Urban shelter function loss evaluation system under strong wind-waterlogging multiple disasters

Abstract

The invention relates to an urban shelter function loss evaluation system under strong wind-waterlogging multiple disasters, and belongs to the technical field of urban toughness and disaster prevention and reduction. The building module is used for building an urban road network-shelter function network topological structure model and basic data for disaster physical loss analysis; the monitoring module comprises meteorological observation data and is used for acquiring real-time disaster intensity parameters such as wind speed, wind direction and rainfall intensity parameters; the calculation module comprises a disaster damage analysis system used for calculating physical damage of urban road networks, building groups and shelter assemblies caused by strong wind and waterlogging disasters and a function loss analysis system used for calculating urban shelter function loss caused by corresponding physical damage. The established system more accurately quantifies the urban shelter function loss considering the influence of the traffic network under the combined action of multiple disasters of strong wind-waterlogging.

Description

Technical Field

[0001] The present invention belongs to the technical field of urban resilience and disaster prevention and mitigation, and relates to an evaluation system for the functional loss of urban shelters under multiple disasters of strong wind and urban waterlogging, and particularly relates to an evaluation system for the functional loss of urban shelters applicable to the combined action of strong wind and urban waterlogging and considering the influence of the traffic road network. Background Art

[0002] Typhoons and severe convective weather often trigger strong winds accompanied by heavy rainfall. Strong winds are likely to cause serious damage to the enclosure systems of building clusters, and large areas of roadside trees on the road network are prone to lodging, resulting in traffic being affected or interrupted; heavy rainfall is likely to induce urban waterlogging, causing low-lying communities to be flooded and the road network traffic to be paralyzed due to water accumulation. The impacts of strong winds and urban waterlogging are both important and need to be considered simultaneously.

[0003] Some communities are uninhabitable due to severe wind-induced damage to the enclosure system or urban waterlogging, resulting in a large number of people who need to be transferred and resettled. The urban road network is interrupted due to the lodging of roadside trees or excessive water accumulation, and the traffic efficiency of the road network drops sharply, seriously affecting the transfer of shelter-seeking people and the daily travel of residents. There is a coupling effect between the traffic system and shelter.

[0004] Regarding natural disasters, the following related loss assessment method studies are available:

[0005] (1) Evaluation method for the function of the urban medical system after an earthquake

[0006] The main process is as follows: a. Establish a finite element model of a typical hospital building and a finite element model of a typical residential building, and carry out dynamic elastoplastic analysis of earthquake loads; b. According to the response results of the finite element analysis, determine the damage levels of the hospital building and the community building, and determine the remaining functional levels of each floor of the hospital after the earthquake; c. Determine the number of injured people in different communities according to empirical methods, and analyze the blocked state of the road network based on the building damage level and the post-earthquake debris model of the building; d. Analyze the accessibility level of the injured people to the hospital and the waiting time for medical treatment in the hospital, and compare with the pre-disaster function to evaluate the functional loss of the medical system after the earthquake.

[0007] (2) Evaluation method for the functional loss of the urban road network under strong wind or urban waterlogging

[0008] The main process is as follows: a. According to the wind speed or rainfall intensity data observed by meteorology, conduct physical damage analysis of roadside trees on the urban road network or carry out urban waterlogging simulation; b. Analyze the physical damage state of roadside trees on the urban road network or the spatial distribution of urban waterlogging, and determine the road interruptions caused by the lodging of roadside trees or water accumulation; c. Analyze the connectivity between each node in the road network to evaluate the functional loss of the urban road network after strong wind or urban waterlogging disasters.

[0009] (3) Evaluation method for the physical loss of low-rise buildings (groups) under strong wind and urban waterlogging

[0010] The main process is as follows: a. Obtain the wind load coefficient and wind-driven rain intensity coefficient on the surface of low-rise buildings (groups) through wind tunnel tests or numerical simulations; b. Combine the measured wind speed and rain intensity data to calculate the magnitude of the wind load on the surface of low-rise buildings (groups) and determine whether the surface enclosure system has wind-induced damage; c. If wind-induced damage occurs, further calculate the amount of wind-driven rain invading the indoor area; d. Calculate the indoor and outdoor economic losses caused by wind-induced damage and rainwater intrusion to evaluate the physical damage level of low-rise buildings (groups) under strong winds or heavy rains.

[0011] Different from the safety assessment of single-project structures, the function of urban shelters is not only related to the safety of their own structures and enclosure systems but also affected by the traffic efficiency of road networks and the number of people they can accommodate. However, existing technologies mainly focus on the physical damage of road network components and the assessment of road network functions under single disasters such as strong winds or inland floods. Some technologies only analyze the transfer process of shelter-seeking people in the road network after disasters; there is a lack of consideration of the impact of physical damage to community building groups, road network components, and shelters on the function of urban shelters under strong wind-inland flood multiple disasters, and there is no quantitative method for evaluating the function loss of shelters considering the impact of the traffic road network under the combined action of strong wind-inland flood multiple disasters.

[0012] Currently, when facing strong wind-inland flood multiple disasters, the emergency management department mainly formulates corresponding shelter strategies based on disaster warning levels. However, due to the lack of support for the quantitative value of the function loss of shelters under strong wind-inland flood multiple disasters, the existing decision-making methods are inefficient and inaccurate. To ensure the safety of shelter-seeking people, the emergency management department needs to always know whether urban shelters are safe, accessible, and can accommodate shelter-seeking people, so as to formulate a reasonable transfer plan for shelter-seeking people. It is necessary to evaluate the function loss of urban shelters under strong wind-inland flood multiple disasters. During the evaluation process, the combined action of strong winds and inland floods and the functional coupling effect between the transportation system and shelters need to be considered.

[0013] Therefore, there is an urgent need to establish a function loss assessment system for urban shelters considering the impact of the traffic road network under the combined action of strong wind-inland flood multiple disasters, which can provide a decision-making basis for urban emergency management departments and is of great significance for reducing the function loss of urban shelters caused by strong wind-inland flood multiple disasters and improving the disaster prevention resilience of cities. Summary of the Invention

[0014] In view of this, the present invention aims to solve the problems that existing technologies generally only target single disasters such as strong winds or inland floods, lack consideration of the impact of physical damage to community building groups, road network components, and shelters on the function loss of urban shelters under strong wind-inland flood multiple disasters, and lack a function loss assessment system for shelters considering the impact of the traffic road network under the combined action of strong wind-inland flood multiple disasters. The present invention provides a function loss assessment system for urban shelters under strong wind-inland flood multiple disasters, which can analyze the function loss level of urban shelters under different combinations of disaster parameters in real time based on meteorological observation data.

[0015] To achieve the above object, the present invention provides the following technical solutions:

[0016] An urban shelter function loss assessment system under strong wind - waterlogging multi - disasters, comprising a basic data processing module, a monitoring module and a calculation module;

[0017] Among them, the basic data processing module includes network open - source data, a topology and data processing system, which is used to construct an urban road network - shelter function network topology model and basic data for disaster physical loss analysis; the monitoring module includes meteorological observation data, which is used to obtain real - time disaster intensity parameters, such as wind speed, wind direction and rainfall intensity parameters, etc.; the calculation module includes a disaster damage analysis system for calculating the physical damage of urban road networks, building groups and shelter components caused by strong wind and waterlogging disasters, and a function loss analysis system for calculating the function loss of urban shelters caused by the corresponding physical damage.

[0018] Furthermore, the specific process of the loss assessment system is as follows:

[0019] S1. The network open - source data obtained in the basic data processing module mainly includes map data and function data. Input the map data and function data of the study area into the topology and data processing system, and output the urban road network - shelter function network topology model and basic data of vulnerable components;

[0020] S2. The disaster intensity parameters in the monitoring module, that is, strong wind - waterlogging disaster parameters, mainly include wind speed, wind direction and rainfall intensity data, which can be obtained from the meteorological observation station where the study area is located;

[0021] S3. Input the strong wind - waterlogging disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module, and the physical damage data of urban components under the current strong wind and waterlogging disasters can be analyzed; then input the component physical damage data and the urban road network - shelter function network output by the basic data processing module into the function loss analysis system, and the impact of component physical damage on the function loss of urban shelters can be analyzed, and finally the function loss value of shelters considering the influence of the traffic road network is output.

[0022] Furthermore, the map data in step S1 includes open - source road network data, satellite map photos, geographical elevation and building geometric contour information, etc., and the acquisition methods are as follows:

[0023] S11. Download urban road network data (including road network coordinates, lane grades, etc.) through the open - source map OpenStreetMap for establishing the geometric topology of the road network;

[0024] S12. Download satellite map photos, geographic elevation information, and building contour information through Tianditu for identifying the locations and geometric parameters of vulnerable components.

[0025] Further, the functional data in step S1 includes real-time road network situation data, names of shelters, coordinates, and designed accommodation capacities, etc.; the acquisition methods are as follows:

[0026] S13. Obtain traffic situation data of the road network on Amap (including road section names, coordinates, vehicle speeds, etc.) through crawler code for calculating road network topological function parameters.

[0027] S14. Obtain shelter data (shelter names, coordinates, designed accommodation capacities) from government management departments for establishing geometric topology and functional parameters of shelters.

[0028] Further, after obtaining the above-mentioned network open-source data, perform parsing and processing in the topology and data processing system, specifically as follows:

[0029] S15. Parsing and processing of satellite map photos:

[0030] Determine the types and coordinates of low-rise building roofs vulnerable to wind loads, as well as the geometric dimensions and coordinates of street tree crowns through image recognition algorithms; among them, the roof types are classified as tile roofs and metal roofs. After obtaining the geometric dimensions of street tree crowns, further calculate the height information of street trees based on the statistical function of the relationship between tree height and crown width.

[0031] S16. Parsing and processing of urban road network and shelter coordinate data:

[0032] S161. Simplify the downloaded urban road network data, screen out urban arterial roads, first-class and second-class roads, simplify road network intersections into nodes, and road sections into lines to construct the geometric topology of the urban road network.

[0033] S162. Simplify shelters into nodes, and further perform spatial overlay with the geometric topology of the urban road network according to the shelter coordinates.

[0034] S163. Construct the geometric topology network of the urban road network - shelters.

[0035] S17. Parsing and processing of traffic situation and shelter functional data:

[0036] S171. Based on the speed-flow relationship, convert the average passing vehicle speed of some road sections monitored by the traffic situation into passing flow, and use the traffic flow inversion algorithm to obtain the traffic travel demands between each node of the normally operating road network and the initial road network flow distribution.

[0037] S172. Assign the number of people that the shelter can accommodate to the shelter nodes in the geometric topology network, assign the initial road network traffic distribution to the road network edges in the geometric topology network, and assign the travel demand to the road network nodes in the geometric topology network;

[0038] S173. Output the urban road network - shelter functional network topology structure model with functional parameters.

[0039] Furthermore, in step S2, the wind speed, wind direction, and rainfall intensity data of the study area are obtained through the anemometer and wind vane and the rain intensity meter in the meteorological observation station. Among them, the anemometer can observe the wind speed data in the range of 0 - 70 m / s and the wind direction data in the range of 0 - 360°. The rain intensity meter adopts a tipping bucket rain gauge, which can record the rain intensity of 0 - 100 mm / day, and the resolution is 0.1 - 0.5 mm. The recorded wind speed, wind direction, and rainfall intensity data will be input into the calculation module to conduct disaster loss analysis.

[0040] Furthermore, the disaster damage analysis system is divided into two parts, respectively for strong wind and waterlogging disasters.

[0041] Furthermore, the damage analysis system of the disaster damage analysis system for strong wind is specifically as follows:

[0042] S311. Input the wind speed and wind direction data recorded by the monitoring module, and combine the wind load models of typical roof enclosures and road network street trees obtained based on wind tunnel tests, and the roof type / coordinates and street tree data output by the basic data processing module, and calculate the wind load values on the surfaces of roofs and street trees at different positions;

[0043] S312. Based on the established wind-induced failure resistance models of roof enclosures and street trees, and combine the roof type / coordinates and street tree data output by the basic data processing module, and calculate the resistance values of roofs and street trees at different positions;

[0044] S313. Compare the relationship between the resistance and the wind load. When the resistance is less than the wind load, it is considered that the roof / street tree is damaged;

[0045] S314. When the roof enclosure is damaged, combine the building roof type / coordinates output by the basic data processing module and the geographical elevation information and building contour coordinate information obtained from the basic data processing module, and conduct wind-induced projectile damage analysis to determine the building complex further impacted by the wind-induced projectiles and the damage data of the shelter;

[0046] S315. When the street tree is damaged, combine the basic street tree data output by the basic data processing module, calculate the spatial relationship between the fallen position of the street tree and the road, judge whether the street tree will cause road blockage, and calculate the width of the blocked road;

[0047] S316. Output the results such as the wind-induced damage data of the building envelopes of the output building complex, the wind-induced projectile damage data of the building complex, and the width of the road network blocked by fallen trees.

[0048] Furthermore, the damage analysis system for waterlogging is specifically as follows:

[0049] S317. Input the rainfall intensity data recorded by the monitoring module and the geographical elevation information obtained by the basic data processing module, combine with the designed drainage capacity of the study area, and use the surface runoff generation and concentration analysis model to carry out urban waterlogging simulation, and output the spatio-temporal distribution results of urban waterlogging;

[0050] S318. Combine the road network coordinate information and building contour coordinate information output by the basic data processing module to identify the communities and road networks where the water accumulation depth exceeds the threshold;

[0051] S319. Output the communities that are not suitable for living due to excessive water accumulation, and the results such as the water accumulation depth of each section of the road network.

[0052] Furthermore, the functional loss analysis system is specifically as follows:

[0053] S321. Input the severely wind-induced damaged buildings and communities with excessive water accumulation output by the disaster damage analysis system, combine with the building contour coordinate information provided by the basic data processing module to estimate the number of households in each building, estimate the number of people / coordinates in need of post-disaster shelter caused by buildings not suitable for living, determine the buildings of shelters that may be damaged, and update the number of people that can be accommodated in the shelters;

[0054] S322. Input the blocked width of the road section, interrupted road sections and water accumulation depth of the road section output by the disaster damage analysis system, combine with the urban road network-shelter function topological network model provided by the basic data processing module, and further update the remaining passable width of the road section in the topological network, remove the interrupted road sections and the attenuated passing vehicle speed considering the influence of water accumulation;

[0055] S323. On the basis of this updated road network-shelter network, while considering the new shelter demand and the traffic demand of the road network in the pre-disaster normal operation state, carry out traffic flow assignment simulation;

[0056] S324. Calculate the post-disaster shelter function index Q according to the simulation results 1 , this index comprehensively considers the function parameters of shelter safety, accessibility and the number of people that can be accommodated; take the ratio of Q 1 to the pre-disaster shelter function index Q 0 as the final shelter function loss index R; R = 1 indicates that the shelter function has no functional loss, R > 1 indicates that the shelter function has functional loss, and the larger the value, the greater the loss.

[0057] The beneficial effects of the present invention are as follows:

[0058] 1. The urban shelter function loss assessment system under strong wind - waterlogging multi - disasters disclosed by the present invention fully considers the impact of physical damage to urban road networks and building groups on urban shelter functions through the established system, and more accurately quantifies the function loss of urban shelters considering the influence of traffic road networks under the combined action of strong wind - waterlogging multi - disasters. It can solve the problem that due to the lack of support for the quantitative value of the function loss of urban shelters affected by traffic road networks under the combined action of strong wind - waterlogging multi - disasters, the emergency shelter decision - making is inefficient and inaccurate.

[0059] 2. The urban shelter function loss assessment system under strong wind - waterlogging multi - disasters disclosed by the present invention establishes an urban road network - shelter function network topology model based on network open - source data, conducts physical damage analysis of strong wind and waterlogging disasters for urban road networks and building groups based on the monitored wind speed, wind direction and rainfall intensity data, and calculates the function loss value of urban shelters under strong wind - waterlogging multi - disasters through the function loss analysis system.

[0060] 3. The urban shelter function loss assessment system under strong wind - waterlogging multi - disasters disclosed by the present invention can provide decision - making technical support for urban emergency management departments, and is of great significance for reducing the function loss of urban shelters caused by strong wind - waterlogging multi - disasters and improving the disaster prevention resilience of cities.

[0061] Other advantages, objectives and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be learned from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, where:

[0063] Figure 1 is the structural block diagram of an urban shelter function loss assessment system under strong wind - waterlogging multi - disasters of the present invention;

[0064] Figure 2 is the flow chart of the basic data processing module in the urban shelter function loss assessment system under strong wind - waterlogging multi - disasters of the present invention;

[0065] Figure 3 is the structural block diagram of the monitoring module in the urban shelter function loss assessment system under strong wind - waterlogging multi - disasters of the present invention;

[0066] Figure 4 This is the flowchart of the calculation module in a functional loss assessment system for urban shelters under strong wind and waterlogging disasters according to the present invention. Specific embodiments

[0067] The following uses specific examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0068] As Figure 1 shown, a functional loss assessment system for urban shelters under strong wind and waterlogging disasters includes a basic data processing module (Module 1), a monitoring module (Module 2), and a calculation module (Module 3).

[0069] S1. The basic data processing module includes network open-source data, a topology and data processing system. Input the map data and functional data of the study area into the topology and data processing system, and output the urban road network-shelter function network topology structure model and the basic data of vulnerable components. It is used to construct the urban road network-shelter function network topology structure model and the basic data for analyzing the physical losses of disasters; its specific process is shown in Figure 2 shown. The network open-source data mainly includes map data and functional data. The map data includes open-source road network data, satellite map photos, geographical elevation, and building geometric contour information, etc. The acquisition methods are as follows:

[0070] S11. Download the urban road network data (including road network coordinates, lane grades, etc.) through the open-source map OpenStreetMap for establishing the geometric topology of the road network;

[0071] S12. Download satellite map photos, geographical elevation information, and building contour information through Tianditu for identifying the positions and geometric parameters of vulnerable components.

[0072] The functional data includes real-time road network situation data, shelter names, coordinates, and designed accommodation numbers, etc.; the acquisition methods are as follows:

[0073] S13. Obtain the traffic situation data of the road network on Amap (including road section names, coordinates, vehicle speeds, etc.) through crawler code for calculating the topological function parameters of the road network;

[0074] S14. Obtain the data of evacuation shelters (shelter name, coordinates, and designed capacity) through government management departments for establishing the geometric topology and functional parameters of evacuation shelters.

[0075] After obtaining the above-mentioned open-source network data, perform parsing and processing in the topology and data processing system. Specifically:

[0076] S15. Satellite map photos:

[0077] Determine the roof types and coordinates of low-rise buildings vulnerable to wind load effects, as well as the geometric dimensions and coordinates of the crown widths of street trees through image recognition algorithms. Among them, the roof types are classified into tile roofs and metal roofs. After obtaining the geometric dimensions of the crown widths of street trees, further calculate the height information of street trees based on the statistical function of the relationship between tree height and crown width.

[0078] S16. Urban road network and evacuation shelter coordinate data:

[0079] S161. Simplify the downloaded urban road network data, screen out urban arterial roads, first-class and second-class roads, simplify the road network intersections into nodes, and simplify the road sections into lines to construct the geometric topology of the urban road network.

[0080] S162. Simplify the evacuation shelters into nodes, and further perform spatial overlay with the geometric topology of the urban road network according to the coordinates of the evacuation shelters.

[0081] S163. Construct the urban road network - evacuation shelter geometric topology network.

[0082] S17. Traffic situation and evacuation shelter function data:

[0083] S171. Based on the speed-flow relationship, convert the average passing speed of some road sections monitored in the traffic situation into passing flow, and use the traffic flow back-calculation algorithm to obtain the traffic travel demand between each node of the normal operation road network and the initial road network flow distribution.

[0084] S172. Assign the capacity of the evacuation shelter to the evacuation shelter nodes in the geometric topology network, assign the initial road network flow distribution to the road network edges in the geometric topology network, and assign the traffic travel demand to the road network nodes in the geometric topology network.

[0085] S173. Output the functional network topology structure model of the urban road network - evacuation shelter with functional parameters.

[0086] S2. As Figure 3The monitoring module shown includes meteorological observation data. Disaster intensity parameters are obtained through the meteorological observation station in the study area, which are used to obtain real-time disaster intensity parameters, such as wind speed, wind direction, and rainfall intensity parameters, etc. The disaster intensity parameters, namely the strong wind - waterlogging disaster parameters, mainly include wind speed, wind direction, and rainfall intensity data, which can be obtained through the meteorological observation station in the study area. The wind speed, wind direction, and rainfall intensity data of the study area are obtained through the anemometer and wind vane in the meteorological observation station and the rain gauge; among them, the anemometer can observe wind speed data in the range of 0 - 70 m / s and wind direction data in the range of 0 - 360°, and the rain gauge adopts a tipping bucket rain gauge, which can record rainfall intensity data in the range of 0 - 100 mm / day, with a resolution of 0.1 - 0.5 mm; the recorded wind speed, wind direction, and rainfall intensity data will be input into the calculation module to carry out disaster loss analysis.

[0087] S3. Input the strong wind - waterlogging disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module, and the physical damage data of urban components under the current strong wind and waterlogging disasters can be analyzed; then input the component physical damage data and the urban road network - shelter function network output by the basic data processing module into the function loss analysis system, and the impact of component physical damage on the loss of urban shelter function can be analyzed, and finally the loss value of the shelter function considering the impact of the transportation road network is output. The calculation module includes a disaster damage analysis system for calculating the physical damage of urban road networks, building complexes, and shelter components caused by strong wind and waterlogging disasters and a function loss analysis system for calculating the loss of urban shelter function caused by the corresponding physical damage. The specific process is as Figure 4 shown.

[0088] S31. The disaster damage analysis system is divided into two parts, respectively for strong wind and waterlogging disasters.

[0089] Among them, the damage analysis system for strong wind is specifically as follows:

[0090] S311. Input the wind speed and wind direction data recorded by the monitoring module, combine with the wind load models of typical roof enclosures and road network street trees obtained based on wind tunnel tests, and the roof type / coordinates and street tree data output by the basic data processing module to calculate the wind load values on the surfaces of roofs and street trees at different positions;

[0091] S312. Based on the established wind-induced failure resistance models of roof enclosures and street trees, and combined with the roof type / coordinates and street tree data output by the basic data processing module, calculate the resistance values of roofs and street trees at different positions;

[0092] S313. Compare the relationship between the resistance and the wind load. When the resistance is less than the wind load, it is considered that the roof / street tree is damaged;

[0093] S314. When the roof enclosure structure is damaged, based on the building roof type / coordinates output by the basic data processing module and the geographical elevation information and building outline coordinate information obtained from the basic data processing module, conduct an analysis of wind-induced projectile damage to determine the building complexes further impacted by wind-induced projectiles and the damage data of the evacuation shelters;

[0094] S315. When street trees are damaged, based on the basic data of street trees output by the basic data processing module, calculate the spatial relationship between the fallen position of the street trees and the road, determine whether the street trees will cause road blockage, and calculate the width of the blocked road;

[0095] S316. Output the results such as the wind-induced damage data of the roof enclosures of building complexes, the wind-induced projectile damage data of building complexes, and the width of the road network blocked by fallen trees.

[0096] The damage analysis system for waterlogging is specifically as follows:

[0097] S317. Input the rainfall intensity data recorded by the monitoring module and the geographical elevation information obtained from the basic data processing module, and combine with the designed drainage capacity of the study area. Use the surface runoff generation and concentration analysis model to conduct urban waterlogging simulation and output the spatio-temporal distribution results of urban waterlogging;

[0098] S318. Combine the road network coordinate information and building outline coordinate information output by the basic data processing module to identify the communities and road networks where the water depth exceeds the threshold;

[0099] S319. Output the communities that are uninhabitable due to excessive waterlogging and the water depth of each section of the road network, etc.

[0100] S32. The function loss analysis system is specifically as follows:

[0101] S321. Input the severely wind-damaged buildings and communities with excessive waterlogging output by the disaster damage analysis system, estimate the number of households in each building based on the building outline coordinate information provided by the basic data processing module, estimate the number of people / coordinates in need of evacuation after the disaster caused by uninhabitable buildings, determine the buildings of evacuation shelters that may be damaged, and update the capacity of the evacuation shelters;

[0102] S322. Input the blocked width of road sections, interrupted road sections, and the water depth of road sections output by the disaster damage analysis system, and combine with the urban road network - evacuation shelter function topological network model provided by the basic data processing module to further update the remaining passable width of road sections in the topological network, remove the interrupted road sections, and consider the attenuation of traffic speed affected by waterlogging;

[0103] S323. Based on this updated road network - evacuation network, while considering the new evacuation needs and the traffic demand of the road network in the pre-disaster normal operation state, conduct traffic flow assignment simulation;

[0104] S324. Calculate the functional index Q of the post-disaster shelter according to the simulation results 1 , which comprehensively considers the functional parameters of the safety, accessibility, and the number of people that can be accommodated in the shelter; take Q 1 and the ratio of the functional index Q of the pre-disaster shelter 0 as the final functional loss index R of the shelter; R being 1 indicates that there is no functional loss in the shelter, and R greater than 1 indicates that there is a functional loss in the shelter, and the larger the value, the greater the loss.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the purpose and scope of the present technical solution, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A system for assessing the functional loss of urban shelters under strong winds and flooding disasters, characterized in that: It includes basic data processing module, monitoring module and calculation module; The basic data processing module includes network open source data, topology and data processing systems, which are used to construct a topological structure model of the urban road network-shelter functional network and basic data for disaster physical loss analysis; the monitoring module includes meteorological observation data, which is used to obtain real-time disaster intensity parameters; the calculation module includes a disaster damage analysis system for calculating the physical damage to urban road networks, buildings and shelter components caused by strong winds and waterlogging disasters, and a functional loss analysis system for calculating the functional loss of urban shelters caused by the corresponding physical damage.

2. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 1, characterized in that: The specific process of the loss assessment system is as follows: S1. The network open source data obtained in the basic data processing module includes map data and functional data. The map data and functional data of the study area are input into the topology and data processing system, and the urban road network-shelter functional network topology structure model and vulnerable component basic data are output; S2, the disaster intensity parameters in the monitoring module, namely the strong wind-waterlogging disaster parameters, including wind speed, wind direction and rainfall intensity data, are obtained through the meteorological observation station in the study area; S3. Input the strong wind-waterlogging disaster parameters provided by the monitoring module and the basic data of vulnerable components output by the basic data processing module into the disaster damage analysis system in the calculation module to analyze the physical damage data of urban components under the current strong wind and waterlogging disasters; then input the component physical damage data and the urban road network-shelter function network output by the basic data processing module into the function loss analysis system to analyze the impact of component physical damage on the loss of urban shelter function, and finally output the shelter function loss value considering the impact of the traffic road network.

3. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 2, characterized in that: The map data in step S1 includes open source road network data, satellite map photos, geographic elevation and building geometric outline information, which are obtained in the following way: S11. Download urban road network data such as road network coordinates and lane levels through the open source map OpenStreetMap to establish road network geometric topology; S12. Download satellite map photos, geographic elevation information and building outline information through Tianditu to identify the location and geometric parameters of vulnerable components.

4. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 3, characterized in that: The functional data in step S1 includes real-time road network situation data, shelter name, coordinates and designed number of people; the acquisition method is: S13. Obtaining the traffic situation data of the Amap road network through the crawler code, such as the road section name, coordinates, and vehicle speed, for calculating the road network topology function parameters; S14. Obtain shelter data from government management departments, such as the name of the shelter, coordinates, and designed capacity, to establish the geometric topology and functional parameters of the shelter.

5. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 4, characterized in that: After obtaining the network open source data in step S1, the topology and data processing system performs parsing and processing, specifically: S15. Satellite map photo analysis and processing: The image recognition algorithm is used to determine the types and coordinates of low-rise building roofs that are susceptible to wind loads, as well as the geometric dimensions and coordinates of the crown width of street trees. The roof types are classified into tile roofs and metal roofs. After obtaining the geometric dimensions of the crown width of street trees, the height information of street trees is further calculated based on the statistical function of the relationship between tree height and crown width. S16. Analysis and processing of urban road network and shelter coordinate data: S161, simplifying the downloaded urban road network data, screening out urban trunk roads, primary and secondary roads, simplifying road network intersections into nodes, simplifying road sections into lines, and constructing the urban road network geometric topology; S162, simplifying the shelters into nodes, and further spatially superimposing them with the geometric topology of the urban road network according to the coordinates of the shelters; S163, construct the geometric topological network of urban road network-shelter; S17. Traffic situation and shelter function data analysis and processing: S171, based on the vehicle speed-flow relationship, convert the average vehicle speed of some road sections monitored by the traffic situation into the traffic flow, and use the vehicle flow reverse calculation algorithm to obtain the traffic travel demand between each node of the normal operation road network and the initial road network flow distribution; S172, assigning the number of people accommodated in the shelter to the shelter node in the geometric topological network, assigning the initial road network flow distribution to the road network edge in the geometric topological network, and assigning the traffic travel demand to the road network node in the geometric topological network; S173. Output a city road network-shelter functional network topology model with functional parameters.

6. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 5, characterized in that: Step S2 obtains the wind speed, wind direction and rainfall intensity data of the study area through the wind speed and wind direction observation instrument and the rainfall intensity meter in the meteorological observation station; wherein, the wind speed and wind direction observation instrument can observe the wind speed of 0-70m / s and the wind direction range of 0-360°, and the rainfall intensity meter adopts a tipping bucket rain gauge, which can record the rainfall intensity of 0-100mm / day with a resolution of 0.1-0.5mm; the recorded wind speed, wind direction and rainfall intensity data will be input into the calculation module to carry out disaster loss analysis.

7. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 6, characterized in that: In step S3, the disaster damage analysis system is divided into two parts, targeting strong wind and waterlogging disasters respectively.

8. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 7, characterized in that: The disaster damage analysis system in step S3 is specifically for the damage analysis system of strong winds: S311, input the wind speed and direction data recorded by the monitoring module, combine the typical roof enclosure structure and road network roadside tree wind load model obtained based on the wind tunnel test, the roof type / coordinates and roadside tree data output by the basic data processing module, and calculate the surface wind load values ​​of the roof and roadside trees at different positions; S312, based on the established wind damage resistance model of the roof enclosure structure and the street trees, and in combination with the roof type / coordinates and street tree data output by the basic data processing module, calculate the resistance values ​​of the roof and street trees at different locations; S313. Compare the relationship between resistance and wind load. When the resistance is less than the wind load, it is considered that the roof / roadside trees are damaged. S314. When the roof enclosure structure is damaged, the wind-induced flying object damage analysis is carried out in combination with the building roof type / coordinates output by the basic data processing module and the geographic elevation information and building outline coordinate information obtained in the basic data processing module to determine the damage data of the building complex and the shelter that are further hit by the wind-induced flying objects; S315, when a roadside tree is damaged, the spatial relationship between the fallen position of the roadside tree and the road is calculated in combination with the basic data of the roadside tree output by the basic data processing module, to determine whether the roadside tree will cause road obstruction, and to calculate the width of the blocked road; S316. Output wind-induced damage data of roof enclosure structures of building complexes, wind-induced missile damage data of building complexes, and road network obstruction width results caused by fallen trees.

9. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 8, characterized in that: The disaster damage analysis system in step S3 is specifically for waterlogging damage analysis system: S317, input the rainfall intensity data recorded by the monitoring module and the geographic elevation information obtained by the basic data processing module, combine the designed drainage capacity of the study area, use the surface runoff analysis model to carry out urban waterlogging simulation, and output the spatiotemporal distribution results of urban waterlogging; S318, combining the road network coordinate information and the building outline coordinate information output by the basic data processing module, identifying communities and road networks where the water depth exceeds the threshold; S319: Output the communities that are unsuitable for living due to excessive waterlogging, as well as the waterlogging depth results for each section of the road network.

10. The system for assessing the loss of urban shelter function under strong wind and flood disasters as claimed in claim 9, characterized in that: The function loss analysis system in step S3 is specifically: S321. Input the severely wind-damaged buildings and communities with deep waterlogging output by the disaster damage analysis system, and estimate the number of households in each building in combination with the building outline coordinate information provided by the basic data processing module, estimate the number of people / coordinates required for post-disaster shelters caused by buildings that are unsuitable for living, determine the buildings of shelters that may be damaged, and update the number of people that can be accommodated in the shelters; S322, inputting the blocked width of the road section, the interrupted road section and the water depth of the road section output by the disaster damage analysis system, combining with the urban road network-shelter function topological network model provided by the basic data processing module, further updating the remaining passable width of the road section in the topological network, removing the interrupted road section and the attenuated passing speed considering the influence of water accumulation; S323. Based on the updated road network-evacuation network, the traffic flow distribution simulation is carried out by taking into account the newly added evacuation demand and the traffic demand of the road network in normal operation before the disaster. S324. Calculate the post-disaster shelter function index Q1 based on the simulation results, which comprehensively considers the functional parameters of the shelter, such as safety, accessibility and the number of people that can be accommodated; take the ratio of Q1 to the pre-disaster shelter function index Q0 as the final shelter function loss index R; R of 1 indicates that there is no function loss in the shelter, and R greater than 1 indicates that there is a function loss in the shelter, and the larger the value, the greater the loss.

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