A method and system for quantitatively evaluating highway sliding risk

Abstract

This invention relates to a method and system for quantitatively assessing highway landslide risk. The method includes acquiring basic parameters and vehicle loads of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff; calculating the highway slope's anti-sliding force, slope sliding force, pavement bearing capacity, and pavement load force based on the basic parameters and vehicle loads; subsequently calculating the slope sliding risk coefficient and pavement collapse risk coefficient; comparing the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; comparing the pavement collapse risk coefficient with the corresponding pavement collapse risk threshold coefficient to obtain the pavement collapse risk level; and evaluating the highway landslide risk based on the slope sliding risk level and pavement collapse risk level. This invention enables the quantitative characterization of slope sliding risk coefficients and pavement collapse risk coefficients, and allows for the evaluation of potential highway landslide risks.

Description

Technical Field

[0001] This invention relates to the field of highway slope safety status evaluation technology, and in particular to a method and system for quantitative evaluation of highway landslide risk. Background Technology

[0002] In recent years, affected by natural disasters and human activities, the frequency of highway slope landslides has been increasing, and these landslides are characterized by their suddenness, unpredictability, and severity. Especially under the combined influence of surface rainfall, rainwater runoff, and bedrock fissure development, landslides often result in significant traffic disruptions, property damage, and casualties. Studies show that highway slope landslides are closely linked to rainfall infiltration, rainwater runoff, bedrock fissure development, and load application. The reduction in slope resistance and pavement bearing capacity creates conditions for landslide formation and is a key factor affecting highway stability.

[0003] Currently, instead of taking measures such as closing roads or reinforcing them, the approach is to directly close roads or reinforce them, rather than conducting a comprehensive assessment of the actual stability of the road after discovering potential landslide hazards. In fact, some roads have a low risk of landslides and can be prevented through monitoring and regular maintenance. Traditional landslide risk management methods, to some extent, waste human and material resources and fail to effectively utilize existing resources for targeted risk management.

[0004] Therefore, it is necessary to research and develop methods for assessing highway landslide risk in order to accurately evaluate landslide risk and provide a reliable basis for highway management decisions. Summary of the Invention

[0005] The purpose of this invention is to supplement the shortcomings of the prior art. This invention aims to provide a method and system for quantitatively evaluating the risk of highway landslides, which can scientifically identify the stability state of highway slopes and realize the quantitative characterization of the possibility of highway landslides.

[0006] A method for quantitatively assessing highway landslide risk, the method comprising: (1) Obtain the basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads; (2). Calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle loads. (3). The slope sliding risk coefficient is calculated based on the slope anti-sliding force and the slope sliding force, and the road surface collapse risk coefficient is calculated based on the road surface bearing capacity and the road surface load force. (4) Compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; compare the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level; (5) Evaluate the risk of highway landslides based on the slope sliding risk level and the road surface collapse risk level.

[0007] In addition to the aspects described above and any possible implementation, a further implementation is provided, wherein the basic parameters include the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, and pore pressure reduction factor of the subgrade soil; the unit weight, thickness, width, internal friction angle, yield strength, static pavement pressure coefficient, and width of the potential sliding surface region of the pavement structure layer; the height of the groundwater level, the seepage length of rainfall infiltration, the hydraulic gradient, and the unit weight of water; the water head, pressure coefficient, infiltration velocity, effective infiltration time, and water pressure coefficient of bedrock fissure water; and the length of the section affected by rainfall confluence and the rainfall confluence area.

[0008] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein step (2) specifically includes: (21) Calculate the anti-sliding force of highway slopes based on the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, pore pressure reduction coefficient, groundwater level, bedrock fissure water head, pressure coefficient, seepage length of rainfall infiltration, hydraulic gradient and unit weight of water. (22). Calculate the sliding force of the highway slope based on the unit weight, height, slope gradient, unit weight, width and thickness of the pavement structure layer, vehicle load, effective infiltration time of bedrock fissure water, infiltration velocity, unit weight of water, rainfall runoff area, length of the section affected by rainfall runoff, and width of the potential sliding surface area. (23). Calculate the bearing capacity of the highway pavement based on the yield strength, thickness, unit weight, internal friction angle, static pavement pressure coefficient, and width of the potential sliding surface area of ​​the pavement structure layer; (24). Calculate the load force on the highway pavement based on the vehicle load, the length of the section affected by rainfall runoff, the width of the pavement structure layer, its unit weight and thickness, the width of the potential sliding surface area, the unit weight of water, the rainfall runoff area, the infiltration velocity of bedrock fissure water and the effective infiltration time. Steps (21)-(24) are performed simultaneously or in no particular order.

[0009] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the slope sliding risk coefficient in step (3) is the ratio of the slope anti-sliding force to the slope sliding force, and the road surface collapse risk coefficient is the ratio of the road surface bearing capacity to the road surface load force.

[0010] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the slope sliding risk threshold coefficient includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient, and the road surface collapse threshold coefficient includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient, specifically including: (41). Calculate the soil redundancy coefficient and soil damage coefficient based on the elastic stage shear strain, plastic stage shear strain and peak shear strain of the subgrade soil in the basic parameters. (42). Calculate the redundancy coefficient and damage coefficient of the pavement structure layer based on the compressive strain of the elastic stage, the compressive strain of the plastic stage and the peak compressive strain of the pavement structure layer in the basic parameters. (43). Set the critical sliding coefficient of the slope as the first threshold coefficient of the slope sliding risk, and multiply the soil redundancy coefficient and the soil damage coefficient by the first threshold coefficient respectively. The resulting products are used as the second threshold coefficient and the third threshold coefficient of the slope sliding risk respectively. (44). Set the critical collapse coefficient of the road surface as the first threshold coefficient of road surface collapse, and multiply the redundancy coefficient of the road surface structure layer and the damage coefficient of the road surface structure layer by the first threshold coefficient respectively. The resulting products are used as the second threshold coefficient and the third threshold coefficient of road surface collapse respectively.

[0011] (41)-(42) and (43)-(44) are performed simultaneously or in no particular order.

[0012] In addition to the aspects described above and any possible implementation, a further implementation is provided, wherein the soil redundancy coefficient is the ratio of the peak shear strain of the subgrade soil to the elastic stage shear strain of the subgrade soil, and the soil damage coefficient is the ratio of the peak shear strain of the subgrade soil to the plastic stage shear strain of the subgrade soil.

[0013] In addition to the aspects described above and any possible implementation, a further implementation is provided in which the pavement structure layer redundancy coefficient is the ratio of the peak compressive strain of the pavement structure layer to the elastic stage of the pavement structure layer, and the pavement structure layer damage coefficient is the ratio of the peak compressive strain of the pavement structure layer to the plastic stage compressive strain of the pavement structure layer.

[0014] In addition to the aspects and any possible implementations described above, a further implementation is provided in which the slope sliding risk coefficient is compared with the corresponding slope sliding risk threshold coefficient in step (4) to obtain the slope sliding risk level, specifically including: If the slope sliding risk coefficient is less than or equal to the first threshold coefficient, the slope sliding is considered to have an extremely high risk; if the slope sliding risk coefficient is greater than the first threshold coefficient and less than or equal to the second threshold coefficient, the slope sliding is considered to have a high risk; if the slope sliding risk coefficient is greater than the second threshold coefficient and less than or equal to the third threshold coefficient, the slope sliding is considered to have a low risk; if the slope sliding risk coefficient is greater than the third threshold coefficient, the slope sliding is considered to have an extremely low risk.

[0015] In addition to the aspects and any possible implementations described above, a further implementation is provided, wherein the comparison of the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient in step (4) to obtain the road collapse risk level specifically includes: if the road collapse risk coefficient is less than or equal to the first road collapse risk threshold coefficient, then the road collapse is considered to have an extremely high risk; if the road collapse risk coefficient is greater than the first road collapse risk threshold coefficient and less than or equal to the second road collapse risk threshold coefficient, then the road collapse is considered to have a high risk; if the road collapse risk coefficient is greater than the second road collapse risk threshold coefficient and less than or equal to the third road collapse risk threshold coefficient, then the road collapse is considered to have a low risk; if the road collapse risk coefficient is greater than the third road collapse risk threshold coefficient, then the road collapse is considered to have an extremely low risk.

[0016] The present invention also provides a quantitative assessment system for highway landslide risk, the system being used to implement the method, comprising: The acquisition module is used to acquire basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads. The first calculation module is used to calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle load. The second calculation module is used to calculate the slope sliding risk coefficient based on the slope anti-sliding force and the slope sliding force, and to calculate the road collapse risk coefficient based on the road surface bearing capacity and the road surface load force. The comparison module is used to compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; and to compare the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level. The evaluation module is used to assess the risk of highway landslides based on the slope sliding risk level and the road surface collapse risk level.

[0017] Beneficial effects Compared with the prior art, the present invention has the following advantages: (1) The slope sliding risk coefficient was quantitatively characterized. Based on the stress characteristics of highway slopes, this invention derives the anti-sliding force and sliding force of highway slopes by considering rainfall infiltration, bedrock fissure water and rainfall runoff, and quantitatively characterizes the slope sliding risk coefficient through engineering measured parameters.

[0018] (2) The road surface collapse risk coefficient was quantitatively characterized. Based on the mechanical properties of highway pavement structure, this invention analyzes the impact of potential sliding surfaces, bedrock fissure water, and rainfall runoff on the pavement. Through engineering measured parameters, it analyzes the bearing capacity and load force of the highway pavement and quantitatively characterizes the pavement collapse risk coefficient.

[0019] (3) The risk level of highway landslides was quantitatively evaluated. This invention proposes to classify risk levels based on the calculation results of two coefficients. By jointly evaluating the slope sliding risk coefficient and the road surface collapse risk coefficient, it provides a method for assessing the potential risk of highway landslides, and provides a basis for guiding the prevention and treatment of highway landslide risks. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the method steps of the present invention; Figure 2 This is a schematic diagram of a highway structure in an embodiment of the present invention. Detailed Implementation

[0022] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0023] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0024] To address the shortcomings of existing technologies, this invention provides a quantitative assessment method for highway landslide risk based on rainfall runoff and fissure water action, which is used to evaluate the potential risks of highway landslides and to provide a basis for the prevention and mitigation of highway landslide risks.

[0025] A method for quantitatively assessing highway landslide risk, the method comprising: (1) Obtain the basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads; (2). Calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle loads. (3). The slope sliding risk coefficient is calculated based on the slope anti-sliding force and the slope sliding force, and the road surface collapse risk coefficient is calculated based on the road surface bearing capacity and the road surface load force. (4) Compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; compare the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level; (5) Evaluate the risk of highway landslides based on the slope sliding risk level and the road surface collapse risk level.

[0026] Furthermore, the basic parameters include the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, and pore pressure reduction factor of the subgrade soil; the unit weight, thickness, width, internal friction angle, yield strength, static pavement pressure coefficient, and width of the potential sliding surface area of ​​the pavement structure layer; the height of the groundwater level, the seepage length of rainfall infiltration, the hydraulic gradient, and the unit weight of water; the water head, pressure coefficient, infiltration velocity, effective infiltration time, and water pressure coefficient of bedrock fissure water; and the length of the section affected by rainfall confluence and the rainfall confluence area.

[0027] Furthermore, step (2) specifically includes: (21) Calculate the anti-sliding force of highway slopes based on the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, pore pressure reduction coefficient, groundwater level, bedrock fissure water head, pressure coefficient, seepage length of rainfall infiltration, hydraulic gradient and unit weight of water. (22). Calculate the sliding force of the highway slope based on the unit weight, height, slope gradient, unit weight, width and thickness of the pavement structure layer, vehicle load, effective infiltration time of bedrock fissure water, infiltration velocity, unit weight of water, rainfall runoff area, length of the section affected by rainfall runoff, and width of the potential sliding surface area. (23). Calculate the bearing capacity of the highway pavement based on the yield strength, thickness, unit weight, internal friction angle, static pavement pressure coefficient, and width of the potential sliding surface area of ​​the pavement structure layer; (24). Calculate the load force on the highway pavement based on the vehicle load, the length of the section affected by rainfall runoff, the width of the pavement structure layer, its unit weight and thickness, the width of the potential sliding surface area, the unit weight of water, the rainfall runoff area, the infiltration velocity of bedrock fissure water and the effective infiltration time. Steps (21)-(24) are performed simultaneously or in no particular order.

[0028] Furthermore, in step (3), the slope sliding risk coefficient is the ratio of the slope anti-sliding force to the slope sliding force, and the road surface collapse risk coefficient is the ratio of the road surface bearing capacity to the road surface load force.

[0029] Furthermore, the slope sliding risk threshold coefficient includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient, and the road surface collapse threshold coefficient also includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient, specifically including: (41). Calculate the soil redundancy coefficient and soil damage coefficient based on the elastic stage shear strain, plastic stage shear strain and peak shear strain of the subgrade soil in the basic parameters. (42). Calculate the redundancy coefficient and damage coefficient of the pavement structure layer based on the compressive strain of the elastic stage, the compressive strain of the plastic stage and the peak compressive strain of the pavement structure layer in the basic parameters. (43). Set the critical sliding coefficient of the slope as the first threshold coefficient of the slope sliding risk, and multiply the soil redundancy coefficient and the soil damage coefficient by the first threshold coefficient respectively. The resulting products are used as the second threshold coefficient and the third threshold coefficient of the slope sliding risk respectively. (44). Set the critical collapse coefficient of the road surface as the first threshold coefficient of road surface collapse, and multiply the redundancy coefficient of the road surface structure layer and the damage coefficient of the road surface structure layer by the first threshold coefficient respectively. The resulting products are used as the second threshold coefficient and the third threshold coefficient of road surface collapse respectively.

[0030] Steps (41)-(42) and (43)-(44) may be performed simultaneously or in no particular order.

[0031] Furthermore, the soil redundancy coefficient is the ratio of the peak shear strain of the subgrade soil to the elastic stage shear strain of the subgrade soil, and the soil damage coefficient is the ratio of the peak shear strain of the subgrade soil to the plastic stage shear strain of the subgrade soil.

[0032] Furthermore, the redundancy coefficient of the pavement structure layer is the ratio of the peak compressive strain of the pavement structure layer to the elastic stage of the pavement structure layer, and the damage coefficient of the pavement structure layer is the ratio of the peak compressive strain of the pavement structure layer to the plastic stage compressive strain of the pavement structure layer.

[0033] Further, step (4) involves comparing the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level, specifically including: If the slope sliding risk coefficient is less than or equal to the first threshold coefficient, the slope sliding is considered to have an extremely high risk; if the slope sliding risk coefficient is greater than the first threshold coefficient and less than or equal to the second threshold coefficient, the slope sliding is considered to have a high risk; if the slope sliding risk coefficient is greater than the second threshold coefficient and less than or equal to the third threshold coefficient, the slope sliding is considered to have a low risk; if the slope sliding risk coefficient is greater than the third threshold coefficient, the slope sliding is considered to have an extremely low risk.

[0034] Further, in step (4), comparing the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level specifically includes: if the road collapse risk coefficient is less than or equal to the first road collapse risk threshold coefficient, then the road collapse is considered to have an extremely high risk; if the road collapse risk coefficient is greater than the first road collapse risk threshold coefficient and less than or equal to the second road collapse risk threshold coefficient, then the road collapse is considered to have a high risk; if the road collapse risk coefficient is greater than the second road collapse risk threshold coefficient and less than or equal to the third road collapse risk threshold coefficient, then the road collapse is considered to have a low risk; if the road collapse risk coefficient is greater than the third road collapse risk threshold coefficient, then the road collapse is considered to have an extremely low risk.

[0035] Specifically, the process of this invention is as follows: like Figure 2 As shown, the highway selected in this invention is a embankment highway in a rainy mountainous area. The highway structure consists of a pavement structure layer and a subgrade soil layer from top to bottom. This section of the road has abundant rainfall and good runoff conditions. There is an upper water catchment area above the highway structure, and rainwater can easily form runoff along the slope and infiltrate into the subgrade soil. Bedrock fissures are well-developed and the fissure water head is high, allowing fissure water to directly infiltrate into the subgrade soil. Bedrock fissures are distributed inside the subgrade soil and are in direct contact with it. The potential sliding surface is an easily slippery interface formed later. Specifically, the infiltration water from the upper water catchment and the bedrock fissure water have a long-term seepage effect on the subgrade soil, resulting in soil particle loss, increased porosity, and a significant reduction in shear strength. As a result, a continuous weak interface, namely the potential sliding surface, is gradually formed inside the subgrade soil. Among them, the upper runoff erodes the slope through surface runoff and the infiltration water weakens the surface soil of the roadbed, while the bedrock fissure water reduces the stability of the deep soil by intruding into the lower soil of the roadbed. The synergistic effect of the two accelerates the development and expansion of the potential sliding surface.

[0036] A quantitative assessment of highway landslide risk based on rainfall runoff and fissure water action is conducted, with the specific steps as follows: Figure 1 As shown, it includes: S1. Obtain basic parameters and vehicle loads for the subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff. Basic subgrade parameters include the unit weight, height, slope gradient, internal friction angle, and cohesion of the subgrade soil. Basic pavement parameters include the unit weight, thickness, width, internal friction angle, yield strength, static pavement pressure coefficient, and width of the potential sliding surface area of ​​each pavement structural layer. Basic rainfall parameters include the groundwater level, pore pressure ratio of the subgrade soil, pore pressure reduction factor, seepage length of rainfall infiltration, hydraulic gradient, and water weight. The basic parameters of bedrock fissure water include bedrock fissure water head, pressure coefficient, infiltration velocity, effective infiltration time, and bedrock fissure water pressure coefficient; the basic parameters of rainfall runoff include the length of the section affected by rainfall runoff and the rainfall runoff area; the unit weight of the subgrade soil and pavement structure layer is obtained by weighing standard core samples obtained by micro-core drilling equipment; the height of the subgrade soil, the slope of the subgrade soil, the width of the pavement structure layer, the length of the section affected by rainfall runoff, the rainfall runoff area, and the vehicle load are obtained through field surveys.

[0037] The unit weight of the subgrade soil and pavement structure layer was obtained by weighing standard core samples obtained from micro-core drilling equipment; the height of the subgrade soil, the slope of the subgrade soil, the width of the pavement structure layer, the length of the section affected by rainfall runoff, the rainfall runoff area, and the vehicle load were obtained through field surveys; the internal friction angle of the subgrade soil, the cohesion of the subgrade soil, and the internal friction angle of the pavement structure layer were obtained through direct shear tests on standard core samples obtained from micro-core drilling equipment; the groundwater level, the bedrock fissure water head, and the hydraulic gradient of rainfall infiltration were obtained through multiple conductivity level gauges; the bedrock fissure water infiltration velocity and the effective infiltration time were obtained through level sensors; and the thickness of the pavement structure layer was determined by the following parameters: The seepage length of rainfall infiltration was obtained using a micro-core drilling rig; the pore pressure ratio of the subgrade soil was obtained through unconsolidated drainage tests on standard core specimens obtained using a micro-core drilling rig; the elastic stage shear strain, plastic stage shear strain, and peak shear strain of the subgrade soil were obtained through direct shear tests on standard core specimens obtained using a micro-core drilling rig; the elastic stage compressive strain, plastic stage compressive strain, peak compressive strain, and yield strength of the pavement structural layer were obtained through unconfined compression tests on standard core specimens obtained using a micro-core drilling rig; and the width of the potential sliding surface region was obtained through non-destructive testing using ground-penetrating radar. The equipment and testing methods used to obtain the above parameters are existing technologies and will not be described in detail in this invention.

[0038] S2. Calculate the anti-sliding force p1 of the highway slope: Based on the unit weight of the subgrade soil, the height of the subgrade soil, the slope gradient of the subgrade soil, the internal friction angle of the subgrade soil, the cohesion of the subgrade soil, the groundwater level, the pore pressure ratio of the subgrade soil, the pore pressure reduction factor, the bedrock fissure water pressure coefficient, the seepage length of rainfall infiltration, the hydraulic gradient of rainfall infiltration, the unit weight of water, and the bedrock fissure water head obtained in step S1, calculate the anti-sliding force of the highway slope. The specific calculation formula is as follows: (1) In the above formula, p1 is the anti-sliding force of the highway slope, and γ s H is the unit weight of the roadbed soil. s β is the height of the subgrade soil, β is the slope of the subgrade soil, φ1 is the internal friction angle of the subgrade soil, and c s H represents the cohesion of the subgrade soil. w R is the height of the groundwater level. w L is the pore pressure ratio of the subgrade soil. w Let G be the seepage length of rainfall infiltration, G be the hydraulic gradient of rainfall infiltration, and H be the infiltration length of rainfall infiltration. f For bedrock fissure water head, γ w The specific gravity of water is taken as 9.81 kN / m³ in this invention. 3 ŋ is the pore pressure reduction factor, which is taken as 0.4 in this invention, K f The bedrock fissure water pressure coefficient is taken as 1 in this invention; where γ s H s , β, φ, c s H w H f L w G and G are known values.

[0039] S3. Calculate the sliding force p2 of the highway slope: Based on the unit weight of the subgrade soil, the height of the subgrade soil, the slope of the subgrade soil, the unit weight of the pavement structure layer, the thickness of the pavement structure layer, the vehicle load, the effective infiltration time of bedrock fissure water, the infiltration velocity of bedrock fissure water, the unit weight of water, the rainfall catchment area, the length of the section affected by rainfall catchment, the width of the pavement structure layer, and the width of the potential sliding surface area obtained in step S1, calculate the sliding force of the highway slope. The specific calculation formula is as follows: (2) In the above formula, p2 is the sliding force of the highway slope, and γ r For the density of the pavement structural layer, B r Q represents the thickness of the pavement structural layer. v For vehicle load, L s W represents the length of the section affected by rainfall runoff. v W is the width of the pavement structure layer. sA is the width of the potential sliding surface region. u v represents the rainfall catchment area. f γ is the infiltration velocity of bedrock fissure water, and T is the effective infiltration time of bedrock fissure water; where γ r B r Q v L s W v W s A u v f T and T are known values.

[0040] S4. Calculate the bearing capacity p3 of the highway pavement: Based on the yield strength, thickness, unit weight, static pavement pressure coefficient, internal friction angle, and width of the potential sliding surface region of the pavement structure layer obtained in step S1, calculate the bearing capacity of the highway pavement. The specific calculation formula is as follows: (3) In the above formula, p3 is used to calculate the bearing capacity of the highway pavement, and σ r φ2 is the yield strength of the pavement structural layer, K is the internal friction angle of the pavement structural layer, and K is the yield strength of the pavement structural layer. r The static road surface pressure coefficient is taken as 0.8 in this invention; where σ r φ2 and φ2 are known values.

[0041] S5. Calculate the load force p4 on the highway pavement: Based on the vehicle load, the length of the section affected by rainfall runoff, the width of the pavement structure layer, the width of the potential sliding surface area, the unit weight of the pavement structure layer, the thickness of the pavement structure layer, the unit weight of water, the rainfall runoff area, the infiltration velocity of bedrock fissure water, and the effective infiltration time of bedrock fissure water obtained in step S1, calculate the load force on the highway pavement. The specific calculation formula is as follows: (4) In the above formula, p4 represents the load force applied by the road surface.

[0042] S6. Calculate the slope sliding risk coefficient R s The specific calculation formula is as follows: (5) In the above formula, R s This represents the slope sliding risk coefficient.

[0043] S7. Calculate the road collapse risk coefficient R c The specific calculation formula is as follows: (6) In the above formula, R c This represents the risk factor for road surface collapse.

[0044] S8. Classification of Landslide Risk Levels: The critical sliding coefficient R0 of the slope is set as the first threshold coefficient. Based on this, a second and third threshold coefficient are set, resulting in a total of three corresponding threshold coefficients. According to the relationship between the slope sliding risk coefficient and these threshold coefficients, the highway slope is sequentially divided into four stages: crack development, plastic deformation, local sliding, and overall landslide. Similarly, the critical collapse coefficient R1 of the pavement is set as the first threshold coefficient. Based on this, a second and third threshold coefficient are set, resulting in a total of three corresponding threshold coefficients. According to the relationship between the pavement collapse risk coefficient and the three threshold coefficients, the highway pavement is sequentially divided into four stages: crack development, plastic deformation, local depression, and overall collapse. R0 and R1 can be determined based on extreme environmental conditions and extreme working condition characteristics.

[0045] The threshold coefficient for slope sliding risk is calculated as follows: The soil redundancy coefficient a1 is expressed as: (7) In the above formula, S3 is the peak shear strain of the subgrade soil, and S1 is the elastic stage shear strain of the subgrade soil.

[0046] The soil damage coefficient a2 can be expressed as: (8) In the above formula, S2 is the plastic stage shear strain of the subgrade soil.

[0047] The shear strain of the subgrade soil follows a progressive evolution law of "elastic-plastic-peak". The elastic stage shear strain corresponds to the critical state of reversible deformation of particles; the plastic stage shear strain corresponds to the critical state of irreversible deformation with particle slippage and microcrack initiation; and the peak stage is the ultimate strain before complete structural failure. Its strain level increases exponentially with each stage, and the corresponding shear strain satisfies... Furthermore, the difference between each stage is greater than 1. Combining formulas (7) and (8), it can be deduced that... .

[0048] The threshold coefficient for road surface collapse risk is calculated as follows: The redundancy coefficient a3 of the pavement structure layer can be expressed as: (9) In the above formula, S6 is the peak compressive strain of the pavement structure layer, and S4 is the compressive strain of the pavement structure layer in the elastic stage.

[0049] The damage coefficient a4 of the pavement structure layer can be expressed as: (10) In the above formula, S5 represents the compressive strain of the pavement structure layer during the plastic stage.

[0050] The compressive strain of the pavement structural layer follows a progressive evolution law of "elastic-plastic-peak". The elastic stage compressive strain corresponds to the critical state of reversible deformation of particles; the plastic stage compressive strain corresponds to the critical state of irreversible deformation with particle slippage and microcrack initiation; and the peak stage is the ultimate compressive strain before complete structural failure. Its strain level increases exponentially with each stage, corresponding to a shear strain that satisfies... Furthermore, the difference between each stage is greater than 1. Combining formulas (9) and (10), it can be deduced that... .

[0051] Based on the four stages (cracking, deformation, movement, and sliding) and three threshold values ​​of highway slopes, the landslide risk level is classified as follows: Grade A risk is extremely high risk. That is, the slope sliding risk coefficient is less than or equal to the first threshold coefficient. ; Category B risk is high risk: That is, the slope sliding risk coefficient is greater than the first threshold coefficient. And less than or equal to the second threshold coefficient ; Level C risk means low risk: This means the slope sliding risk coefficient is greater than the second threshold coefficient. And less than or equal to the third threshold coefficient ; Level D risk means extremely low risk: That is, the slope sliding risk coefficient is less than the third threshold coefficient. ; Furthermore, the risk levels for road surface collapse are classified as follows: Grade A risk is extremely high risk. That is, the road surface collapse risk coefficient is less than or equal to the first threshold coefficient. ; Category B risk is high risk: This means the road surface collapse risk coefficient is greater than the first threshold coefficient. And less than the second threshold coefficient ; Level C risk means low risk: That is, the road surface collapse risk coefficient is greater than the second threshold coefficient. And less than the third threshold coefficient ; Level D risk means extremely low risk: That is, the road surface collapse risk coefficient is greater than the third threshold coefficient. ; S9. According to Rs and R c The calculated value is used to determine the level of highway landslide risk. The overall highway landslide risk level is jointly determined by the slope sliding risk level and the road surface collapse risk level according to the "highest risk level priority principle", that is, the higher risk level of the two is selected as the overall highway landslide risk level; if the two risk levels are the same, the overall highway landslide risk is directly identified as that same level.

[0052] S10. Evaluation of Highway Landslide Risk Level and Remedial Measures: When the slope landslide risk level is A, the highway slope has an extremely high probability of landslide. In this case, high-intensity slope reinforcement work must be initiated immediately to ensure safety and prevent disasters. When the slope landslide risk level is B, the highway slope has a relatively high probability of landslide. In this case, preventative slope reinforcement work must be initiated to ensure slope stability. When the slope landslide risk level is C, the highway slope has a low probability of landslide, and its safety should be ensured through regular inspections and periodic slope reinforcement work. When the slope landslide risk level is D, the highway slope has an extremely low probability of landslide, and routine inspections and periodic assessments are sufficient to ensure the long-term normal condition of the slope. When the road surface collapse risk level is A, the road surface has an extremely high probability of collapse. In this case, the affected road section must be immediately closed, and emergency road repair work must be initiated simultaneously. When the road surface collapse risk level is B, the road surface has a relatively high probability of collapse. In this case, traffic control should be implemented on the affected road surface, and existing micro-cracks should be sealed with crack sealant. Areas with high roadbed moisture content should be reinforced with grouting. When the road surface collapse risk level is C, the road surface has a low probability of collapse, and its safety should be ensured through regular road surface inspections and maintenance. When the road surface collapse risk level is D, the road surface has an extremely low probability of collapse, and routine road surface inspections and maintenance are sufficient to ensure the long-term normal condition of the slope.

[0053] As an embodiment of the present invention, the present invention also provides a quantitative assessment system for highway landslide risk, the system being used to implement the method, comprising: The acquisition module is used to acquire basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads. The first calculation module is used to calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle load. The second calculation module is used to calculate the slope sliding risk coefficient based on the slope anti-sliding force and the slope sliding force, and to calculate the road collapse risk coefficient based on the road surface bearing capacity and the road surface load force. The comparison module is used to compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; and to compare the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level. The evaluation module is used to assess the risk of highway landslides based on the slope sliding risk level and the road surface collapse risk level.

[0054] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be applied to various other embodiments within the present invention. Modifications made within the scope of the aforementioned concepts, based on the teachings or techniques and knowledge in related fields, are permitted. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of this invention should be considered within the protection scope of the appended claims.

Claims

1. A method for quantitatively assessing highway landslide risk, characterized in that, The method includes the following steps: (1) Obtain the basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads; (2). Calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle loads. (3). The slope sliding risk coefficient is calculated based on the slope anti-sliding force and the slope sliding force, and the road surface collapse risk coefficient is calculated based on the road surface bearing capacity and the road surface load force. (4) Compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; The road collapse risk coefficient is compared with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level; (5) Evaluate the risk of highway landslides based on the risk levels of slope sliding and road surface collapse.

2. The method according to claim 1, characterized in that, The basic parameters include the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, and pore pressure reduction factor of the subgrade soil; the unit weight, thickness, width, internal friction angle, yield strength, static pavement pressure coefficient, and width of the potential sliding surface area of ​​the pavement structure layer; the height of the groundwater level, the seepage length of rainfall infiltration, the hydraulic gradient, and the unit weight of water; the water head, pressure coefficient, infiltration velocity, effective infiltration time, and water pressure coefficient of bedrock fissure water; and the length of the section affected by rainfall confluence and the rainfall confluence area.

3. The method according to claim 2, characterized in that, Step (2) specifically includes: (21) Calculate the anti-sliding force of highway slopes based on the unit weight, height, slope gradient, internal friction angle, cohesion, pore pressure ratio, pore pressure reduction coefficient, groundwater level, bedrock fissure water head, pressure coefficient, seepage length of rainfall infiltration, hydraulic gradient and unit weight of water. (22). Calculate the sliding force of the highway slope based on the unit weight, height, slope gradient, unit weight, width and thickness of the pavement structure layer, vehicle load, effective infiltration time of bedrock fissure water, infiltration velocity, unit weight of water, rainfall runoff area, length of the section affected by rainfall runoff, and width of the potential sliding surface area. (23). Calculate the bearing capacity of the highway pavement based on the yield strength, thickness, unit weight, internal friction angle, static pavement pressure coefficient, and width of the potential sliding surface area of ​​the pavement structure layer; (24). Calculate the load force on the highway pavement based on the vehicle load, the length of the section affected by rainfall runoff, the width of the pavement structure layer, its unit weight and thickness, the width of the potential sliding surface area, the unit weight of water, the rainfall runoff area, the infiltration velocity of bedrock fissure water and the effective infiltration time. Steps (21)-(24) are calculated simultaneously or in no particular order.

4. The method according to claim 1, characterized in that, In step (3), the slope sliding risk coefficient is the ratio of the slope anti-sliding force to the slope sliding force, and the road surface collapse risk coefficient is the ratio of the road surface bearing capacity to the road surface load.

5. The method according to claim 1, characterized in that, The slope sliding risk threshold coefficient includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient; the road surface collapse threshold coefficient also includes a first threshold coefficient, a second threshold coefficient, and a third threshold coefficient, specifically including: (41). Calculate the soil redundancy coefficient and soil damage coefficient based on the elastic stage shear strain, plastic stage shear strain and peak shear strain of the subgrade soil in the basic parameters. (42). Calculate the redundancy coefficient and damage coefficient of the pavement structure layer based on the compressive strain of the elastic stage, the compressive strain of the plastic stage and the peak compressive strain of the pavement structure layer in the basic parameters. (43). Set the critical sliding coefficient of the slope as the first threshold coefficient of the slope sliding risk, and multiply the soil redundancy coefficient and the soil damage coefficient by the first threshold coefficient respectively. The resulting products are used as the second threshold coefficient and the third threshold coefficient of the slope sliding risk respectively. (44). Set the critical collapse coefficient of the road surface as the first threshold coefficient for road surface collapse. Multiply the redundancy coefficient and damage coefficient of the road surface structure layer by the first threshold coefficient, respectively. The resulting products are used as the second and third threshold coefficients for road surface collapse, respectively. (41)-(42) and (43)-(44) are performed simultaneously or in no particular order.

6. The method according to claim 5, characterized in that, The soil redundancy coefficient is the ratio of the peak shear strain of the subgrade soil to the elastic stage shear strain of the subgrade soil, and the soil damage coefficient is the ratio of the peak shear strain of the subgrade soil to the plastic stage shear strain of the subgrade soil.

7. The method according to claim 5, characterized in that, The redundancy coefficient of the pavement structure layer is the ratio of the peak compressive strain of the pavement structure layer to the elastic stage of the pavement structure layer, and the damage coefficient of the pavement structure layer is the ratio of the peak compressive strain of the pavement structure layer to the plastic stage compressive strain of the pavement structure layer.

8. The method according to claim 5, characterized in that, Step (4) involves comparing the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level. Specifically, this includes: If the slope sliding risk coefficient is less than or equal to the first threshold coefficient, the slope sliding is considered to have an extremely high risk; if the slope sliding risk coefficient is greater than the first threshold coefficient and less than or equal to the second threshold coefficient, the slope sliding is considered to have a high risk; if the slope sliding risk coefficient is greater than the second threshold coefficient and less than or equal to the third threshold coefficient, the slope sliding is considered to have a low risk; if the slope sliding risk coefficient is greater than the third threshold coefficient, the slope sliding is considered to have an extremely low risk.

9. The method according to claim 5, characterized in that, Step (4) involves comparing the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level. Specifically, this includes: if the road collapse risk coefficient is less than or equal to the first road collapse risk threshold coefficient, then the road collapse is considered to have an extremely high risk; if the road collapse risk coefficient is greater than the first road collapse risk threshold coefficient and less than or equal to the second road collapse risk threshold coefficient, then the road collapse is considered to have a high risk; if the road collapse risk coefficient is greater than the second road collapse risk threshold coefficient and less than or equal to the third road collapse risk threshold coefficient, then the road collapse is considered to have a low risk; and if the road collapse risk coefficient is greater than the third road collapse risk threshold coefficient, then the road collapse is considered to have an extremely low risk.

10. A quantitative assessment system for highway landslide risk, characterized in that, The system is used to implement the method according to any one of claims 1-9, comprising: The acquisition module is used to acquire basic parameters of the selected highway's subgrade, pavement, rainfall, bedrock fissure water, and rainfall runoff, as well as vehicle loads. The first calculation module is used to calculate the anti-skid force of the highway slope, the sliding force of the highway slope, the bearing capacity of the highway pavement, and the load force of the highway pavement based on the basic parameters and vehicle load. The second calculation module is used to calculate the slope sliding risk coefficient based on the slope anti-sliding force and the slope sliding force, and to calculate the road collapse risk coefficient based on the road surface bearing capacity and the road surface load force. The comparison module is used to compare the slope sliding risk coefficient with the corresponding slope sliding risk threshold coefficient to obtain the slope sliding risk level; and to compare the road collapse risk coefficient with the corresponding road collapse risk threshold coefficient to obtain the road collapse risk level. The evaluation module is used to assess the risk of highway landslides based on the slope sliding risk level and the road surface collapse risk level.

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