Method for Planning Off-site Emergency Evacuation Routes of Nuclear Power Plants

Abstract

A method for planning off-site emergency evacuation routes of nuclear power plants is disclosed. In the method, the wind speed and the leakage point source intensity outside the nuclear power plant are collected to construct a radiation dose field diffusion model, the road condition information outside the nuclear power plant is collected to construct a road resistance function model of real-time traffic. With the evacuation time as the optimization objective, a vehicle deployment plan, that is, the corresponding relationship between the garage, the assembly point, and the resettlement point, is obtained by solving integer linear programming. Furthermore, the optimal evacuation route is solved. The total vehicle evacuation time and the personnel radiation exposure dose are selected as the objective functions for the path planning during the round-trip evacuation of nuclear emergency vehicles. The evacuation itinerary of each vehicle is solved by the non-dominated fast genetic algorithm to obtain a diverse solution set on the Pareto front, and the diverse solution set is screened by setting the upper limit threshold of the personnel radiation exposure dose. The TOPSIS decision-making method is used to evaluate the optimal solution set on the Pareto front selected, and the optimal evacuation route is obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of nuclear emergency, and particularly relates to a method for planning off-site emergency evacuation routes of nuclear power plants. Background Art

[0002] Developing nuclear energy is an important measure for implementing energy conservation and emission reduction strategies around the world. For a long time, the danger of nuclear accidents has been an obstacle to the development of nuclear energy. Temporary evacuation is the fastest and most effective emergency measure to ensure the safety of residents in the short term after a nuclear accident, and formulating a nuclear accident emergency evacuation plan is considered to be one of the most effective ways to avoid and mitigate the harm of the incident. How to make a scientific and reasonable decision on the emergency evacuation of nuclear accidents in the shortest time is a common problem faced by many nuclear accident emergency departments.

[0003] Nuclear emergency is the ultimate bottom line to ensure nuclear safety, indicating that in some unconventional situations, rapid actions are required to mitigate the harm of a large release of radioactive substances to human health and safety, quality of life, property or the environment. After a nuclear accident occurs, the radiation dose field shows the characteristics of a wide distribution range and dynamic changes in diffusion concentration due to complex meteorological factors. The total number of people to be evacuated is large and the distribution is not concentrated, and the real-time traffic situation is uncertain. Therefore, it is difficult for nuclear emergency management personnel to quickly propose an effective and scientific evacuation plan. At present, when formulating a nuclear accident emergency evacuation plan, the decisions made mainly based on personal work experience and basic safety rules and regulations are difficult to cope with actual emergency situations, lacking basis and low in efficiency.

[0004] Based on this, for nuclear emergency evacuation, in a complex and changeable nuclear radiation environment, how to make the best use of limited information to provide decision-making technical support for public transportation evacuation related to emergencies and make decisions quickly in an uncertain environment is the core issue for effectively reducing the risk of nuclear accidents.

[0005] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0006] The object of the present invention is to provide a method for planning off-site emergency evacuation routes of nuclear power plants, a method for planning off-site emergency evacuation routes of nuclear power plants based on integer linear programming and fast non-dominated sorting genetic algorithm, to overcome the safety and time problems of personnel evacuation under the conditions of dynamic changes in the nuclear radiation dose field and multi-batch evacuation requirements. To achieve the above object, the present invention provides the following technical solutions:

[0007] A method for planning off-site emergency evacuation routes of nuclear power plants according to the present invention includes:

[0008] In the first step, the wind speed outside the nuclear power plant and the leakage point source intensity are collected to construct a radiation dose field diffusion model.

[0009]

[0010] Among them, C(x0, y0, z0, t) represents the gas concentration at the spatial point (x0, y0, z0) at a certain time point t, Q is the leakage point source intensity, u is the wind speed, and are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively;

[0011] In the second step, the road condition information of N sections outside the nuclear power plant is collected to construct a road resistance function model for real-time traffic. Among them, T represents the driving time of the vehicle on the feasible path under real conditions, T f represents the driving time of the vehicle on the feasible path under ideal conditions, q n represents the number of vehicles choosing section n per unit time, C n represents the maximum number of vehicle passages on section n per unit time, α and β are the blocking coefficients, σ and ρ are the introduced road vehicle congestion weight parameter and road passability weight parameter respectively, and F is the scheme margin parameter;

[0012] In the third step, a path network is established based on the nuclear power plant, garage, assembly point, and resettlement point, and a vehicle allocation plan is formulated with the evacuation time as the optimization goal to establish a vehicle allocation plan model. Among them, the time t required for vehicle i in garage y to evacuate for the jth time y,i,j The expression is:

[0013]

[0014] Among them, i represents the vehicle number, j represents the jth evacuation, y represents the garage number, g and p represent the numbers of the assembly points, S represents the set of resettlement points, s and s g represent the numbers of the resettlement points in the resettlement point set S, d y,p represents the average driving time between garage y and assembly point p under ideal conditions, d p,s represents the average driving time between assembly point p and resettlement point s under ideal conditions, represents the driving time of the vehicle from resettlement point s g to assembly point p under ideal conditions, w represents the waiting time for each evacuation, s y,i,j,p represents that its value is 1 when vehicle i in garage y passes through assembly point p during the jth evacuation, otherwise it is 0. represents that vehicle i in garage y evacuates from assembly point g to resettlement point s during the (j - 1)th evacuation g , and during the jth evacuation from resettlement point s gIt is 1 when reaching the gathering point p, otherwise 0, L y Represents the maximum number of evacuations of garage y, and the total evacuation time At of vehicle i in garage y for the j-th time y,i,j Expression formula:

[0015] Among them, i represents the vehicle number, j represents the number of evacuations, y represents the garage number, k represents the k-th evacuation, and sum up the times of the j evacuations, t y,i,k Represents the time required for the k-th evacuation of vehicle i in garage y, L y Represents the maximum number of evacuations of garage y,

[0016] For the path planning problem with known starting and ending points, taking the evacuation time and the radiation exposure dose of personnel as the optimization objectives, solving the optimal vehicle evacuation path, and establishing a path optimization model. The expression of the evacuation time for the j-th evacuation of vehicle i in garage y:

[0017]

[0018] In the formula, i represents the vehicle number, j represents the j-th evacuation, y represents the garage number, g, p represent the numbers of the gathering points, N represents the set of feasible paths, n, m, f represent the path numbers in the feasible path N, S represents the set of resettlement points, s, s g Represents the resettlement point number in the resettlement point set S, T y,p,i,n Represents the driving time of vehicle i in garage y from garage y to the feasible path n of the gathering point p in the real situation, T y,p,s,i,m Represents the driving time of vehicle i in garage y from the gathering point p to the feasible path m of the resettlement point s in the real situation, w represents the waiting time for each evacuation, s y,i,j,p Represents that its value is 1 when vehicle i in garage y passes through the gathering point p during the j-th evacuation, otherwise 0, Represents that vehicle i in garage y travels from the gathering point g to the resettlement point s during the (j - 1)-th evacuation g and its value is 1 when reaching the gathering point p from the resettlement point s during the j-th evacuation g otherwise 0, Represents the driving time of vehicle i in garage y from the resettlement point s g to the feasible path f of the gathering point p in the real situation, T y,i,j Represents the driving time of vehicle i in garage y during the j-th evacuation in the real situation, L y Represents the maximum number of evacuations of garage y,

[0019] Sum up the driving times of the j evacuations to obtain the total evacuation time T of vehicle i y,i Expression:

[0020] Among them, i represents the vehicle number, j represents the evacuation times, y represents the garage number, k represents the k-th evacuation, and T y,i,k represents the time required for the k-th evacuation of vehicle i in garage y, and L y represents the maximum number of evacuations in garage y,

[0021] The radiation exposure dose C for the j-th evacuation of vehicle i in garage y y,i,j Expression:

[0022]

[0023] Among them, i represents the vehicle number, j represents the evacuation times, y represents the garage number, g and p represent the numbers of the assembly points, and s and s g represent the numbers of the resettlement points, and C y , i,j is the radiation exposure dose for the j-th evacuation of vehicle i in garage y. Each evacuation represents the successful evacuation of a batch of people to be evacuated, so the radiation exposure doses of this batch of evacuated people are the same, which is C y,i,j . C y is the radiation exposure dose of the people at garage y, C p is the radiation exposure dose of the people at assembly point p, C s is the radiation exposure dose of the people at resettlement point s, is the radiation exposure dose of the people at resettlement point s g at, and T y,i,j represents the driving time for the j-th evacuation of vehicle i in garage y under real conditions, and s y,i,j,p represents 1 when vehicle i in garage y passes through assembly point p during the j-th evacuation, and 0 otherwise, represents that the (j - 1)-th evacuation of vehicle i in garage y goes from assembly point g to resettlement point s g , and during the j-th evacuation, when it goes from resettlement point s g to assembly point p, its value is 1, and 0 otherwise, and L y represents the maximum number of evacuations in garage y;

[0024] In the fourth step, vehicle allocation is a combinatorial optimization problem, which can usually be formulated as an integer programming problem, that is, among a finite number of alternative solutions, find the best solution that meets certain constraints. Integer programming means that the variables (all or part) in the programming are restricted to integers. If in a linear model, the variables are restricted to integers, it is called integer linear programming. The variables include the number of vehicles and the maximum number of evacuations. By solving the vehicle allocation plan model through integer linear programming, multiple solution sets are obtained, and the diversity solution sets are screened by setting the upper and lower limit thresholds of the total evacuation time to obtain the optimal solution set. Obtain the corresponding relationships among the garages, assembly points, and resettlement points, that is, the vehicle allocation plan.

[0025] Step 5: Solve the optimal evacuation route. Select the total vehicle evacuation time and the personnel radiation exposure dose as the objective functions for path planning during nuclear power plant emergency evacuation. Solve the optimal time for each evacuation and the minimum personnel radiation exposure dose, and obtain the total evacuation time by calculating the optimal times of multiple evacuations. Combining the two optimization objective functions of the total vehicle evacuation time and the personnel radiation exposure dose, based on the solution results of Step 4, under the conditions of known starting and ending points, use the non-dominated fast genetic algorithm to solve the evacuation itinerary of each vehicle (garage, road, assembly point, road, resettlement point), obtain a diverse solution set on the Pareto front, set the upper limit threshold of the personnel radiation exposure dose to screen the diverse solution set, and use the TOPSIS decision-making method to evaluate the optimal solution set on the Pareto front selected, so as to obtain the optimal evacuation route.

[0026] In the described off-site emergency evacuation path planning method for a nuclear power plant, the path planning problem of multiple round trips is decomposed into two stages: First, with the evacuation time as the optimization objective, calculate the starting point (vehicle yard), intermediate point (assembly point), and ending point (resettlement point) of the vehicle's multiple round trips, and determine the vehicle deployment plan; Finally, through the non-dominated fast genetic algorithm, solve the Pareto solution set based on the known nodes, and then calculate the distances d from all solutions on the Pareto front to the ideal point + , and the distance d to the non-ideal point - , and through its proximity [d - / (d - + d + )] criterion, obtain the optimal solution on the Pareto front with the maximum proximity.

[0027] In the described off-site emergency evacuation path planning method for a nuclear power plant, the scheme margin parameter F is F = K·E, where K is a 1×5 possibility matrix representing the passability of the optional paths, and E is a 5×1 unit matrix.

[0028] In the above technical solution, the off-site emergency evacuation path planning method provided by the present invention has the following beneficial effects: Combining with the improved Gaussian puff model, a calculation method for the personnel radiation exposure dose that changes dynamically with the time window is given, which is more reliable than the path planning method in the static dose field; Through phased optimization, for the global route planning problem of nuclear emergency evacuation, optimize the vehicle deployment plan model with the evacuation time as the objective function, and optimize the vehicle path model with the evacuation time and radiation dose as the objective functions, reduce the complexity of large-scale global path planning, and reduce the number of scheme traversals; Output multiple evacuation routes through the genetic algorithm, so that nuclear emergency decision-makers can make decisions according to the actual situation, improving the decision-making efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments described in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0030] Figure 1 It is a schematic flowchart of the off-site emergency evacuation path planning method in the present invention for nuclear power plants.

[0031] Figure 2 It is a schematic diagram of the road network simplification of the off-site emergency evacuation path planning method in the present invention for nuclear power plants.

[0032] Figure 3 It is a schematic diagram of the evacuation area division of the off-site emergency evacuation path planning method in the present invention for nuclear power plants.

[0033] Figure 4 It is a schematic diagram of the radiation dose field diffusion model of the off-site emergency evacuation path planning method in the present invention for nuclear power plants.

[0034] Figures 5(a) to 5(d) It is a schematic diagram of the change trend of the Pareto optimal solution set during the genetic process of the off-site emergency evacuation path planning method in the present invention for nuclear power plants. Among them, Fig. 5(a) is the 50th generation, Fig. 5(b) is the 50th generation, Fig. 5(c) is the 300th generation, and Fig. 5(d) is the TOPSIS optimal solution decision.

[0035] Figure 6 It is a schematic diagram of the longitude and latitude of the off-site emergency evacuation path planning method in the present invention for nuclear power plants. Detailed implementation manners

[0036] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0037] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0038] It should be noted that like reference numerals and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it will not be necessary to further define and explain it in subsequent figures.

[0039] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation on the present invention.

[0040] In addition, the terms "first" and "second" are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0041] In the present invention, unless otherwise clearly specified and limited, the terms such as "mounted", "connected", "connected to", "fixed" and the like should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or integrated; it may be directly connected or indirectly connected through an intermediate medium, and it may be the internal communication of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0042] In the present invention, unless otherwise clearly specified and limited, the first feature being "above" or "below" the second feature may include the direct contact between the first and second features, or may include the situation where the first and second features are not in direct contact but in contact through other features therebetween. Moreover, the first feature being "above", "over" and "on" the second feature includes that the first feature is directly above and obliquely above the second feature, or merely means that the horizontal height of the first feature is higher than that of the second feature. The first feature being "under", "beneath" and "under" the second feature includes that the first feature is directly below and obliquely below the second feature, or merely means that the horizontal height of the first feature is lower than that of the second feature.

[0043] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the drawings. As Figures 1-6 shown, a method for planning an off-site emergency evacuation route of a nuclear power plant includes

[0044] Method for planning off-site emergency evacuation route of nuclear power plant, comprising the following steps:

[0045] Step 1: Determine the radiation dose field diffusion model:

[0046] The radiation dose of personnel is used as the optimization goal of the route planning model. During the evacuation process, it shows characteristics that change with time. It is necessary to first establish a nuclear radiation diffusion calculation model for easy calling in the route planning model.

[0047] For the instantaneous leakage accident of a fixed point source, the Gaussian puff diffusion model is selected for mathematical representation. A coordinate system is established based on the wind direction, and the diffusion expression formula of nuclides in the atmosphere is:

[0048]

[0049] where C(x0, y0, z0, t) represents the gas concentration at the spatial point (x0, y0, z0) at a certain time point t, Q is the leakage point source intensity, u is the wind speed, are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively;

[0050] Step 2: Determine the road impedance function model of real-time traffic:

[0051] In the route planning model with time as the optimization goal, the shortest time path in the ideal case is equivalent to the shortest distance path. In non-ideal cases such as road capacity limitations and the impact of emergencies, for the problem that the shortest distance path does not necessarily equal the shortest time path, a road impedance function model is established to correct the path travel time to make it more in line with the actual situation.

[0052] The road impedance function used by the American Highway Administration is:

[0053]

[0054] In the formula, T represents the driving time of the vehicle on the feasible path under real conditions, T f represents the driving time of the vehicle on the feasible path under ideal conditions, q n represents the number of vehicles choosing section n per unit time, C n represents the maximum number of vehicle passages on section n per unit time, n represents the section number, and α and β are the blocking coefficients, both of which are parameters to be calibrated.

[0055] In this scenario, the formula causes relatively small time fluctuations within the range of variable vehicle numbers and cannot significantly show the impact of road congestion on vehicle driving time. At the same time, considering that emergencies in actual traffic conditions will affect the road travel time, the node scheme margin parameter F is introduced to correct the function.

[0056] F = K·E

[0057] Where K is a possibility matrix of size 1×5 representing the passability of the optional paths, and E is an identity matrix of size 5×1. The function is corrected to adapt to the actual situation:

[0058]

[0059] Where T represents the driving time of the vehicle on the feasible path under the actual situation, and T f represents the driving time of the vehicle on the feasible path under the ideal situation, q n represents the number of vehicles selecting section n per unit time, C n represents the maximum number of vehicle passages on section n per unit time, n represents the section number, α and β are blocking coefficients, and σ and ρ are respectively the introduced road vehicle congestion weight parameter and road passability weight parameter. The parameters σ, ρ, α, and β are determined through data calibration, and the values are σ = 25, ρ = 0.15, α = 1.5, and β = 4.0.

[0060] Step 3. Derive the objective function:

[0061] Formulation of a vehicle allocation plan with the evacuation time as the optimization objective:

[0062] When calculating the total evacuation time, the driving time and waiting time of different sections should be considered. The waiting time includes the time for people to get on the vehicle, get off the vehicle, and the departure interval time.

[0063] The time t required for vehicle i in garage y to evacuate for the jth time y,i,j The expression is:

[0064]

[0065] Where i represents the vehicle number, j represents the jth evacuation, y represents the garage number, g and p represent the numbers of the assembly points, S represents the set of resettlement points, s and s g represent the numbers of the resettlement points in the set of resettlement points S. d y,p represents the average driving time between garage y and assembly point p under the ideal state, d p,s represents the average driving time between assembly point p and resettlement point s under the ideal state, represents the driving time of the vehicle from resettlement point s g to assembly point p under the ideal state, and w represents the waiting time for each evacuation. s y,i,j,p represents 1 when vehicle i in garage y passes through assembly point p during the jth evacuation, otherwise 0, represents that vehicle i in garage y evacuates from assembly point g to resettlement point s during the (j - 1)th evacuationg and its value is 1 when the j-th evacuation is from the resettlement point s g to the assembly point p, otherwise it is 0. L y represents the maximum number of evacuations from garage y.

[0066] Then the total evacuation time At of the j-th evacuation of vehicle i in garage y y,i,j Expression formula:

[0067]

[0068] In the formula, i represents the vehicle number, j represents the number of evacuations, y represents the garage number, k represents the k-th evacuation, and the time of the j-th evacuation is summed up, t y,i,k represents the time required for the k-th evacuation of vehicle i in garage y, L y represents the maximum number of evacuations from garage y.

[0069] Solve the optimal vehicle evacuation route:

[0070] Derivation of the evacuation time expression

[0071] The vehicle allocation plan is obtained from the above content, that is, the emergency evacuation order of each vehicle is obtained, and the problem is transformed into a middle road planning problem with multiple known starting points (garages), intermediate nodes (assembly points) and end points (resettlement points). For the path planning problem with known starting and ending points, the optimal vehicle evacuation path is solved with the evacuation time and the radiation exposure dose of personnel as the optimization objectives.

[0072] Evacuation time expression for the j-th evacuation of vehicle i in garage y:

[0073]

[0074] In the formula, i represents the vehicle number, j represents the j-th evacuation, y represents the garage number, g, p represent the numbers of the assembly points, N represents the set of feasible paths, n, m, f represent the path numbers in the feasible path N, S represents the set of resettlement points, s, s g represents the resettlement point number in the resettlement point set S. T y,p,i,n represents the driving time of the feasible path n of vehicle i in garage y from garage y to the assembly point p in the real situation, T y,p,s,i,m represents the driving time of the feasible path m of vehicle i in garage y from the assembly point p to the resettlement point s in the real situation, w represents the waiting time for each evacuation. s y,i,j,p represents that its value is 1 when vehicle i in garage y passes through the assembly point p during the j-th evacuation, otherwise it is 0, represents the (j - 1)-th evacuation of vehicle i in garage y from the assembly point g to the resettlement point s g , and the j-th evacuation is from the resettlement point s gIts value is 1 when it reaches the gathering point p, otherwise 0. Indicates the driving time T of the vehicle i in the garage y from the placement point s g to the feasible path f of the gathering point p in the actual situation. y,i,j Indicates the driving time of the j-th evacuation of the vehicle i in the garage y in the actual situation. L y Indicates the maximum number of evacuations of the garage y.

[0075] Sum the driving times of the j-th evacuations to obtain the total evacuation time T of the vehicle i y,i Expression:

[0076]

[0077] Among them, i represents the vehicle number, j represents the number of evacuations, y represents the garage number, k represents the k-th evacuation, T y,i,k Indicates the time required for the k-th evacuation of the vehicle i in the garage y, L y Indicates the maximum number of evacuations of the garage y.

[0078] Derivation of the expression for the radiation exposure dose of personnel

[0079] For the convenience of calculation, the plane diffusion area is further simplified. Taking the nuclear power plant as the origin of the coordinate system, a 10Km×10Km range is taken as the effective diffusion area. For the convenience of calculation, the radiation dose between sections is taken as the product of the average of the starting point radiation dose and the ending point radiation dose and the section driving time.

[0080] The radiation exposure dose C of the j-th evacuation of the vehicle i in the garage y y,i,j Expression:

[0081]

[0082] In the formula, i represents the vehicle number, j represents the number of evacuations, y represents the garage number, g, p represent the numbers of the gathering points, s, s g Represents the placement point number, C y,i,j Is the radiation exposure dose of the j-th evacuation of the vehicle i in the garage y. Each evacuation represents the successful evacuation of a batch of people to be evacuated, and the radiation exposure dose of this batch of evacuated people is the same, that is, C y,i,j . C y Is the radiation exposure dose of the people at the garage y, C p Is the radiation exposure dose of the people at the gathering point p, C s Is the radiation exposure dose of the people at the placement point s, For the placement point s g The radiation exposure dose of the people at the place, T y,i,j Indicates the driving time of the j-th evacuation of the vehicle i in the garage y in the actual situation, s y,i,j,pIt is 1 when vehicle i in garage y passes through assembly point p for the jth evacuation, and 0 otherwise. It represents that vehicle i in garage y evacuates from assembly point g to resettlement point s for the (j - 1)th time. g , and it is 1 when evacuating from resettlement point s to assembly point p for the jth time, and 0 otherwise. L g It represents the maximum number of evacuations from garage y. y

[0083] Step 4. Solving the optimal public emergency vehicle deployment plan:

[0084] Combining the road network parameters outside the nuclear power plant and the information of personnel and vehicles, multiple solution sets are obtained by solving the vehicle deployment plan model through integer linear programming, and the diversity solution sets are screened by setting the upper and lower limit thresholds of the total evacuation time to obtain the optimal solution set.

[0085] Step 5. Solving the optimal evacuation route:

[0086] Select the total vehicle evacuation time and the personnel radiation exposure dose as the objective functions for path planning during nuclear power plant emergency evacuation. Solve the optimal time and minimum radiation exposure dose for each evacuation according to the above steps, and then obtain the total evacuation time and the personnel radiation exposure dose by calculating the sum of the optimal times and minimum radiation doses for multiple evacuations. Set the upper limit threshold of the personnel radiation exposure dose to further screen the diversity solution sets.

[0087] Emergency evacuation involves the round-trip travel of public emergency vehicles and is a complex network system composed of multiple trips. First, the corresponding relationship between the garage → assembly point → resettlement point is obtained by using integer programming.

[0088] Next, add the intermediate roads, combine the two optimization objective functions of the total vehicle evacuation time and the personnel radiation exposure dose, and use the non-dominated sorting genetic algorithm with elitist retention. Set the initial population size to 100, and the initialization method is to randomly assign 0 or 1 to the binary code with a length of 108. Solve the evacuation itinerary of each vehicle through the non-dominated fast genetic algorithm: garage → road → assembly point → road → resettlement point.

[0089] Finally, use the TOPSIS decision method to select the optimal solution on the Pareto front. Since the dimensions of the total evacuation time and the personnel radiation exposure dose in the objective function are different, the Euclidean distance is used to unify their dimensions. The distances (d + ) from all solutions on the calculated Pareto front to the ideal point, and the distances (d - ) to the non-ideal point are obtained. Through their closeness [d - / (d - + d + ​)]The standard is used to obtain the solution with the maximum proximity, that is, the optimal solution that comprehensively considers the two optimization objectives of the total evacuation time and the personnel radiation exposure dose.

[0090] Decode the optimal solution to obtain a specific evacuation plan, and compare it with the evacuation efficiency and safety without the intelligent algorithm. It is found that after adopting the intelligent algorithm, the total evacuation time is significantly reduced, the personnel radiation exposure dose is visualized, the personnel radiation exposure dose is controlled within a safe range, and the decision-making efficiency and reliability are improved.

[0091] In one embodiment, Step 1, scenario assumption:

[0092] The environmental factors that need to be considered in the nuclear accident emergency evacuation plan are complex. In the real situation, it is difficult to obtain the real-time positions of personnel and vehicles, the influence of weather on dose diffusion is variable, and personnel emotions, social opinions, traffic conditions, etc. will all affect the evacuation efficiency. Therefore, when formulating the plan, it is assumed that all evacuation actions are carried out in an organized manner:

[0093] The locations of the assembly points, resettlement points, and garages are known;

[0094] Do not consider the preparation time of personnel, and assume that personnel are already waiting at the assembly point for evacuation;

[0095] Consider the preparation time of emergency vehicles from the garage to the assembly point and the evacuation time from the assembly point to the resettlement point;

[0096] Emergency vehicles all depart from 3 fixed garages;

[0097] The same emergency vehicle shuttles between the same assembly point and resettlement point;

[0098] The vehicle driving speed is the maximum speed allowed by the road section;

[0099] Do not consider the waiting time of emergency vehicles at intersections;

[0100] The number of personnel at each assembly point is known;

[0101] The personnel radiation dose on the same vehicle is the same;

[0102] Consider the influence of the radiation dose field at different time periods on the evacuation path;

[0103] After a certain time after the off-site emergency instruction is issued, the public vehicle emergency evacuation begins.

[0104] Step 2, simplify the road network:

[0105] For the public emergency vehicle deployment problem, with the evacuation time as the optimization objective and not involving the real path selection, the road nodes between the garage → assembly point → resettlement point can be ignored, and the road network can be simplified as shown in the appendixFigure 2 as shown

[0106] Step 3. Determine the radiation dose field diffusion model:

[0107] For a continuous leakage accident of a fixed point source, the Gaussian puff diffusion model is selected for mathematical representation, and its expression formula is:

[0108]

[0109] where C(x0,y0,z0,t) represents the gas concentration at the spatial point (x0,y0,z0) at a certain time point t, Q is the leakage point source intensity, u is the wind speed, are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively; z0 represents the height from the ground, in meters. For the convenience of calculation, z0 = 2m is taken to obtain the nuclide gas concentration at the corresponding height:

[0110]

[0111] In the real nuclear radiation diffusion process, nuclide decay is an important factor affecting radiation attenuation, and the above Gaussian model is corrected:

[0112]

[0113] In the formula, exp(-0.00358t) is the nuclear radiation concentration attenuation rate. C(x0,y0,2,t) represents the gas concentration at the spatial point (x0,y0,2) at a certain time point t, Q is the leakage point source intensity, u is the wind speed, are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively, and the values are empirical formulas: is the distance from the leakage point source.

[0114] In order to ensure that the horizontal axis X of the Gaussian model is consistent with the downwind direction, coordinate transformation is required. Assuming that the wind direction remains unchanged during the gas diffusion process, the coordinates of the nuclear leakage point source in the IOJ coordinate system are O0=(i0,j0). Taking this point as the origin, a Cartesian coordinate system XO0Y is established, and the wind direction is the positive direction of the X axis. Let the angle between the wind direction and the positive direction of the I axis be θ. Then the expression of the radiation gas concentration of any point A(x1,y1) in the plane diffusion region 2m above the ground in the reference coordinate system IOJ is:

[0115]

[0116] Wherein, exp(-0.00358t) is the decay rate of nuclear radiation concentration. C(i1,j1,2,t) represents the gas concentration at the spatial point (i1,j1,2) at a certain time point t in the IOJ coordinate system, (i0,j0) is the coordinate of the leakage source point in the IOJ coordinate system, Q is the leakage point source intensity, u is the wind speed, are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively, and θ is the angle between the wind direction and the positive direction of the I-axis.

[0117] Step Four: Derive the objective function:

[0118] The optimization of the vehicle deployment plan aims to minimize the evacuation time:

[0119] Derivation of the evacuation time expression

[0120] First, initialize the driving time and waiting time for different sections. The expression for the driving time of a vehicle from the garage to the assembly point is:

[0121]

[0122] Wherein, y represents the garage number, p represents the assembly point number, Y represents the set of garages, P represents the set of assembly points, l y,p represents the distance between garage y and assembly point p, v ave represents the average driving speed of the vehicle, d y,p represents the average driving time of the vehicle between garage y and assembly point p under ideal conditions.

[0123] The expression for the driving time of a vehicle from the assembly point to the resettlement point is:

[0124]

[0125] Wherein, p represents the assembly point number, s represents the resettlement point number, P represents the set of all assembly points, S represents the set of all resettlement points, l p,s represents the distance between assembly point p and resettlement point s, v ave represents the average driving speed of the vehicle, d p,s represents the average driving time of the vehicle between assembly point p and resettlement point s under ideal conditions.

[0126] Vehicles are required to depart from the garage at regular intervals:

[0127] l y,i = Δ×i + ε×ρ y,i,1 , i = 1, 2, 3,..., 20

[0128] Wherein, Δ represents the departure interval, i represents the vehicle number, y represents the garage number, ε represents the interval departure time after the accident, ρ y,i,1It is 1 when vehicle i departs from garage y for the first evacuation, otherwise it is 0, l y,i It represents the time taken by vehicle numbered i in garage y from the occurrence of the accident to its departure.

[0129] The expression for the waiting time of the vehicle is specified as:

[0130] w = l y,i + h p + u s

[0131] In the formula, i represents the vehicle number, y represents the garage number, p represents the assembly point number, s represents the resettlement point number, l y,i represents the time taken by vehicle numbered i in garage y from the occurrence of the accident to its departure, h p represents the time for loading personnel at the assembly point, u s represents the time for unloading personnel at the resettlement point, and w represents the waiting time for each evacuation.

[0132] Then the expression for the time required for the j-th evacuation of vehicle i in garage y is:

[0133]

[0134] In the formula, i represents the vehicle number, j represents the number of evacuations, y represents the garage number, g and p represent the assembly point numbers, s and s g represent the resettlement point numbers, and S represents the set of all resettlement points. d y,p represents the average driving time of the vehicle between garage y and assembly point p under ideal conditions, d p,s represents the average driving time of the vehicle between assembly point p and resettlement point s under ideal conditions, represents the driving time of the vehicle from resettlement point s g to assembly point p under ideal conditions, and w represents the waiting time for each evacuation. s y,i,j,p It is 1 when vehicle i in garage y passes through assembly point p during the j-th evacuation, otherwise it is 0, It represents that vehicle i in garage y departs from assembly point g to resettlement point s during the (j - 1)-th evacuation g , and during the j-th evacuation, it departs from resettlement point s g to assembly point p and its value is 1, otherwise it is 0, L y represents the maximum number of evacuations from garage y.

[0135] Then the total evacuation time At of vehicle i in garage y y,i,j The expression formula:

[0136]

[0137] where \(i\) represents the vehicle number, \(j\) represents the evacuation times, \(y\) represents the garage number, \(k\) represents the \(k\)th evacuation, and the sum of the times for \(j\) evacuations is \(t\). y,i,k represents the time required for the \(k\)th evacuation of vehicle \(i\) in garage \(y\), \(L\). y represents the maximum number of evacuations from garage \(y\).

[0138] In summary, the optimization formula for the evacuation time can be obtained and organized into a minimization form:

[0139]

[0140] where \(i\) represents the vehicle number, \(j\) represents the evacuation times, \(k\) represents the \(k\)th evacuation, \(y\) represents the garage number, \(g\) and \(p\) represent the numbers of the assembly points, \(s\) and \(s\). g represent the numbers of the resettlement points, and \(S\) represents the set of all resettlement points. \(At\). y,i,j represents the total time of the \(j\)th evacuation of vehicle \(i\) in garage \(y\), \(d\). y,p represents the average driving time of the vehicle between garage \(y\) and assembly point \(p\) in the ideal state, \(d\). p,s represents the average driving time of the vehicle between assembly point \(p\) and resettlement point \(s\) in the ideal state. represents the driving time of the vehicle from resettlement point \(s\) g to assembly point \(p\) in the ideal state, \(l\). y,i represents the time from the accident occurrence to the departure of vehicle \(i\) numbered in garage \(y\), \(h\). p represents the personnel loading time at the assembly point, \(u\). s represents the personnel unloading time at the resettlement point, \(s\). y,i,k,p represents 1 when the \(k\)th evacuation of vehicle \(i\) in garage \(y\) passes through assembly point \(p\), and 0 otherwise. represents that the \((k - 1)\)th evacuation of vehicle \(i\) in garage \(y\) goes from assembly point \(g\) to resettlement point \(s\). g and the \(k\)th evacuation goes from resettlement point \(s\). g to assembly point \(p\) and its value is 1, otherwise 0, \(L\). y represents the maximum number of evacuations from garage \(y\).

[0141] Constraint setting

[0142] Solve \(\min At\). y,i,j , first, constrain the maximum number of evacuations of each emergency vehicle:

[0143]

[0144] where \(i\) represents the vehicle number, \(y\) represents the garage number, \(p\) represents the number of the assembly point, \(v\) represents the vehicle driving speed, \(P\) represents the set of all assembly points, \(Y\) represents the set of all garages, \(D\). p represents the number of people waiting to be evacuated at assembly point \(p\). According toFigure 3 Divide the evacuation area into three zones, calculate the number of evacuation times required for all vehicles in a garage y to evacuate all the people in a certain area, and take this number as the maximum evacuation times of all vehicles in garage y. K y Represents the total number of vehicles at garage y, C v Represents the maximum number of people that can be accommodated by public emergency vehicles, L y Represents the maximum evacuation times of the vehicles in garage y.

[0145] To make the parameters s y, i, j ,p and maintain consistency:

[0146]

[0147] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, g and p represent the numbers of the assembly points, s g represents the number of the resettlement point, s y,i,j,p represents that its value is 1 when the vehicle i in garage y passes through the assembly point p for the j-th evacuation, otherwise it is 0, represents that the vehicle i in garage y travels from the assembly point g to the resettlement point s for the (j - 1)-th evacuation g , and its value is 1 when traveling from the resettlement point s to the assembly point p for the j-th evacuation, otherwise it is 0, s g represents that its value is 1 when the vehicle i in garage y passes through the assembly point p for the (j - 1)-th evacuation, otherwise it is 0, s y,i,j-1,p represents that its value is 1 when the vehicle i in garage y passes through the assembly point g for the (j - 1)-th evacuation, otherwise it is 0. P represents the set of all assembly points, Y represents the set of all garages, S represents the set of all resettlement points, K y,i,j-1,g represents the total number of vehicles at garage y, L y represents the maximum evacuation times of garage y. y represents the maximum evacuation times of garage y.

[0148] To ensure that the public emergency vehicle evacuation plan can evacuate all the people to be evacuated safely:

[0149]

[0150] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, p represents the number of the assembly point, D y,i,j represents the number of people evacuated by the vehicle i in garage y for the j-th evacuation, P represents the set of all assembly points, Y represents the set of all garages, K y represents the total number of vehicles at garage y, L y represents the maximum evacuation times of garage y, D p represents the number of people to be evacuated at the assembly point p.

[0151] All the people to be evacuated at the assembly point p should be fully evacuated:

[0152]

[0153] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, p represents the number of the assembly point, P represents the set of all assembly points, Y represents the set of all garages, K y represents the total number of vehicles at garage y, L y represents the maximum evacuation times of garage y, D p represents the number of people to be evacuated at the assembly point p, D y,i,j represents the number of evacuated people when vehicle i at garage y is evacuated for the j-th time, s y,i,j,p represents 1 when vehicle i at garage y passes through the assembly point p during the j-th evacuation, and 0 otherwise.

[0154] Assume that the capacity of each public emergency vehicle is the same:

[0155]

[0156] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, v represents the vehicle driving speed, Y represents the set of all garages, K y represents the total number of vehicles at garage y, L y represents the maximum evacuation times of garage y, D y,i,j represents the number of evacuated people when vehicle i at garage y is evacuated for the j-th time, C v represents the maximum capacity of the vehicle.

[0157] To prevent the vehicle from evacuating with an empty load, the remaining number of people at the assembly point p to be evacuated should be greater than or equal to 0:

[0158]

[0159] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, P represents the set of all assembly points, Y represents the set of all garages, K y represents the total number of vehicles at garage y, L y represents the maximum evacuation times of garage y, D p represents the number of people to be evacuated at the assembly point p, D y,i,j-1 represents the number of evacuated people when vehicle i at garage y was evacuated for the (j - 1)-th time, s y,i,j-1,p represents 1 when vehicle i at garage y passed through the assembly point p during the (j - 1)-th evacuation, and 0 otherwise.

[0160] During emergency evacuation, all vehicles should be used:

[0161]

[0162] In the formula, i represents the vehicle number, y represents the garage number, and x y,i,1 represents that vehicle i departs from garage y for the first evacuation from garage y, and K y represents the total number of vehicles at garage y, and Y represents the set of all garages.

[0163] Since the capacity of the resettlement point is limited, constraint conditions should be set:

[0164]

[0165] In the formula, i represents the vehicle number, j represents the evacuation times, y represents the garage number, and v y,i,j,s represents that vehicle i of garage y arrives at resettlement point s for the jth evacuation, and B s represents the maximum number of people that can be accommodated at resettlement point s, Y represents the set of all garages, S represents the set of all resettlement points, and K y represents the total number of vehicles at garage y, and L y represents the maximum number of evacuations from garage y.

[0166] Step Five: Solving the Optimal Public Emergency Vehicle Deployment Plan:

[0167] First, there are 3 garages, 14 assembly points, and 3 resettlement points. There are 126 kinds of correlation relationships among them. There are 20, 20, and 21 vehicles in the garages respectively. Therefore, there are 2562 kinds of the first evacuation plans for the vehicles. To reduce the number of traversals and calculation time, according to the distribution of the garages, resettlement points, and assembly points around the nuclear power plant, as shown in the appendix Figure 2 shown, the relationships among the three are initially correlated. After determining the initial deployment plan, only 442 kinds of vehicle deployment plans need to be traversed, the time objective function values corresponding to different vehicle evacuation plans are calculated, and the plan with the shortest time is selected, as shown in Table 2. The specific form of the vehicle evacuation plan is shown in Appendix 3, and other parameters are shown in Appendix 1.

[0168] Appendix 1 Information Table of Garages and Resettlement Points:

[0169]

[0170] Appendix 3 Vehicle Deployment Plan Table:

[0171]

[0172] Table 1 Initial Deployment Plan

[0173]

[0174]

[0175] Table 2 The three optimal vehicle evacuation plans

[0176]

[0177] Step 6. Real emergency evacuation road network model:

[0178] Using the basic data such as garages, assembly points, resettlement points, and roads as data sources, connect the nodes with line segments to establish a road network in the reference coordinate system IOJ, as shown in the appendix Figure 3 shown. Number all the roads between the garage → assembly point and the assembly point → resettlement point, and calculate the lengths of all the roads.

[0179] Step 7. Derive the objective function:

[0180] For the path planning problem with known starting and ending points, taking the evacuation time and the radiation exposure dose of personnel as the optimization objectives, solve the optimal vehicle evacuation path.

[0181] Derivation of the evacuation time expression

[0182] Ideal travel time expression for feasible paths in the real road network:

[0183]

[0184]

[0185] In the formula, y represents the garage number, p represents the assembly point number, n represents the path number in the feasible path N, s represents the resettlement point number in the resettlement point set S, N represents the set of feasible paths, Y represents the set of all garages, P represents the set of all assembly points, S represents the set of all resettlement points, E y,p,n represents the length of the feasible path n from the garage y to the assembly point p for the vehicle, E p,s,n represents the length of the feasible path n from the assembly point p to the resettlement point s for the vehicle, v ave represents the average driving speed of the vehicle, represents the driving time of the feasible path n from the garage y to the assembly point p for the vehicle in the ideal state, represents the driving time of the feasible path n from the assembly point p to the resettlement point s for the vehicle in the ideal state.

[0186] When too many vehicles choose the same path, it will reduce the road traffic capacity and increase the travel time. Therefore, a more realistic travel time expression is obtained through the road impedance function:

[0187]

[0188]

[0189] Wherein, i represents the vehicle number, j represents the j-th evacuation, y represents the garage number, p represents the assembly point number, n represents the path number in the set of feasible paths N, s represents the settlement point number in the set of settlement points S, N represents the set of feasible paths, Y represents the set of all garages, P represents the set of all assembly points, S represents the set of all settlement points, and K y represents the total number of vehicles at garage y, C n represents the maximum vehicle passing capacity on section n, α and β are blockage coefficients, F is the node plan margin parameter, σ and ρ are the road vehicle congestion weight parameter and the road passability weight parameter respectively, a y,i,p,n represents that when vehicle i at garage y selects the feasible path n from garage y to the assembly point p, it takes the value of 1, otherwise 0, b y,p,i,s,n represents that when vehicle i at garage y selects the feasible path n from the assembly point p to the settlement point s, it takes the value of 1, otherwise 0. represents the driving time of the feasible path n for the vehicle from garage y to the assembly point p under ideal conditions, represents the driving time of the feasible path n for the vehicle from the assembly point p to the settlement point s under ideal conditions. T y,p,i,n represents the driving time of the feasible path n for vehicle i at garage y from garage y to the assembly point p in the real situation, T y,p,s,i,n represents the driving time of the feasible path n for vehicle i at garage y from the assembly point p to the settlement point s in the real situation.

[0190] Evacuation time expression for the j-th evacuation of vehicle i in garage y:

[0191]

[0192] Wherein, i represents the vehicle number, j represents the j-th evacuation, y represents the garage number, g and p represent the assembly point numbers, n, m, and f represent the path numbers in the set of feasible paths N, s, s g represents the settlement point number in the set of settlement points S, w represents the waiting time for each evacuation, N represents the set of feasible paths, S represents the set of all settlement points, L y represents the maximum evacuation times of garage y, T y,p,i,n represents the driving time of the feasible path n for vehicle i at garage y from garage y to the assembly point p in the real situation, T y,p,s,i,m represents the driving time of the feasible path m for vehicle i at garage y from the assembly point p to the settlement point s in the real situation, s y,i,j,p represents that when vehicle i in garage y passes through the assembly point p during the j-th evacuation, its value is 1, otherwise 0, represents that vehicle i in garage y evacuates from the assembly point g to the settlement point s during the (j - 1)-th evacuation g and during the j-th evacuation from the settlement point s gIts value is 1 when it reaches the gathering point p, otherwise it is 0. Indicates that vehicle i in garage y in the actual situation departs from the resettlement point s g The travel time of the feasible path f from the resettlement point s to the gathering point p, T y,i,j Indicates the travel time of the j-th evacuation of vehicle i in garage y in the actual situation.

[0193] Sum the travel times of the j evacuations to obtain the total evacuation time of vehicle i:

[0194]

[0195] In summary, the optimization formula for the evacuation time can be obtained:

[0196]

[0197] In the formula, i represents the vehicle number, j represents the number of evacuations, k represents the k-th evacuation, y represents the garage number, g and p represent the numbers of the gathering points, m and f represent the path numbers in the feasible path set N, s and s g Represent the numbers of the resettlement points in the resettlement point set S, N represents the set of feasible paths, S represents the set of all resettlement points, L y Represents the maximum number of evacuations of garage y, Indicates that vehicle i in garage y in the actual situation departs from the resettlement point s g The travel time of the feasible path f from the resettlement point s to the gathering point p, T y,p,s,i,m Represents the travel time of the feasible path m from the gathering point p to the resettlement point s of vehicle i in garage y, s y,i,k,p Its value is 1 when the k-th evacuation of vehicle i in garage y passes through the gathering point p, otherwise it is 0, Indicates that the (k - 1)-th evacuation of vehicle i in garage y goes from the gathering point g to the resettlement point s g , and its value is 1 when the k-th evacuation goes from the resettlement point s g To the gathering point p, otherwise it is 0, l y,i Represents the time from the occurrence of the accident to the departure of vehicle i numbered i in garage y, h p Represents the personnel loading time at the gathering point, u s Represents the personnel unloading time at the resettlement point, T y,i The total evacuation time of vehicle i in garage y.

[0198] Derivation of the expression for the radiation exposure dose of personnel

[0199] According to the radiation dose field diffusion model, assume that the origin of the coordinate system XO0Y of the Gaussian plume coincides with the origin of the reference coordinate system IOJ, as shown in the appendix Figure 4 Shown, then the diffusion model should be:

[0200]

[0201] In the formula, exp(-0.00358t) is the decay rate of the nuclear radiation concentration. C(i1,j1,2,l,t) represents the gas concentration at the spatial point (i1,j1,2) at a certain time point t in the IOJ coordinate system. is the distance from the leakage point source, Q is the leakage point source intensity, u is the wind speed, and θ is the angle between the wind direction and the positive direction of the I axis.

[0202] For the convenience of calculation, the plane diffusion area is further simplified. Taking the leakage point as the center, a 10Km×10Km range is taken as the effective diffusion area, and the radiation dose between sections is taken as the product of the average value of the doses at two points and the driving time of the section.

[0203] The expression of the radiation exposure dose for the i-th vehicle in garage y during the j-th evacuation:

[0204]

[0205] In the formula, i represents the vehicle number, j represents the evacuation number, k represents the k-th evacuation, y represents the garage number, g and p represent the numbers of the assembly points, s and s g represent the numbers of the resettlement points in the resettlement point set S, r is the horizontal axis of the reference coordinate system, e is the vertical axis of the reference coordinate system, r y 、r p 、r s 、 are respectively the abscissas of the garage y, the assembly point p, the resettlement point s, and the resettlement point s g in the reference coordinate system, e y 、e p 、e s 、 are respectively the ordinates of the garage y, the assembly point p, the resettlement point s, and the resettlement point s g in the reference coordinate system, x y 、x p 、x s 、 are respectively the straight-line distances from the garage y, the assembly point p, the resettlement point s, and the resettlement point s g to the leakage point in the reference coordinate system. L y represents the maximum number of evacuations of garage y. Δ represents the departure interval, T y,p,i,n represents the driving time of the feasible path n of vehicle i in garage y from garage y to assembly point p in the real situation, T y,i,j represents the driving time of the j-th evacuation of vehicle i in garage y in the real situation, T y,i,k represents the driving time of the k-th evacuation of vehicle i in garage y in the real situation, T y,p,s,i,mDenote the driving time of vehicle i in garage y from the assembly point p to the resettlement point s along the feasible path m under the actual situation. Denote that for vehicle i in garage y under the actual situation, from the resettlement point s g to the driving time of the feasible path f to the assembly point p. s y,i,j,p Denote that when vehicle i in garage y passes through the assembly point p for the j-th evacuation, its value is 1, otherwise 0. Denote that for the (j - 1)-th evacuation of vehicle i in garage y from the assembly point g to the resettlement point s g , and when for the j-th evacuation from the resettlement point s g to the assembly point p, its value is 1, otherwise 0. C(r y , e y , 2, x y , Δ) is the radiation exposure dose when vehicle i in garage y starts to evacuate from garage y for the first time. C(r p , e p , 2, x p , T y,p,i,n ) is the radiation exposure dose of vehicle i in garage y at the assembly point p during the first evacuation. C(r s , e s , 2, x s , T y,i,j ) is the radiation exposure dose of vehicle i in garage y at the resettlement point s during the first evacuation. is the radiation exposure dose of vehicle i in garage y at the resettlement point s during the (j - 1)-th evacuation. g is the radiation exposure dose of vehicle i in garage y at the assembly point p during the (j - 1)-th evacuation. is the radiation exposure dose of vehicle i in garage y at the resettlement point s during the j-th evacuation. C y,i,j is the radiation exposure dose of vehicle i in garage y during the j-th evacuation. Each evacuation represents the successful evacuation of a batch of people to be evacuated, and the radiation exposure doses of this batch of evacuated people are the same, that is C y,i,j .

[0206] In summary, the path planning model to be optimized can be obtained and unified into the minimization form:

[0207]

[0208] In the formula, i represents the vehicle number, j represents the evacuation times, k represents the k-th evacuation, y represents the garage number, g, p represent the numbers of the assembly points, n, m, f represent the path numbers in the feasible path set N, s, s g represent the numbers of the resettlement points in the resettlement point set S, r is the abscissa of the reference coordinate system, e is the ordinate of the reference coordinate system, r y , r p, r s , are respectively the abscissa of the garage y, the assembly point p, the resettlement point s, and the resettlement point s g in the reference coordinate system, e y , e p , e s , are respectively the abscissa of the garage y, the assembly point p, the resettlement point s, and the resettlement point s g the ordinate in the reference coordinate system, x y , x p , x s , are respectively the abscissa of the garage y, the assembly point p, the resettlement point s, and the resettlement point s g the straight-line distance from the leakage point in the reference coordinate system. N represents the set of feasible paths, S represents the set of all resettlement points, L y represents the maximum number of evacuation times of the garage y, Δ represents the departure interval, l y,i represents the time taken for the vehicle numbered i in the garage y to depart from the accident occurrence, h p represents the personnel loading time at the assembly point, u s represents the personnel unloading time at the resettlement point. T y,p,i,n represents the driving time of the vehicle i in the garage y from the garage y to the feasible path n of the assembly point p in the actual situation, T y,i,j represents the driving time of the jth evacuation of the vehicle i in the garage y, T y,i,k represents the driving time of the kth evacuation of the vehicle i in the garage y, T y,p,s,i,m represents the driving time of the vehicle i in the garage y from the assembly point p to the feasible path m of the resettlement point s in the actual situation, represents the vehicle i in the garage y from the resettlement point s g to the driving time of the feasible path f of the assembly point p. s y,i,j,p represents that when the vehicle i in the garage y passes through the assembly point p for the jth evacuation, its value is 1, otherwise it is 0, represents that the (j - 1)th evacuation of the vehicle i in the garage y goes from the assembly point g to the resettlement point s g , and when the jth evacuation goes from the resettlement point s g to the assembly point p, its value is 1, otherwise it is 0, s y,i,k,p represents that when the vehicle i in the garage y passes through the assembly point p for the kth evacuation, its value is 1, otherwise it is 0, represents that the (k - 1)th evacuation of the vehicle i in the garage y goes from the assembly point g to the resettlement point s g , and when the kth evacuation goes from the resettlement point s g to the assembly point p, its value is 1, otherwise it is 0. C(r y , e y , 2, xy , Δ) is the radiation exposure dose when vehicle i in garage y departs for the first evacuation from garage y, C(r p , e p , 2, x p , T y,p,i,n ) is the radiation exposure dose of vehicle i in garage y at assembly point p during the first evacuation, C(r s , e s , 2, x s , T y,i,j ) is the radiation exposure dose of vehicle i in garage y at resettlement point s during the first evacuation, is the radiation exposure dose of vehicle i in garage y at resettlement point s during the (j - 1)-th evacuation g of vehicle i in garage y, is the exposure dose of vehicle i in garage y at assembly point p during the (j - 1)-th evacuation, is the radiation exposure dose of vehicle i in garage y at resettlement point s during the j-th evacuation. C y,i,j is the radiation exposure dose of vehicle i in garage y during the j-th evacuation, T y,i is the total evacuation time of vehicle i in garage y.

[0209] The constraint conditions are the same as in Step 6.

[0210] Step 8. Solve for the optimal evacuation route:

[0211] Parameter setting

[0212] According to the characteristics of radionuclide leakage, the parameters of the Gaussian puff model are given as shown in Appendix 2, and the parameters of the off-site road network of the nuclear power plant are shown in Appendix 1.

[0213] Appendix 2 Dose field parameter information table:

[0214]

[0215]

[0216] NSGA-II two-objective optimization

[0217] Make a decision by combining the two objective functions of the total evacuation time and the radiation exposure dose of personnel. There are a total of 7 decision nodes for one evacuation in the road network, including 2 fixed decision points, representing the garage and vehicle number, and 5 random decision points. Each random node has 3, 5, 7, 5, and 3 decision opportunities respectively. When using binary coding, all path information needs to be included. Therefore, the total coding length is 108, and the total number of decision libraries is 2 108The non-dominated sorting genetic algorithm with elitist retention is adopted. The initial population size is set to 100, and the initialization method is to randomly assign 0 or 1 to the binary code with a length of 108. At this time, each individual contains the path information of all solutions, and the basis for judging superiority and inferiority is the dominance relationship between the evacuation time and the radiation exposure dose on the projection plane. The changing trend of the Pareto optimal solution set during the genetic process is as shown in the appendix Figures 5(a) to 5(d) 。

[0218] Use the TOPSIS decision-making method to select the optimal solution on the Pareto front

[0219] Since the dimensions of the objective functions of the total evacuation time and the personnel radiation exposure dose are different, the Euclidean distance needs to be used to normalize their dimensions

[0220] Next, calculate the distances (d + ) from all solutions on the obtained Pareto front to the ideal point, and the distances (d - ) to the non-ideal point. Through their closeness [d - / (d - +d + )] criterion, obtain the solution with the maximum closeness, that is, the optimal solution considering the two optimization objectives of the total evacuation time and the personnel radiation exposure dose

[0221] The method is to overcome the safety and time problems of personnel evacuation under the conditions of dynamic changes in the nuclear radiation dose field and multi-batch evacuation requirements. The method includes: combining an improved Gaussian puff model to give a calculation method for the personnel radiation exposure dose that changes dynamically with the time window, which is more reliable than the path planning method in the static dose field; through phased optimization, aiming at the global route planning problem of nuclear emergency evacuation, optimizing the vehicle allocation plan model with the evacuation time as the objective function, and optimizing the vehicle path model with the evacuation time and radiation dose as the objective function, reducing the complexity of large-scale global path planning and reducing the number of solution traversals; outputting multiple evacuation routes through the genetic algorithm so that nuclear emergency decision-makers can make decisions according to the actual situation and improve the decision-making efficiency

[0222] Finally, it should be noted that: the described embodiments are only a part of the embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present application

[0223] Only some exemplary embodiments of the present invention have been described by way of illustration above. Undoubtedly, for those of ordinary skill in the art, the described embodiments can be modified in various different ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention

Claims

1. A method for planning the off-site emergency evacuation routes of a nuclear power plant, characterized in that, It includes the following steps: The first step is to collect the wind speed outside the nuclear power plant and the leakage point source intensity, and construct a radiation dose field diffusion model. ， Among them, represents the gas concentration at a certain point in time at the spatial point The gas concentration at the point is the leakage source strength is the wind speed are the diffusion parameters in the downwind, crosswind, and vertical wind directions respectively; In the second step, collect the road condition information of N sections outside the nuclear power plant and construct a road impedance function model for real-time traffic, , where represents the driving time of the vehicle on the feasible path under real conditions, represents the driving time of the vehicle on the feasible path under ideal conditions, represents the number of vehicles selecting section per unit time, represents the maximum number of vehicles passing through section per unit time, and are blocking coefficients, are respectively the introduced road vehicle congestion weight parameter and road passability weight parameter, is the scheme margin parameter; In the third step, a path network is established based on nuclear power plants, garages, assembly points, and resettlement points, and a vehicle allocation plan is formulated with the evacuation time as the optimization objective to establish a vehicle allocation plan model. Among them, the vehicles in the garage The time required for the nth evacuation is expressed as: ， Among them, represents the vehicle number, represents the th evacuation, represents the garage number, 、 represents the number of the assembly point, represents the assembly of the settlement points, 、 represents the assembly of the settlement points in the settlement point number, represents the average driving time of the vehicle between the garage and the assembly point in the ideal state, represents the average driving time of the vehicle between the assembly point and the settlement point in the ideal state, represents the driving time of the vehicle from the settlement point to the assembly point in the ideal state, represents the waiting time for each evacuation, represents that when the vehicle in the garage passes through the assembly point for the th evacuation, its value is 1, otherwise it is 0, represents that the vehicle in the garage for the th evacuation goes from the assembly point to the settlement point , and when the th evacuation goes from the settlement point to the assembly point and the th evacuation goes from the settlement point to the assembly point its value is 1, otherwise it is 0, represents the maximum number of evacuations of the garage for the vehicle in the garage the total evacuation time of the expression formula: , where represents the vehicle number, represents the evacuation times, represents the garage number, represents the th evacuation, and sums the times of the th evacuation, represents the vehicle in the garage the th evacuation time required, represents the maximum evacuation times of the garage ​ For the path planning problem with known starting and ending points, taking the evacuation time and the radiation exposure dose of personnel as the optimization objectives, solving the optimal vehicle evacuation path, establishing a path optimization model, the vehicles in the garage The expression of the evacuation time for the th evacuation: In the formula, represents the vehicle number, represents the th evacuation, represents the garage number, 、 represent the number of the assembly point, represents the set of feasible paths, 、 、 represent the path number in the feasible path The path number in the feasible path represents the set of resettlement points, 、 represent the resettlement point number in the set of resettlement points The resettlement point number in the set of resettlement points represents the vehicle of the garage in the real situation from the garage to the assembly point The feasible path The travel time of the vehicle, represents the vehicle of the garage in the real situation from the assembly point to the resettlement point The feasible path The travel time of the vehicle, represents the waiting time for each evacuation, represents when the vehicle of the garage in the real situation the th evacuation passes through the assembly point its value is 1, otherwise it is 0, represents the vehicle of the garage in the real situation the th evacuation from the assembly point to the resettlement point and the th evacuation from the resettlement point to the assembly point its value is 1, otherwise it is 0, represents the vehicle of the garage in the real situation from the resettlement point to the assembly point The feasible path The travel time of the vehicle, represents the vehicle of the garage in the real situation the th evacuation travel time, represents the garage The maximum number of evacuations, For the driving times of the subsequent evacuations are summed to obtain the total evacuation time of the vehicle, with the expression: , where represents the vehicle number, represents the number of evacuations, represents the garage number, represents the th evacuation, represents the garage in the vehicle the th evacuation time required, represents the garage maximum number of evacuations, Garage Vehicles in The radiation exposure dose for the th evacuation is expressed as: ， Among them, represents the vehicle number, represents the number of evacuations, represents the garage number, 、 represents the number of the assembly point, 、 represents the number of the resettlement point, is the vehicle in the garage The th radiation exposure dose during the th evacuation. Each evacuation represents the successful evacuation of a batch of people to be evacuated, and the radiation exposure doses of this batch of evacuated people are the same, which is , is the radiation exposure dose of the people at the garage , is the radiation exposure dose of the people at the assembly point , is the radiation exposure dose of the people at the resettlement point , is the radiation exposure dose of the people at the resettlement point , represents the driving time of the vehicle in the garage during the th evacuation in the real situation, represents that when the vehicle in the garage passes through the assembly point during the th evacuation, its value is 1, otherwise it is 0, represents that when the vehicle in the garage goes from the assembly point to the resettlement point and from the resettlement point to the assembly point during the th evacuation, and its value is 1 when it goes from the resettlement point to the assembly point during the th evacuation, otherwise it is 0, represents the maximum number of evacuations when the garage ; In the fourth step, the vehicle deployment plan model restricts variables including the number of vehicles and the maximum number of evacuation times to integers based on integer linear programming. By solving the vehicle deployment plan model through integer linear programming, multiple solution sets are obtained. The upper and lower limit thresholds of the total evacuation time are set to screen the diverse solution sets, and the optimal solution set is obtained to obtain the vehicle allocation plan for the corresponding relationship between the garage, the assembly point and the resettlement point In the fifth step, to solve the optimal evacuation route, the total vehicle evacuation time and the personnel radiation exposure dose are selected as the objective functions for path planning during the nuclear power plant emergency evacuation. The optimal time for each evacuation and the minimum personnel radiation exposure dose are solved. The total evacuation time is obtained by calculating the optimal times of multiple evacuations. Combining the two optimization objective functions of the total vehicle evacuation time and the personnel radiation exposure dose, based on the vehicle allocation plan, under the conditions of known garages and resettlement points, the evacuation itinerary of each vehicle is solved by the non-dominated fast genetic algorithm. The evacuation itinerary includes the garage, roads, assembly points, roads, and resettlement points, obtaining a diverse solution set on the Pareto front. And a threshold value for the upper limit of the personnel radiation exposure dose is set to screen the diverse solution set. The TOPSIS decision-making method is used to evaluate the optimal solution set on the Pareto front selected, obtaining the optimal evacuation route. The path planning problem of multiple round trips is decomposed into two stages: First, with the evacuation time as the optimization objective, calculate the vehicle yards, assembly points, and resettlement points for multiple round trips of the vehicle to determine the vehicle deployment plan; Finally, through the non-dominated fast genetic algorithm, solve the Pareto solution set based on the known nodes, and then calculate the distances from all solutions on the Pareto front to the ideal point , and the distance to the non-ideal point . Through its proximity criterion, obtain the Pareto front optimal solution with the maximum proximity Step 6. Real emergency evacuation road network model: Using the garage, assembly point, resettlement point, and road basic data as data sources, connect the nodes with line segments to establish a reference coordinate system of the road network therein.

2. The method for planning an off-site emergency evacuation route of a nuclear power plant according to claim 1, wherein Scheme margin parameter is , where is a possibility matrix of size 1×5, representing the passability of alternative paths is an identity matrix of size 5×1

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