CN104156525B - A kind of method for improving storm surge disaster risk profile precision - Google Patents
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Abstract
The invention discloses a kind of method for improving storm surge disaster risk profile precision, the described method comprises the following steps：Storm surge disaster scene is built based on condition analysis method；Propose storm surge disaster Three-dimensional Numerical Simulation Method；The big flood for building multi-mode multiple target is taken refuge optimal route selection model；Wherein, the proposition storm surge disaster Three-dimensional Numerical Simulation Method is specially：1) three-dimensional grid model of region landform is set up；2) the SST k ω advance of freshet Three-dimensional Turbulent Flow models of coupling VOF methods are set up；3) based on Three-dimensional simulation result drawing three-dimensional risk map.Invention increases the flowing of flood dynamic realtime and the authenticity and effect of visualization of disaster Annual distribution；The integrity and reasonability of emergency-sheltering system are further improved with the emergency route evacuation model of multi-mode multiple target, calamity emergency prediction scheme is effectively formulated, multiple modules coupling, the storm surge disaster risk analysis system that integrity degree is high, exploitativeness is strong is set up.
Description
Technical Field
The invention relates to the technical field of civil construction and water conservancy engineering, in particular to a method for improving the risk prediction precision of storm surge disasters.
Background
Storm surge disasters, the first of which is ocean disasters, have received high attention from the nation and government, and the research on disasters naturally becomes important. At present, the main means for researching storm surge disasters is numerical simulation, and the storm surge numerical simulation comprises numerical simulation of disaster forecast and numerical simulation of disaster flood submergence. The invention aims to solve the problems of real-time dynamic simulation of flood after storm surge disaster, disaster space-time distribution rule and emergency plan making, and provides powerful technical support for the disaster prevention and reduction project of storm surge.
Granger in foreign storm surge disaster research[1]The method carries out quantitative research on storm surge disaster risks in Cairns city of Australia, designs different storm surge exposure scenes according to different storm surge tide heights, Digital Elevation (DEM) models and flood submerging depths, and designs storm surge exposure scenes of buildings and urban infrastructureThe exposure is evaluated, and an urban community vulnerability evaluation index system and a comprehensive evaluation index are established; benavente j[2]Researching the storm surge and flood risks in coastal areas of the spanish plus the Bay, calculating the storm surge and the tidal height, establishing a DEM (dynamic effect model) model and a two-dimensional storm surge and flood evolution model, and drawing a storm surge and flood risk map; rafaelThe method comprises the following steps of (1) researching the flood submerging situation of an obstacle area along the coast of the long island in New York, USA under the storm surge disaster by adopting Delft3D-Flow software and applying a two-dimensional hydrodynamic model; RosemaryA.E.Smith [4]Simulating the influence of flood inundation of typhoon storm surge along the coast in the southwest region of England based on a two-dimensional hydraulic model and by combining radar data, calculating the flood inundation area, and analyzing disaster situations; andre' b[5]Establishing a storm surge disaster flood submerging model based on a two-dimensional shallow water model, calculating hydraulic parameters such as storm surge flood submerging depth, area and the like of a certain area of the grapefruits in different reappearance periods, and further drawing a flood submerging risk graph;
in the research of storm surge disasters in China, Zhang Weng Ting and the like[6]Based on the GIS technology, a two-dimensional flood submerging evolution model is established by adopting a seed spreading method, and two-dimensional storm surge flood embankment submerging parameters are obtained, so that the flood risk level is further calculated, and a flood risk graph is drawn; zhu military administration and the like[7]By establishing a two-dimensional hydrodynamic model, the flooding condition of storm surge when tidal water overflows is realized under the condition that a seawall exists; all-grass of Yemingwu[8]Starting from a typhoon storm surge disaster risk system, performing numerical simulation on the breakwater situation of the storm surge disaster by adopting a two-dimensional hydrodynamic model, and establishing a personnel evacuation emergency evacuation system by taking the shortest evacuation time as a target; all-grass of Ardisia[9]On the basis of typhoon storm surge risk level zoning, calculating the storm surge flood submerging range and water depth by using an ADCirc mode, and calculating the optimal vehicle evacuation path through a cellular transmission model; fu xi Fu[10]Aiming at the storm surge in the coastal new area, 4 strong weather systems are selected, a two-dimensional storm surge flood model is established in an ADCirc mode, and a storm surge model is combinedDrawing a disaster risk graph according to the storm flood risk and the vulnerability of the disaster-bearing body.
From a series of researches and applications developed at home and abroad, the researches on storm surge disasters are mainly single-aspect and single-scenario researches on overflow, flood or levee breaking and the like based on simple assumptions, a storm surge disaster composite scenario analysis system with a certain logic analysis and various phenomena such as flood, overflow, levee breaking, wave crossing and the like is not formed, the researches on the disaster scenarios are incomplete, and the comprehensive reflection capability is poor; the numerical simulation of a single scene is only limited to a two-dimensional or even one-dimensional hydrodynamic model, and has a certain difference with the three-dimensional flow of the actual storm surge and flood; the emergency refuge research on storm surge flood is usually the solving calculation of a single optimization target in a single evacuation mode of personnel evacuation or vehicle evacuation, and the effectiveness and the applicability of an emergency scheme need to be improved.
Disclosure of Invention
The invention provides a method for improving the storm surge disaster risk prediction precision, which adopts the technology of coupling scene analysis, flood three-dimensional evolution and emergency refuge model to establish a multi-module coupled high-integrity strong-implementability storm surge disaster risk analysis system, and the following description refers to:
a method of improving storm surge disaster risk prediction accuracy, the method comprising the steps of:
constructing storm surge disaster scenes based on a scene analysis method; providing a storm surge disaster three-dimensional numerical simulation method;
constructing a multi-mode multi-target flood refuge optimal path selection model; wherein,
the proposed storm surge disaster three-dimensional numerical simulation method specifically comprises the following steps:
1) establishing a three-dimensional grid model of regional terrain;
2) establishing an SST k-omega flood evolution three-dimensional turbulence model of a coupling VOF method;
3) and drawing a three-dimensional risk graph based on the three-dimensional numerical simulation result.
The three-dimensional SST k-omega turbulence closed mathematical model specifically comprises the following steps:
the continuous equation:
the momentum equation:
SST k- ω turbulence equation:
Φ3＝F1Φ1+(1-F1)Φ2
wherein rho is density; t is time; x is the number ofi、xjIs a coordinate component; u. ofi、ujIs xi、xjA velocity component in the direction; p is pressure; mu is the molecular dynamic viscosity coefficient; mu.stIs the turbulent flow viscosity coefficient; phi1、Φ2、Φ3Respectively representing the k-omega, k-and SST models, F1Is a mixing function; v istIs the vortex-viscosity coefficient, omega is the vorticity, F2Is a mixing function, k is the turbulence energy, ω is the specific dissipation ratio; ν is kinematic viscosity; CD (compact disc)kωA positive term that is a cross-diffusion term; sigmaω2、α1Is the turbulence model constant and y is the distance from the wall.
The boundary conditions of the three-dimensional turbulence model are as follows:
1) inlet boundary conditions: the relative atmospheric pressure at the inlet is 0;
2) exit boundary conditions: the velocity components and k and ω are taken as boundary conditions of the second type, i.e.Phi is taken as a constant pressure boundary of which the velocity component outlets in the x direction, the y direction and the z direction are zero relative to the atmospheric pressure;
3) the wall-fixing boundary condition is that the wall surface adopts the conditions of no sliding, isothermal wall and zero normal pressure, the wall surface boundary condition of the turbulent kinetic energy k equation in the calculation condition of the turbulence model near the wall surface is zero, and the wall surface boundary condition of the omega equation is omega-60 v/[ β ]1(Δy1)2]Wherein v is kinematic viscosity, β1As coefficient of turbulence, Δ y1The distance from the first layer of grid points on the wall surface to the wall surface.
4) The boundary of the underlying surface: the boundary of the underlying surface is processed by an equivalent roughness method, and the roughness is a comprehensive coefficient representing various factors of the boundary surface influencing the water flow resistance.
The technical scheme provided by the invention has the beneficial effects that:
1. the scene of the storm surge disaster is researched and determined by adopting a scene analysis method, so that the disaster scene with certain strict logic analysis is formed, the direction of numerical simulation of storm surge and flood is determined, and the blindness of numerical simulation research is reduced.
2. The SSTk-omega equation combines the advantages of a k-omega model and a k-omega model, so that the simulation fineness of a turbulent boundary layer is improved, the real-time dynamic simulation of the storm surge flood three-dimensional turbulence is more in line with the actual situation, and the applicability is stronger.
3. The three-dimensional terrain risk and storm surge flood disaster are combined, the comprehensive risks of the three-dimensional terrain risk and the storm surge flood disaster are diffused through the data field model, the expression of the three-dimensional risks of the storm surge disaster is realized on the basis of the regional three-dimensional terrain, the reliability of the spatial and temporal distribution of the storm surge disaster risks is improved, and the flexibility and the visualization effect of the risk map are enhanced.
4. By using the method of combining human-vehicle mixed evacuation and double-layer optimization targets and calculating the optimal path through the ant colony algorithm improved by the potential field method, the construction of the multi-mode and multi-target emergency evacuation system is realized, the emergency system is more complete, and the emergency scheme has stronger practicability and applicability.
Drawings
FIG. 1 is a flow chart of a method of improving storm surge disaster risk prediction accuracy;
FIG. 2 is a flow chart of a storm surge disaster scenario determination technique based on scenario analysis;
FIG. 3 is a three-dimensional numerical simulation and risk map study framework for storm surge and flood;
FIG. 4 is a schematic view of a storm surge disaster emergency refuge system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention are described in further detail below.
The method mainly comprises three parts: determining the possible scene of the storm surge disaster by combining the scene analysis model, and determining the disaster analysis direction; based on a water-gas two-phase flow three-dimensional turbulence model, a storm surge flood submerging real-time dynamic, real and reliable simulation method mainly aiming at the flood three-dimensional flow of a complex coastal region is realized, and a disaster risk three-dimensional distribution rule analysis mode is established by combining a data field model; on the basis of disaster risk analysis, a multi-mode multi-target flood refuge optimal path selection model is constructed, the construction of a disaster risk system is completed, and the overall research framework is shown in fig. 1.
101: constructing storm surge disaster scenes based on a scene analysis method;
the storm surge disaster is a sudden natural disaster consisting of a storm surge natural ecosystem and a human social economic system, the disaster scene is the occurrence of the disaster process and the consequence of the storm surge, and the determination is the premise of further analysis of the disaster. The scene analysis method is a method for analyzing and predicting future uncertain events by continuously enriching scene arrangement in a logic-conforming manner with definite hypothesis as background and finally obtaining corresponding conclusions, and is mainly applied to the fields of traffic, agricultural development, environment or climate change and the like[11]The method is rarely applied to storm surge disaster analysis. Due to the fact that a large amount of uncertainty exists in the forming, developing and evolving processes of storm surge disasters, the applicability of the scene analysis method to the determination of the scenes of the storm surge disasters is high. The diversified scene of storm surge disaster is formed by continuously evolving various key influence factors to different directions, so the recognition of the storm surge disaster influence factors, the determination of the key influence factors and the basic sceneThe construction of the method (the main process of the scene analysis method) becomes the key for determining the scene of the storm surge disaster, and the technical route is shown in fig. 2.
(1) The identification of the factors influencing the storm surge disasters, namely the storm surge disasters, relates to a plurality of uncertain factors including natural, social, microscopic, macroscopic and the like, and is combined with the storm surge disaster risk law to identify disaster causing factors, pregnancy factors, disaster bearing factors and disaster prevention and reduction factors of disasters from the forming process of the storm surge disasters so as to screen out the factors influencing the storm surge disasters. On the basis of the influence factors of storm surge disasters, the factors with overlapping and internal connection are combined into one factor to be classified and integrated.
(2) Determining key influence factors, namely, the key influence factors of the storm surge disaster are fuzzy, and fuzzy comprehensive evaluation is to quantitatively research the fuzzy concept, so that the key influence factors of the storm surge disaster are determined by adopting a fuzzy comprehensive evaluation method. The classified and integrated storm surge disaster influence factors are subjected to 'setting a comment set', determining the weight of an index (influence factor) 'establishing an evaluation matrix-comprehensive evaluation' (fuzzy comprehensive evaluation method)[12]And determining a plurality of factors with higher influence degree on the disaster, and taking the factors as key influence factors of the storm surge disaster.
(3) Basic scene determination-when there are two or three key uncertain factors, the common scene matrix constructs scenes, and there are two completely opposite development trends in each scene dimension[13](as shown in the scene matrix in fig. 2). And taking the key influence factors determined through comprehensive evaluation as basic dimensionalities of the disaster scene, and carrying out scene combination on the storm surge disaster through the scene matrix to construct the basic scene of the disaster.
(4) The scene evolution-PSR model is a model which is proposed by Anthony-Friend in 1979 and used for describing phenomena occurring in a complex system, has a very clear causal relationship, and is suitable for analyzing and evaluating a certain dynamic and changing attribute of the complex system. Thus, the method pairConstructed basic scenario passes through PSR model[14]Further (as shown in the scene evolution in fig. 2) the market scenario deduction, wherein "pressure", "status" and "response" are respectively represented by P, S, R, and the scene development direction is represented by horizontal and vertical arrows. The horizontal arrow indicates that the 'state S' is in the 'pressure P', the 'response R' is effective, the event develops towards the best direction, the vertical arrow indicates that the 'response R' is ineffective, and the event develops towards the worst direction, so that the evolution process of the storm surge disaster is analyzed, and the disaster development path and the disaster situation are determined.
102: provides a three-dimensional numerical simulation method for storm surge disasters
And solving and calculating the storm surge flood under certain grid models, mathematical models and boundary conditions to obtain real-time dynamic three-dimensional numerical simulation of flood evolution. The method comprises the steps of acquiring storm surge flood flooding situation information based on numerical simulation, adding terrain risk factors, and drawing a disaster three-dimensional risk map by using a data field model, wherein the disaster three-dimensional risk map is specifically shown in fig. 3.
(1) Establishing three-dimensional grid model of regional terrain
The three-dimensional model containing the terrain information of the complex area is converted into stl data format, the stl data format is introduced into Computational Fluid Dynamics (CFD) software through a data interface of the CFD software, and a Computational grid model is established by adopting a body-attached grid and local encryption grid division technology, so that the accurate expression of the complex terrain of the area in the Computational Fluid software Computational model is realized.
(2) Closed mathematical model adopting three-dimensional SST k-omega turbulence
Aiming at the turbulent flow problem of storm surge flood, one-dimensional and two-dimensional models are mostly adopted for numerical simulation, and a few three-dimensional water flow simulations are mostly based on a k-turbulent flow model[15]The model has good effect in the simulation of water flow far away from the wall surface, but has poor effect in the simulation of turbulent fluctuation of water flow near the wall surface, so that the invention establishes the water-gas two-phase flow SST (Shear-Stress Tra) coupled with the VOF (volume of flow) methodTransport) k-omega three-dimensional flood routing model. VOF method[15]The effective method proposed by Hirt and Nichols for treating free surfaces captures the moving free water surface by solving the convective transport equation of a fluid volume function, which can describe the surface variations of storm surge floods more finely. The SST (Shear-Stress Transport) k-omega turbulence model is the Menter[16]The model for simulating the water flow turbulence phenomenon based on the k-omega and k-turbulence models integrates the advantages of the two models, retains the original k-omega model on the near wall surface, increases the cross diffusion term, considers the conveying process of the shear stress in the definition of the turbulence viscosity coefficient, enables the model to be better suitable for various physical phenomena of pressure gradient change and the simulation of a viscous inner layer, and has more precise simulation effect.
The fundamental equation of the VOF method coupled SST turbulence model mainly comprises the following steps: continuity equation, momentum equation, SST k-omega turbulence closed equation. The continuity equation and the momentum equation are control equations of main fluid flow, the SST k-omega turbulence equation is a selected turbulence closed equation, and the specific equation of the model is as follows:
the continuous equation:
the momentum equation:
SST k- ω turbulence equation:
Φ3＝F1Φ1+(1-F1)Φ2
where ρ is density, kg/m3(ii) a t is time, s; x is the number ofi、xjIs the coordinate component, m; u. ofi、ujIs xi、xjThe velocity component in the direction, m/s; p is pressure, Pa; mu is a molecular dynamic viscosity coefficient, N.m/s; mu.stIs the turbulent flow viscosity coefficient; phi1、Φ2、Φ3Respectively representing the k-omega, k-and SST models, F1Is a mixing function. V istIs the vortex viscosity coefficient, m/s2Omega is vorticity, 1/s, F2For the mixing function, k is the kinetic energy of turbulence, m2/s2Omega is specific dissipation rate, 1/s; v is kinematic viscosity, m2/s；CDkωA positive term that is a cross-diffusion term; sigmaω2、α1Is the turbulence model constant, dimensionless, y is the distance from the wall, m.
(3) Three-dimensional turbulence model boundary conditions
1) Inlet boundary conditions: and determining the size of the disaster inflow according to the actual conditions of different storm surge disaster scenes, and further analyzing and calculating the inlet flow velocity distribution of storm surge flood. Since the inlet is directly connected to the atmosphere, it is set as a constant pressure boundary, 0 relative to atmospheric pressure.
2) Exit boundary conditions: the velocity components and k and ω are taken as boundary conditions of the second type, i.e.Phi is taken as u, v, w, k, omega (u, v, w are velocity components in x, y, z directions, respectively). The outlet is directly connected to the atmosphere and is set as a constant pressure boundary with zero relative atmospheric pressure.
3) And (3) wall fixing boundary conditions: the wall surface adopts the conditions of no sliding, isothermal wall and zero normal pressure, the wall surface boundary condition of the turbulent kinetic energy k equation in the turbulence model near-wall surface calculation condition is zero, and the wall surface boundary condition of the omega equation[2]Is omega 60v/[ β1(Δy1)2]Wherein v is kinematic viscosity, β1As coefficient of turbulence, Δ y1The distance from the first layer of grid points on the wall surface to the wall surface.
4) The boundary of the underlying surface: the friction effect of the lower cushion surface boundary on water flow is considered, and an equivalent roughness method is adopted for processing. The roughness is a comprehensive coefficient of various factors for representing the influence of the boundary surface on the water flow resistance, and is also a characteristic quantity for measuring the energy loss of the water flow. The roughness values are different because different boundary surfaces have different effects on the water flow movement.
(4) Three-dimensional risk mapping
The risk graph is intuitive embodiment of disaster distribution, most of the existing risk graphs are intuitive expression of disaster two-dimensional distribution, drawing of the three-dimensional risk graph gradually becomes mainstream of research, but the drawing technology is not mature. Aiming at drawing a storm surge flood inundation three-dimensional risk graph, a data field model is introduced on the basis of a three-dimensional terrain[17]And (3) carrying out three-dimensional information diffusion and clustering on the comprehensive risk of the disaster situations, analyzing the three-dimensional distribution rule of the storm surge and flood disaster situations, drawing a three-dimensional risk map of the storm surge and flood disaster, and realizing the visual display of the disaster risk.
1) Three-dimensional terrain building
Generating a regional three-dimensional terrain surface by using a NURBS method. Firstly, performing interpolation calculation based on extracted topographic data information, and establishing a control point data set of a curved surface; secondly, the topographic profile characteristics of the whole research area are realized through NURBS calculation and Boolean operation.
2) Integrated risk calculation
The calculation of the comprehensive risk comprises the following four steps: (1) acquiring disaster information of each area, such as the submerged depth, the flow velocity, the flood arrival time and the like of the area through storm surge and flood three-dimensional numerical simulation; (2) the acquired disaster situation data is arranged into a data structure with a grid as a basic research unit; (3) calculating the weight coefficients of the terrain risk factors and the disaster factors by adopting an analytic hierarchy process; (4) and (4) carrying out weighted calculation on the terrain risk factors and disaster data to obtain a comprehensive risk value.
3) Application of data field model
The data field regards a group of data objects as a whole, and the data space can be mapped to the data field space through an influence function between data, often expressed by equipotential lines (surfaces). Therefore, the calculated comprehensive risk value of the storm surge flood disaster is mapped to a data space by adopting a data field model, is analyzed and diffused to form a disaster risk three-dimensional equipotential surface, and is superposed with the regional three-dimensional terrain, so that a three-dimensional flood risk map is drawn.
103: and constructing a multi-mode multi-target flood refuge optimal path selection model.
The emergency refuge scheme is formulated mainly by determining a refuge mode, evacuation points and refuge places, an optimization target and a solving algorithm, and the specific process is shown in fig. 4.
(1) Determination of refuge mode
The emergency refuge system for storm surge disasters adopts a point-line-surface combined mode, based on storm surge flood three-dimensional numerical calculation, a damaged area is divided into a plurality of units and abstracted into evacuation points, meanwhile, road networks in a research area are abstracted into lines, refuge service ranges are abstracted into surfaces, and the three parts jointly form a point-line-surface flood control refuge network. In the aspect of personnel evacuation, in order to fully utilize the regional road network and improve evacuation efficiency, a mode of combining personnel pedestrian evacuation and vehicle evacuation is adopted for emergency evacuation.
(2) Determination of evacuation points
According to the analysis[18]When the depth of the submerged water exceeds 0.5m and the flow velocity reaches a certain degree, people can hardly live in the submerged water. Therefore, an area with the storm surge flood submerging depth larger than 0.5m is selected as an evacuation area, the evacuation area is further abstracted into evacuation points, and the evacuation sequence of the evacuation points is determined according to the flood submerging degree.
(3) Determination of refuge
1) The initial selection of the refuge place, namely the refuge place, is generally selected to be far away from a submerged area according to the safety, accessibility and effectiveness of the place, has relatively high topography and strong flood resistance of the place, is guaranteed not to be attacked by flood, is close to a traffic trunk and has certain space capacity and a place with basic living facilities. Accordingly, parks, schools, large sports venues, and the like are selected as refuge places for storm surge and flood disasters.
2) Optimized selection of refuge places-in the preliminarily selected refuge places, not all refuge places can be used for people to refuge, and due to the influence of traffic, the capacity of the refuge places and the like, the refuge places are often required to be further optimized and selected so as to enable the refuge system to reach the optimal service state. In the optimal choice of refuge, distance from the point of evacuation, safety, distance from the medical facility are the most important concerns. Accordingly, an optimal mathematical model for optimal selection of the multi-target refuge place closest to the evacuation point, the highest safety and the closest to the medical institution is established, and multiple targets are converted into single targets by using weight coefficients as follows:
min f＝ω1f1+ω2f2+ω3f3
in the formula, ω1+ω2+ω31, the weight coefficients of the three objective functions are respectively set;is the nearest objective function from the evacuation point;the target function with the highest safety is obtained;is the nearest objective function to the medical institution; n is the number of refuge places; i represents an evacuation place number; x is the number ofi1 or 0, respectively indicating that the ith refuge place is selected or not selected as an emergency refuge area; li、si、diRespectively shows the distance from the ith evacuation site to the evacuation point, the safety degree, and the distance from the medical institution.
(4) Optimization model of refuge path
The refuge path is optimized from the perspective of decision makers and evacuees. For the decision maker, the main evacuation goals are: the total evacuation time is shortest, the utilization rate of the evacuation grid is maximum, and the time-space conflict of the evacuation grid is minimum; for evacuating individuals, the main evacuation goals are: the evacuation time is shortest, the evacuation path is shortest, the route risk degree is lowest, the moving speed is fastest, the space-time crowding degree of the route is lowest, and the comfort level and the acceptance degree are highest. Therefore, based on the above objectives, a double-layer planning model is constructed by fully considering decision maker and evacuee systems formed by evacuation time, network mixing utilization rate, space-time conflict and path distance.
From the perspective of decision makers and evacuees, a double-layer optimization model is established by taking the shortest evacuation time, the maximum network utilization rate, the minimum time-space conflict and the shortest distance as targets. The decision maker angle optimization model (upper layer optimization model) takes the shortest evacuation time, the maximum network utilization rate and the minimum space-time conflict as objective functions, and the evacuator angle optimization model (lower layer optimization model) takes the shortest evacuation time and the shortest distance as objective functions. The two-layer optimization model is as follows:
decision maker angle optimization model (upper optimization model):
min Z1＝λ1z1+λ2z2+λ3z3
decision-maker angle optimization model (lower layer optimization model):
in the formula, λ1+λ2+λ3＝1，Is a weight coefficient, z1、z2、z3、z4Respectively representing the shortest evacuation time, the maximum network utilization (minimum network air limit), the minimum time-space conflict and the shortest distance objective function.
(5) Optimization calculation for improving ant colony algorithm by potential field method
The potential field method can enhance the searching capability of the algorithm by improving the heuristic information of the ant colony algorithm, so the ant colony algorithm improved by the artificial potential field method is adopted to solve the emergency refuge mathematical model. Combined with artificial potential field method[19]The evacuation point is used as a repulsion point, the evacuation place is used as a attraction point, and the evacuation object is respectively acted by the repulsion and the attraction in a virtual artificial potential field formed by the evacuation point and the difficulty avoidance point, and the path is searched according to a certain rule under the common influence of the two acting forces.
The improvement of the ant colony algorithm by the potential field method is mainly embodied in the heuristic information, the original single heuristic information is improved into the composite heuristic information, and the composite heuristic information comprises two parts: one part is combined with the idea of a potential field method, ants are subjected to potential field resultant force in the environment (resultant force formed by the repulsive force of an evacuation point on an evacuation object and the attractive force of an evacuation object from an evacuation place), and heuristic information enabling the ants to tend to walk along the direction of the resultant force is formed; the other part is provided by the distance (or the right of way) of the ants from the target position, so the construction heuristic information is as follows:
η＝η1·η2
η2＝1/d2
wherein η is a modified heuristic, η1For heuristic information under the action of the resultant force of the potential field, η2Heuristic information provided for the right of way to the target location, FtThe angle between the selected path direction and the resultant force is theta, and d is the distance (or the road weight) between the object and the target position.
And adding the improved heuristic information into the ant colony algorithm, and searching and calculating the optimal solution through a state transition probability formula and an pheromone updating formula. The ant colony algorithm adopts a distributed parallel computing mechanism, so that the ant colony algorithm has stronger robustness, and the improvement of the heuristic function by the potential field method enhances the searching performance of the algorithm, is not easy to fall into the local optimal solution, ensures that the searching result is more credible, and realizes the improvement and the perfection of the intelligent algorithm for solving the optimal path. Reference documents:
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Those skilled in the art will appreciate that the drawings are only schematic illustrations of preferred embodiments, and the above-described embodiments of the present invention are merely provided for description and do not represent the merits of the embodiments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (2)
1. A method for improving the prediction accuracy of storm surge disaster risks is characterized by comprising the following steps:
constructing storm surge disaster scenes based on a scene analysis method; providing a storm surge disaster three-dimensional numerical simulation method;
constructing a multi-mode multi-target flood refuge optimal path selection model; wherein,
the proposed storm surge disaster three-dimensional numerical simulation method specifically comprises the following steps:
1) establishing a three-dimensional grid model of regional terrain;
2) establishing an SST k-omega flood evolution three-dimensional turbulence model of a coupling VOF method;
3) drawing a three-dimensional risk graph based on a three-dimensional numerical simulation result;
the boundary conditions of the three-dimensional turbulence model are specifically as follows:
1) inlet boundary conditions: the relative atmospheric pressure at the inlet is 0;
2) exit boundary conditions: the velocity components and k and ω are taken as boundary conditions of the second type, i.e.Phi is taken as a constant pressure boundary of which the velocity component outlets in the x direction, the y direction and the z direction are zero relative to the atmospheric pressure; k is the turbulent kinetic energy and ω is the specific dissipation ratio;
3) the wall-fixing boundary condition is that the wall surface adopts the conditions of no slip, isothermal wall and zero normal pressure, the wall surface boundary condition of the turbulent kinetic energy k equation in the calculation condition of the turbulence model near the wall surface is zero, and the wall surface boundary condition of the omega equation is omega-60 v/[ β ]1(Δy1)2]Wherein v is kinematic viscosity, β1As coefficient of turbulence, Δ y1The distance from the first layer of grid points on the wall surface to the wall surface;
4) the boundary of the underlying surface: the boundary of the underlying surface is processed by an equivalent roughness method, and the roughness is a comprehensive coefficient representing various factors of the boundary surface influencing the water flow resistance.
2. The method of claim 1, wherein the flood routing three-dimensional turbulence model is specifically:
the continuous equation:
the momentum equation:
SST k- ω turbulence equation:
Φ3＝F1Φ1+(1-F1)Φ2
wherein rho is density; t is time; x is the number ofi、xjIs a coordinate component; u. ofi、ujIs xi、xjA velocity component in the direction; p is pressure; mu is the molecular dynamic viscosity coefficient; mu.stIs the turbulent flow viscosity coefficient; phi1、Φ2、Φ3Respectively representing the k-omega, k-and SST models, F1Is a mixing function; v. oftIs the vortex-viscosity coefficient, omega is the vorticity, F2Is a mixing function, k is the turbulence energy, ω is the specific dissipation ratio; v is kinematic viscosity; CD (compact disc)kωA positive term that is a cross-diffusion term; sigmaω2、α1Is the turbulence model constant and y is the distance from the wall.
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