Urban road collapse risk calculation method under extreme flood condition

Abstract

The invention discloses an urban road collapse risk calculation method under an extreme flood condition, and the method comprises the following steps: S1, determining the damage condition of an underground structure, and determining the simulation parameters of a road, a soil body, underground water and a flood scene; s2, establishing a three-dimensional road structure model based on DEM-CFD bidirectional coupling according to the road structure and the particle flow microscopic parameters and hydrodynamic parameters of the soil body, and simulating a cavity development process caused by a damaged underground structure under a long-time extreme flood condition; and S3, according to the simulation result, applying a dynamic vehicle load and an FWD load, and evaluating the road collapse risk and traffic capacity. The method simulates the interaction of the road structure and the underground structure under the whole flood process, can recognize the potential collapse risk of the urban road under the flood condition, evaluates the traffic capacity of the urban road after flood, improves the safety of the urban road, can more accurately give the traffic control opinion of the urban road after flood disaster, and improves the traffic control effect of the urban road after flood disaster. And a certain reference is provided for post-disaster road traffic management and repair.

Description

Technical Field

[0001] The invention belongs to the technical field of urban road disaster assessment, and in particular relates to a method for calculating the risk of urban road collapse under extreme flood conditions. Background Art

[0002] Actively preventing and resisting climate risks and improving the ability to adapt to climate change have become a global consensus today. my country has a vast territory and a wide range of climates. It faces severe urban flood risks, and extreme heavy rainfall seriously affects social economy and personnel safety. Therefore, in order to control urban casualties and economic losses caused by flood disasters, and to ensure emergency rescue during disasters and rapid recovery of traffic after disasters, it is necessary to analyze the risk of urban road collapse under extreme flood conditions.

[0003] At present, more and more researchers are using DEM models to simulate road collapse: Patent CN117422006A provides a road collapse disaster simulation method based on the joint algorithm of CFD-DEM and FEM, establishes a bidirectional coupled particle flow and flow field model, simulates the soil settlement process around the damaged pipe, and then applies loads in the FEM module to calculate the plastic damage of the soil; Patent CN113569312A provides a method for evaluating the safety margin of empty roads in urban underground construction scenarios, simulates the development process of voids under underground construction vibration, determines the critical safety distance and the actual bearing capacity of the road under the disaster state, and calculates the safety margin of empty roads. The above patents are respectively aimed at the scenes of broken pipe leakage and underground engineering construction, lacking consideration of the cause of collapse caused by seepage under long-term waterlogging conditions under flood conditions, and the model lacks the influence of road cross sections on seepage, and the accuracy of road collapse simulation needs to be improved. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a method for calculating the risk of urban road collapse under extreme flood conditions to address the deficiencies in the prior art.

[0005] In order to achieve the above object, the present invention is achieved through the following technical solutions:

[0006] A method for calculating the risk of urban road collapse under extreme flood conditions is provided, which includes the following steps:

[0007] S1. Determine the damage of underground structures and the simulation parameters of roads, soil, groundwater and flooding scenarios;

[0008] S2. According to the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil, a three-dimensional road structure model based on DEM-CFD bidirectional coupling was established to simulate the cavity development process caused by damaged underground structures under long-term extreme flood conditions;

[0009] S3. Based on the simulation results, dynamic vehicle loads and FWD loads are applied to evaluate the road collapse risk and traffic capacity.

[0010] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the specific process of determining the damage of underground structures in step S1 includes: scanning the structural damage of air-raid shelters and wells within the road red line range, determining the relative position of the damaged structure and the road, and obtaining the position and size of the leakage point on the damaged structure.

[0011] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the specific process of determining the road and soil simulation parameters in step S1 includes: determining the road structure and soil distribution based on design data, obtaining the macro material properties of the road and soil, and calculating the micro parameters of the three-dimensional DEM particle flow model and the fluid dynamics parameters of the CFD model.

[0012] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the specific process of determining the simulation parameters of groundwater and flood scenarios in step S1 includes: obtaining the water level changes and groundwater level rise during the flood inundation process, and determining the groundwater level, water head height changes and duration during road structure simulation.

[0013] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, in which the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil in step S2 include particle diameter range, damping, density, friction coefficient, contact model type, contact model parameters, permeability coefficient and matrix suction; the three-dimensional road structure model includes the structure of the entire road cross-section within the road red line, specifically including the central dividing strip, motor vehicle lane, motor and non-motor vehicle dividing strip, non-motor vehicle lane, green belt and sidewalk.

[0014] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the specific process of establishing a three-dimensional road structure model based on DEM-CFD bidirectional coupling in step S2 includes:

[0015] S2.1, DEM part establishes the particle flow geometric model of road structure and soil;

[0016] S2.2, CFD part establishes the unsaturated flow field model of road structure and soil, sets the pore water pressure at the groundwater level to 0, and applies the time-varying water head as a long-term flood simulation;

[0017] S2.3. The DEM model and CFD model are bidirectionally coupled to simulate the development process of underground cavities caused by damaged underground structures under long-term extreme flood conditions.

[0018] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the water head of the CFD model in step S2.2 is applied to the permeable road structure and the central dividing strip, the non-vehicle dividing strip, and the green belt. The simulation process of the CFD model includes the entire process of the flood, specifically including the process of gradual increase in the water head on the road surface when the flood occurs, the process of maintaining the water head during the flood, and the process of decreasing the water head when the flood recedes.

[0019] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, a three-dimensional DEM particle flow model is established using PFC3D software, and a three-dimensional CFD model is established by calling the FIPY data package of python using the built-in module of PFC3D software.

[0020] As described above, in the method for calculating the risk of urban road collapse under extreme flood conditions, the specific process of applying dynamic vehicle load and FWD load in step S3 to evaluate the risk of road collapse and traffic capacity includes:

[0021] S3.1. Based on the particle flow model after the flood recedes, apply dynamic loads of vehicles with different axle loads to different lanes to determine the vehicle axle load range and speed that the road structure can bear;

[0022] S3.2. According to the particle flow model after the flood recedes, the application of the falling weight deflectometer (FWD) load is simulated to obtain the road deflection;

[0023] S3.3. Using the development of cavities under vehicle dynamic loads, deformation and damage of road structures, and FWD deflection as indicators, comprehensively assess the risk of road collapse and determine the road capacity.

[0024] As described in the method for calculating the risk of urban road collapse under extreme flood conditions, the FISH language is used to apply vehicle dynamic loads and falling weight deflectometer (FWD) loads to different lanes.

[0025] The beneficial effects of the technical solution of the present invention are:

[0026] 1. The present invention simulates the interaction between the road structure and the underground structure under the whole process of flooding, can identify the potential collapse risk of urban roads under flooding conditions, evaluate the traffic capacity of urban roads after flooding, identify the potential collapse risk in advance, and improve the safety of urban roads;

[0027] 2. The present invention effectively improves the accuracy of urban road collapse simulation by establishing a DEM-CFD bidirectional coupling three-dimensional simulation model of the entire road cross section;

[0028] 3. The present invention proposes indicators for assessing the risk of urban road collapse, which can more accurately provide suggestions for urban road traffic control after floods and provide a certain reference for post-disaster road traffic management and repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] To further illustrate the above-mentioned objectives, structural features and effects of the present invention, the present invention will be described in detail below with reference to the accompanying drawings.

[0030] Figure 1 This is a flow chart of a method for calculating the risk of urban road collapse under extreme flood conditions in a preferred embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of underground cavities caused by underground structure damage in a preferred embodiment of the present invention;

[0032] In the figure: 1. Road structure; 2. Green belt; 3. Sidewalk; 4. Soil; 5. Underground structure; 6. Damaged points; 7. Underground cavities; 8. Infiltration of flood water. DETAILED DESCRIPTION

[0033] The terms "invention", "present invention" and "the present invention" used in this specification are intended to refer broadly to all subject matter of this specification and any patent claims below. Statements containing these terms should not be understood to limit the subject matter described herein or to limit the meaning or scope of any patent claim below. In addition, this specification does not attempt to describe or limit the subject matter covered by any claim of any specific component, paragraph, statement or figure of this application. The subject matter should be understood with reference to the entire specification, all drawings and any claims below. The present invention may have other embodiments and be practiced or implemented in other ways. Moreover, it should be understood that the words and terms used herein are for illustrative purposes and should not be considered as limiting.

[0034] The details of the present invention will now be discussed with reference to the accompanying drawings which illustrate the present invention by way of example only. In the accompanying drawings, similar features or components may be marked with the same reference numerals.

[0035] The use of "including," "having," and "comprising" and variations thereof herein is meant to encompass the items listed thereafter and their equivalents and additional items. Although reference may be made to directions such as above, below, upward, downward, rearward, bottom, top, front, rear, etc., in describing the drawings, for convenience, reference is made relative to the drawings. These directions are not intended to literally accept or limit the present invention in any form. In addition, terms such as "first," "second," "third," etc., are used herein for illustrative purposes and are not intended to indicate or imply importance or significance.

[0036] See also Figure 1As shown, in a preferred embodiment, the method for calculating the risk of urban road collapse under extreme flood conditions of the present invention includes the following steps:

[0037] S1. Determine the damage of underground structures and determine the simulation parameters of roads, soil, groundwater and flood scenarios. The specific process of determining the damage of underground structures includes: scanning the structural damage of air-raid shelters and wells within the red line of the road, determining the relative position of the damaged structure and the road, and obtaining the location and size of the leakage point on the damaged structure.

[0038] The specific process of determining the simulation parameters of roads and soil includes: determining the road structure and soil distribution according to the design data, obtaining the macro material properties of the road and soil, and calculating the micro parameters of the three-dimensional DEM particle flow model and the fluid dynamics parameters of the CFD model.

[0039] The specific process of determining the simulation parameters of groundwater and flood scenarios includes: obtaining the water level changes and groundwater level rise during the flood inundation process, and determining the groundwater level, head height changes and duration during road structure simulation.

[0040] S2. According to the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil, a three-dimensional road structure model based on DEM-CFD bidirectional coupling was established to simulate the cavity development process caused by damaged underground structures under long-term extreme flood conditions.

[0041] The particle flow microscopic parameters and fluid dynamic parameters of road structure and soil include particle diameter range, damping, density, friction coefficient, contact model type, contact model parameters, permeability coefficient and matrix suction.

[0042] The three-dimensional road structure model based on DEM-CFD bidirectional coupling includes the structure of the entire road cross-section within the road red line, including the central dividing strip, motor vehicle lane, motor vehicle and non-motor vehicle dividing strip, non-motor vehicle lane, green belt and sidewalk.

[0043] The specific process of establishing a three-dimensional road structure model based on DEM-CFD bidirectional coupling includes:

[0044] S2.1, DEM part establishes the particle flow geometric model of road structure and soil.

[0045] S2.2, CFD part establishes the unsaturated flow field model of road structure and soil, sets the groundwater level as pore water pressure level 0, and applies the water head that changes with time as a long-term flood simulation. The water head of the CFD model is applied to the permeable road structure and the central dividing strip, the non-vehicle dividing strip, and the green belt. The simulation process of the CFD model includes the whole process of flood occurrence, including the process of gradual increase of water head on the road surface when flood occurs, the process of maintaining water head during flood inundation, and the process of water head decrease when flood recedes.

[0046] S2.3. The DEM model and CFD model are bidirectionally coupled to simulate the development process of underground cavities caused by damaged underground structures under long-term extreme flood conditions.

[0047] S3. Based on the simulation results, dynamic vehicle load and FWD load are applied to evaluate the road collapse risk and traffic capacity. The specific process includes:

[0048] S3.1. Based on the particle flow model after the flood recedes, apply dynamic loads of vehicles with different axle loads to different lanes to determine the vehicle axle load range and speed that the road structure can bear;

[0049] S3.2. According to the particle flow model after the flood recedes, the application of the falling weight deflectometer (FWD) load is simulated to obtain the road deflection;

[0050] S3.3. Using the development of cavities under vehicle dynamic loads, deformation and damage of road structures, and FWD deflection as indicators, comprehensively assess the risk of road collapse and determine the road capacity.

[0051] Traffic capacity includes available lanes and the axle load and speed of vehicles.

[0052] See also Figure 2 As shown, a specific embodiment is further described:

[0053] 1. Determine the damage of underground structures and simulation parameters.

[0054] This embodiment uses a scenario in which there is a damaged air-raid shelter under the road for calculation. The road adopts a secondary road cross-section: 2m sidewalk 3+2.5m green belt 2+15m motor vehicle lane+2.5m green belt 2+2m sidewalk 3. The soil 4 is clay. The damaged position is 3m underground 2m away from the edge of the motor vehicle lane. The groundwater level is 2m underground. In the flood scenario, the water depth increases linearly to 1m within 12 hours, and the water depth is maintained for 60 hours and then decreases linearly to 0 within 12 hours.

[0055] 2. Simulate the cavity development process caused by damaged underground structures under long-term extreme flood conditions.

[0056] According to the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil, a three-dimensional road structure model based on DEM-CFD bidirectional coupling is established, as follows:

[0057] The three-dimensional DEM particle flow model was established using PFC3D software. Since the number of particles in the full-scale particle flow model is too large, which can reach tens of millions, this embodiment uses a similarity ratio of 10 to establish a scaled particle flow model, that is, the size is 1 / 10, the gravity acceleration is 10g, and the permeability coefficient is 10 times. The soil particle flow model with a porosity of 0.38 was established by the layered compaction method. The upper surface is a free boundary, and a crack with a width of 5 times the average particle diameter is set on the lower surface as a representation of the damaged underground structure. The other interfaces are all walls.

[0058] The built-in module of PFC3D software was used to call the FIPY data package of Python to establish a three-dimensional CFD model. The model size corresponded to the granular flow model. First, the steady-state seepage field without applied water head was calculated. Then, the time-varying water head was applied to the green belt, and the flow field at different positions of the road cross section was calculated. The control equation was based on Darcy's law.

[0059] The DEM model and the CFD model are bidirectionally coupled, and the particle flow model exchanges data with the CFD model every 100 calculations, using fluid drag as the coupling link. During the model simulation, under the action of long-term flood seepage, the damage to the underground structure gradually develops and gradually expands under the pavement structure.

[0060] 3. Assess road collapse risk and traffic capacity.

[0061] Obtain the model state after the flood recedes, replace the rigid road structure with a road structure composed of granular flow, cancel the coupling callback with the CFD module, balance the stress of the model, and eliminate the unbalanced force.

[0062] The FISH language is used to apply vehicle dynamic loads to different lanes. The vehicle load tire pressure is 0.7Mpa, the axle load adopts the standard axle load of 100kn and the load coefficient is 0.5-1.5. The development of voids under dynamic loads and the damage of road structure 1 are used as the basis for judging the risk of road collapse. The range of vehicle axle loads and speeds that the lanes can bear are determined based on the criteria that underground voids 7 do not continue to develop and road structure 1 does not damage under dynamic loads.

[0063] Use FISH language to apply falling weight deflectometer (FWD) loads to different lanes to obtain the corresponding road deflection. According to the road design data, determine whether the deflection meets the design requirements. If the lane deflection does not meet the design standards, the structural strength of the lane is severely damaged and cannot be used for traffic.

[0064] The above are only preferred embodiments of the present invention, and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating the risk of urban road collapse under extreme flood conditions, characterized in that: The following steps are involved: S1. Determine the damage of underground structures and the simulation parameters of roads, soil, groundwater and flooding scenarios; S2. According to the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil, a three-dimensional road structure model based on DEM-CFD bidirectional coupling was established to simulate the cavity development process caused by damaged underground structures under long-term extreme flood conditions; S3. Based on the simulation results, dynamic vehicle loads and FWD loads are applied to evaluate the road collapse risk and traffic capacity.

2. The urban road collapse risk calculation method under extreme flood conditions as claimed in claim 1, characterized in that: The specific process of determining the damage of the underground structure in step S1 includes: scanning the structural damage of the air-raid shelter and the well within the road red line, determining the relative position of the damaged structure and the road, and obtaining the position and size of the leakage point on the damaged structure.

3. The urban road collapse risk calculation method under extreme flood conditions as claimed in claim 1 is characterized in that: The specific process of determining the simulation parameters of the road and soil in step S1 includes: determining the road structure and soil distribution according to the design data, obtaining the macro material properties of the road and soil, and calculating the micro parameters of the three-dimensional DEM particle flow model and the fluid dynamics parameters of the CFD model.

4. The method for calculating the risk of urban road collapse under extreme flood conditions as claimed in claim 1, characterized in that: The specific process of determining the simulation parameters of groundwater and flood scenarios in step S1 includes: obtaining the water level change and groundwater level rise during the flood inundation process, and determining the groundwater level, water head height change and duration during road structure simulation.

5. The method for calculating the risk of urban road collapse under extreme flood conditions as claimed in claim 1, characterized in that: In step S2, the particle flow microscopic parameters and fluid dynamics parameters of the road structure and soil include particle diameter range, damping, density, friction coefficient, contact model type, contact model parameters, permeability coefficient and matrix suction; the three-dimensional road structure model includes the structure of the entire road cross section within the road red line, specifically including the central dividing strip, motor vehicle lane, motor and non-motor vehicle dividing strip, non-motor vehicle lane, green belt and sidewalk.

6. The urban road collapse risk calculation method under extreme flood conditions as claimed in claim 1, characterized in that: The specific process of establishing the three-dimensional road structure model based on DEM-CFD bidirectional coupling in step S2 includes: S2.1, DEM part establishes the particle flow geometric model of road structure and soil; S2.2, CFD part establishes the unsaturated flow field model of road structure and soil, sets the pore water pressure at the groundwater level to 0, and applies the time-varying water head as a long-term flood simulation; S2.

3. The DEM model and CFD model are bidirectionally coupled to simulate the development process of underground cavities caused by damaged underground structures under long-term extreme flood conditions.

7. The method for calculating the risk of urban road collapse under extreme flood conditions as claimed in claim 6, characterized in that: The water head of the CFD model in step S2.2 is applied to the permeable road structure and the central dividing strip, the non-vehicle dividing strip, and the green belt. The simulation process of the CFD model includes the entire process of flood occurrence, specifically including the process of gradual increase in road surface water head when flood occurs, the process of maintaining water head during flood inundation, and the process of water head decrease when the flood recedes.

8. The method for calculating the risk of urban road collapse under extreme flood conditions as claimed in claim 6, characterized in that: The three-dimensional DEM particle flow model was established using PFC3D software, and the three-dimensional CFD model was established by calling the FIPY data package of Python using the built-in module of PFC3D software.

9. The method for calculating the risk of urban road collapse under extreme flood conditions as claimed in claim 1, characterized in that: The specific process of applying dynamic vehicle load and FWD load in step S3 to evaluate the road collapse risk and traffic capacity includes: S3.

1. Based on the particle flow model after the flood recedes, apply dynamic loads of vehicles with different axle loads to different lanes to determine the vehicle axle load range and speed that the road structure can bear; S3.

2. According to the particle flow model after the flood recedes, the application of the falling weight deflectometer (FWD) load is simulated to obtain the road deflection; S3.

3. Using the development of cavities under vehicle dynamic loads, deformation and damage of road structures, and FWD deflection as indicators, comprehensively assess the risk of road collapse and determine the road capacity.

10. The urban road collapse risk calculation method under extreme flood conditions as claimed in claim 9, characterized in that: The FISH language is used to apply vehicle dynamic loads and falling weight deflectometer (FWD) loads to different lanes.

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