. In addition, the scale effect analysis module 2 of the present invention simulates and analyzes the mesoscale range of 20 kilometers around the wind below the plant area, but in implementation, The mesoscale simulation module 2 can perform a simulated mesoscale simulation range of 2 to 2000 kilometers.

It should be noted that, in order to accelerate the calculation speed, the situation simulation mode 22 does not calculate every grid, but adopts a screening mechanism, considering only the influence of the gas cloud concentration of the chemical on the wind speed and the diffusion coefficient. Surround, and ignore other simulation ranges. The situation simulation mode 22 is divided into two stages. The first stage: limiting the calculation range of the grid, only calculating the half plane of the downwind source of the bleed source, and the angle between the crosswind direction and the wind direction is less than the grid range within the positive and negative θ degrees, and The operation is performed using equation (3).

θ= tan ^-1 (5σ _y / x ) (3)

Where: θ = angle between the crosswind direction and the downwind direction at the downwind; x = wind distance from the bleed source (meter, m); σ _y = crosswind direction gas cloud diffusion coefficient (meter, m ).

The wind distance ( x ) from the bleed source is the wind speed multiplied by the simulation time, and the leeward direction is the positive and negative y-axis direction, and the downwind direction is the x-axis direction. That is to say, because the chemical gas cloud mainly diffuses along the wind direction to the downwind, instead of 360 degrees equidistant diffusion, the area calculated by the present invention is limited to a higher concentration range, thereby avoiding unnecessary operations. Improves computing efficiency and saves time. The second stage: the calculation of the limit concentration, only the gas cloud concentration within the crosswind direction of the downwind is less than 5 times the cross-wind direction gas cloud diffusion coefficient (5σ _y ).

In addition, the scenario simulation mode 22 of the present invention can calculate the diffusion path of the chemical concentration as the wind direction changes during the simulation execution time according to the setting of the wind direction, and can be closer to the real situation and accurately predicted.

First, the original wind source position is simulated at the first wind direction used at the beginning of the simulation. After a predetermined time, the wind direction will be transformed from the first wind direction to a second wind direction, at which time the gas cloud has drifted along the first wind direction. A leeward distance ( Dist ) reaches a first simulated position, wherein the leeward distance ( Dist ) is a value obtained by multiplying the wind speed by the predetermined time.

At this time, in order to simulate the change of the wind direction into the downwind path of the gas cloud after the second wind direction, the first simulation position before the change of the wind direction must be the center of rotation, and the original source position is converted into a virtual state by the formula (4). From the source location, subsequent diffusion simulations can be continued from the first simulated location.

Where: SO _x = x-axis coordinate of the original source location (m, m); SO _y = y-axis coordinate of the original source location (meters, m); SO' _x = x-axis of the virtual source location Coordinate (meter, m); SO' _y = y-axis coordinate of the virtual discharge source position (meter, m); Dist = downwind distance (meter, m); α = first wind direction angle; β = second Wind direction angle.

The lethal analysis mode 23 of the mesoscale consequence analysis module 2 includes a toxic gas effect unit 231, a lethal probability conversion unit 232, and a plot output unit 233.

The toxic gas effect unit 231 can input the first toxic gas parameter ( K ₁ ), the second toxic gas parameter ( K ₂ ) and the toxicity index value ( n ), and cooperate with the situational simulation mode 22 of the mesoscale consequence analysis module 2 The output concentration distribution plan is calculated by the formula (1) to calculate a hazard probability unit value ( Y _{x, y, z} ). Wherein, the concentration of the chemical in each grid in the concentration distribution plan is the toxic gas concentration value ( F _{x, y, z} ) at the different position.

The lethality conversion unit 232 can input the hazard probability unit value ( Y _{x, y, z} ) produced by the toxic gas effect unit 231, and calculate a person lethality ( P ) by the formula (2). The drawing output unit 233 is configured to input the human lethality rate, and cooperate with the mesoscale simulation area map generated by the situation simulation mode 22, and the human lethality probability is nested to the mesoscale simulation area map, and the output is as shown in the figure. The mesoscale fatality diagram shown in Fig. 7, wherein the process of nesting the person's lethality to the mesoscale simulated area map is the same as described above and will not be described in detail. As shown in Fig. 7, the probability of death of the person can be clearly determined by the right-hand scale according to different colors, and the distribution of the death rate of the personnel in the mesoscale range is clearly seen.

The target town consequence analysis module 3 of the present embodiment includes a situation simulation mode 31 and a lethal analysis mode 32. The scenario simulation mode 31 includes a model construction simulation unit 311 and an animation output analysis unit 312.

The model construction simulation unit 311 can input the construction equipment data of the target town, divide the simulation grid number, simulate the situation parameter, and cooperate with the concentration distribution plan output by the mesoscale consequence analysis module 2 to read in the target town. The concentration distribution values in a specific grid within the range are calculated, and a town flow field concentration data is calculated and a town 3D model as shown in FIG. Among them, the urban flow field concentration data contains information on the chemical concentration values in each grid at each time point. Since the establishment of the model is not the focus of the improvement of the present invention, it will not be described in detail. Wherein, as shown in FIG. 9, the graph (a) of FIG. 9 is an enlarged chemical gas cloud of a specific region in the concentration distribution plan view. Concentration equipotential plots, and regions of different concentrations are represented by color circles of different colors, wherein the chemical concentration and position can be calculated from the two-dimensional array of chemical concentration values and array coordinates calculated by the aforementioned scenario simulation mode 22 Learned.

The black curve in Fig. 9(a) is the township boundary in the simulated area, the red line represents the traveling path of the wind, and the red represents the wind direction. In the figure (a) of Fig. 9, the path along the wind can be seen as the approaching arrow. The concentration of the front end of the gas cloud is relatively low. The closer the concentration is to the center point of the gas cloud, the higher the concentration is. After the gas cloud center point is reached, the concentration gradually decreases, reaching the back end of the gas cloud, and the gas cloud concentration and gas at the back end of the gas cloud. The concentration of the cloud front end is the same. As shown in Figure (b) of Figure 9, the wind speed can be used to estimate the concentration of gas cloud into the town over time, in order to simulate the situation of different concentrations of gas clouds entering the town continuously, as follows: From the map of the color ring and the nested map in Figure (a) of Figure 9, we can know the distance between different color rings, and divide the distance by the current wind speed to know the need to move the distance in the downwind direction. time. Then, taking the time as the horizontal axis and the concentration of each color ring as the vertical axis, a step-like curve of the concentration of the gas cloud with time can be obtained, which is the graph (b) of FIG. 9 , which describes the fluctuation trend of the concentration of the gas cloud. Will gradually enter the urban area with the wind at that time. Wherein, (a) and (b) of FIG. 9 describe the same moving chemical gas cloud, which is presented in a different manner, and the more the equipotential line in the diagram (a) of FIG. 9 is denser. Then, the curve of the graph (b) of Fig. 9 will be smoother, and the resolution obtained by the simulation will be higher.

It should be noted that the output of the mesoscale consequence analysis module 2 is In the concentration distribution plan, the concentration distribution values in the specific grid within the target town are only a rough average, and the terrain and obstacle effects are not considered. Therefore, the target town consequence analysis module 3 The model construction simulation unit 311 re-simulates the microscale. The animation output analysis unit 312 can construct the urban flow field concentration data generated by the simulation unit 311 according to the model, and calculate an animated map of the urban flow field concentration of each grid chemical concentration in a simulation range with time. . The animated map of the urban flow field concentration is also in the form of a three-dimensional animated map, and can directly observe the influence range and process of the accident with the time axis, and the figure (b) of the figure (a) of FIG. 10 is the town. The flow field concentration animated map is the instantaneous urban flow field concentration map taken under the simulation time of 20 seconds and 50 seconds. Each grid has a chemical concentration, which can be observed by the right concentration scale according to different colors. The distribution, the results of the simulation in Figure 10, show the diffusion of chemical gas clouds into the target town.

The lethal analysis mode 32 of the target town consequence analysis module 3 includes a toxic gas effect unit 321, a lethal probability conversion unit 322, and a plot output unit 323.

The toxic gas effect unit 321 can input the first toxic gas parameter ( K ₁ ), the second toxic gas parameter ( K ₂ ) and the toxicity index value ( n ), and cooperate with the situation simulation mode 31 of the target urban consequence analysis module 3 The output of the urban flow field concentration data, wherein the unit of the concentration of the urban flow field concentration data is the molar fraction, so multiply by 10 ^{6 to} convert the unit of the concentration into parts per million (ppm), that is, The toxic gas concentration value ( F _{x, y, z} ) at the different positions can be obtained, and a hazard probability unit value ( Y _{x, y, z} ) can be calculated by the formula (1).

The lethal probability conversion unit 322 can input the hazard probability unit value ( Y _{x, y, z} ) produced by the toxic gas effect unit 321 and calculate a person lethality rate ( P ) by the formula (2). The drawing output unit 323 can input the probability of human death caused by the lethal probability conversion unit 322, and cooperate with the three-dimensional model of the town generated by the situation simulation mode 31 to fold the death probability of the person to the three-dimensional model of the town. And output a town death rate diagram as shown in Figure 11, wherein the personnel death rate can be seen by the right ruler in different colors, clearly showing the distribution of the death rate of the town's personnel. In addition, the process of nesting the person's lethality to the three-dimensional model of the town is the same as described above and will not be described in detail.

The risk quantification module 4 includes a personal risk analysis mode 41 and a community risk analysis mode 42.

The personal risk analysis mode 41 is used to predict the probability that a person within the target range is affected by the hazard accident and includes a personal risk calculation unit 411 and a personal risk drawing unit 412.

The personal risk calculation unit 411 can input the total number of hazard events ( n ), the frequency of event occurrence of the hazard event ( F _I ), the probability of occurrence of the person at the coordinate (x, y, z) position ( P _Z ), and the specific coordinate position ( x, y, z population under _{the) (P x, y, z} ), the harmful consequences of case wind probability (P _{wind, i)} and the atmospheric stability probability consequences of case hazard (P _{AS, i),} and mating the plant plant accident consequence analysis module 1 in FIG lethal probability, where the probability of death is to draw a three-dimensional array of values from the probability of death, it can retrieve the harmful consequences of cases from different locations i lethal probability (P _{D, i),} and The individual risk value ( IR _{x, y, z} ) of a particular coordinate position (x, y, z) can be calculated by equation (5).

Where: IR _{x, y, z} = personal risk (number/year) at a specific location (x, y, z); n = total number of hazard events (times); F _I = frequency of occurrence of hazard events (times/year) P _wind,i = wind direction probability of the case of harmful consequences; P _AS,i = probability of atmospheric stability in the case of harmful consequences; P _x,y,z = population under specific coordinates (x,y,z) P _Z = probability of occurrence of the person at the coordinate (x, y, z) position; P _{D, i} = the probability of death of the case i .

The personal risk mapping unit 412, in combination with the personal risk value of the specific location, and the three-dimensional model of the site of the accident plant analysis component 1, the personal risk value of the specific location is nested to the three-dimensional model of the plant, and the output is A personal risk map for the accident site can be output.

The personal risk drawing unit 412 is completed by a drawing software (Matfor), wherein the part of the model nesting is also the same as the foregoing, and the method is as follows: firstly, the model of the accident plant area analysis module 1 is constructed into an analog unit. The building construction system in 111 is converted into the building construction system of the personal risk drawing unit 412 in a one-to-one size. Then, the personal risk value of the specific location in each grid in the three-dimensional model of the plant is imported into the array of the personal risk mapping unit 412 according to the corresponding grid, and the personal risk mapping unit 412 can be targeted by the personal risk mapping unit 412. The difference in values is individually colored to present different personal risks.

FIG. 12 is a diagram showing the personal risk map of the accident factory area calculated by the personal risk analysis mode 41 according to the plant death rate diagram of the module 1 of the accident site analysis. As shown in Figure 12, the individual risk value can be clearly indicated by the upper scale according to different colors, and the distribution of personal risk values of the plant area can be clearly seen, thereby predicting the possible number of deaths per year at different locations within the target range.

The mesoscale mesoscale effects analysis module 2 outputs lethal FIG probability by which to obtain the harmful consequences of the case of a particular location i lethal probability (P _{D, i),} may also be calculated by the risk that the individual unit 411, And input the total number of hazard events ( n ), the frequency of incidents of the hazard event ( F _I ), the probability of occurrence of the person at the coordinates (x, y, z) ( P _Z ), and the position of the specific coordinates (x, y, z) After the population ( P _{x, y, z} ), the wind direction probability ( P _{wind, i} ) and the atmospheric stability probability ( P _{AS, i} ) of the case of harmful consequences, can be calculated by equation (5) A personal risk value ( IR _{x, y, z} ) for a particular location ( _{x, y, z} ).

The personal risk mapping unit 412, in combination with the personal risk value of the specific location and the mesoscale simulated area map produced by the mesoscale consequence analysis module 2, the personal risk value of the specific location is nested to the mesoscale. The area map is simulated, and a mesoscale personal risk map can be output, wherein the part of the nesting is the same as the foregoing and will not be described in detail.

FIG. 13 is a graph showing the mesoscale personal risk map calculated according to the mesoscale fatality diagram of the mesoscale consequence analysis module 2, as shown in FIG. 13 , and the personal risk value may be determined by the right scale. According to different colors, the distribution of personal risk values in the mesoscale range is clearly seen.

The target town urban lethal consequences analyze the probability of drawing module 3 outputs, by which made the case against the consequences of a particular position i of the death probability (P _{D, i),} also by the individual risk calculation unit 411, and Enter the total number of hazard events ( n ), the frequency of incidents of the hazard event ( F _I ), the probability of occurrence of the person at the coordinates (x, y, z) ( P _Z ), and the location of the specific coordinates (x, y, z) After the population ( P _{x, y, z} ), the wind direction probability of the damage consequence case ( P _{wind, i} ) and the atmospheric stability probability ( P _AS,i ) of the case of the damage consequence, it can be calculated by the formula (5) The personal risk value ( IR _{x, y, z} ) for a particular location (x _{, y, z} ).

The personal risk mapping unit 412, in combination with the personal risk value of the specific location, and the three-dimensional model of the town generated by the target urban consequence analysis module 3, the personal risk value of the specific location is nested to the three-dimensional model of the town. Instead, a personal risk map of the target town can be output, wherein the portion of the nesting is the same as described above and will not be described in detail.

FIG. 14 is a diagram showing the personal risk map of the target town calculated according to the urban death rate diagram of the target town consequence analysis module 3, as shown in FIG. 14 , the individual risk value may be different according to the upper scale. The color clearly shows the distribution of personal risk values within the town.

The community risk analysis mode 42 is for assessing the total number of deaths of community residents due to a specific hazard event, and includes a death toll calculation unit 421, an event accumulation unit 422, and a community risk mapping unit 423.

The death toll calculation unit 421 is configured to input a population ( P _{x, y, z} ) at a specific coordinate (x, y, z) position, and cooperate with the mesoscale extermination probability map of the mesoscale consequence analysis module 2, The value of the probability of death ( P _f,i ) at a specific position (x, y, z) after the occurrence of the event consequence case in each grid of the mesoscale lethal probability map can be calculated by equation (6) The number of deaths ( N _i ) caused by the incident consequence case i.

Where: N _i = number of deaths (number of people) caused by event consequence case i; P _{x, y, z} = population (number of people) at a specific coordinate (x, y, z) position; P _{f, i} = specific The probability of death at position (x, y, z).

The event accumulating unit 422 can input the frequency of occurrence of the event consequence case ( F _i ), the number of deaths caused by the event consequence case i ( N _i ), and calculate an event frequency accumulating value by the formula (7) ( F _N ).

Where: F _N = cumulative frequency of events (times/years); F _i = frequency of occurrences of event consequences cases i (times/years); N _i = number of deaths (number of people) caused by case consequences i.

The community risk mapping unit 423 can input the number of deaths caused by the event consequence case i produced by the death toll calculation unit 421, and the cumulative value of the event occurrence frequency generated by the event accumulation unit 422, and the consequences of the event The death toll caused by case i is the horizontal axis, the cumulative frequency of the event is the vertical axis, and a community risk curve shown in Figure 15 is output, and the community risk curve is presented for the community residents or plant personnel due to specific hazards. Community risk caused by the incident.

As shown in FIG. 15, the social risk values simulated in this embodiment are shown. Exceeding the upper limit of the Dutch risk standard, which is lower than the upper limit of the UK risk standard, indicates that such social risk is unacceptable in terms of Dutch standards, but such social risk is acceptable in terms of British standards.

In general, some advanced industrial countries have set social risk standards for new industrial developments or existing industrial processes in their countries. Usually, there are upper and lower limits for this standard, and each country is different, such as the Dutch social risk standard. The requirements for the upper and lower limits are stricter than those for the UK. When the social risk curve exceeds the upper limit of this standard, it indicates that the safety of the new industrial development case or the existing industrial process is too low, and in the event of an accident, a large number of casualties may be caused and cannot be accepted. Below the lower limit of the standard, the new industrial development case or the existing industrial process is highly safe, but it must pay considerable security costs, so that it is unrealistic and its risk can be ignored. The general social risk curve is between the upper and lower limits of this standard. The business owner can use the cost that can actually be implemented to minimize the risk of the new industrial development case or the existing industrial process.

Since there is no relevant standard in Taiwan, in this embodiment, the upper limit of the social risk standard in the Netherlands is defined as the lower limit of Taiwan's social risk standard, and the upper limit of the social risk standard in the United Kingdom is defined as the upper limit of Taiwan's social risk standard, in order to take the middle ground. From the social risk curve in Figure 15, the social risk caused by the consequences of the accident in this embodiment can be accepted, but the number of deaths is between 100 and 2,000, and the owner of the accident still has room for improvement.

Referring to Figures 1 and 16, the integrated cross-scale poisoning disaster analysis method of the present invention comprises the following steps:

Step 91: Establish an integrated cross-scale poison in the computer device Afforestation consequences analysis system.

The above-mentioned integrated cross-scale poisoning disaster consequence analysis system is built in a computer device, and the computer device is used to simulate and analyze a chemical accident in a plant area, the accident is several hundred kilometers around the plant area. The micro-scale range of the ruler, the mesoscale range of 20 km around the wind below the plant, and the hazard and risk caused by the micro-scale range of a few hundred meters around a selected target town.

Step 92: Fruit simulation and analysis after the micro-scale range of the accident plant.

The construction equipment data, grid setting parameters and simulation situation parameters of the plant area are input into the accident plant area consequence analysis module 1 of the integrated cross-scale poisoning disaster consequence analysis system, and the situation of the module 1 is analyzed through the accident plant area. The model of the simulation mode 11 constructs the simulation unit 111, and simulates a three-dimensional model of the plant area and a flow field concentration data of a plant. Then, by the animation output analyzing unit 112 of the situation simulation mode 11, the plant flow field concentration data is converted into an animated map of the plant flow field concentration which can display the chemical concentration in each grid as a function of time.

Then, the first toxic gas parameter, the second toxic gas parameter and the toxicity index value are input into the lethal analysis mode 12 of the accident plant analysis component 1 , and the plant flow field concentration data calculated by the situation simulation mode 11 is used, The toxic gas effect unit 121 of the analysis mode 12 is lethal, and a hazard probability unit value is calculated. The hazard probability unit value is then converted to a human lethality rate by the lethal probability conversion unit 122 of the lethal analysis mode 12. Finally, the drawing output unit 123 of the lethal analysis mode 12 is used, together with the personnel death rate and the factory area generated by the situation simulation mode 11 The 3D model, while outputting a plant dead rate map.

Step 93: Fruit simulation and analysis after the mesoscale range.

The gas cloud numerical interception mode 21 of the mesoscale consequence analysis module 2 intercepts the flow field concentration data generated by the accident plant analysis component 1 and outputs a gas cloud discharge.

Then, the grid setting parameter, the emission source setting parameter, the environment setting parameter and the output setting parameter are input into the mesoscale consequence analysis module 2, and the gas cloud emission amount generated by the gas cloud numerical interception mode 21 is used, From the situation simulation mode 22 of the mesoscale consequence analysis module 2, a mesoscale simulation area map and a concentration distribution plan are simulated.

Finally, the first toxic gas parameter, the second toxic gas parameter and the toxicity index value are input into the lethal analysis mode 23 of the mesoscale consequence analysis module 2, and the concentration distribution plan output by the situation simulation mode 22 is matched, and the lethal analysis is performed. The toxic gas effect unit 231 of mode 23 calculates a hazard probability unit value. Then, by the lethal probability conversion unit 232 of the lethal analysis mode 23, the hazard probability unit value is converted into a person lethality rate. Finally, the drawing output unit 233 of the lethal analysis mode 23 is used, and the meso-scale dead zone rate and the mesoscale simulated area map produced by the situation simulation mode 22 are simultaneously matched, and a mesoscale lethal probability map is output.

Step 94: Fruit simulation and analysis after the target town microscale range.

The building equipment data, the number of divided simulation grids, and the simulated situation parameters of the target town are input into the target town consequence analysis module 3, and the concentration distribution plan generated by the mesoscale consequence analysis module 2 is matched with the target. Model Construction of Situational Simulation Model 31 of Urban Consequence Analysis Module 3 The simulation unit 311 can estimate the concentration change curve of the gas cloud entering the town with time, in order to simulate the situation that the gas clouds of different concentrations continuously enter the town, and simulate a town three-dimensional model and a town flow field concentration data. Then, the animation output analysis unit 312 of the situation simulation mode 31 converts the urban flow field concentration data generated by the model construction simulation unit 311 into one, showing that the concentration of the chemical in each grid changes with time. Animated map of urban flow field concentration.

Then, the first gas parameter, the second gas parameter and the toxicity index value are input into the lethal analysis mode 32 of the target town consequence analysis module 3, and the urban flow field concentration data calculated by the situation simulation mode 31 is used, The toxic gas effect unit 321 of the death analysis mode 32 is operated to calculate a hazard probability unit value. The lethal probability unit value is then converted to a human lethality rate by the lethal probability conversion unit 322 of the lethal analysis mode 32. Finally, the drawing output unit 323 of the lethal analysis mode 32 is used, and at the same time, the person's lethality rate and the town three-dimensional model produced by the situation simulation mode 31 are output, and a town death probability map is output.

Step 95: Personal risk analysis of the micro-scale, mesoscale range of the accident site and the micro-scale of the target town.

The micro-scale personal risk analysis of the accident site is as follows: the total number of hazard events, the frequency of hazard events, the probability of occurrence of personnel at a particular coordinate location, the number of people at a particular coordinate location, the probability of a case of hazard consequences, and the consequences of the consequences The atmospheric stability probability is input into the personal risk analysis mode 41 of the risk quantification module 4, and cooperates with the plant dead rate map generated by the accident plant analysis component 1 by the personal risk analysis module. The personal risk calculation unit 411 of the formula 41 calculates the personal risk value of the specific position within the simulation range. Then, using the personal risk mapping unit 412 of the personal risk analysis mode 41, the personal risk value of the specific location is matched with the three-dimensional model of the factory generated by the accident plant consequence analysis module 1, and the personal risk of an accident factory area is calculated. Figure.

The practice of personal risk analysis in the mesoscale range is as follows: the total number of hazard events, the frequency of hazard events, the probability of occurrence of a person at a particular coordinate location, the number of people at a particular coordinate location, the probability of a case of hazard consequences, and the case of harmful consequences. The atmospheric stability probability is input to the personal risk analysis mode 41 of the risk quantification module 4, and the mesoscale lethality probability map produced by the mesoscale consequence analysis module 2, by the personal risk calculation unit of the personal risk analysis mode 41 411, and calculate the personal risk value of a specific location within the simulation range. Then, using the personal risk mapping unit 412 of the personal risk analysis mode 41, the personal risk value of the specific location is matched with the mesoscale simulation area map generated by the mesoscale consequence analysis module 2, and a mesoscale is calculated. Personal risk chart.

The practice of personal risk analysis in the target town microscale range is as follows: the total number of hazard events, the frequency of hazard events, the probability of occurrence of personnel at a particular coordinate location, the number of people at a particular coordinate location, the probability of a case of hazard consequences, and the consequences of the hazard The atmospheric stability probability of the case is input to the personal risk analysis mode 41 of the risk quantification module 4, and the urban death rate map produced by the target urban consequence analysis module 3 is calculated by the personal risk analysis mode 41 Unit 411 calculates the personal risk value for a particular location within the simulated range. Then, use the personal risk analysis module The personal risk drawing unit 412 of the formula 41 calculates the personal risk map of a target town by matching the personal risk value of the specific location to the three-dimensional model of the town generated by the target town consequence analysis module 3.

Step 96: Social risk analysis of the mesoscale range.

Entering the population number under the specific coordinate position into the death toll calculation unit 421 of the community risk analysis mode 42 and matching the mesoscale death rate map generated by the mesoscale consequence analysis module 2, an event consequence case can be calculated. The number of deaths caused. Then, the frequency of occurrence of the event consequence case and the number of deaths caused by the event consequence case are input into the community risk analysis mode 42 of the risk quantification module 4, and an event occurrence unit 422 is calculated by the event accumulation unit 422 of the community risk analysis mode 42 Frequency accumulated value. Finally, the community risk mapping unit 423 of the community risk analysis mode 42 is used, and the number of deaths caused by the event consequence case is the horizontal axis, and the cumulative frequency of the event frequency is the vertical axis, and a community risk curve graph can be output.

In summary, the integrated cross-scale poisoning disaster consequence analysis system of the present invention can directly undertake the situation simulation mode of the accident plant analysis component 1 by the gas cloud numerical interception mode 21 of the mesoscale consequence analysis module 2 11 outflow data of the plant flow field output is output and a gas cloud emission is output, and the scenario simulation mode 22 of the mesoscale consequence analysis module 2 can be used for the analysis of the mesoscale range of the downwind of the subsequent accident plant. The concentration distribution plan produced by the situation simulation mode 22 of the mesoscale consequence analysis module 2 can also be directly used for the situation simulation mode 31 of the target urban consequence analysis module 3, thereby simultaneously simulating and analyzing the mesoscale range. Hazardous material distribution and microscale The impact of the spread of hazardous materials within the scope, and a more accurate assessment of the diffusion of toxic gases caused by chemical spills, the micro-scale range of several hundred meters around the plant, and the mesoscale range of 20 km around the wind below the plant area, And the hazards and risks of a micro-scale range of a few hundred meters around a selected target town. In addition, the scenario simulation mode 22 of the present invention can calculate the diffusion path of the chemical concentration as the wind direction changes during the simulation execution time according to the setting of the wind direction data, and can be closer to the real situation and accurately predicted, and the situation simulation mode 22 can omit unnecessary arithmetic ranges, so it can improve computing efficiency and save time.

That is to say, the integrated cross-scale poisoning disaster consequence analysis system of the invention not only improves the limitation of the simulation area and the accuracy of the simulation, but also saves the resources and time required for the simulation operation process, and the simulation results of the present invention can be As a reference for determining the evacuation range and route during regional chemical disasters and emergency response drills, the purpose of the present invention can be achieved.

The above is only the preferred embodiment of the present invention, and the scope of the invention is not limited thereto, that is, the simple equivalent changes and modifications made by the scope of the invention and the description of the invention are All remain within the scope of the invention patent.

1‧‧‧Accidental Area Consequence Analysis Module

11‧‧‧Scenario simulation mode

111‧‧‧Model construction simulation unit

112‧‧‧Animation output analysis unit

12‧‧‧ Lethal analysis mode

121‧‧‧Toxic gas effect unit

122‧‧‧Death rate conversion unit

123‧‧‧Drawing output unit

2‧‧‧Mesoscale consequence analysis module

21‧‧‧ gas cloud numerical interception mode

22‧‧‧Scenario simulation mode

23‧‧‧ Lethal analysis mode

231‧‧‧Toxic gas effect unit

232‧‧‧Death rate conversion unit

233‧‧‧Drawing output unit

3‧‧‧ Target town consequence analysis module

31‧‧‧Scenario simulation mode

311‧‧‧Model construction simulation unit

312‧‧‧Animation output analysis unit

32‧‧‧ Lethal analysis mode

321‧‧‧Toxic gas effect unit

322‧‧‧Death rate conversion unit

323‧‧‧Drawing output unit

4‧‧‧ Risk Quantification Module

41‧‧‧ Personal risk analysis model

411‧‧‧personal risk calculation unit

412‧‧‧Personal Risk Mapping Unit

42‧‧‧Community risk analysis model

421‧‧‧Deaths Calculation Unit

422‧‧‧Accumulation unit

423‧‧‧Community risk mapping unit

91~96‧‧‧Steps

1 is a functional block diagram of a preferred embodiment of an integrated cross-scale poisoning disaster consequence analysis system of the present invention; FIG. 2 is a three-dimensional model of a plant area of the preferred embodiment; FIG. 3 (a) and FIG. b) is a transient plant flow field concentration map taken in the preferred embodiment in the case of a simulation time of 1 second and 12 seconds, respectively; 4 is a diagram showing a dead rate of a plant in the preferred embodiment; FIG. 5 is a mesoscale simulation area diagram of the preferred embodiment; FIG. 6 is a plan view of concentration distribution of the preferred embodiment; One of the preferred embodiments is a mesoscale lethality map; FIG. 8 is a three-dimensional model of the town of the preferred embodiment; and FIG. 9(a) is a concentration distribution plan of the preferred embodiment at a certain time. The concentration equipotential curve of the chemical gas cloud at the ground in a specific area, and (b) is the relationship between the chemical concentration and the time interval of the graph (a); the graphs (a) and (b) of Fig. 10 are respectively The preferred embodiment shows a transient urban flow field concentration map taken in the case of a simulation time of 20 seconds and 50 seconds; FIG. 11 is a diagram showing the urban lethality rate of the preferred embodiment; FIG. 12 is the preferred embodiment. Figure 1 is a personal risk map of a mesoscale of the preferred embodiment; Figure 14 is a personal risk map of a target town in the preferred embodiment; Figure 15 is a preferred embodiment of the preferred embodiment Example of a community risk curve; and Figure 16 is an integrated cross-scale poisoning disaster analysis method of the present invention A flowchart of steps.

1‧‧‧Accidental Area Consequence Analysis Module

11‧‧‧Scenario simulation mode

111‧‧‧Model construction simulation unit

112‧‧‧Animation output analysis unit

12‧‧‧ Lethal analysis mode

121‧‧‧Toxic gas effect unit

122‧‧‧Death rate conversion unit

123‧‧‧Drawing output unit

2‧‧‧Mesoscale consequence analysis module

21‧‧‧ gas cloud numerical interception mode

22‧‧‧Scenario simulation mode

23‧‧‧ Lethal analysis mode

231‧‧‧Toxic gas effect unit

232‧‧‧Death rate conversion unit

233‧‧‧Drawing output unit

3‧‧‧ Target town consequence analysis module

31‧‧‧Scenario simulation mode

311‧‧‧Model construction simulation unit

312‧‧‧Animation output analysis unit

32‧‧‧ Lethal analysis mode

321‧‧‧Toxic gas effect unit

322‧‧‧Death rate conversion unit

323‧‧‧Drawing output unit

4‧‧‧ Risk Quantification Module

41‧‧‧ Personal risk analysis model

411‧‧‧personal risk calculation unit

412‧‧‧Personal Risk Mapping Unit

42‧‧‧Community risk analysis model

421‧‧‧Deaths Calculation Unit

422‧‧‧Accumulation unit

423‧‧‧Community risk mapping unit

Claims (10)

An integrated cross-scale poisoning disaster consequence analysis system, which can simulate and analyze a micro-scale of a plant area in the event of a chemical spill in a plant, and a mesoscale at the wind below the plant area. The risk caused by the scope, the integrated cross-scale poisoning disaster consequence analysis system includes: an accident plant area consequence analysis module, including a situation simulation mode, and a lethal analysis mode, the situation simulation mode includes a model construction simulation unit, And an animation output analysis unit, the model construction simulation unit is configured to input the construction equipment data, the grid setting parameter and the simulation situation parameter of the plant area, and output a 3D model of the plant area and a flow field concentration data of the plant, the animation output analysis unit can For inputting the flow field concentration data of the plant and outputting an animated map of the flow field concentration of the plant in which the concentration of the chemical in each grid changes with time, and the lethal analysis mode can be input to the flow field concentration data of the plant and output a plant death rate diagram; and a mesoscale consequence The analysis module includes a gas cloud numerical interception mode, a situational simulation mode, and a lethal analysis mode, and the gas cloud numerical interception mode can input the flow field concentration data of the plant to output a gas cloud emission amount, and the situation simulation mode The grid setting parameter, the emission source setting parameter, the environment setting parameter and the output setting parameter are input, and a mesoscale simulation area map and a concentration distribution plan are output according to the gas cloud emission amount, and the lethal analysis mode is available for inputting a concentration distribution plan view and output a mesoscale lethal probability map, and the grid setting parameter The number includes an origin coordinate, a grid size, and a grid number. The source setting parameter includes an emission source coordinate, and the environment setting parameter includes a wind speed, a wind direction probability, an atmospheric stability probability, a surface type, and an ambient temperature, and the output setting parameter includes Simulate execution time, time interval, and type of spilled material. According to the integrated cross-scale poisoning disaster consequence analysis system described in claim 1 of the patent application scope, a target urban consequence analysis module is also included, and the target urban consequence analysis module includes a situation simulation mode and a lethal analysis mode. The situation simulation mode includes a model construction simulation unit and an animation output analysis unit, which constructs the simulation unit for inputting the construction equipment data of the target town, dividing the simulation grid number, simulating the situation parameters, and matching the concentration distribution plan. Output a town 3D model and a town flow field concentration data, the animation output analysis unit can input the town flow field concentration data and output a town flow field concentration of each grid chemical concentration in time within a simulation range An animated map, and the lethal analysis mode can be used to input the town flow field concentration data and output a town death rate map. According to the integrated cross-scale poisoning disaster consequence analysis system described in claim 2, wherein the fatal analysis mode of the accident plant consequence analysis module includes a toxic gas effect unit, a lethal probability conversion unit, and a drawing The output unit, the toxic gas effect unit can input the first toxic gas parameter, the second toxic gas parameter and the toxicity index value, and cooperate with the flow field concentration data of the plant, and can output a hazard probability unit value, and the lethal probability conversion unit can For inputting the hazard probability unit value and outputting a person death rate, the drawing output unit is available for input The person died of the chance and cooperated with the three-dimensional model of the plant area to output the dead rate map of the plant. According to the integrated cross-scale poisoning disaster consequence analysis system described in claim 3, wherein the cryogenic analysis mode of the mesoscale consequence analysis module includes a toxic gas effect unit, a lethal probability conversion unit, and a drawing The output unit, the toxic gas effect unit is configured to input the first toxic gas parameter, the second toxic gas parameter and the toxicity index value, and cooperate with the concentration distribution plan to output a hazard probability unit value, and the lethal probability conversion unit is input The hazard probability unit value outputs a person lethality rate, and the drawing output unit is configured to input the person's lethal probability and cooperate with the mesoscale simulated area map to output the mesoscale lethal probability map. According to the integrated cross-scale poisoning disaster consequence analysis system described in item 4 of the patent application scope, the lethal analysis mode of the target urban consequence analysis module includes a toxic gas effect unit, a lethal probability conversion unit, and a drawing The output unit, the toxic gas effect unit is configured to input the first toxic gas parameter, the second toxic gas parameter and the toxicity index value, and cooperate with the urban flow field concentration data to output a hazard probability unit value, and the lethal probability conversion unit can A human death rate is output by inputting the hazard probability unit value, and the drawing output unit is configured to input the person's lethality rate, and output the town death rate map in conjunction with the town three-dimensional model. According to the integrated cross-scale poisoning disaster consequence analysis system described in item 5 of the patent application scope, a risk quantification module is also included, and the risk quantification The module includes a personal risk analysis mode including a personal risk calculation unit and an individual risk mapping unit that can input the total number of hazardous events, the frequency of the hazard event, and the person at a particular coordinate. The probability of occurrence of the location, the population under a specific coordinate position, the probability of the wind direction of the case of the damage consequences, and the probability of atmospheric stability of the case of the damage consequence, and the plant death rate diagram produced by the accident plant analysis component, and output The personal risk value of a specific location, the personal risk mapping unit can input the personal risk value of the specific location, and output the personal risk map of the accident factory area according to the three-dimensional model of the factory generated by the accident plant consequence analysis module. The integrated cross-scale poisoning disaster consequence analysis system according to claim 5 of the patent application scope also includes a risk quantification module, the risk quantification module includes a personal risk analysis mode, and the personal risk analysis mode includes a personal risk A calculation unit, and a personal risk calculation unit, the personal risk calculation unit can input the total number of hazard events, the frequency of occurrence of the hazard event, the probability of occurrence of the person at a specific coordinate position, the population under a specific coordinate position, and the weather direction of the case of the damage consequence The probability of atmospheric stability of the probability and the consequences of the consequences, together with the mesoscale fatality rate map produced by the mesoscale consequence analysis module, can output a personal risk value at a specific location, the individual risk mapping unit can be input into the foregoing The personal risk value at a specific location is combined with the mesoscale simulated area map produced by the mesoscale consequence analysis module to output a mesoscale personal risk map. The integrated cross-scale poisoning disaster consequence analysis system according to claim 5 of the patent application scope also includes a risk quantification module, the risk quantification module includes a personal risk analysis mode, and the personal risk analysis mode includes a personal risk A calculation unit, and a personal risk calculation unit, the personal risk calculation unit can input the total number of hazard events, the frequency of occurrence of the hazard event, the probability of occurrence of the person at a specific coordinate position, the population under a specific coordinate position, and the weather direction of the case of the damage consequence The probability of atmospheric stability of the probability and the consequences of the consequences, and in conjunction with the urban death rate map produced by the target urban consequence analysis module, can output a personal risk value of a specific location, the personal risk mapping unit can input the specific The personal risk value of the location is combined with the urban three-dimensional model produced by the target urban consequence analysis module to output a personal risk map of the target town. According to the integrated cross-scale poisoning disaster consequence analysis system described in claim 7 of the patent application scope, the risk quantification module further comprises a community risk analysis mode, wherein the community risk analysis mode includes a death toll calculation unit and an event a cumulative unit, and a community risk mapping unit, wherein the death number calculation unit can input the population under a specific coordinate position, and cooperate with the mesoscale death rate graph generated by the mesoscale consequence analysis module to output an event The number of deaths caused by the consequences case, the cumulative unit of the event is available for inputting the frequency of occurrence of the event consequence case, the number of deaths caused by the event consequence case, and outputting an event occurrence frequency cumulative value, the community risk mapping unit is available for input The number of deaths caused by the event consequences case and the cumulative value of the event frequency A community risk curve can be output. The integrated cross-scale poisoning disaster consequence analysis system according to claim 9 of the patent application scope, wherein the simulation scenario parameter includes an initial condition including a simulation time, a gas type, a gas leakage amount and a concentration, and a boundary condition, The position of the point and the ignition position are monitored, and the boundary conditions include wind speed, wind direction, and whether the fluid is free to enter and exit the boundary layer of the simulation range.