CN114611780A - Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning - Google Patents
Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning Download PDFInfo
- Publication number
- CN114611780A CN114611780A CN202210211265.0A CN202210211265A CN114611780A CN 114611780 A CN114611780 A CN 114611780A CN 202210211265 A CN202210211265 A CN 202210211265A CN 114611780 A CN114611780 A CN 114611780A
- Authority
- CN
- China
- Prior art keywords
- road
- path
- flood
- time
- calculating
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000011156 evaluation Methods 0.000 claims abstract description 27
- 238000011160 research Methods 0.000 claims abstract description 24
- 238000004088 simulation Methods 0.000 claims abstract description 16
- 238000012546 transfer Methods 0.000 claims abstract description 15
- 238000005457 optimization Methods 0.000 claims abstract description 11
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 230000008569 process Effects 0.000 claims abstract description 10
- 230000010354 integration Effects 0.000 claims abstract description 8
- 230000006870 function Effects 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 16
- 238000004422 calculation algorithm Methods 0.000 claims description 13
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 10
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000010276 construction Methods 0.000 claims description 6
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 6
- 239000012530 fluid Substances 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 230000003068 static effect Effects 0.000 claims description 4
- 230000003930 cognitive ability Effects 0.000 claims description 3
- 239000007789 gas Substances 0.000 claims description 3
- 230000001788 irregular Effects 0.000 claims description 3
- 239000003345 natural gas Substances 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000012800 visualization Methods 0.000 claims description 3
- 230000009172 bursting Effects 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 4
- 230000002708 enhancing effect Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 4
- 238000005452 bending Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 239000002537 cosmetic Substances 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
- 230000007704 transition Effects 0.000 description 2
- 241001391944 Commicarpus scandens Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000002787 reinforcement Effects 0.000 description 1
- 238000010187 selection method Methods 0.000 description 1
- 238000010937 topological data analysis Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
- G06Q50/265—Personal security, identity or safety
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- General Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Computer Hardware Design (AREA)
- Geometry (AREA)
- Evolutionary Computation (AREA)
- Development Economics (AREA)
- Databases & Information Systems (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Remote Sensing (AREA)
- General Health & Medical Sciences (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Data Mining & Analysis (AREA)
- Computer Security & Cryptography (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Quality & Reliability (AREA)
- Primary Health Care (AREA)
- Algebra (AREA)
- Computing Systems (AREA)
- Fluid Mechanics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Mathematical Physics (AREA)
- Pure & Applied Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for calculating an optimal scheme for emergency refuge site selection and path planning for dam break, which solves the problems of refuge site selection optimization and path planning difficulty in the process of dam break flood emergency refuge transfer in the prior art. The invention comprises the following steps: 1. constructing a numerical simulation model of the dam break flood; 2. risk avoiding, transferring and evacuating units and people number analysis; 3. establishing an evaluation index selection principle and an index system; 4. the combination based on division integration method is weighted; 5. a comprehensive assigning model of refuge site selection based on TOPSIS; 6. and constructing a risk avoiding transfer path optimization model. The technology analyzes the dam-breaking flood evolution condition of the dike protection area while avoiding flood disasters through engineering measures, is dedicated to refuge site selection planning and path planning research after the dike breaks, and has important significance for improving emergency rescue efficiency, improving emergency flood control decision-making capability and level, enhancing flood control safety guarantee capability of the dike engineering and reducing potential dam-breaking loss.
Description
Technical Field
The invention relates to the technical field of water conservancy and hydropower, in particular to a method for calculating an optimized scheme for breaking dam emergency refuge site selection and path planning.
Background
The dike is used as an important component in river flood control and disaster reduction system engineering, and has outstanding achievement in the development process of Chinese water conservancy projects. However, many projects take earth nearby, the embankment foundation and filling quality is poor, the flood control standard is low, and the embankment is easy to break under the flood condition, so that great threat is caused to the life and property safety of people in the protection area. In recent years, with global climate change, extreme rainfall events frequently occur, which brings greater risks to the safety of river dikes, and breakwater events occur occasionally.
The current management measures for dealing with the flood bank breaking risk mainly comprise engineering measures and non-engineering measures. Engineering measures are taken to carry out danger-removing reinforcement on the dike engineering or improve flood control standards, but large-scale construction of high-standard dikes is difficult due to technical and economic reasons and the like. The non-engineering measures mainly comprise flood area management, flood forecast alarm, flood insurance, a flood risk map and the like, and the method can play a role of achieving double results with half the effort in the levee risk management and control. However, as one of the very important contents in non-engineering measures, the current research on emergency refuge transfer of the risk population under the condition of bank breaking is not mature enough: firstly, how to determine a risk area under the action of the dam break flood and determine a relatively accurate refuge risk population; secondly, how to establish a perfect index system and an evaluation method to construct a refuge capable of effectively accommodating the dam break risk population; and thirdly, how to plan a scientific risk avoidance transfer path to ensure the rapid transfer of risk population.
Therefore, as a low-probability high-loss accident, the evaluation and management of the risk of bank break should be paid more attention.
Disclosure of Invention
The invention improves the problems of refuge site selection optimization and path planning difficulty in the emergency refuge transfer process of the dam break flood in the prior art, and provides a calculated dam break emergency refuge site selection optimization scheme and a path planning method which have higher emergency rescue efficiency, emergency flood prevention decision-making capability and higher level.
The technical scheme of the invention is to provide a method for calculating the optimal solution of the break bank emergency shelter site selection and the path planning, which comprises the following steps: comprises the following steps:
step 2, risk avoiding, transferring and evacuating units and people number analysis;
step 3, establishing an evaluation index selection principle and an index system;
step 4, giving weights to the combination based on a division integration method;
step 5, a comprehensive assigning model of refuge site selection based on TOPSIS;
and 6, constructing a risk avoidance transfer path optimization model.
Preferably, said step 1 comprises the steps of,
step 1.1, selecting a dike protection area where dike breaking occurs for many times, and preprocessing DEM data of a research area by utilizing ArcMap, GlobalMapper and AutoCAD related software to obtain scattered point data (.xyz) required by MKIE 21;
step 1.2, performing numerical simulation by using an FM unstructured grid in an MIKE 21 model and a finite volume method of a unit center, using an irregular triangular grid as a calculation area, performing grid subdivision by using a Mesh Generator module in MIKE, and performing grid generation, adjustment and interpolation to obtain the terrain grid subdivision of the embankment protection area;
step 1.3, according to the roughness of the model in the levee and the utilization data of the land in the levee, performing interpolation processing by combining the Mesh Generator with the terrain grid manufactured in the step 1.2, and drawing a roughness cloud picture of a research area;
step 1.4, calibrating model parameters, wherein the model parameters comprise breach selection, simulation time, time step, boundary conditions and vortex viscosity coefficients;
and step 1.5, combining the operation results from the step 1.1 to the step 1.4, and utilizing fluid simulation software MIKE to carry out numerical simulation on the levee dam bursting flood to obtain basic water condition data of the protected area when the historical extra-large flood occurs, such as the flood submerging range, the arrival time and the maximum flow rate.
Preferably, in the step 2, the flooding situation data and the population density data are combined, and the embankment flood risk-avoiding transfer evacuation unit and the number of people are analyzed and processed by using a geospatial analysis tool ArcGIS.
Preferably, in the step 3, the evaluation indexes of the emergency refuge place are selected according to three index selection principles of safety, accessibility and effectiveness, and an evaluation index system of the levee protection area break flood refuge site selection is constructed, wherein the evaluation indexes of the system comprise the distance from a geological disaster point, the distance from a gas station, the distance from a natural gas service station, the gradient, the distance from medical treatment, fire protection, public security and water source, the road service level, the cognitive ability and the service population ability.
Preferably, said step 4 comprises the steps of,
step 4.1, obtaining subjective weight vector omega of evaluation index by using an analytic hierarchy process and an entropy weight method respectivelyAHPAnd objective weight ωEWM；
Step 4.2, carrying out optimization combination of subjective and objective weights according to a division integration method, wherein an objective function is as follows,
in the formula: omega is the combining weight, omegaAHPCalculating a weight, ω, for an analytic hierarchy processEWMWeights are calculated for the entropy weight method.
Preferably, the TOPSIS method in step 5 constructs a decision weighting matrix by matrix initialization and standardization, combining the combined weights, defines positive and negative ideal solutions, calculates the distance between each addressing scheme and the positive and negative ideal solutions and the relative pasting degree, sorts the addressing schemes according to the relative pasting degree, and finally selects the best scheme from the proposed addressing schemes.
Preferably, said step 6 comprises the steps of,
step 6.1, shortest distance path optimizing model based on Dijkstra algorithm
6.1.1, assuming the road network structure of the research area, recording the initial nodes C0The other nodes are CiThe shortest distance between each node is d (i-1, i); adding a set U and a set V, wherein the set U represents the nodes of the shortest path which is solved, the set U is an empty set initially, and the set V represents the nodes of the remaining shortest paths to be solved;
6.1.2, constructing an adjacent matrix C for storing the road network information in the step 6.1.1;
6.1.3, initial calculation, i.e. from C1Starting from C1Put into the set U, where U is { C }0}，V＝{C1,Ci-1,CiB, }; calculating all path distances of the set U → the set V and marking out the shortest path C0→C1Distance d of shortest pathmin；
6.1.4, selecting the nearest node C selected in step 6.1.31Put into the set U, where U is { C }0,C1}，V＝{Ci-1,CiA } is sent to the central processing unit; calculating all path distances of the set U → the set V and marking out the shortest path C1→Ci-1Distance d of shortest pathmin；
6.1.5, sequentially circulating the operation of 6.1.4 steps, checking whether the set V is an empty set, if not, continuing to circulate, and if the set V is the empty set, ending the calculation, and further screening out the static path distance from the evacuation unit to the addressing scheme;
step 6.2, based on the improved Dijkstra algorithm, the shortest time path optimizing model
6.2.1, a road weight assignment principle, namely, a Dijkstra algorithm principle is combined with real-time traffic conditions to perform time weighting on a road network between an evacuation unit and a refuge place, namely, the road time weight is determined, the determination of the road weight is determined by analyzing and determining a road resistance function describing the relationship between the cost or time of vehicles on the road and the road traffic conditions, and the shortest time path to be spent on breaking the dam, avoiding danger and transferring victims is carefully evaluated by researching and combining the Dijkstra algorithm principle and selecting a proper road resistance function;
6.2.2, correcting the road resistance function parameters, selecting a cosmetic function, and carrying out time weight assignment on the road network in the research area, as shown in the following formula,
in the formula: t is tmTraffic flow for road segment m is xmA time of flight time; t is t0The free flow time is that the traffic volume of the road section m is 0 or extremely small; x is the number ofmIs the traffic flow for road segment m; cmIs the actual traffic capacity of the section m; alpha and beta are constants to be calibrated, alpha is (2 beta-1) (2 beta-2), beta is larger than 1, and a pedestrian interference influence coefficient gamma is introduced1Road curvature degree influence coefficient gamma2And road width influence coefficient gamma3In pair formula t0Correction is made to the pedestrian interference influence coefficient gamma1The value range from heavy to light according to the influence of the pedestrian interference is 0.5-1, and the influence coefficient gamma of the road curvature degree2The value range of the road curvature degree from high to low is 0.7-1, and the road width influence coefficient gamma3According to the condition that the value range of the road width influence from narrow to wide is 0.5-1.3, the traffic volume of the road reaches the maximum service traffic volume and the traffic capacity meets the reference traffic capacity, the actual road load degree x is measuredm/CmCorrecting;
6.2.3, optimizing the shortest time, and replacing the distance weight of each node in the step 6.1 with the road resistance of the road section calculated in the step 6.2.2 to calculate the dynamic time path from the evacuation unit to the addressing scheme;
and 6.3, based on GIS (geographic information system) levee breaking flood danger avoiding transfer path visualization, carrying out topology analysis and construction on the road network of the research area by combining GIS on the basis of the model principle in the step 6.1 and the step 6.2, and further calculating and drawing the shortest distance and the dynamic time from the evacuation unit to the addressing scheme.
Compared with the prior art, the method for calculating the optimal solution for the emergency refuge site selection and the path planning of the break embankment has the following advantages: and a comprehensive disaster prevention system combining engineering measures and non-engineering measures is constructed, so that the accident loss can be effectively reduced. Therefore, while flood disasters are avoided through engineering measures, the dam-breaking flood evolution situation of the dam protection area is analyzed, refuge site selection planning and path planning research after the dam break of the dam are dedicated, and the method has important scientific significance for improving emergency rescue efficiency, improving emergency flood control decision-making capability and level, enhancing flood control safety guarantee capability of the dam engineering and reducing potential dam-breaking loss.
Taking the river-west career dike protection area where breakwater happens many times as an example, mature commercial fluid simulation software MIKE is used for carrying out dike breakwater flood numerical simulation to obtain basic water situation data of the protection area when historical extra-large flood occurs, such as flood submerging range, arrival time, maximum flow rate and the like. And determining the units to be transferred and the number of people to be transferred in the protected area by combining the flood submerging range and the maximum flow velocity and utilizing GIS layer superposition and space analysis functions, and laying a foundation for site selection and path planning of subsequent refuges.
Drawings
FIG. 1 is a schematic workflow diagram of the present invention;
FIG. 2 is a schematic diagram of an evaluation index system for refuge site selection according to the present invention;
FIG. 3 is a diagram of the present invention with directed weights;
fig. 4 is a simplified schematic diagram of a risk avoidance transition road network according to the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for calculating the optimal solution for the break emergency refuge site selection and the path planning according to the present invention is further described with reference to the accompanying drawings and the specific implementation manners: in the embodiment, a numerical simulation model of the levee flood is constructed firstly, commercial software MIKE 21 is adopted to extract the data of the levee flood submerging characteristics, and the space processing GIS technology is utilized to solve the number of evacuation units and the number of persons evacuated in the levee; secondly, establishing a levee flood refuge site selection evaluation index system, calculating subjective weight by adopting an Analytic Hierarchy Process (AHP), calculating objective weight by adopting an Entropy Weight Method (EWM), and optimizing and recombining the subjective weight and the objective weight based on a division integration method; then, a reliable scheme comparison and selection method, TOPSIS, is introduced, a breakwater flood refuge site selection model is constructed, the primary site selection scheme outside the submerging range is subjected to quality sorting, and the breakwater flood refuge position is preliminarily determined; and finally, based on a Dijkstra algorithm and a road resistance function coupling method, the static distance and dynamic time path planning of the breakwater flood risk-avoiding transfer is realized by combining a GIS.
In order to solve the technical problems, the invention adopts the following specific technical scheme:
step one, constructing a numerical simulation model of the flood of the break dam
Taking the river-west career dike protection area where breakwater happens many times as an example, mature commercial fluid simulation software MIKE is used for carrying out dike breakwater flood numerical simulation to obtain basic water situation data of the protection area when historical extra-large flood occurs, such as flood submerging range, arrival time, maximum flow rate and the like.
(1) Model data preprocessing
Relevant software such as ArcMap, Global Mapper and AutoCAD is used for preprocessing DEM data of the research area to obtain scattered point data (xyz) required by MKIE 21.
(2) Mesh generation
In order to simulate the actual terrain more accurately, FM unstructured grids in the MIKE 21 model are adopted, numerical simulation is carried out by adopting a finite volume method of a unit center, irregular triangular grids are adopted in a calculation area, a Mesh Generator module in the MIKE is used for Mesh subdivision, and the area of each grid is not more than 0.1Km2In addition, some more special terrain and ground objects are encrypted, such as G316, Fuyin expressway and the like. And obtaining the topographic grid subdivision of the embankment protection area through grid generation, adjustment and interpolation manufacturing.
(3) Roughness cloud picture making method
Considering the roughness of the levee, the roughness of the model refers to a roughness value range given by flood risk map compilation technical rules and waterpower calculation handbook in view of the lack of actual measurement data. And drawing a roughness cloud picture of a research area by combining the land utilization data (Chinese academy resource and environment science, data center and global earth surface coverage official network) in the levee.
(4) Model parameter calibration
1) Breach selection
The influence factors of the breach position selection are numerous, many factors have strong ambiguity, and no universal specification is available at present to accurately judge the breach position. The breach is selected according to the principles of possible breach, disadvantage and concern by referring to the existing research and combining the research on the field and the literature.
2) Analog time and time step
And (4) selecting starting time and ending time according to the actual situation of the broken levee in the simulation time, and calculating the time step number and the step length through multiple times of calibration of the model.
3) Boundary condition
The model boundary conditions mainly include an open boundary and a dry-wet boundary.
The boundary is opened. And selecting a time-flow change process as a boundary setting condition on the model.
Dry and wet boundaries. In order to ensure the continuity of model calculation, a dry-wet processing technology is adopted. The dry and wet water depth respectively adopts the default values of 0.005m and 0.1m, namely when the water depth of the calculation area is less than 0.005m, the calculation area is marked as 'dry' and does not participate in calculation; when the water depth is greater than 0.1m, the calculation area is marked as 'wet', and the calculation is carried out again.
4) Coefficient of vortex viscosity
The vortex-viscosity coefficient is divided into a horizontal vortex-viscosity coefficient and a vertical vortex-viscosity coefficient, only the horizontal vortex-viscosity coefficient needs to be considered in a two-dimensional model, and an expression formula proposed by Smagorinsky in 1963 can be adopted, as shown in formula (1).
In the formula: cs is a constant and has a value range of 0.25-1.0; l is a characteristic length; sijIs the deformation ratio. A constant value of 0.28 is typically used.
5) Others
The requirements on wind, waves and tides are low in flood simulation, and data of the research area are missing, so that the wind, waves and tides and the like are not considered in the flood evolution process of the Kai dike protection area.
Step two, risk avoiding, transferring and evacuating unit and people number analysis
And analyzing and processing the breach flood risk avoiding and transferring evacuation units and the number of people by utilizing a geographic space analysis tool GIS according to the requirements of flood risk map compilation guide rules (SL483-2017) in combination with flooding water situation data and population density data.
Step three, evaluating index selection principle and index system
(1) Principle of selecting evaluation index
When the problem of the emergency refuge place of the burst flood is researched, a scientific evaluation index system is to be established. The key of the evaluation system construction is how to select indexes, so that the subsequent content development is facilitated, the objective evaluation is achieved, and the selected evaluation indexes can truly reflect evaluation objects. The coverage is comprehensive, the overlapping is avoided, the independent and mutual connection is realized, the evaluation key points can be highlighted, and clear levels are formed. Therefore, when the evaluation indexes of the emergency shelter are selected, three index selection principles of safety, accessibility and effectiveness are considered by combining a large number of previous research results and corresponding laws and regulations.
(2) Index system construction
According to the safety, accessibility and effectiveness selection principle, an embankment protection zone break flood refuge site selection evaluation index system is constructed so as to achieve the site selection target with the strongest comprehensive utilization capability and the smallest risk of site selection points as far as possible. The method mainly comprises 11 evaluation indexes such as distance from a geological disaster point, distance from a gas station, distance from a natural gas service station, gradient, distance from medical treatment, fire protection, public security, water source, road service level, cognitive ability, service population ability and the like, and is shown in figure 2.
Step four, combination empowerment based on division integration method
(1) Obtaining subjective weight vector omega of evaluation index by using Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM)AHPAnd objective weight ωEWM。
(2) And (3) carrying out optimization combination of subjective and objective weights according to a division integration method, wherein an objective function is shown as a formula (2).
In the formula: omega is the combining weight, omegaAHPCalculating a weight, ω, for an analytic hierarchy processEWMWeights are calculated for the entropy weight method.
Step five, comprehensive assigning model for refuge site selection based on TOPSIS
The TOPSIS method is a commonly used multi-attribute decision method, positive and negative ideal solutions are defined by constructing a decision weighting matrix, the distance between each addressing scheme and the positive ideal solution and the negative ideal solution and the relative pasting progress are calculated, and the addressing schemes are ranked according to the relative pasting progress. And (3) carrying out subjective and objective weight coupling through a combined weight method, and selecting an optimal scheme from the formulated site selection schemes based on a TOPSIS decision method.
Step six, constructing a risk avoidance transfer path optimization model
(1) Dijkstra algorithm-based shortest distance path optimization model
1) Assuming a road network structure of a research area, as shown in FIG. 3, divide intoRespectively recording initial node C0The other nodes are CiThe shortest distance between each node is d(i-1,i)(ii) a And adding a set U and a set V, wherein the set U represents the nodes of the shortest path which is solved (an empty set at the beginning), and the set V represents the nodes of the remaining shortest paths to be solved.
2) An adjacency matrix C is constructed to store the information of fig. 3, as shown in table 1.
Table 1 adjacency matrix information table
| C | C0 | C1 | Ci-1 | Ci |
| C0 | 0 | d(0,1) | d(0,i-1) | d(0,i) |
| C1 | ∞ | 0 | d(1,i-1) | d(1,i) |
| Ci-1 | ∞ | ∞ | 0 | d(i-1,i) |
| Ci | ∞ | ∞ | ∞ | 0 |
3) Starting from the initial calculation, i.e. from C1Starting from C1Put into the set U, where U is { C }0}，V＝{C1,Ci-1,CiB, }; calculating all path distances of the set U → the set V and marking out the shortest path C0→C1Distance d of shortest pathmin。
4) The nearest node C selected in the third step1Put into the set U, where U is { C }0,C1}，V＝{Ci-1,CiB, }; calculating all path distances of the set U → the set V and marking out the shortest path C1→Ci-1Distance d of shortest pathmin。
5) And sequentially circulating the fourth step of operation, checking whether the set V is an empty set, if not, continuing circulation, and if so, ending the calculation. And then screening out the static path distance from the evacuation unit to the addressing scheme.
(2) Shortest time path optimizing model based on improved Dijkstra algorithm
1) And (4) road weight assignment principle. According to the Dijkstra algorithm principle, the road network between the evacuation unit and the refuge place is subjected to time weighting only by combining with real-time traffic conditions, and the road time weight is determined. The determination of the right of way can be analyzed and determined by a road resistance function describing the relationship between the cost (or time) of vehicles on the road and the road traffic condition. Therefore, the research combines Dijkstra algorithm principle and selects a proper road resistance function to carry out detailed evaluation on the shortest time path which is required by breaking the dam, avoiding danger and transferring the disaster victims.
2) And correcting the parameters of the road resistance function. And selecting a simple and common cosmetic function, and performing time weight assignment on the road network of the research area, as shown in formula (3).
In the formula: t is tmTraffic flow for road segment m is xmA time of flight time; t is t0The free flow time when the traffic volume of the road section m is 0 or extremely small is adopted; x is the number ofmIs the traffic flow for road segment m; cmIs the actual traffic capacity of the section m; α and β are constants to be calibrated, α ═ 2 β -1 (2 β -2), β is greater than 1, corrected for reference to prior studies; reference to Highway engineering technology Standard (JTB-2014) and existing research introduces pedestrian interference influence coefficient gamma1Road curvature influence coefficient gamma2And road width influence coefficient gamma3In pair formula t0The correction was made, see tables 1-3; in the process of calculating the risk avoidance transfer planning theory, the most adverse condition, namely the condition that the traffic volume of a road reaches the maximum service traffic volume and the traffic capacity meets the reference traffic capacity, should be considered, and the actual road load degree x is subjected tom/CmAnd (6) correcting.
TABLE 1 pedestrian interference influence coefficient γ1
| Relative degree of interference | Is very serious | Severe severity of disease | Is more serious | In general | Is very small | Interference-free |
| γ1 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 1.0 |
TABLE 2 road camber influence coefficient γ2
| Degree of bending | High degree of bending | Moderate flexion | Low degree of bending |
| γ2 | 0.7～0.8 | 0.8～0.9 | 0.9～1.0 |
TABLE 3 road Width influence coefficient γ3
| Road width (m) | Coefficient of influence gamma3 | Road width (m) | Coefficient of influence gamma3 |
| 2.5 | 0.50 | 4.5 | 1.20 |
| 3.0 | 0.75 | 5.0 | 1.26 |
| 3.5 | 1.00 | 5.5 | 1.26 |
| 4.0 | 1.11 | 6.0 | 1.30 |
And further analyzing and calibrating each parameter in the formula (3).
3) Simplifying the model and the calculation step, wherein the synchronization step six (1) is basically consistent, and the main difference is that the road weight assignment attributes are different, wherein the former is a distance attribute, and the latter is a time attribute. The risk avoidance transition road network is simplified as shown in fig. 4.
(3) Flood risk-avoiding transfer path visualization based on GIS (geographic information system) levee break
And (3) carrying out topological analysis and construction on a road network of the research area by combining a GIS on the basis of the model principles of (1) and (2), and further calculating and drawing the shortest distance and the dynamic time from the evacuation unit to the site selection scheme.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (7)
1. A method for calculating an optimized solution for emergency refuge site selection and path planning for a break dam is characterized by comprising the following steps: comprises the following steps:
step 1, constructing a numerical simulation model of the burst flood;
step 2, risk avoiding, transferring and evacuating units and people number analysis;
step 3, establishing an evaluation index selection principle and an index system;
step 4, the combination based on the division integration method is endowed with the weight;
step 5, a comprehensive assigning model of refuge site selection based on TOPSIS;
and 6, constructing a risk avoidance transfer path optimization model.
2. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: the step 1 comprises the following steps of,
step 1.1, selecting a dike protection area where dike breaking occurs for many times, and preprocessing DEM data of a research area by utilizing ArcMap, GlobalMapper and AutoCAD related software to obtain scattered point data (.xyz) required by MKIE 21;
step 1.2, performing numerical simulation by using an FM unstructured grid in an MIKE 21 model and a finite volume method of a unit center, using an irregular triangular grid as a calculation area, performing grid subdivision by using a Mesh Generator module in MIKE, and performing grid generation, adjustment and interpolation to obtain the terrain grid subdivision of the embankment protection area;
step 1.3, according to the roughness of the model in the levee and the utilization data of the land in the levee, performing interpolation processing by combining the Mesh Generator with the terrain grid manufactured in the step 1.2, and drawing a roughness cloud picture of a research area;
step 1.4, calibrating model parameters, wherein the model parameters comprise breach selection, simulation time, time step length, boundary conditions and vortex-viscosity coefficients;
and step 1.5, combining the operation results from the step 1.1 to the step 1.4, and utilizing fluid simulation software MIKE to carry out numerical simulation on the levee dam bursting flood to obtain basic water condition data of the protected area when the historical extra-large flood occurs, such as the flood submerging range, the arrival time and the maximum flow rate.
3. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: and (3) analyzing and processing the risk-avoiding transferring and evacuating units and the number of people for the burst flood by combining the flooding situation data and the population density data and utilizing a geospatial analysis tool ArcGIS.
4. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: and 3, selecting emergency refuge place evaluation indexes according to three safety, accessibility and effectiveness selection principles, and constructing a levee protection area break flood refuge site selection evaluation index system, wherein the evaluation indexes of the system comprise geological disaster point distance, gas station distance, natural gas service station distance, gradient, medical treatment, fire protection, public security and water source distance, road service level, cognitive ability and service population ability.
5. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: the step 4 comprises the following steps of,
step 4.1, obtaining subjective weight vector omega of evaluation index by using an analytic hierarchy process and an entropy weight method respectivelyAHPAnd objective weight ωEWM；
Step 4.2, carrying out optimization combination of subjective and objective weights according to a division integration method, wherein an objective function is as follows,
in the formula: omega is the combining weight, omegaAHPCalculating a weight, ω, for an analytic hierarchy processEWMWeights are calculated for the entropy weight method.
6. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: in the step 5, the TOPSIS method constructs a decision weighting matrix by matrix initialization and standardization processing and combining the combined weights, defines positive and negative ideal solutions, calculates the distance between each addressing scheme and the positive and negative ideal solutions and the relative pasting progress, sorts the advantages and disadvantages of the addressing schemes according to the size of the relative pasting progress, and finally selects the best scheme from the drawn addressing schemes.
7. The method for calculating the optimal addressing scheme and path planning for the emergency refuge of the dam according to claim 1, wherein: said step 6 comprises the following steps,
step 6.1, shortest distance path optimizing model based on Dijkstra algorithm
6.1.1, assuming the road network structure of the research area, recording the initial nodes C0The other nodes are CiThe shortest distance between each node is d (i-1, i); adding a set U and a set V, wherein the set U represents the nodes of the shortest path which is solved, the set U is an empty set initially, and the set V represents the nodes of the remaining shortest paths to be solved;
6.1.2, constructing an adjacent matrix C for storing the road network information in the step 6.1.1;
6.1.3, initial calculation, i.e. from C1Starting from C1Put into the set U, where U is { C }0}，V＝{C1,Ci-1,CiA } is sent to the central processing unit; calculating all path distances of the set U → the set V and marking the shortest path C0→C1Distance d of shortest pathmin；
6.1.4, selecting the nearest node C selected in step 6.1.31Put into the set U, where U is { C }0,C1}，V＝{Ci-1,CiA } is sent to the central processing unit; calculating all path distances of the set U → the set V and marking out the shortest path C1→Ci-1Distance d of shortest pathmin；
6.1.5, sequentially circulating for 6.1.4 steps, checking whether the set V is an empty set, if not, continuing to circulate, and if the set V is the empty set, ending the calculation, and further screening out the static path distance from the evacuation unit to the site selection scheme;
step 6.2, based on the improved Dijkstra algorithm, the shortest time path optimizing model
6.2.1, a road weight assignment principle, namely, a Dijkstra algorithm principle is combined with real-time traffic conditions to perform time weighting on a road network between an evacuation unit and a refuge place, namely, the road time weight is determined, the determination of the road weight is determined by analyzing and determining a road resistance function describing the relationship between the cost or time of vehicles on the road and the road traffic conditions, and the shortest time path to be spent on breaking the dam, avoiding danger and transferring victims is carefully evaluated by researching and combining the Dijkstra algorithm principle and selecting a proper road resistance function;
6.2.2, correcting the road resistance function parameters, selecting a concrete function, carrying out time weight assignment on the road network in the research area, and obtaining the following formula,
in the formula: t is tmTraffic flow for road segment m is xmA time of flight time; t is t0The free flow time when the traffic volume of the road section m is 0 or extremely small is adopted; x is the number ofmA traffic flow for road segment m; cmIs the actual traffic capacity of the section m; alpha and beta are constants to be calibrated, alpha is (2 beta-1) (2 beta-2), beta is larger than 1, and a pedestrian interference influence coefficient gamma is introduced1Road curvature influence coefficient gamma2And road width influence coefficient gamma3In pair formula t0Corrected for the pedestrian interference influence coefficient gamma1The value range from heavy to light according to the influence of the pedestrian interference is 0.5-1, and the influence coefficient gamma of the road curvature degree2The value range of the road curvature degree from high to low is 0.7-1, and the road width influence coefficient gamma3According to the condition that the value range of the road width influence from narrow to wide is 0.5-1.3, the traffic volume of the road reaches the maximum service traffic volume and the traffic capacity meets the standard traffic capacity, the actual road load degree x is measuredm/CmCorrecting;
6.2.3, optimizing the shortest time, and replacing the distance weight of each node in the step 6.1 with the road resistance of the road section calculated in the step 6.2.2 to calculate the dynamic time path from the evacuation unit to the addressing scheme;
and 6.3, based on GIS breakwater flood risk avoiding transfer path visualization, carrying out topology analysis and construction on a road network of the research area by combining GIS on the basis of the model principle in the steps 6.1 and 6.2, and further calculating and drawing the shortest distance and the dynamic time from the evacuation unit to the site selection scheme.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210211265.0A CN114611780A (en) | 2022-03-05 | 2022-03-05 | Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210211265.0A CN114611780A (en) | 2022-03-05 | 2022-03-05 | Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114611780A true CN114611780A (en) | 2022-06-10 |
Family
ID=81860656
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210211265.0A Pending CN114611780A (en) | 2022-03-05 | 2022-03-05 | Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114611780A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115274084A (en) * | 2022-08-09 | 2022-11-01 | 河南大学 | Site selection method for emergency medical service facilities in mountainous villages |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109767042A (en) * | 2019-01-17 | 2019-05-17 | 中国人民解放军陆军工程大学 | Works of service team for civil air defence's site selecting method based on land used assessment |
| US20210287459A1 (en) * | 2018-09-30 | 2021-09-16 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| CN113869354A (en) * | 2021-08-16 | 2021-12-31 | 天津大学 | Comprehensive evaluation method for risk of levee in ice flood season |
| CN113902168A (en) * | 2021-09-08 | 2022-01-07 | 长江信达软件技术（武汉）有限责任公司 | Flood emergency evacuation method based on real-time crowd data fusion |
| CN113935609A (en) * | 2021-10-08 | 2022-01-14 | 天津大学 | Long-river-section multi-break-opening flood flooding combined risk assessment method |
| CN114049031A (en) * | 2021-11-22 | 2022-02-15 | 太原理工大学 | Method for optimizing site selection of rainwater storage tank |
-
2022
- 2022-03-05 CN CN202210211265.0A patent/CN114611780A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210287459A1 (en) * | 2018-09-30 | 2021-09-16 | Strong Force Intellectual Capital, Llc | Digital twin systems and methods for transportation systems |
| CN109767042A (en) * | 2019-01-17 | 2019-05-17 | 中国人民解放军陆军工程大学 | Works of service team for civil air defence's site selecting method based on land used assessment |
| CN113869354A (en) * | 2021-08-16 | 2021-12-31 | 天津大学 | Comprehensive evaluation method for risk of levee in ice flood season |
| CN113902168A (en) * | 2021-09-08 | 2022-01-07 | 长江信达软件技术（武汉）有限责任公司 | Flood emergency evacuation method based on real-time crowd data fusion |
| CN113935609A (en) * | 2021-10-08 | 2022-01-14 | 天津大学 | Long-river-section multi-break-opening flood flooding combined risk assessment method |
| CN114049031A (en) * | 2021-11-22 | 2022-02-15 | 太原理工大学 | Method for optimizing site selection of rainwater storage tank |
Non-Patent Citations (3)
| Title |
|---|
| 刘卫林等: "基于MIKE FLOOD的中小河流溃堤洪水风险分析", 水利水电技术, no. 01, 31 May 2019 (2019-05-31), pages 91 - 102 * |
| 康琳: "基于山区堰塞湖溃决模拟的避难路径规划方法", 《中国优秀硕士学位论文全文数据库工程科技Ⅰ辑》, no. 3, 15 March 2020 (2020-03-15), pages 026 - 109 * |
| 程晓娟: "《面向设计的产品生命周期成本控制研究》", vol. 1, 31 March 2017, 《西安交通大学出版社》, pages: 114 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115274084A (en) * | 2022-08-09 | 2022-11-01 | 河南大学 | Site selection method for emergency medical service facilities in mountainous villages |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Cova et al. | Modelling community evacuation vulnerability using GIS | |
| CN104156525B (en) | A kind of method for improving storm surge disaster risk profile precision | |
| CN104821013A (en) | Method and system for specific surface area extraction based on geodetic coordinate system digital elevation model | |
| CN113283802A (en) | Landslide risk assessment method for complex and difficult mountain area | |
| CN115329691B (en) | CFD and GIS-based ultra-large city wind environment simulation method | |
| CN110377674A (en) | A kind of Typhoon Storm Surge Over methods of risk assessment and system based on ArcGIS platform | |
| CN113139760B (en) | Typhoon risk comprehensive evaluation method and system based on wind and rain big data | |
| CN108764702A (en) | Consider the area to be protected against floods flood risk assessment method of flood control works safety | |
| CN110544305B (en) | Terrain steeple ridge line information fusion method constructed by DEM (digital elevation model) oriented to regular grids | |
| CN114611780A (en) | Method for calculating optimal solution for location selection of emergency refuge for levee breaking and path planning | |
| CN115115262A (en) | Flood risk disaster assessment method | |
| Rui et al. | Urban growth modeling with road network expansion and land use development | |
| Lyu et al. | Sensitivity analysis of typhoon-induced floods in coastal cities using improved ANP-GIS | |
| CN113869804B (en) | Power grid equipment risk early warning method and system under flood disaster | |
| Wang et al. | A non-uniform grid approach for high-resolution flood inundation simulation based on GPUs | |
| CN101763659A (en) | Method for automatically generating large-scale digitization altitude data model based on image set | |
| CN114842163A (en) | Multi-scale dynamic gridding model construction method for disaster assessment | |
| CN114004114A (en) | Reservoir dam-break flood evolution rapid simulation method based on GPU parallel acceleration | |
| Panchal et al. | Expert based landslide susceptibility mapping for energy infrastructure planning | |
| Vatvani et al. | Cyclone induced storm surge and flood forecasting system for India | |
| CN113408201B (en) | Landslide susceptibility evaluation method based on terrain unit | |
| Zhang et al. | Study on the spatial expansion of Garden City under the ecological green spaces protection (Qujing area, China). | |
| Yingying et al. | A Study of Urban Flood Safety Patterns in Built-up Areas of Bangkok Based on Complex Network Theory | |
| Zhou et al. | Flood submergence simulation and risk analysis based on GIS in plain area | |
| CN106709668B (en) | Land risk assessment method and device based on sea level rise |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |