A method, system and electronic device for optimizing personnel evacuation in the event of a toxic gas leak
By using the Gaussian plume diffusion model and Dijkstra's algorithm, the distribution of toxic gas concentrations was quantified and the path with minimum toxicity load was constructed. This solved the problem of insufficient scientific rigor in the delineation of evacuation areas and path optimization in hazardous chemical leak accidents, reduced the risk of secondary injury to personnel, and improved the scientific rigor and safety of evacuation decisions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANCHANG INST OF TECH
- Filing Date
- 2026-03-03
- Publication Date
- 2026-06-05
AI Technical Summary
In hazardous chemical spill accidents, existing technologies rely on experience or single concentration thresholds to define evacuation areas, lacking quantitative simulation. This makes it difficult to effectively prevent secondary injuries caused by personnel passing through areas with high concentrations of toxic gas, and evacuation route optimization ignores the cumulative damage of toxic gases to the human body.
The Gaussian plume diffusion model was used to quantify the distribution of toxic gas concentrations, and the zones of lethality, serious injury, minor injury, and safety were divided. The toxicity load was calculated using a discretization method, and the path with the minimum toxicity load and the optimal evacuation plan were constructed by combining Dijkstra's algorithm and linear programming.
It has achieved a systematic integration of quantitative assessment and path planning for toxic gas diffusion, significantly reducing the cumulative risk of injury to personnel and improving the scientific nature and safety of evacuation decisions.
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Figure CN122155055A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of emergency management technology for hazardous chemical accidents, and provides an optimized method for personnel evacuation in the event of a toxic gas leak. Background Technology
[0002] As the scale of the hazardous chemical storage, transportation, and use industry continues to expand, the pressure of accident prevention and control is also intensifying. Toxic gas leaks account for nearly 40% of major and above hazardous chemical accidents. Leaked gases spread with the airflow, forming dynamic risk zones. If evacuation decisions lack a scientific basis, it can easily lead to secondary casualties caused by exposure to high concentrations of toxic gases. Therefore, scientifically determining the evacuation scope and optimizing evacuation routes have become the core link in reducing personnel injuries from hazardous chemical toxic gas leaks, and are also an important research and application need in the field of emergency management.
[0003] Existing technologies have conducted numerous studies on the simulation of hazardous chemical leaks and emergency evacuation route planning. Some studies use Gaussian models, SLAB models, and other methods to simulate the diffusion of toxic gases, and combine the simulation of accident consequences to delineate the emergency evacuation range. They also use GIS to identify areas that need to be evacuated. In terms of evacuation route planning, classic algorithms such as ant colony algorithms and Dijkstra's algorithm are often used to construct emergency evacuation decision models with the goal of minimizing evacuation time and distance. At the same time, some studies have attempted to combine factors such as toxic gas concentration fields and path relationships to plan evacuation routes. Some methods also use dynamic principles to describe the evacuation speed of personnel and dynamically allocate the flow of evacuated people or vehicles.
[0004] Existing technologies still have significant technical shortcomings. On the one hand, the delineation of evacuation areas relies heavily on experience or single concentration thresholds, lacking quantitative simulations and grading standards to support the evacuation of toxic gases, resulting in insufficient scientific rigor and precision. On the other hand, the core optimization objectives still focus on efficiency indicators such as evacuation time and distance. Even when some studies consider the impact of toxic gases, they rarely take into account the exposure time of evacuees in toxic gases, neglecting the cumulative harm of toxic gases to the human body. They cannot quantify the health hazards of toxic gases to personnel during evacuation, which may lead to evacuation routes passing through areas with high concentrations of toxic gases, making it difficult to fundamentally avoid the risk of secondary injury to personnel. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention provides an optimized method for personnel evacuation in the event of a toxic gas leak. This method can achieve a systematic integration of toxic gas diffusion quantification, toxicity risk assessment and path planning, and flow allocation. However, the comprehensiveness and practicality of the decision-making basis need to be improved.
[0006] The technical solution of the present invention includes: The gas mass concentration distribution field of toxic gas at any point downwind of the leak point is obtained by using a Gaussian plume diffusion model. Based on the gas mass concentration, lethal zone, serious injury zone, minor injury zone and safe zone are divided. The axial length of the minor injury zone downwind is used as the protection distance. A square emergency evacuation range with the leak source as the center point and the side length equal to the protection distance is constructed. By using a discretization method, each directed road segment in the evacuation road network within the emergency evacuation range is divided into several micro-segments. The toxicity load of each micro-segment is obtained according to the toxicity load calculation formula, thereby obtaining the toxicity load of all directed road segments. An evacuation optimization model is constructed based on the toxicity load of all directed road segments, with the goal of minimizing the total toxicity load. The model is constrained by the capacity of refuge points, the conservation of the number of evacuees, and the non-negativity of the evacuation volume. Using the road segment toxicity load as the edge weight, the minimum toxicity load path from each evacuation source point to each refuge point is solved by the Dijkstra algorithm. The minimum toxicity load of each source point-refuge point pair is obtained. Then, the minimum toxicity load of the path is substituted into the evacuation optimization model, and the optimal evacuation volume from each evacuation source point to each refuge point is obtained by linear programming, forming an evacuation plan that includes the optimal path and the allocation of evacuees.
[0007] Furthermore, the Gaussian plume diffusion model is as follows: In the formula, For spatial points The mass concentration of toxic gas, For the strength of the leakage source, The average wind speed, The horizontal diffusion coefficient is... The vertical diffusion coefficient is... The effective height of the leakage source is defined by the x-axis, which represents the average wind direction. The y-axis is perpendicular to the x-axis on the horizontal plane and is located to the left of the x-axis. The z-axis is perpendicular to the horizontal plane xoy and is located upwards.
[0008] Furthermore, the formula for calculating toxicity load is as follows: In the formula, Toxicity load, The concentration of toxic gas at the location of personnel exposure. For exposure time, This represents the toxicity coefficient.
[0009] Furthermore, the formula for calculating the total toxicity load for each road segment is as follows: In the formula, For road section Total toxicity load, For the first The concentration of toxic gas in each micro-element segment, The length of the infinitesimal segment. denoted as the total number of micro-segments of this road section, and v as the constant evacuation speed of personnel.
[0010] Furthermore, the evacuation optimization model is as follows: The capacity constraint of the refuge point is: The evacuation number conservation constraint is: The non-negativity constraint for evacuation volume is: In the formula, A represents the total number of evacuation sources, and B represents the total number of refuge points. In order to evacuate the source, As a refuge, From arrive The number of people evacuated for Total number of evacuees for Maximum capacity for arrive The toxicity load of the minimum toxicity load path.
[0011] Furthermore, the Dijkstra algorithm's solution method is as follows: A toxicity-weighted road network is constructed, using the toxicity load of each directed road segment as the weight of the road network edges. The road network nodes include evacuation source points, road network intersections, and refuge points. Each evacuation source point is sequentially used as a starting point, and the shortest weighted path from that source point to each refuge point, i.e., the minimum toxicity load path, is found by traversing the road network using Dijkstra's algorithm. The minimum toxicity load paths for all source-refuge point pairs are recorded, and the total toxicity load value of that path is extracted. This forms a table of toxicity load parameters for source-refuge pairs.
[0012] Furthermore, the total toxicity load of this pathway... As known coefficients, they are substituted into the already constructed total toxicity load minimum evacuation optimization model; the number of evacuees from each source point to each refuge point is taken as the evacuation number. As decision variables, the model constraints maintain the conservation of refuge capacity, evacuation numbers, and non-negativity of evacuation volume. The optimal solution of the objective function that minimizes the total toxicity load under all constraints is obtained by solving the linear programming method, thus obtaining the optimal evacuation numbers for each source-refuge pair.
[0013] Furthermore, the method for obtaining the evacuation plan is to map the path with the minimum toxicity load to the optimal number of evacuees, clarify the optimal path and the number of people on that path, thereby forming a complete evacuation plan that includes the selection of the optimal path and the precise allocation of the number of people.
[0014] This invention also provides a personnel evacuation optimization system for hazardous chemical toxic gas leak accidents, used to implement the aforementioned personnel evacuation optimization method for toxic gas leaks, comprising: The toxic gas diffusion simulation and evacuation range delineation module is used to call the Gaussian plume diffusion model to calculate the toxic gas mass concentration distribution field at any point in space downwind of the leak point. Based on the toxic gas mass concentration classification standard, it divides the area into lethal zone, serious injury zone, minor injury zone and safe zone. The axial length of the minor injury zone downwind is used as the protection distance. A square emergency evacuation range with the leak source as the center and the side length equal to the protection distance is constructed. Road network discretization and toxicity load calculation module: The discretization method is used to divide each directed road segment of the evacuation road network within the emergency evacuation range into several micro-segments. The toxicity load of each micro-segment is solved according to the toxicity load calculation formula. The total toxicity load of all directed road segments is accumulated and the data is stored. Evacuation optimization model construction module: With the minimum total toxicity load as the core objective, combined with the refuge point capacity constraint, the evacuation personnel conservation constraint, and the non-negativity constraint of evacuation volume, a complete mathematical model for personnel evacuation optimization in hazardous chemical gas leak accidents is constructed, supporting flexible configuration and modification of model parameters; The optimal evacuation plan solution module uses the road segment toxicity load as the edge weight and solves the minimum toxicity load path from each evacuation source point to each refuge point using the Dijkstra algorithm to obtain the minimum toxicity load of each source point-refuge point pair. This data is then substituted into the evacuation optimization model, and the optimal evacuation volume from each evacuation source point to each refuge point is obtained through linear programming. The solutions are then integrated to form a complete evacuation plan that includes the optimal evacuation path and the allocation of the number of people, and then output.
[0015] The present invention also provides an electronic device, characterized in that it comprises: Memory, used to store computer programs; When a processor executes a computer program stored in memory, it implements the aforementioned optimized method for personnel evacuation in the event of a toxic gas leak.
[0016] The technical solution provided by this invention has the following advantages compared with the prior art: This invention quantifies the evacuation range using a Gaussian plume diffusion model, addressing the shortcomings of traditional evacuation range delineation methods that rely on experience and lack scientific rigor and precision. It quantifies the toxicity load of each road segment using a discretization method, and combines Dijkstra's algorithm with linear programming to achieve minimum toxicity load path selection and optimal evacuation flow allocation. This breaks through the limitations of traditional evacuation planning, which focuses on time and distance as core optimization objectives, taking into account the cumulative harm effects of toxic gas concentration and personnel exposure time. It quantifies the health hazards of toxic gases during evacuation, fundamentally avoiding the risk of secondary harm caused by personnel passing through high-concentration toxic gas areas. Simultaneously, it achieves a systematic integration of toxic gas diffusion quantification, toxicity risk assessment, path planning, and flow allocation, making personnel evacuation decisions in hazardous chemical gas leak accidents more scientific, comprehensive, and practical. It significantly reduces the cumulative harm of toxic gases to personnel with only a slight increase in evacuation distance, improving the safety and rationality of emergency evacuation.
[0017] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic diagram of the evacuation area for a toxic gas leak.
[0020] Figure 2 This is a schematic diagram showing the coordinates of road sections and nodes within the evacuation area. Detailed Implementation
[0021] The following detailed description of a specific embodiment of the present invention is provided in conjunction with the accompanying drawings. However, it should be understood that the scope of protection of the present invention is not limited to the specific embodiment.
[0022] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the technical solution of this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0023] In the description of the embodiments of the present invention, unless otherwise stated, "a plurality of" means two or more.
[0024] This invention provides an optimized method for personnel evacuation in the event of a toxic gas leak, comprising: The gas mass concentration distribution field of toxic gas at any point downwind of the leak point is obtained by using a Gaussian plume diffusion model. Based on the gas mass concentration, lethal zone, serious injury zone, minor injury zone and safe zone are divided. The axial length of the minor injury zone downwind is used as the protection distance. A square emergency evacuation range with the leak source as the center point and the side length equal to the protection distance is constructed. By using a discretization method, each directed road segment in the evacuation road network within the emergency evacuation range is divided into several micro-segments. The toxicity load of each micro-segment is obtained according to the toxicity load calculation formula, thereby obtaining the toxicity load of all directed road segments. An evacuation optimization model is constructed based on the toxicity load of all directed road segments, with the goal of minimizing the total toxicity load. The model is constrained by the capacity of refuge points, the conservation of the number of evacuees, and the non-negativity of the evacuation volume. Using the road segment toxicity load as the edge weight, the minimum toxicity load path from each evacuation source point to each refuge point is solved by the Dijkstra algorithm. The minimum toxicity load of each source point-refuge point pair is obtained. Then, the minimum toxicity load of the path is substituted into the evacuation optimization model, and the optimal evacuation volume from each evacuation source point to each refuge point is obtained by linear programming, forming an evacuation plan that includes the optimal path and the allocation of evacuees.
[0025] Furthermore, the Gaussian plume diffusion model is as follows: In the formula, For spatial points The mass concentration of toxic gas, For the strength of the leakage source, The average wind speed, The horizontal diffusion coefficient is... The vertical diffusion coefficient is... The effective height of the leakage source is defined by the x-axis, which represents the average wind direction. The y-axis is perpendicular to the x-axis on the horizontal plane and is located to the left of the x-axis. The z-axis is perpendicular to the horizontal plane xoy and is located upwards.
[0026] Furthermore, the formula for calculating toxicity load is as follows: In the formula, Toxicity load, The concentration of toxic gas at the location of personnel exposure. For exposure time, This represents the toxicity coefficient.
[0027] Furthermore, the formula for calculating the total toxicity load for each road segment is as follows: In the formula, For road section Total toxicity load, For the first The concentration of toxic gas in each micro-element segment, The length of the infinitesimal segment. Let v be the total number of micro-segments of the road section, v be the constant evacuation speed of personnel, and l be the movement distance of the road section.
[0028] Furthermore, the evacuation optimization model is as follows: The capacity constraint of the refuge point is: The evacuation number conservation constraint is: The non-negativity constraint for evacuation volume is: In the formula, A represents the total number of evacuation sources, and B represents the total number of refuge points. In order to evacuate the source, As a refuge, From arrive The number of people evacuated for Total number of evacuees for Maximum capacity for arrive The toxicity load of the minimum toxicity load path.
[0029] Furthermore, the Dijkstra algorithm's solution method is as follows: A toxicity-weighted road network is constructed, using the toxicity load of each directed road segment as the weight of the road network edges. The road network nodes include evacuation source points, road network intersections, and refuge points. Each evacuation source point is sequentially used as a starting point, and the shortest weighted path from that source point to each refuge point, i.e., the minimum toxicity load path, is found by traversing the road network using Dijkstra's algorithm. The minimum toxicity load paths for all source-refuge point pairs are recorded, and the total toxicity load value of that path is extracted. This forms a table of toxicity load parameters for source-refuge pairs.
[0030] Furthermore, the total toxicity load of this pathway... As known coefficients, they are substituted into the already constructed total toxicity load minimum evacuation optimization model; the number of evacuees from each source point to each refuge point is taken as the evacuation number. As decision variables, the model constraints maintain the conservation of refuge capacity, evacuation numbers, and non-negativity of evacuation volume. The optimal solution of the objective function that minimizes the total toxicity load under all constraints is obtained by solving the linear programming method, thus obtaining the optimal evacuation numbers for each source-refuge pair.
[0031] Furthermore, the method for obtaining the evacuation plan is to map the path with the minimum toxicity load to the optimal number of evacuees, clarify the optimal path and the number of people on that path, thereby forming a complete evacuation plan that includes the selection of the optimal path and the precise allocation of the number of people.
[0032] Example: The liquid chlorine storage tank in the chemical storage company's warehouse had exceeded its service life, and the valve on the tank had a slight leak. Because warehouse workers disliked the odor, they failed to move the leaking tank outdoors as required by the company's "Chlorine Safe Storage and Use Management System." Later, condensation formed at the tank opening, dissolving some of the leaked chlorine in it, increasing its corrosiveness and causing the valve to malfunction, resulting in a chlorine leak. The storage tank had a volume of 50 m³ and weighed approximately 800 kg. The day of the accident was cloudy, with a temperature of 25°C, a wind force of level 3, a wind speed of 4 m / s, and an easterly wind direction. The incident occurred in an open storage area outside the warehouse, near several residential areas. None of these residents had adequate protective equipment for chlorine leaks. After other measures proved ineffective, the surrounding residents had to be evacuated to prevent poisoning and minimize casualties.
[0033] like Figure 1 As shown, based on the human body's reactions to different concentrations of chlorine, the hazard zones of this leak accident are divided into four zones according to the harm to the human body: lethal zone, serious injury zone, minor injury zone, and safe zone. The boundary concentrations and characteristics of the four hazard zones are shown in Table 1, and the relevant parameters are shown in Tables 2 and 3.
[0034] Table 1: Boundary Delineation and Characteristics of the Accident Area Table 2: Calculation parameters after the accident spread Table 3: Coefficient values in the expression of atmospheric diffusion parameters The leak source is located near a densely populated area. To minimize casualties, nearby residents must be evacuated quickly. The evacuation area is based on the U.S. Department of Transportation's "Emergency Response Guidelines 2012," which specifies that the evacuation area for chemical products should be an equilateral rectangle extending downwind from the accident site, with sides equal to the protection distance. The safety protection distance is the longitudinal axis of the area with the highest concentration of the exposed gas downwind after it has evaporated.
[0035] The diffusion concentration distribution of chlorine gas was calculated using a Gaussian plume diffusion model, where wind speed... u =4m / s, atmospheric stability level B. , The evacuation of people mainly relies on nasal inhalation of toxic gases. To simplify calculations, the sampling height for chlorine concentration distribution is taken as 1.6m, which is the height in the Gaussian model. Z =1.6. The chlorine concentration range is based on the chlorine hazard concentration thresholds in the "Acute Exposure Guidelines". The calculated axial length of the maximum permissible concentration zone downwind after chlorine diffusion is 1848m. The accident area has 25 evacuation points and one leak source (0,0), with two evacuation starting points S1 and S2, and three refuge points S6, S12, and S13. The coordinates of the road sections and main nodes within the evacuation area are as follows: Figure 2 As shown. A total of 90 people will be evacuated from the evacuation area, with 35 people in S1 and 55 people in S2. The three temporary shelters outside the evacuation area can accommodate 35 people in S6, 45 people in S12, and 55 people in S13.
[0036] The spatial coordinates of nodes S1 and S2 are (240,0) and (332,220) respectively, from which the road segment between S1 and S2 can be derived. R 1-2 The rectangular coordinate equation is in the form of: y =2.39 x -574; Referring to the green paper of the Dutch TNO, the correlation coefficient for chlorine is: n =2.75; the evacuation speed is taken as 1m / s.
[0037] This leads to the deduction of the road section. Toxicity load The calculation formula is: like Figure 2 The diagram shows the coordinates of road sections and nodes within the evacuation area. The formula for calculating the toxicity load of a road section (taking section S1→S2 as an example) is as follows: The information for the remaining road segments is shown in Table 4.
[0038] Table 4: Length of each evacuation route and toxicity load Using toxicity load and road length as values for each road segment in the evacuation network roadmap, the classic Dijkstra algorithm was used to solve the directed weighted connected graph on the Matlab 2020b platform. The minimum toxicity load path and the shortest evacuation distance path from each evacuation node to the refuge node were obtained, as shown in Tables 5 and 6.
[0039] Table 5: Minimum Toxicity Load Pathway Table 6: Shortest Evacuation Distance Paths The evacuation volumes from source point S1 to refuge points D1, D2, and D3 are respectively represented by... x 11 , x 12 , x 13 Indicated; the evacuation volumes from source point S2 to refuge points D1, D2, and D3 are respectively represented by... x 21 , x 22 , x 23 express.
[0040] Using equation (4), an evacuation optimization model with the objective of minimizing toxicity load is established as follows: The solution results are shown in Table 7.
[0041] Table 7: Solution results of the model with the objective of minimizing toxicity load If the evacuation optimization model aims at finding the shortest path, then the evacuation optimization model can be modified as follows, with the constraints remaining unchanged.
[0042] The solution results are shown in Table 8.
[0043] Table 8: Solution results of the shortest path model A comparison of Tables 7 and 8 shows that the evacuation model targeting minimum toxic load significantly reduces the per capita toxic load compared to the evacuation model targeting shortest path, while the difference in evacuation path length is not significant. For hazardous chemical gas leak accidents, evacuation decisions should be made with minimum toxic load as the objective for the safety of evacuees.
[0044] This invention also provides a personnel evacuation optimization system for hazardous chemical toxic gas leak accidents, used to implement the aforementioned personnel evacuation optimization method for toxic gas leaks, comprising: The toxic gas diffusion simulation and evacuation range delineation module is used to call the Gaussian plume diffusion model to calculate the toxic gas mass concentration distribution field at any point in space downwind of the leak point. Based on the toxic gas mass concentration classification standard, it divides the area into lethal zone, serious injury zone, minor injury zone and safe zone. The axial length of the minor injury zone downwind is used as the protection distance. A square emergency evacuation range with the leak source as the center and the side length equal to the protection distance is constructed. Road network discretization and toxicity load calculation module: The discretization method is used to divide each directed road segment of the evacuation road network within the emergency evacuation range into several micro-segments. The toxicity load of each micro-segment is solved according to the toxicity load calculation formula. The total toxicity load of all directed road segments is accumulated and the data is stored. Evacuation optimization model construction module: With the minimum total toxicity load as the core objective, combined with the refuge point capacity constraint, the evacuation personnel conservation constraint, and the non-negativity constraint of evacuation volume, a complete mathematical model for personnel evacuation optimization in hazardous chemical gas leak accidents is constructed, supporting flexible configuration and modification of model parameters; The optimal evacuation plan solution module uses the road segment toxicity load as the edge weight and solves the minimum toxicity load path from each evacuation source point to each refuge point using the Dijkstra algorithm to obtain the minimum toxicity load of each source point-refuge point pair. This data is then substituted into the evacuation optimization model, and the optimal evacuation volume from each evacuation source point to each refuge point is obtained through linear programming. The solutions are then integrated to form a complete evacuation plan that includes the optimal evacuation path and the allocation of the number of people, and then output.
[0045] The present invention also provides an electronic device, characterized in that it comprises: Memory, used to store computer programs; When a processor executes a computer program stored in memory, it implements the aforementioned optimized method for personnel evacuation in the event of a toxic gas leak.
[0046] It should be noted that any parts not disclosed or specifically described in this invention are existing technology or conventional configurations, and their specific structures and working principles will not be elaborated further. In this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0047] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. It can be applied to various fields suitable for the present invention. Other modifications can be readily implemented by those skilled in the art. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and examples shown and described herein.
Claims
1. An optimized method for personnel evacuation in the event of a toxic gas leak, characterized in that, include: By obtaining the toxic gas mass concentration distribution field at any point downwind of the leak point, the lethal zone, serious injury zone, minor injury zone and safe zone are divided according to the toxic gas mass concentration. The axial length of the minor injury zone downwind is used as the protection distance, and a square emergency evacuation range with the leak source as the center point and the side length equal to the protection distance is constructed. Each directed road segment in the evacuation road network within the emergency evacuation range is divided into several micro-segments. The toxicity load of each micro-segment is obtained according to the toxicity load calculation formula, thereby obtaining the toxicity load of all directed road segments. An evacuation optimization model is constructed based on the toxicity load of all directed road segments, with the goal of minimizing the total toxicity load. The model is constrained by the capacity of refuge points, the conservation of the number of evacuees, and the non-negativity of the evacuation volume. Using the road segment toxicity load as the edge weight, the minimum toxicity load path from each evacuation source point to each refuge point is solved by the Dijkstra algorithm. The minimum toxicity load of each source point-refuge point pair is obtained. Then, the minimum toxicity load of the path is substituted into the evacuation optimization model, and the optimal evacuation volume from each evacuation source point to each refuge point is obtained by linear programming, forming an evacuation plan that includes the optimal path and the allocation of evacuees.
2. The optimized personnel evacuation method for toxic gas leaks according to claim 1, characterized in that, The mass concentration distribution field of the toxic gas was obtained using a Gaussian plume diffusion model, with the following formula: In the formula, For spatial points The mass concentration of toxic gas, For the strength of the leakage source, The average wind speed, The horizontal diffusion coefficient is... The vertical diffusion coefficient is... The effective height of the leakage source is defined by the x-axis, which represents the average wind direction. The y-axis is perpendicular to the x-axis on the horizontal plane and is located to the left of the x-axis. The z-axis is perpendicular to the horizontal plane xoy and is located upwards.
3. The optimized personnel evacuation method for toxic gas leaks according to claim 2, characterized in that, The formula for calculating the toxicity load is as follows: In the formula, Toxicity load, The concentration of toxic gas at the location of personnel exposure. For exposure time, This represents the toxicity coefficient.
4. The optimized personnel evacuation method for toxic gas leaks according to claim 3, characterized in that, The formula for calculating the total toxicity load of each road segment is: In the formula, For road section Total toxicity load, For the first The concentration of toxic gas in each micro-element segment, The length of the infinitesimal segment. denoted as the total number of micro-segments of this road section, and v as the constant evacuation speed of personnel.
5. The optimized personnel evacuation method for toxic gas leaks according to claim 4, characterized in that, The evacuation optimization model is as follows: The capacity constraint of the refuge point is: The evacuation number conservation constraint is: The non-negativity constraint for evacuation volume is: In the formula, A represents the total number of evacuation sources, and B represents the total number of refuge points. In order to evacuate the source, As a refuge, From arrive The number of people evacuated for Total number of evacuees for Maximum capacity for arrive The toxicity load of the minimum toxicity load path.
6. The optimized personnel evacuation method for a toxic gas leak according to claim 5, characterized in that, The solution method of Dijkstra's algorithm is as follows: A toxicity-weighted road network is constructed using the toxicity load of each directed road segment as the weight of the road network edge. The road network nodes include evacuation source points, road network intersections, and refuge points. Each evacuation source point is taken as the starting point in turn, and the Dijkstra algorithm is used to traverse the road network to find the shortest weighted path from the source point to each refuge point, that is, the path with the minimum toxicity load. Record the minimum toxicity load path for all source-refuge pairs, and extract the total toxicity load value for that path. This forms a table of toxicity load parameters for source-refuge pairs.
7. The optimized personnel evacuation method for a toxic gas leak according to claim 6, characterized in that, Total toxicity load of this pathway As known coefficients, they are substituted into the already constructed minimum evacuation optimization model for total toxicity load; The number of people evacuated from each source point to each refuge point For decision variables, the model constraints maintain the conservation of refuge capacity, the number of evacuees, and the non-negativity of evacuation volume; The optimal solution of the objective function that minimizes the total toxicity load under all constraints is obtained by solving the linear programming method, thus obtaining the optimal number of evacuees for each source-refuge point pair.
8. The optimized personnel evacuation method for a toxic gas leak according to claim 7, characterized in that, The method for obtaining the evacuation plan is as follows: By mapping the path with the minimum toxic load to the optimal number of evacuees, the optimal path and the number of people on that path are clearly defined, thus forming a complete evacuation plan that includes the selection of the optimal path and the precise allocation of the number of people.
9. A personnel evacuation optimization system for hazardous chemical toxic gas leak accidents, used to implement the personnel evacuation optimization method for toxic gas leaks as described in any one of claims 1 to 8, characterized in that, include: The toxic gas diffusion simulation and evacuation range delineation module is used to call the Gaussian plume diffusion model to calculate the toxic gas mass concentration distribution field at any point in space downwind of the leak point. Based on the toxic gas mass concentration classification standard, it divides the area into lethal zone, serious injury zone, minor injury zone and safe zone. The axial length of the minor injury zone downwind is used as the protection distance. A square emergency evacuation range with the leak source as the center and the side length equal to the protection distance is constructed. Road network discretization and toxicity load calculation module: The discretization method is used to divide each directed road segment of the evacuation road network within the emergency evacuation range into several micro-segments. The toxicity load of each micro-segment is solved according to the toxicity load calculation formula. The total toxicity load of all directed road segments is accumulated and the data is stored. Evacuation optimization model construction module: With the minimum total toxicity load as the core objective, combined with the refuge point capacity constraint, the evacuation personnel conservation constraint, and the non-negativity constraint of evacuation volume, a complete mathematical model for personnel evacuation optimization in hazardous chemical gas leak accidents is constructed, supporting flexible configuration and modification of model parameters; The optimal evacuation plan solution module uses the road segment toxicity load as the edge weight and uses the Dijkstra algorithm to solve for the minimum toxicity load path from each evacuation source point to each refuge point, obtaining the minimum toxicity load of each source point-refuge point pair. Substituting this data into the evacuation optimization model, the optimal evacuation volume from each evacuation source point to each refuge point is solved using the linear programming method. The solutions are then integrated to form a complete evacuation plan that includes the optimal evacuation path and the allocation of the number of people, and then output.
10. An electronic device, characterized in that, include: Memory, used to store computer programs; The processor, when executing the computer program stored in the memory, implements the personnel evacuation optimization method for toxic gas leaks as described in any one of claims 1 to 8.