TWI466052B - An integrated cross-scaled consequence analysis system for toxic/chemical disaster - Google Patents
An integrated cross-scaled consequence analysis system for toxic/chemical disaster Download PDFInfo
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本發明是有關於一種分析系統，特別是指一種用於模擬並分析化學品洩漏的工業事故所造成的危害的整合式跨尺度之毒化災後果分析系統。 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.
近年來由於人們對於能源及電子產品需求的持續走高，使得石化、半導體業的規模不斷擴大，這股趨勢使得一些新建工廠為了因應製程所需，而儲存了比以前更大量的危害性物質。上述工廠一旦發生嚴重的化學品洩漏事故，屆時危害影響之區域之廣，將不僅造成工安問題，還可能牽涉出公共衛生及環境問題，但目前並沒有較佳的方法或合適的工具可以進行此類危害之風險評估。 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.
目前大多數對於大氣中擴散的研究，通常是根據高斯擴散模式或對流擴散方程式所寫成的網格模式，此模式可模擬污染物在2~2000公里的中尺度範圍內之擴散沉降行為，並且對電腦要求規格低，模擬時間較短。然而高斯擴散模式並未考慮障礙物效應，而無法模擬在數公尺至2公里處的局部區域內，風與障礙物所產生的局部渦流對排放物質流動之影響，而造成模擬解析度不佳。 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. .
而計算流體力學(Computational Fluid Dynamics,CFD)模式通常以有限體積法解析Navier-Stokes偏微分聯立方程組，可同時考慮危害物質在流體中流動的熱傳、質傳、動傳，以及建築物、障礙物及地形所造成的氣流漩渦效應 (Eddy Effect)等問題，故相較於前述高斯擴散模式而言，計算流體力學模式在數十公尺小範圍內之局部區域的污染物濃度變化的預測較為準確。然而，計算流體力學運算會消耗掉大量的電腦資源且模擬時間較久，再加上網格大小會影響其解析度，而不適合用於大範圍的模擬。 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.
因此，本發明之目的，即在提供一種能改善模擬區域的限制及模擬的準確度，並能節省模擬的運算過程所需之資源及時間的整合式跨尺度之毒化災後果分析系統。 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.
於是，本發明整合式跨尺度之毒化災後果分析系統，可經由一個計算機裝置來模擬並分析一個廠區在發生化學品洩漏的事故時，對於該廠區的微尺度範圍，及位於該廠區之下風處中尺度範圍所造成之風險。該整合式跨尺度之毒化災後果分析系統包含：一個事故廠區後果分析模組，以及一個中尺度後果分析模組。 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.
該事故廠區後果分析模組，包括一個情境模擬模式，以及一個致死分析模式。該情境模擬模式包括一個模型建構模擬單元，以及一個動畫輸出分析單元。該模型建構模擬單元可供輸入該廠區之建築設備資料、網格設定參數及模擬情境參數，而輸出一個廠區三維模型與一個廠區流場濃度資料。該動畫輸出分析單元可供輸入該廠區流場濃度資料而輸出一個可顯示每一個網格內之化學品濃度隨著時間變化的廠區流場濃度動畫圖。而該致死分析模式可供輸入該廠區流場濃度資料而輸出一個廠區致死機率圖。 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.
該中尺度後果分析模組包括一個氣雲數值截取模式、一個情境模擬模式，以及一個致死分析模式。該氣雲數值截取模式可供輸入該廠區流場濃度資料而輸出一個氣雲排放量。該情境模擬模式可供輸入網格設定參數、排放源設定參數、環境設定參數與輸出設定參數，並配合該氣雲排放量而輸出一個中尺度模擬區域圖與一個濃度分佈平面圖。該致死分析模式可供輸入該濃度分佈平面圖而輸出一個中尺度致死機率圖。而該網格設定參數包括原點座標、網格大小與網格數。該排放源設定參數包括排放源座標。該環境設定參數包括風速、風向機率、大氣穩定度機率、地表類型與環境溫度。該輸出設定參數包括模擬執行時間、時間間距與外洩物質種類。 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.
本發明之功效在於：藉由該事故廠區後果分析模組進行事故廠區的微尺度範圍分析而輸出一個廠區流場濃度資料，而該中尺度後果分析模組的氣雲數值截取模式可直接承接該廠區流場濃度資料而輸出一個氣雲排放量，以利該中尺度後果分析模組進行後續事故廠區下風處之中尺度範圍分析。藉此整合微尺度模式與中尺度模式之優點，而可改善模擬區域的限制及模擬的準確度，並能節省運算所需之資源及時間。 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.
有關本發明之前述及其他技術內容、特點與功效，在以下配合參考圖式之一個較佳實施例的詳細說明中，將可清楚的呈現。 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.
參閱圖1，本發明整合式跨尺度之毒化災後果分析系統之一個較佳實施例適合用於建置在一個圖未示的計算機裝置中，所述計算機裝置例如電腦，並透過該計算機裝置執行該整合式跨尺度之毒化災後果分析系統，從而分析一個廠區在發生化學品洩漏的事故時，該事故對於該廠區周圍幾百公尺的微尺度範圍、該廠區之下風處周圍20公里的中尺度範圍，以及一個選定的目標城鎮周圍幾百公尺的微尺度範圍所造成的危害與風險。 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.
而使用者可經由一個圖未示的鍵盤或一個傳輸線等傳輸方式，將所需之資料或設定匯入該整合式跨尺度之毒化災後果分析系統中，並透過一個圖未示的顯示器或一個圖未示的印表機等輸出裝置，將該整合式跨尺度之毒化災後果分析系統所產出之資料輸出。 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.
本實施例之整合式跨尺度之毒化災後果分析系統包含一個事故廠區後果分析模組1、一個中尺度後果分析模組2、一個目標城鎮後果分析模組3，以及一個風險量化模組4。 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.
本實施例之事故廠區後果分析模組1包括一個情境模擬模式11，以及一個致死分析模式12。該情境模擬模式11包括一個模型建構模擬單元111，以及一個動畫輸出分析單元112。 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.
該模型建構模擬單元111可供使用者設定該廠區之建築設備資料、網格設定參數及模擬情境參數，而計算出一個廠區流場濃度資料與一個如圖2所示的廠區三維模型。其 中，該廠區流場濃度資料包含有每一個時間點內每一個網格中的化學品濃度數值之資訊。由於模型的建立非本發明改良之重點，不再詳述。 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.
在本實施例中，該建築設備參數包括建築物長度、寬度、高度及建築物在網格中的座標位置。該網格設定參數包括原點座標、網格大小與網格數。該模擬情境參數包括初始條件與邊界條件。該初始條件包括模擬時間、氣體種類、氣體洩漏量與濃度、監測點位置及點火位置。該邊界條件包括風速、風向，以及流體是否可自由進出模擬範圍各個邊界層之行為。其中，初始條件與邊界條件為解偏微分聯立方程組所需用到之所有相關初值與邊界值。此外，本實施例是以模擬氯氣儲槽外洩為例。 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.
該動畫輸出分析單元112可依據該模型建構模擬單元111所產出的該廠區流場濃度資料，而計算出一個可顯示每一個網格內之化學品濃度隨著時間變化的廠區流場濃度動畫圖。需要說明的是，所述廠區流場濃度動畫圖為三維動畫圖的形式，並可搭配時間軸直接觀察事故的影響範圍與過程，並且可以將此三維動畫圖剖開以分析隱藏在建築物周遭或內部之化學品氣雲的濃度變化過程，而圖3的圖(a)的圖(b)則分別是將該廠區流場濃度動畫圖在模擬時間為1秒與12秒的情狀下所截取的瞬時廠區流場濃度圖，其中，每一個網格都有一個化學品濃度，並可由右方濃度標尺依不同顏色觀察化學品濃度的分佈，本實施例是模擬氯氣儲槽外洩，紅色代表該處化學品濃度超過氯氣之最高濃 度恕限值(TLV-Ceiling)為1000百萬分率(ppm)，即圖中之0.00100莫耳分率；而化學品氣雲之邊界為藍色，採用氯氣之時量平均恕限值(TLV-TWA)為0.5百萬分率(ppm)，即圖中之0.000005莫耳分率。由圖3中模擬的結果顯示，化學品氣雲受到風向的影響逐漸地往下風處擴散。 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.
該致死分析模式12包括一個毒性氣體效應單元121、一個致死機率轉換單元122，以及一個繪圖輸出單元123。 The lethal analysis mode 12 includes a toxic gas effect unit 121, a lethal probability conversion unit 122, and a plot output unit 123.
該毒性氣體效應單元121可供輸入第一毒氣參數(K 1 )、第二毒氣參數(K 2 )與毒性指標值(n)，並配合該模型建構模擬單元111所算出的廠區流場濃度資料，藉由式(1)而可運算出一個危害機率單位值(Y x,y,z )。所述第一毒氣參數(K 1 )、第二毒氣參數(K 2 )與毒性指標值(n)參見表1。 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 ).
式中：Y x,y,z =危害機率單位值；K 1 =第一毒氣參數；K 2 =第二毒氣參數；△t=不同位置中的有效暴露時間(分鐘，min)；n=毒性指標值；F x,y,z =不同位置下的毒氣濃度值(百萬分率，ppm)；需要說明的是，該廠區流場濃度資料輸出後其濃度的單位是莫耳分率，因此先乘以106將濃度的單位轉換成百萬分率，即可得到該不同位置下的毒氣濃度值F x,y,z ，再將該 不同位置中的有效暴露時間(△t)與該不同位置下的毒氣濃度值(F x,y,z )相乘積後，進行加總，取得的數值代入式(1)中，再代入第一毒氣參數與第二毒氣參數，即可求出危害機率單位值(Y x,y,z )。其中，該不同位置中的有效暴露時間(△t)的定義為化學品濃度大於時量平均恕限值時特定位置之人員暴露時間。 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.
該致死機率轉換單元122可供輸入該毒性氣體效應單元121所產出的危害機率單位值(Y y,y,z )，並且藉由式(2)而運算出一個人員致死機率(P)。 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).
式中： P=人員致死機率(%)；Y x,y,z =危害機率單位值；u=積分變量。 Where: P = person death rate (%); Y x, y, z = hazard probability unit value; u = integral variable.
其中，該積分變量(u)為一個積分之啞變數，存在於積分公式中，不須另外輸入。 Wherein, the integral variable ( u ) is an integral dummy variable, which exists in the integral formula and does not need to be input separately.
該繪圖輸出單元123可供輸入該人員致死機率，並配合該廠區三維模型，將該人員致死機率套疊至該廠區三維模型，而輸出一個如圖4所示的廠區致死機率圖。其中模型套疊的部分，該繪圖輸出單元123是藉由一個繪圖軟體(Matfor)來完成的，其做法如下：先將該事故廠區後果分析模組1的模型建構模擬單元111中的建築物建構系統以一比一的尺寸轉換成該繪圖輸出單元123的建築物建構系統。接著，將該廠區三維模型中每一個網格的該人員致死機率，依相對應的網格匯入該繪圖輸出單元123的陣列中，並藉由該繪圖輸出單元123可針對數值的差異個別上色呈現。如圖4所示，人員致死機率可由右方標尺依不同顏色，清楚看出該廠區內部的人員致死機率的分佈，其中，圖4中的人員致死機率是於地面及x軸為15公尺處剖面之投影來顯示其分布情形，由模擬結果顯示致死範圍侷限於事故場區中央範圍。 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.
本實施例的中尺度後果分析模組2包括一個氣雲數值截取模式21、一個情境模擬模式22，以及一個致死分析模式23。 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.
該氣雲數值截取模式21可依據該事故廠區後果分析模 組1之模型建構模擬單元111所產出的廠區流場濃度資料，而計算出一個氣雲排放量，其中該廠區流場濃度資料包含有每一個時間點內每一個網格中的化學品濃度數值之資訊，而該氣雲排放量代表每一個時間間隔內化學品濃度的變化量。 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.
該氣雲數值截取模式21的計算過程如下：將該模型建構模擬單元111所產出的廠區流場濃度資料帶入對應的網格矩陣中，其中，網格內的數值大於零者即為化學品氣雲濃度，因每一個網格大小為已知，故可計算出該網格內之氣雲重量。將上述每一個網格中氣雲重量加總即為該時間下於模擬範圍內之氣雲總量。由於模擬範圍內之氣雲總量，會隨著氣雲擴散而逐漸流出模擬邊界並且不斷減少，將相鄰兩個時間下模擬範圍內之氣雲總量相減，即代表在該時間間隔內流出模擬邊界的氣雲量，此即為本實施例中所述之氣雲排放量。 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.
該情境模擬模式22可供輸入網格設定參數、排放源設定參數、環境設定參數與輸出設定參數，並配合該氣雲數值截取模式21所輸出的氣雲排放量，而計算出一個如圖5的中尺度模擬區域圖與一個如圖6的濃度分佈平面圖。需要說明的是，圖6的該濃度分佈平面圖是將該氣雲排放量依該中尺度模擬區域圖所需之網格大小與數目，先經由該情境模擬模式22計算出模擬區域之三維網格流場濃度矩陣，再擷取欲取得之高度之(X,Y)二維陣列之化學品濃度數值，並依化學品濃度數值個別上色，而繪製成濃度分佈平 面圖。在本實施例中，高度設定在1公尺，因為毒性的化學品氣雲在接近地面時對人員的危害較高。此外，本實施例的模擬區域之網格數分別為長2000個、寬2000個，及高5個，總共20,000,000個。 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.
如圖6所示，每一個互相分離的彩色團塊及其顏色分布，代表同一氣雲在不同時間下之瞬時位置及其濃度分布狀態，其中化學品濃度可由右方濃度標尺依不同顏色觀察對應得知。由圖6中模擬的結果顯示，化學品的氣雲受到自然風向的影響逐漸地擴散至下風處，且隨著距離洩漏源愈遠，氣雲的核心濃度會逐漸降低，其分布範圍也愈來愈大，上述每個瞬時狀態下氣雲之間的時間間距為5分鐘。 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.
在本實施例中，該網格設定參數包括原點座標、網格大小與網格數。該排放源設定參數包括排放源座標、氣體洩放速度、洩放口直徑與儲存溫度。該環境設定參數包括風速、風向機率、大氣穩定度機率、地表類型與環境溫度。該輸出設定參數包括模擬執行時間、時間間距與外洩物質種類。在本實施例中，該儲存溫度為氯氣儲槽內的溫度，此外，本發明之中尺度後果分析模組2是模擬分析該廠區之下風處周圍20公里的中尺度範圍，然而在實施上，該中尺度後果分析模組2能進行模擬的中尺度模擬範圍為2~2000公里。 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.
需要說明的是，該情境模擬模式22為了加速運算速度，並非每一個網格均會進行計算，而是採用一篩選機制，僅考慮化學品之氣雲濃度受風速及擴散係數影響所及之範 圍，而將其他模擬範圍予以忽略。情境模擬模式22分為兩階段進行，第一階段：限制網格之計算範圍，僅計算洩放源下風處半平面，且側風方向與風向夾角小於正負θ度內之網格範圍，並使用式(3)進行運算。 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(5σy/x) (3) θ= tan -1 (5σ y / x ) (3)
式中：θ=下風處側風方向與下風方向的夾角；x=距洩放源之下風距離(公尺，m)；σy=側風方向氣雲擴散係數(公尺，m)。 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 ).
所述距洩放源之下風距離(x)為風速乘上模擬時間，而該下風處側風方向為正負y軸方向，該下風方向為x軸方向。也就是說，因為化學品氣雲主要會順著風向於下風處擴散，而不是360度等距離擴散，因此本發明計算的區域限定在濃度較高的範圍，藉此避免不必要的運算而能提升運算效率並節省時間。第二階段：限制濃度之計算量，僅計算在下風處側風方向小於5倍側風方向氣雲擴散係數(5σy)之內的氣雲濃度。 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 ).
此外，本發明的情境模擬模式22可以依據風向的設定，計算出模擬執行時間內，化學品濃度隨著風向改變的擴散路徑，而能更貼近真實狀況並精準地預測。 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.
首先於模擬剛開始所採用之第一風向對原始排放源位置進行模擬，經過一個預定時間後，風向將由該第一風向轉變成一第二風向，此時氣雲已經順著該第一風向飄移至一個下風距離(Dist)而到達一個第一模擬位置，其中，該 下風距離(Dist)為風速與該預定時間的相乘的數值。 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.
此時，為了模擬風向改變成該第二風向之後的氣雲下風路徑，必須以風向改變前之該第一模擬位置為旋轉圓心，藉由式(4)將原始排放源位置轉換為一個虛擬排放源位置，便可由該第一模擬位置開始持續進行後續之擴散模擬。 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.
式中：SOx=原始排放源位置之x軸座標(公尺，m)；SOy=原始排放源位置之y軸座標(公尺，m)；SO'x=虛擬排放源位置之x軸座標(公尺，m)；SO'y=虛擬排放源位置之y軸座標(公尺，m)；Dist=下風距離(公尺，m)；α=第一風向角度；β=第二風向角度。 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.
該中尺度後果分析模組2的致死分析模式23包括一個毒性氣體效應單元231、一個致死機率轉換單元232，以及一個繪圖輸出單元233。 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.
該毒性氣體效應單元231可供輸入第一毒氣參數(K 1 )、第二毒氣參數(K 2 )與毒性指標值(n)，並配合該中尺度後果分析模組2之情境模擬模式22所輸出的濃度分佈平面圖，藉由式(1)而可運算出一個危害機率單位值(Y x,y,z )。其中，濃度分佈平面圖中的每一個網格內之化學品濃度 即為該不同位置下的毒氣濃度值(F x,y,z )。 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.
該致死機率轉換單元232可供輸入該毒性氣體效應單元231所產出的危害機率單位值(Y x,y,z )，並且藉由式(2)而運算出一個人員致死機率(P)。該繪圖輸出單元233可供輸入該人員致死機率，並配合該情境模擬模式22所產出的中尺度模擬區域圖，將該人員致死機率套疊至該中尺度模擬區域圖，而輸出一個如圖7所示的中尺度致死機率圖，其中，將該人員致死機率套疊至該中尺度模擬區域圖的過程與前述相同，不再詳述。如圖7所示，人員致死機率則可由右方標尺依不同顏色，清楚看出中尺度範圍內的人員致死機率的分佈。 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.
本實施例的目標城鎮後果分析模組3包括一個情境模擬模式31，以及一個致死分析模式32。該情境模擬模式31包括一個模型建構模擬單元311，以及一個動畫輸出分析單元312。 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.
該模型建構模擬單元311可供輸入目標城鎮之建築設備資料、分割模擬網格數、模擬情境參數，並配合該中尺度後果分析模組2所輸出的濃度分佈平面圖來讀取在該目標城鎮之範圍內的特定網格中的濃度分佈數值，而計算出一個城鎮流場濃度資料與一個如圖8所示的城鎮三維模型。其中，該城鎮流場濃度資料包含有每一個時間點內每一個網格中的化學品濃度數值之資訊。由於模型的建立非本發明改良之重點，不再詳述。其中，如圖9所示，圖9的圖(a)為濃度分佈平面圖中某特定區域放大後之化學品氣雲 的濃度等位曲線圖，且不同相同濃度的區域以不同顏色的色環來表示，其中，化學品濃度與位置可經由前述情境模擬模式22計算所得之二維陣列之化學品濃度數值及陣列座標得知。 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.
圖9的圖(a)中黑色曲線為模擬區域內之鄉鎮界，紅色直線代表風的行進路徑，紅色代表風向，圖9的圖(a)中沿著風的行進路徑可看出接近箭頭處的氣雲前端的濃度較低，愈接近氣雲中心點時其濃度愈高，待越過氣雲中心點後濃度又逐漸降低，一直到達氣雲後端，氣雲後端之氣雲濃度與氣雲前端之濃度相同。如圖9的圖(b)所示，藉由風速可推估出氣雲進入城鎮之濃度隨時間變化曲線圖，以便模擬不同濃度之氣雲連續進入城鎮時之狀況，其做法如下： 由圖9的圖(a)中色環與套疊之地圖座標，可以得知不同色環彼此之間的距離，將前述距離除以當時風速即可得知在順風方向移動此距離所需之時間。接著，以時間為橫軸、各色環濃度為縱軸，即可得到一氣雲濃度隨時間變化之階梯狀曲線，此即為圖9的圖(b)，其所描述之氣雲濃度起伏趨勢，會隨著當時之風向緩緩進入城鎮區。其中，圖9的圖(a)與圖(b)是描述同一個移動中的化學品氣雲，只是以不同的方式來呈現，並當圖9的圖(a)中之等位線愈密，則圖9的圖(b)之曲線會愈平滑，而模擬所得之解析度亦愈高。 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.
需要說明的是，由於該中尺度後果分析模組2所輸出 的濃度分佈平面圖中，該目標城鎮之範圍內的特定網格中的濃度分佈數值僅為一概略性之平均值，並未考慮地形及障礙物效應，故藉由該目標城鎮後果分析模組3的模型建構模擬單元311對微尺度重新進行模擬運算。該動畫輸出分析單元312可依據該模型建構模擬單元311所產出的城鎮流場濃度資料，而計算出一個模擬範圍內每一個網格之化學品濃度隨著時間變化的城鎮流場濃度動畫圖。其中，所述城鎮流場濃度動畫圖亦為三維動畫圖的形式，並可搭配時間軸直接觀察事故的影響範圍與過程，而圖10的圖(a)的圖(b)則是將該城鎮流場濃度動畫圖在模擬時間為20秒與50秒的情狀下所截取的瞬時城鎮流場濃度圖，其中，每一個網格都有一個化學品濃度，可由右方濃度標尺依不同顏色觀察濃度的分佈，圖10中模擬的結果顯示化學品氣雲進入該目標城鎮的擴散情況。 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.
該目標城鎮後果分析模組3的致死分析模式32包括一個毒性氣體效應單元321、一個致死機率轉換單元322，以及一個繪圖輸出單元323。 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.
該毒性氣體效應單元321可供輸入第一毒氣參數(K 1 )、第二毒氣參數(K 2 )與毒性指標值(n)，並配合該目標城鎮後果分析模組3之情境模擬模式31所輸出的城鎮流場濃度資料，其中，該城鎮流場濃度資料資料輸出後其濃度的單位是莫耳分率，因此先乘以106將濃度的單位轉換成百萬分率(ppm)，即可得到該不同位置下的毒氣濃度值(F x,y,z )，並藉由式(1)而可運算出一個危害機率單位值(Y x,y, z )。 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).
該致死機率轉換單元322可供輸入該毒性氣體效應單元321所產出的危害機率單位值(Y x,y,z )，並且藉由式(2)而運算出一個人員致死機率(P)。該繪圖輸出單元323可供輸入該致死機率轉換單元322所產出的人員致死機率，並配合該情境模擬模式31所產出的城鎮三維模型，將該人員致死機率套疊至該城鎮三維模型，而輸出一個如圖11所示的城鎮致死機率圖，其中，人員致死機率則可由右方標尺依不同顏色，清楚看出該城鎮的人員致死機率的分佈。此外，將該人員致死機率套疊至該城鎮三維模型的過程與前述相同，不再詳述。 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.
該風險量化模組4包括一個個人風險分析模式41，以及一個社區風險分析模式42。 The risk quantification module 4 includes a personal risk analysis mode 41 and a community risk analysis mode 42.
該個人風險分析模式41用於預測目標範圍內的人員受到危害事故波及而死亡的機率，並包括一個個人風險計算單元411，以及一個個人風險繪圖單元412。 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.
該個人風險計算單元411可供輸入危害事件總數(n)、危害事件之事件發生頻率(F I )、人員在座標(x,y,z)位置之出現機率(P Z )、特定座標位置(x,y,z)下之人口數(P x,y,z )、危害後果案例之風向機率(P wind,i )及危害後果案例之大氣穩定度機率(P AS,i )，並且配合該事故廠區後果分析模組1的廠區致死機率圖，其中，致死機率是由三維致死機率數值陣列繪製而成，故可擷取出不同位置的危害後果案例i之致死機率(P D,i )，並藉由式(5)而可計算出特定 座標位置(x,y,z)之個人風險值(IR x,y,z )。 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).
式中：IR x,y,z =特定位置(x,y,z)之個人風險(人數/年)；n=危害事件總數(次)；F I =危害事件之發生頻率(次/年)；P wind,i =危害後果案例之風向機率；P AS,i =危害後果案例之大氣穩定度機率；P x,y,z =特定座標(x,y,z)位置下之人口數(人數)；P Z =人員在座標(x,y,z)位置之出現機率；P D,i =危害後果案例i之致死機率。 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 .
而該個人風險繪圖單元412將前述特定位置之個人風險值，並且配合該事故廠區後果分析模組1的廠區三維模型，將前述特定位置之個人風險值套疊至該廠區三維模型，而輸出而可輸出一個事故廠區之個人風險圖。 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.
該個人風險繪圖單元412是藉由一個繪圖軟體(Matfor)來完成的，其中模型套疊的部分，亦與前述相同，其做法如下：先將該事故廠區後果分析模組1的模型建構模擬單元111中的建築物建構系統以一比一的尺寸轉換成該個人風險繪圖單元412的建築物建構系統。接著，將該廠區三維模型中每一個網格內的特定位置之個人風險值，依相對應的網格匯入該個人風險繪圖單元412的陣列中，並藉由該個人風險繪圖單元412可針對數值的差異個別上色呈現出不同之個人風險。 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.
圖12為該個人風險分析模式41依據該事故廠區後果分析模組1的廠區致死機率圖，所計算出的事故廠區之個人風險圖。如圖12所示，個人風險值可由上方標尺依不同顏色，清楚看出該廠區的個人風險值的分佈，藉此預測目標範圍內之不同位置處每一年可能的死亡人數。 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.
該中尺度後果分析模組2所產出的中尺度致死機率圖，並由其中取得特定位置的危害後果案例i之致死機率(P D,i )，也可藉由該個人風險計算單元411，並輸入危害事件總數(n)、危害事件之事件發生頻率(F I )、人員在座標(x,y,z)位置之出現機率(P Z )、特定座標(x,y,z)位置下之人口數(P x,y,z )、危害後果案例之風向機率(P wind,i )及危害後果案例之大氣穩定度機率(P AS,i )之後，藉由式(5)而可計算出一個特定位置(x,y,z)之個人風險值(IR x,y,z )。 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 ).
而該個人風險繪圖單元412將前述特定位置之個人風險值，並且配合該中尺度後果分析模組2所產出的中尺度模擬區域圖，將前述特定位置之個人風險值套疊至該中尺度模擬區域圖，而可輸出一個中尺度之個人風險圖，其中套疊的部分與前述相同，不再詳述。 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.
圖13為該個人風險分析模式41依據該中尺度後果分析模組2的中尺度致死機率圖，所計算出的中尺度之個人風險圖，如圖13所示，個人風險值則可由右方標尺依不同顏色，清楚看出中尺度範圍內的個人風險值的分佈。 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.
該目標城鎮後果分析模組3所產出的城鎮致死機率圖 ，並由其中取得特定位置的危害後果案例i之致死機率(P D,i )，亦可藉由該個人風險計算單元411，並輸入危害事件總數(n)、危害事件之事件發生頻率(F I )、人員在座標(x,y,z)位置之出現機率(P Z )、特定座標(x,y,z)位置下之人口數(P x,y,z )、危害後果案例之風向機率(P wind,i )及危害後果案例之大氣穩定度機率(P AS,i )之後，藉由式(5)而可計算出一個特定位置(x,y,z)之個人風險值(IR x,y,z )。 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 ).
而該個人風險繪圖單元412將前述特定位置之個人風險值，並且配合該目標城鎮後果分析模組3所產出的城鎮三維模型，將前述特定位置之個人風險值套疊至該城鎮三維模型，而可輸出一個目標城鎮之個人風險圖，其中套疊的部分與前述相同，不再詳述。 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.
圖14為該個人風險分析模式41依據該目標城鎮後果分析模組3的城鎮致死機率圖，所計算出的目標城鎮之個人風險圖，如圖14所示，個人風險值則可由上方標尺依不同顏色，清楚看出該城鎮內的個人風險值的分佈。 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.
該社區風險分析模式42是用以評估社區居民因為特定危害事件而造成的死亡總人數，並包括一個死亡人數計算單元421、一個事件累計單元422，以及一個社區風險繪圖單元423。 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.
該死亡人數計算單元421一個可供輸入特定座標(x,y,z)位置下之人口(P x,y,z )，並且配合該中尺度後果分析模組2的中尺度致死機率圖，由該中尺度致死機率圖的每一個網 格內取得事件後果案例發生後於特定位置(x,y,z)之致死機率值(P f,i )，藉由式(6)而可計算出一個事件後果案例i所造成之死亡人數(N i )。 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.
式中：N i =事件後果案例i所造成之死亡人數(人數)；P x,y,z =特定座標(x,y,z)位置下之人口數(人數)；P f,i =特定位置(x,y,z)之致死機率值。 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).
該事件累計單元422可供輸入事件後果案例之發生頻率(F i )、事件後果案例i所造成之死亡人數(N i )，並藉由式(7)而計算出一個事件發生頻率累加值(F N )。 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 ).
式中： F N =事件發生頻率累加值(次/年)；F i =事件後果案例i之發生頻率(次/年)；N i =事件後果案例i所造成之死亡人數(人數)。 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.
該社區風險繪圖單元423可供輸入該死亡人數計算單元421所產出的事件後果案例i所造成之死亡人數，以及該事件累計單元422所產出的事件發生頻率累加值，並以該事件後果案例i所造成之死亡人數為橫軸、該事件發生頻率累加值為縱軸，而輸出一個圖15所示的社區風險曲線圖，並可該社區風險曲線圖呈現社區居民或廠區人員因特定危害事件所造成的社區風險。 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.
如圖15所示，顯示本實施例所模擬的社會風險值皆已 超過荷蘭風險標準的上限值，低於英國風險標準的上限值，表示就荷蘭的標準而言，此種社會風險不可接受，但就英國之標準而言，此種社會風險可被接受。 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.
一般而言，一些工業先進國家有針對其國內之新建工業開發案或既有的工業製程訂定社會風險標準，通常此標準有上下限之分，且每個國家不同，例如荷蘭對社會風險標準上下限的要求就比英國來得嚴格。當社會風險曲線超過此標準上限時表示該新建工業開發案或既有的工業製程安全性太低，一旦發生事故時可能會造成大量人員傷亡而不可被接受。而低於標準下限時表示該新建工業開發案或既有的工業製程安全性很高，但必須付出相當大之安全成本，以至於不切實際，其風險可被忽略。一般社會風險曲線界於此標準上下限之間，事業主可以視狀況用實際上可被實施的成本讓該新建工業開發案或既有的工業製程之風險盡量降低。 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.
由於台灣沒有相關標準，故在本實施例中以荷蘭之社會風險標準上限定義為台灣社會風險標準下限，而以英國之社會風險標準上限定義為台灣社會風險標準上限，以取其中庸之道。由圖15中之社會風險曲線觀之，本實施例之事故後果所造成之社會風險可被接受，但在死亡人數介於100至2,000之間，事故業主仍有改善之空間。 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.
參閱圖1、16，本發明整合式跨尺度之毒化災後果分析方法包含以下步驟： Referring to Figures 1 and 16, the integrated cross-scale poisoning disaster analysis method of the present invention comprises the following steps:
步驟91：在計算機裝置中建置一個整合式跨尺度之毒 化災後果分析系統。 Step 91: Establish an integrated cross-scale poison in the computer device Afforestation consequences analysis system.
先於一個計算機裝置中建置上述之整合式跨尺度之毒化災後果分析系統，並經由該計算機裝置用來模擬分析一個廠區在發生化學品洩漏的事故時，該事故對於該廠區周圍幾百公尺的微尺度範圍、該廠區之下風處周圍20公里的中尺度範圍，以及一個選定的目標城鎮周圍幾百公尺的微尺度範圍所造成的危害與風險。 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.
步驟92：事故廠區微尺度範圍之後果模擬與分析。 Step 92: Fruit simulation and analysis after the micro-scale range of the accident plant.
將該廠區之建築設備資料、網格設定參數與模擬情境參數輸入該整合式跨尺度之毒化災後果分析系統之事故廠區後果分析模組1中，並經由該事故廠區後果分析模組1之情境模擬模式11的模型建構模擬單元111，模擬運算出一個廠區三維模型與一個廠區流場濃度資料。然後藉由該情境模擬模式11的動畫輸出分析單元112，將該廠區流場濃度資料而轉換成一個可顯示每一個網格內之化學品濃度隨著時間變化的廠區流場濃度動畫圖。 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.
接著，將第一毒氣參數、第二毒氣參數與毒性指標值輸入該事故廠區後果分析模組1之致死分析模式12，同時配合該情境模擬模式11所算出的廠區流場濃度資料，藉由該致死分析模式12的毒性氣體效應單元121，而運算出一個危害機率單位值。然後藉由該致死分析模式12的致死機率轉換單元122，將危害機率單位值轉換成一個人員致死機率。最後使用該致死分析模式12的繪圖輸出單元123，同時配合該人員致死機率與該情境模擬模式11所產出的廠區 三維模型，而輸出一個廠區致死機率圖。 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.
步驟93：中尺度範圍之後果模擬與分析。 Step 93: Fruit simulation and analysis after the mesoscale range.
藉由該中尺度後果分析模組2的氣雲數值截取模式21，來截取該事故廠區後果分析模組1所產出的廠區流場濃度資料，而輸出一個氣雲排放量。 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.
接著，將網格設定參數、排放源設定參數、環境設定參數與輸出設定參數輸入該中尺度後果分析模組2中，並配合該氣雲數值截取模式21所產出的氣雲排放量，藉由該中尺度後果分析模組2之情境模擬模式22，模擬運算出一個中尺度模擬區域圖與一個濃度分佈平面圖。 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.
最後，將第一毒氣參數、第二毒氣參數與毒性指標值輸入該中尺度後果分析模組2之致死分析模式23，同時配合該情境模擬模式22所輸出的濃度分佈平面圖，藉由該致死分析模式23的毒性氣體效應單元231，而運算出一個危害機率單位值。然後藉由該致死分析模式23的致死機率轉換單元232，將危害機率單位值轉換成一個人員致死機率。最後使用該致死分析模式23的繪圖輸出單元233，同時配合該人員致死機率與該情境模擬模式22所產出的中尺度模擬區域圖，而輸出一個中尺度致死機率圖。 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.
步驟94：目標城鎮微尺度範圍之後果模擬與分析。 Step 94: Fruit simulation and analysis after the target town microscale range.
將該目標城鎮之建築設備資料、分割模擬網格數、模擬情境參數輸入該目標城鎮後果分析模組3中，同時配合該中尺度後果分析模組2所產出的濃度分佈平面圖，經由該目標城鎮後果分析模組3之情境模擬模式31的模型建構 模擬單元311，可推估出氣雲進入城鎮之濃度隨時間變化曲線圖，以便模擬不同濃度之氣雲連續進入城鎮時之狀況，並模擬運算出一個城鎮三維模型與一個城鎮流場濃度資料。然後藉由該情境模擬模式31的動畫輸出分析單元312，將該模型建構模擬單元311所產出的城鎮流場濃度資料而轉換成一個顯示出每一個網格內之化學品濃度隨著時間變化的城鎮流場濃度動畫圖。 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.
接著，將第一毒氣參數、第二毒氣參數與毒性指標值輸入該目標城鎮後果分析模組3之致死分析模式32，同時配合該情境模擬模式31所算出的城鎮流場濃度資料，藉由該致死分析模式32的毒性氣體效應單元321而運算出一個危害機率單位值。然後藉由該致死分析模式32的致死機率轉換單元322，將危害機率單位值轉換成一個人員致死機率。最後使用該致死分析模式32的繪圖輸出單元323，同時配合該人員致死機率與該情境模擬模式31所產出的城鎮三維模型，而輸出一個城鎮致死機率圖。 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.
步驟95：事故廠區微尺度、中尺度範圍與目標城鎮微尺度範圍之個人風險分析。 Step 95: Personal risk analysis of the micro-scale, mesoscale range of the accident site and the micro-scale of the target town.
事故廠區微尺度之個人風險分析的做法如下：將危害事件總數、危害事件之發生頻率、人員在特定座標位置之出現機率、特定座標位置下之人口數、危害後果案例之風向機率及危害後果案例之大氣穩定度機率輸入該風險量化模組4的個人風險分析模式41，配合該事故廠區後果分析模組1所產出的廠區致死機率圖，藉由該個人風險分析模 式41的個人風險計算單元411，而運算出模擬範圍內的特定位置之個人風險值。然後，使用該個人風險分析模式41的個人風險繪圖單元412，將前述特定位置之個人風險值配合該事故廠區後果分析模組1所產出的廠區三維模型，而運算出一個事故廠區之個人風險圖。 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.
中尺度範圍之個人風險分析的做法如下：將危害事件總數、危害事件之發生頻率、人員在特定座標位置之出現機率、特定座標位置下之人口數、危害後果案例之風向機率及危害後果案例之大氣穩定度機率輸入該風險量化模組4的個人風險分析模式41，配合該中尺度後果分析模組2所產出的中尺度致死機率圖，藉由該個人風險分析模式41的個人風險計算單元411，而運算出模擬範圍內的特定位置之個人風險值。然後，使用該個人風險分析模式41的個人風險繪圖單元412，將前述特定位置之個人風險值配合該中尺度後果分析模組2所產出的中尺度模擬區域圖，而運算出一個中尺度之個人風險圖。 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.
目標城鎮微尺度範圍之個人風險分析的做法如下：將危害事件總數、危害事件之發生頻率、人員在特定座標位置之出現機率、特定座標位置下之人口數、危害後果案例之風向機率及危害後果案例之大氣穩定度機率輸入該風險量化模組4的個人風險分析模式41，配合該目標城鎮後果分析模組3所產出的城鎮致死機率圖，藉由該個人風險分析模式41的個人風險計算單元411，而運算出模擬範圍內的特定位置之個人風險值。然後，使用該個人風險分析模 式41的個人風險繪圖單元412，將前述特定位置之個人風險值配合該目標城鎮後果分析模組3所產出的城鎮三維模型，而運算出一個目標城鎮之個人風險圖。 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.
步驟96：中尺度範圍之社會風險分析。 Step 96: Social risk analysis of the mesoscale range.
將特定座標位置下之人口數輸入該社區風險分析模式42的死亡人數計算單元421，並且配合該中尺度後果分析模組2所產出的中尺度致死機率圖，而可計算出一個事件後果案例所造成之死亡人數。接著將事件後果案例之發生頻率、事件後果案例所造成之死亡人數輸入該風險量化模組4的社區風險分析模式42，並且藉由該社區風險分析模式42的事件累計單元422運算出一個事件發生頻率累加值。最後，使用該社區風險分析模式42的社區風險繪圖單元423，以該事件後果案例所造成之死亡人數為橫軸、該事件發生頻率累加值為縱軸，而可輸出一個的社區風險曲線圖。 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.
綜上所述，本發明整合式跨尺度之毒化災後果分析系統藉由該中尺度後果分析模組2的氣雲數值截取模式21，可直接承接該事故廠區後果分析模組1之情境模擬模式11所輸出的廠區流場濃度資料而輸出一個氣雲排放量，並可供該中尺度後果分析模組2的情境模擬模式22進行後續事故廠區下風處之中尺度範圍分析。而該中尺度後果分析模組2的情境模擬模式22所產出的濃度分佈平面圖，也可直接供該目標城鎮後果分析模組3之情境模擬模式31使用，藉此同時模擬與分析中尺度範圍之危害物質分佈與微尺度 範圍內之危害物質擴散影響，而可較準確地評估化學品洩漏造成毒性氣體擴散時，對於該廠區周圍幾百公尺的微尺度範圍、該廠區之下風處周圍20公里的中尺度範圍，以及一個選定的目標城鎮周圍幾百公尺的微尺度範圍所造成的危害與風險。此外，本發明的情境模擬模式22可以依據風向數據的設定，計算出模擬執行時間內，化學品濃度隨著風向改變的擴散路徑，而能更貼近真實狀況並精準地預測，同時該情境模擬模式22可以省略不必要的運算範圍，故能提升運算效率並節省時間。 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.
也就是說，本發明整合式跨尺度之毒化災後果分析系統不僅改善模擬區域的限制及模擬的準確度，還能節省模擬的運算過程所需之資源及時間，同時本發明所模擬的結果可作為區域性化學災害、緊急應變演練時決定疏散範圍及路線之參考依據，故確實能達成本發明之目的。 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.
惟以上所述者，僅為本發明之較佳實施例而已，當不能以此限定本發明實施之範圍，即大凡依本發明申請專利範圍及發明說明內容所作之簡單的等效變化與修飾，皆仍屬本發明專利涵蓋之範圍內。 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‧‧‧事故廠區後果分析模組 1‧‧‧Accidental Area Consequence Analysis Module
11‧‧‧情境模擬模式 11‧‧‧Scenario simulation mode
111‧‧‧模型建構模擬單元 111‧‧‧Model construction simulation unit
112‧‧‧動畫輸出分析單元 112‧‧‧Animation output analysis unit
12‧‧‧致死分析模式 12‧‧‧ Lethal analysis mode
121‧‧‧毒性氣體效應單元 121‧‧‧Toxic gas effect unit
122‧‧‧致死機率轉換單元 122‧‧‧Death rate conversion unit
123‧‧‧繪圖輸出單元 123‧‧‧Drawing output unit
2‧‧‧中尺度後果分析模組 2‧‧‧Mesoscale consequence analysis module
21‧‧‧氣雲數值截取模式 21‧‧‧ gas cloud numerical interception mode
22‧‧‧情境模擬模式 22‧‧‧Scenario simulation mode
23‧‧‧致死分析模式 23‧‧‧ Lethal analysis mode
231‧‧‧毒性氣體效應單元 231‧‧‧Toxic gas effect unit
232‧‧‧致死機率轉換單元 232‧‧‧Death rate conversion unit
233‧‧‧繪圖輸出單元 233‧‧‧Drawing output unit
3‧‧‧目標城鎮後果分析模組 3‧‧‧ Target town consequence analysis module
31‧‧‧情境模擬模式 31‧‧‧Scenario simulation mode
311‧‧‧模型建構模擬單元 311‧‧‧Model construction simulation unit
312‧‧‧動畫輸出分析單元 312‧‧‧Animation output analysis unit
32‧‧‧致死分析模式 32‧‧‧ Lethal analysis mode
321‧‧‧毒性氣體效應單元 321‧‧‧Toxic gas effect unit
322‧‧‧致死機率轉換單元 322‧‧‧Death rate conversion unit
323‧‧‧繪圖輸出單元 323‧‧‧Drawing output unit
4‧‧‧風險量化模組 4‧‧‧ Risk Quantification Module
41‧‧‧個人風險分析模式 41‧‧‧ Personal risk analysis model
411‧‧‧個人風險計算單元 411‧‧‧personal risk calculation unit
412‧‧‧個人風險繪圖單元 412‧‧‧Personal Risk Mapping Unit
42‧‧‧社區風險分析模式 42‧‧‧Community risk analysis model
421‧‧‧死亡人數計算單元 421‧‧‧Deaths Calculation Unit
422‧‧‧事件累計單元 422‧‧‧Accumulation unit
423‧‧‧社區風險繪圖單元 423‧‧‧Community risk mapping unit
91~96‧‧‧步驟 91~96‧‧‧Steps
圖1是本發明整合式跨尺度之毒化災後果分析系統之一較佳實施例之功能方塊圖；圖2是該較佳實施例之一廠區三維模型；圖3的圖(a)與圖(b)分別是該較佳實施例在模擬時間為1秒與12秒的情狀下所截取的瞬時廠區流場濃度圖； 圖4是該較佳實施例之一廠區致死機率圖；圖5是該較佳實施例之一中尺度模擬區域圖；圖6是該較佳實施例之一濃度分佈平面圖；圖7是該較佳實施例之一中尺度致死機率圖；圖8是該較佳實施例之一城鎮三維模型；圖9的圖(a)是該較佳實施例之一濃度分佈平面圖中於某一時刻下之化學品氣雲在特定區域地面處之濃度等位曲線圖，圖(b)為圖(a)之化學品濃度與時間間距的關係圖；圖10的圖(a)與圖(b)分別是該較佳實施例在模擬時間為20秒與50秒的情狀下所截取的瞬時城鎮流場濃度圖；圖11是該較佳實施例之一城鎮致死機率圖；圖12是該較佳實施例之一事故廠區之個人風險圖；圖13是該較佳實施例之一中尺度之個人風險圖；圖14是該較佳實施例之一目標城鎮之個人風險圖；圖15是該較佳實施例之一社區風險曲線圖；及圖16是本發明整合式跨尺度之毒化災後果分析方法的步驟的流程圖。 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‧‧‧事故廠區後果分析模組 1‧‧‧Accidental Area Consequence Analysis Module
11‧‧‧情境模擬模式 11‧‧‧Scenario simulation mode
111‧‧‧模型建構模擬單元 111‧‧‧Model construction simulation unit
112‧‧‧動畫輸出分析單元 112‧‧‧Animation output analysis unit
12‧‧‧致死分析模式 12‧‧‧ Lethal analysis mode
121‧‧‧毒性氣體效應單元 121‧‧‧Toxic gas effect unit
122‧‧‧致死機率轉換單元 122‧‧‧Death rate conversion unit
123‧‧‧繪圖輸出單元 123‧‧‧Drawing output unit
2‧‧‧中尺度後果分析模組 2‧‧‧Mesoscale consequence analysis module
21‧‧‧氣雲數值截取模式 21‧‧‧ gas cloud numerical interception mode
22‧‧‧情境模擬模式 22‧‧‧Scenario simulation mode
23‧‧‧致死分析模式 23‧‧‧ Lethal analysis mode
231‧‧‧毒性氣體效應單元 231‧‧‧Toxic gas effect unit
232‧‧‧致死機率轉換單元 232‧‧‧Death rate conversion unit
233‧‧‧繪圖輸出單元 233‧‧‧Drawing output unit
3‧‧‧目標城鎮後果分析模組 3‧‧‧ Target town consequence analysis module
31‧‧‧情境模擬模式 31‧‧‧Scenario simulation mode
311‧‧‧模型建構模擬單元 311‧‧‧Model construction simulation unit
312‧‧‧動畫輸出分析單元 312‧‧‧Animation output analysis unit
32‧‧‧致死分析模式 32‧‧‧ Lethal analysis mode
321‧‧‧毒性氣體效應單元 321‧‧‧Toxic gas effect unit
322‧‧‧致死機率轉換單元 322‧‧‧Death rate conversion unit
323‧‧‧繪圖輸出單元 323‧‧‧Drawing output unit
4‧‧‧風險量化模組 4‧‧‧ Risk Quantification Module
41‧‧‧個人風險分析模式 41‧‧‧ Personal risk analysis model
411‧‧‧個人風險計算單元 411‧‧‧personal risk calculation unit
412‧‧‧個人風險繪圖單元 412‧‧‧Personal Risk Mapping Unit
42‧‧‧社區風險分析模式 42‧‧‧Community risk analysis model
421‧‧‧死亡人數計算單元 421‧‧‧Deaths Calculation Unit
422‧‧‧事件累計單元 422‧‧‧Accumulation unit
423‧‧‧社區風險繪圖單元 423‧‧‧Community risk mapping unit
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