A method for analyzing interaction between slope and engineering structure considering pfc entrainment effect

Abstract

This invention presents a slope-engineering structure interaction analysis method considering the PFC (Polymerization Factor Collective) entrainment effect. Using discrete element method (DEM) software, the contact effect between particles can better represent the entrainment effect of the sliding mass during its sliding process. Through on-site investigation, the boundaries of the landslide source area and flow zone are planned using ArcGIS software. Particles are generated in both the landslide source area and flow zone to represent the surface soil. Damping effects are added between particles in both areas, and friction is added between the particles in the landslide source area and flow zone and the sliding bed, thereby simulating a realistic sliding effect. The contact effect between the sliding mass particles and the flow zone particles in the simulation is consistent with actual conditions. By considering the entrainment effect, the interaction between the sliding mass and the flow zone material can be simulated more comprehensively, making the simulation results of the sliding process closer to reality. The resulting motion characteristics are more accurate, enhancing the realism of the simulation results.

Description

Technical Field

[0001] This invention relates to the field of engineering geology research, and specifically to a method for analyzing the interaction between slopes and engineering structures that considers the PFC entrainment effect. Background Technology

[0002] Slope instability is a significant problem in engineering geology, especially in complex terrain environments, where it can pose serious threats to infrastructure, transportation facilities, and the safety of life and property. With the increasing frequency of extreme weather events, particularly torrential rains and prolonged periods of continuous rainfall, the risk of slope instability has significantly increased, leading to more severe impacts from landslides and collapses on underlying structures and transportation facilities. After slope instability, the kinetic energy carried by the sliding mass not only affects the surrounding environment but also causes significant impact and damage to the underlying structures. Therefore, studying the interaction between slope instability and engineering structures has important practical significance.

[0003] Currently, research on the interaction between slope instability and engineering structures mainly focuses on the basic analysis of slope stability and the dynamic process of landslides. However, many traditional research methods have failed to fully consider the complex interaction between the sliding mass and the underlying structures and infrastructure after slope instability. Furthermore, they have failed to account for the entrainment effect during the sliding process in slope instability simulations. The entrainment effect refers to the entrainment of the sliding mass with surrounding objects during its descent after slope instability, leading to an increase in the kinetic energy of the sliding mass and consequently a stronger impact on the underlying structure. For example, Ming Chengtao et al. (Ming Chengtao et al., Research on the Kinematic Characteristics of Landslides in the Three Gorges Reservoir Area Based on Massflow) studied the kinematic characteristics of landslides in the Three Gorges Reservoir area using the deep integral continuum theory model (Massflow), simulating the dynamic process after landslide instability, but did not consider the entrainment effect during the sliding process. Zhang Yaoming et al. (Zhang Yaoming et al., A method for quantitatively predicting the disaster-causing range of landslides) used DAN3D software to numerically simulate potential landslide hazard points, but the entrainment effect during the sliding process was not included in the model. Xu Yuanhua et al. (Xu Yuanhua et al., Stability analysis and treatment research of complex accumulation bodies based on FLAC3D—taking the accumulation body of Bailong Bridge on Duyun-Anshun Expressway in Guizhou as an example) used FLAC3D software to study the accumulation body of Bailong Bridge on Duyun-Anshun Expressway in Guizhou, analyzed the deformation and failure mechanism and stability of complex accumulation bodies, and proposed corresponding treatment schemes, but did not consider the entrainment effect during the sliding process and its impact on the substructure.

[0004] In recent years, particle fluid dynamics (PFC), as a discrete element numerical simulation method, has demonstrated significant advantages in simulating the dynamic behavior and interparticle interactions of particulate matter. PFC can simulate the collision, friction, and motion behavior between particles in a sliding mass during slope instability, thus more accurately representing the dynamic process after slope instability. Especially in simulating the interaction between the sliding mass and the underlying engineering structure, PFC can effectively capture the deformation effects of the engineering structure, providing a more realistic and efficient tool for studying the interaction between landslides and engineering structures. Although PFC has been widely used in the study of geological hazards such as landslides and debris flows, the effects of entrainment and the interaction with the underlying engineering structure are still not fully considered in the analysis of slope instability processes.

[0005] Therefore, this invention innovatively applies the PFC simulation method to the analysis of the interaction between slope instability and engineering structures, and for the first time introduces the consideration of the entrainment effect. It aims to provide a more accurate and dynamic method for analyzing slope-structure interaction, to better assess the impact and damage of slope instability on underlying structures. By introducing PFC simulation and the entrainment effect, this invention can deeply analyze the dynamic characteristics of landslides during the sliding process, accurately assess the impact of the unstable body on underlying engineering structures, and provide scientific basis and technical support for the prevention and response to slope instability disasters. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention aims to provide a slope-engineering structure interaction analysis method that considers the PFC (Programmable Component Collective) entrainment effect. This method addresses the problem that existing technologies fail to adequately consider the entrainment effect of the sliding mass during slope instability and its impact on the underlying engineering structure. Existing slope instability analysis methods often neglect the interaction between the sliding mass and surrounding objects during the sliding process and do not effectively simulate the impact between the sliding mass and the underlying engineering structure. This invention introduces PFC discrete element numerical simulation software to simulate the entire process of the sliding mass sliding after slope instability, particularly the influence of the entrainment effect on the dynamic behavior of the sliding mass. Furthermore, this invention provides a detailed simulation of the impact during the sliding process, enabling accurate assessment of the impact effect of the sliding mass on underlying buildings and other engineering structures. Through the above numerical simulation, the present invention can more realistically and comprehensively reproduce the dynamic characteristics of the sliding body after slope instability, optimize the shortcomings of the existing technology that cannot fully consider the entrainment effect and the interaction between the sliding body and the substructure, significantly improve the accuracy and realism of slope-engineering structure interaction analysis, and provide a more scientific basis for engineering design, risk assessment and disaster prevention, which has important application significance and innovation.

[0007] The technical solution adopted by the present invention to solve the aforementioned technical problem is as follows:

[0008] A method for analyzing slope-engineering structure interactions considering the PFC entrainment effect, the steps of which are:

[0009] S1: Acquire digital elevation model (DEM) data, satellite imagery data, spatial data of the slope and surrounding area before and after the disaster, as well as basic mechanical parameters of the local soil and rock mass, dimensional information and geometry of the substructure of the local slope, and information on the components used in the substructure, including material type and component size.

[0010] S2: Using the basic mechanical parameter data of the soil and rock mass obtained in step S1, the micro-parameters of the soil and rock mass are calibrated using discrete element PFC software;

[0011] S3: Based on the digital elevation model (DEM) data and satellite imagery data obtained in step S1, analyze and determine the spatial distribution of the landslide source area, flow area, and deposition area after the disaster.

[0012] S4: Based on the digital elevation model (DEM) data of the slope obtained in step S1, the spatial distribution of each zone determined in step S3, and the micro-parameters determined in step S2, a three-dimensional model of the slope and surrounding terrain is performed to obtain a three-dimensional landslide model: First, a sliding bed model of the landslide is established; then, sliding particles are generated in the source area and the flow area to replace the surface soil. The particles in the source area represent the initial particles after the landslide collapse, while the particles in the flow area are used to simulate the dynamic behavior of the rock and soil during the landslide flow, reflecting the movement characteristics and interactions of the landslide body.

[0013] Damping effects are added between particles in the slip source area and the flow area, and friction is added between particles in the slip source area and the flow area and the slide bed to simulate a real sliding effect.

[0014] S5: Correct the 3D landslide model: Use PFC3D software to simulate the landslide after the disaster. Compare the simulation results with the actual situation on site, and adjust the parameters of the model in PFC in reverse, including the friction coefficient between the sliding particles and the sliding bed surface and the damping coefficient between the sliding particles; until the simulation results match the actual situation on site determined in step S3, thereby determining the values ​​of the friction coefficient and damping coefficient parameters, and obtaining the corrected 3D landslide model;

[0015] S6: After establishing the corrected three-dimensional landslide model, use PFC3D software to establish a three-dimensional frame model of the substructure. Generate the corresponding building model particles in PFC3D software to ensure that the size, shape and distribution of the building model particles can accurately match the actual situation on site.

[0016] S7: After modeling the landslide and its substructure, monitoring particles were installed at different locations in the upper, middle, and lower parts of the landslide source and flow zones. These monitoring particles effectively represent the motion characteristics of the landslide body within the overall study area, allowing for a detailed analysis of the landslide's kinematic characteristics. The slope instability is not a single object on a single profile, but rather the impact of the upper landslide source zone on the lower structures. Landslide instability is not a complete collapse, but rather the instability of the upper landslide source zone that drives the flow zone to slide. The landslide instability process was numerically simulated using PFC3D software, simulating the entrainment effect on the flow zone particles during the landslide's descent, causing the particles to move downwards with the landslide and ultimately impact the lower structures, thus obtaining the impact and flow depth of the landslide. PFC3D software was also used to obtain the deformation characteristics and magnitude of the structures at various moments during the interaction between the landslide and the structures, as well as the magnitude of the contact forces between the landslide particles and the structures.

[0017] Furthermore, the results of the PFC3D software simulation were compared with the actual on-site conditions, including the following:

[0018] 1) Compare the spatial location of the landslide particle impact range obtained from the simulation with the on-site post-disaster information determined in step S3 to confirm whether the range of the accumulation area obtained from the simulation is consistent with the actual situation.

[0019] 2) At the same time, the distribution of the landslide body in the flow area after the disaster was determined by the digital elevation data before and after the disaster, and the distribution of particle accumulation in the flow area after the simulation was compared with the distribution of the landslide body.

[0020] 3) Compare the simulated accumulation depth of the sliding particles in the accumulation area with the actual field conditions to ensure that the simulated average accumulation depth is consistent with the actual average accumulation depth on site.

[0021] Once the above conditions are met, the simulation results are considered to be consistent with the actual situation on site, and the values ​​of the friction coefficient and damping coefficient parameters are determined.

[0022] Furthermore, the friction coefficients between the particles and the slide bed in the slip source zone and the flow zone are 0.05 and 0.1, respectively; the damping coefficient between particles in the slip source zone is 0.1; the damping coefficient between particles in the flow zone is 0.3; the internal friction angle of the particles in the slip source zone is 25°; and the internal friction angle of the particles in the flow zone is 45°; the friction coefficient of the building particles is set to 0.5.

[0023] Furthermore, the analysis process of the dynamic process of the interaction between the landslide and the building, the impact effect and its influence on the structural safety of the building are as follows: In this process, the velocity, displacement, friction loss energy and the accumulation effect at different times, including the flow depth of the particles are monitored. According to the flow process at different times, it is determined whether the particles in the landslide source area carry the particles in the flow area to move together. If they move together, the entrainment effect occurs. The data of the monitored particles are used to simulate the entrainment effect of the landslide and its interaction with the building, and to quantify the impact of the particles entrained by the landslide on the building model when the landslide slides down.

[0024] The simulation results of the cross-sectional motion pattern of the sliding body during the sliding process show that the accumulation effect formed by the entrainment effect between the particles in the sliding source area and the particles in the flow area is that the particles in the sliding source area and the particles in the scraping area are mixed together and accumulated together; the particles in the scraping area are particles that move under the combined action of the forward push and entrainment of the particles in the sliding source area and jointly exert an effect on the building.

[0025] Furthermore, in step S5, the specific steps for establishing the three-dimensional frame model of the lower engineering structure using PFC3D software are as follows:

[0026] 1) Based on the dimensional and geometric information of the local slope substructure obtained in step S1, and the relevant information of the components used in the substructure, including the length, width, height, and number of stories of the building, and the dimensions of the components, a three-dimensional frame model of the substructure is established:

[0027] Based on the dimensional data of the beams and load-bearing columns, and according to the structural characteristics of the building, the corresponding geometric parameters are set; then, the coordinate position of the building in the PFC model is determined using the results of the on-site survey.

[0028] Determine the coordinate origin of the building foundation at the location of the building. Use the loop statement and the Ball create command in PFC3D software to generate regularly arranged particles in a loop. Generate the foundation at the location of the building. Then build the building model on the foundation. The building foundation has a constraining effect on the building frame.

[0029] 2) Based on the material information of the building beams and load-bearing columns obtained from the on-site survey, parameters are assigned to the particles. The cmat default model command is used to set the contact model between the beam and column particles as a linear pbond parallel bonded contact model. For the connection between the beam and the load-bearing column, constraints are applied by adjusting the friction coefficient (friction), cohesion (pb_coh), and friction angle (pb_fa) between the particles. For the contact between the load-bearing column and the foundation, the ball fix command is used to fix the particles at the contact point, thereby realizing the constraint effect of the foundation on the load-bearing column. Finally, gravity loading is applied, and the entire building model is brought to mechanical equilibrium through mechanical servo operation, completing the modeling process of the entire building.

[0030] Compared with existing technologies, the advantages of this invention are:

[0031] (1) The contact effect between particles using discrete element software can better demonstrate the entrainment effect of the sliding body during the sliding process. By conducting on-site surveys and using ArcGIS software to plan the scope of the sliding source area and the flow area, particles are generated in the sliding source area and the flow area to replace the surface soil. At the same time, a damping effect is added between the particles in the sliding source area and the flow area, and friction is added between the particles in the sliding source area and the particles in the flow area and the sliding bed, thereby simulating the real sliding effect and realizing that the contact effect between the sliding body particles and the particles in the flow area is consistent with the actual situation.

[0032] (2) During the sliding process, objects in the sliding source area do not simply slide; they also entrain objects in the flow area, causing them to slide down along with the particles in the sliding source area and eventually accumulate in the deposition area. However, current research rarely considers the entrainment effect of the sliding body on objects in the flow area during the sliding process. Therefore, considering the role of the entrainment effect in slope instability numerical simulation is a beneficial supplement to slope numerical simulation. By considering the entrainment effect, this invention can more comprehensively simulate the interaction between the sliding body and the materials in the flow area, making the simulation results of the sliding process closer to the actual situation, and ultimately obtaining more accurate motion characteristics, thus enhancing the realism of the simulation results.

[0033] (3) This invention analyzes the interaction between the landslide and the underlying engineering structure after the landslide, which is a useful supplement to the numerical simulation of slope instability. In the prior art, although many studies have analyzed the stability and motion characteristics of landslides, few studies have taken into account the interaction between landslides and underlying engineering structures (such as buildings, roads, etc.). Many existing numerical simulation studies only focus on the motion process of the landslide itself, without evaluating in detail the impact effect of the landslide on the underlying buildings or other engineering structures. By analyzing the landslide process and its interaction with the structure through numerical simulation, landslide hazard areas can be identified, disaster prevention work can be carried out, and the safety of people's lives and property can be ensured. This has important practical significance and application value, and provides more accurate technical support for the early warning and prevention of landslide disasters.

[0034] (4) This invention tracks and monitors the kinematic characteristics of a landslide throughout its sliding process, addressing a deficiency in existing research. Current studies mostly focus on the initial state and stability analysis of landslides, neglecting detailed changes in physical quantities during the landslide's movement. This makes it difficult to comprehensively and accurately predict the dynamic impact of landslides. This study precisely monitors the kinematic characteristics of the landslide during its sliding process by setting monitoring particles in the landslide source and flow zones, including key physical quantities such as velocity, displacement, and energy changes. This dynamic data not only provides an in-depth analytical perspective for studying the motion behavior of landslide bodies but also provides a more accurate basis for the quantitative prediction of the occurrence and development of landslide disasters, further improving the accuracy of landslide risk assessment and early warning.

[0035] (5) The method of this invention employs three-dimensional modeling and multi-region division, improving the accuracy and comprehensiveness of the modeling. Most existing landslide studies use two-dimensional models for analysis. While two-dimensional models can handle slope instability problems relatively simply, they cannot fully simulate the movement process of the landslide body in three-dimensional space and its interaction with the environment. Three-dimensional models can more realistically reproduce the interaction between the slope and the landslide body, especially considering the complex landslide source area, flow area, and deposition area. This study, by combining topographic data and satellite imagery, accurately delineates the disaster area, establishes a landslide model based on three-dimensional modeling, and clearly delineates the source area, flow area, and deposition area. This allows the model to not only more accurately reflect the spatial evolution process of the landslide but also simulate the movement pattern of the landslide body in complex topographic environments, providing a more accurate foundation for subsequent landslide dynamics simulation.

[0036] (6) Existing landslide risk assessment tools typically rely on static models and simplified assumptions, failing to fully reflect the dynamic changes during the landslide process, resulting in low accuracy in disaster early warning and prevention measures. This invention combines PFC discrete element simulation with 3D modeling technology, enabling not only dynamic tracking of the landslide process but also assessment of the impact effect of the landslide on the underlying structure. This comprehensive and dynamic landslide risk assessment tool is of great significance in improving the accuracy and real-time performance of risk assessment, providing a reliable basis for developing more scientific disaster prevention strategies. Attached Figure Description

[0037] Figure 1 The system monitors the changes in particle velocity and displacement over time. The first column shows the changes in particle velocity and displacement over time in the slip source area, and the second column shows the changes in particle velocity and displacement over time in the flow area.

[0038] Figure 2 Simulation results of landslide profile movement.

[0039] Figure 3 The condition of the engineering structure before it was impacted.

[0040] Figure 4 The condition of the engineering structure after being impacted.

[0041] Figure 5 Displacement diagram of an engineering structure after an impact.

[0042] Figure 6 Schematic diagram of particle distribution monitoring.

[0043] Figure 7 : Post-disaster plan view of the study area in the embodiment. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. Of course, the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0045] This invention provides a slope-engineering structure interaction analysis method considering the PFC entrainment effect, comprising the following steps:

[0046] S1: Acquire digital elevation model (DEM) data and satellite imagery data of the slope and surrounding area before and after the disaster. Determine the basic mechanical parameters of the local soil and rock mass through geological survey data and laboratory physical and mechanical tests. In addition, acquire the dimensional information and geometry of the substructure of the slope, as well as information on the components used in the substructure, including material types and component dimensions (beams and columns, etc.). Obtain accurate spatial data of the slope and surrounding area through remote sensing technology or open-source data websites to provide detailed geographical background information for subsequent landslide model building and analysis. Specifically:

[0047] Using open-source data platforms such as 91 Satellite Assistant software, digital elevation model (DEM) data of the study area before and after the disaster, as well as satellite remote sensing imagery after the disaster, were acquired. Combined with on-site surveys, post-disaster field images of the study area were collected, enabling the acquisition of dimensional information and geometry of the engineering structures under the local slopes, as well as information on the materials used in the building frames, the dimensions of beams and columns, etc., and obtaining basic mechanical parameter data of the on-site soil and rock mass, i.e., macroscopic parameters (such as density, elastic modulus, Poisson's ratio, etc.), providing basic data support for subsequent parameter calibration and 3D modeling.

[0048] The method for downloading elevation data and imagery in the 91 Satellite Assistant software is to obtain a location information .sh file of the study area, import it into 91 Satellite Assistant, and then accurately locate and download digital elevation data. In addition, it can also acquire satellite remote sensing imagery data from historical and current periods.

[0049] S2: Using the basic mechanical parameter data of the soil and rock mass obtained in step S1, the micro-parameters of the soil and rock mass are calibrated using discrete element PFC software;

[0050] By establishing uniaxial and biaxial numerical tests of rock materials using PFC2D, the relationship between microscopic and macroscopic parameters is obtained. Based on the macroscopic parameters of local soil and rock masses, the microscopic parameters between particles in the PFC model (such as effective modulus of parallel bond, effective modulus of linear contact, and stiffness ratio) are optimized and calibrated to ensure that the mechanical behavior of particles in the model is highly consistent with the macroscopic mechanical properties of actual soil and rock masses, thus ensuring the realism and reliability of the simulation process.

[0051] In the experiment, macroscopic parameter conditions (the same macroscopic parameters as the local soil and rock mass, such as density, elastic modulus, Poisson's ratio and uniaxial compressive strength) were used. Multiple calculations were performed using empirical calculations (controlled variable method) to establish the corresponding equation relationship between macroscopic parameters and microscopic parameters. The macroscopic parameters in the actual material were used to assign values, thereby calculating the magnitude of the corresponding microscopic parameters.

[0052] The specific steps for macro-micro parameter calibration are as follows:

[0053] (1) Establish an experimental sample model. The sample size is 50mm×100mm, the particle radius range is 0.3mm~0.498mm and randomly distributed, and the particle size ratio is 1.66. The experimental sample model is obtained by using 1MPa servo confining pressure.

[0054] (2) The parallel bond modulus was calibrated by uniaxial tensile test. The effective linear contact modulus (emod) was kept relatively small (the value of the effective linear contact modulus emod was taken as a relatively small value). The effective parallel bond modulus (Pb_emod) was changed, and the stress and strain curves under direct tensile conditions were obtained. The tensile elastic modulus (peak / peak strain) was obtained based on the stress and strain curves under direct tensile conditions. Then, multiple sets of values ​​corresponding to the tensile elastic modulus and the effective parallel bond modulus were obtained. The corresponding equation relationship between the tensile elastic modulus (peak / peak strain) and Pb_emod was obtained by fitting, so as to achieve the purpose of obtaining the effective parallel bond modulus of the micro-parameter using the macro-parameter tensile elastic modulus.

[0055] (3) The linear effective contact modulus (emod) is calibrated by uniaxial compression test. The parallel bond effective modulus is fixed and the linear effective contact modulus (emod) is changed to obtain the stress and strain curves under direct compression conditions. The compressive elastic modulus (peak / peak strain) is obtained, and then multiple sets of values ​​corresponding to the compressive elastic modulus and the linear effective contact modulus are obtained. The corresponding equation relationship between the compressive elastic modulus and emod is obtained by fitting, so as to achieve the purpose of obtaining the micro-parameter linear effective contact modulus by using the macro-parameter compressive elastic modulus.

[0056] (4) The stiffness ratio (Kratio) was calibrated using biaxial compression experiments. The linear effective contact modulus and the parallel effective bond modulus were fixed, and it was assumed that the stiffness ratio (kratio) of the parallel effective bond modulus and the linear effective contact component were the same. The correspondence between the stiffness ratio and the macroscopic parameter Poisson's ratio was studied. Biaxial compression was performed with stiffness ratios of 0.5, 1.0, 1.5, and 2.0 respectively. The Poisson's ratio was calculated at the position of the nominal strain (the strain corresponding to half of the peak strength) to obtain multiple sets of stiffness ratio and corresponding Poisson's ratio values. The corresponding equation relationship between Poisson's ratio and Kratio was obtained by fitting, thereby achieving the purpose of obtaining the microscopic parameter stiffness ratio using the macroscopic parameter Poisson's ratio.

[0057] S3: By analyzing the post-disaster remote sensing images and field survey maps of the study area obtained in step S1, and combining them with topographic and landslide characteristics, the landslide area is divided into detailed zones. In ArcGIS software, based on the landslide's geomorphological features and post-disaster morphology, the boundaries of the landslide source area, flow area, and deposition area are accurately delineated, providing accurate basic data support for subsequent 3D modeling and landslide simulation.

[0058] S4: Based on the digital elevation model (DEM) data of the slope obtained in step S1 and the spatial distribution of each area determined in step S3, a three-dimensional model of the slope and surrounding terrain is performed to obtain a three-dimensional landslide model: First, a sliding bed model of the landslide is established; then, sliding particles are generated in the source area and the flow area to replace the surface soil. The particles in the source area represent the initial particles after the landslide collapse, while the particles in the flow area are used to simulate the dynamic behavior of the rock and soil during the landslide flow, reflecting the movement characteristics and interactions of the landslide body.

[0059] Damping effects are added between particles in the slip source area and the flow area, and friction is added between particles in the slip source area and the flow area and the slide bed to simulate a real sliding effect.

[0060] S5: Correct the 3D landslide model: Use PFC3D software to simulate the landslide after the disaster. Compare the simulation results with the actual situation on site, and adjust the parameters of the model in PFC in reverse, including the friction coefficient between the sliding particles and the sliding bed surface and the damping coefficient between the sliding particles; until the simulation results match the actual situation on site determined in step S3, thereby determining the values ​​of the friction coefficient and damping coefficient parameters, and obtaining the corrected 3D landslide model;

[0061] S6: After establishing the corrected three-dimensional landslide model, use PFC3D software to establish a three-dimensional frame model of the substructure. Generate the corresponding building model particles in PFC3D software to ensure that the size, shape and distribution of the building model particles can accurately match the actual situation on site.

[0062] By analyzing the geometric shape and dimensions of the building at the site, the span of the building model to be built is determined. Combining the material properties of the beams and load-bearing columns obtained from the site survey, and based on the mechanical properties of different materials, such as strength and stiffness, parameters such as the bond strength between particles, particle stiffness, and friction coefficient are further set using PFC software to accurately reflect the actual condition of the building structure. Based on this data, a three-dimensional frame model of the substructure is constructed.

[0063] S7: After modeling the landslide and its substructure, monitoring particles were installed at different locations in the upper, middle, and lower parts of the landslide source and flow zones. These monitoring particles effectively represent the motion characteristics of the landslide body within the overall study area, allowing for a detailed analysis of the landslide's kinematic characteristics. The slope instability is not a single object on a single profile, but rather the impact of the upper landslide source zone on the lower structures. Landslide instability is not a complete collapse, but rather the instability of the upper landslide source zone that drives the flow zone to slide. The landslide instability process was numerically simulated using PFC3D software, simulating the entrainment effect on the flow zone particles during the landslide's descent, causing the particles to move downwards with the landslide and ultimately impact the lower structures, thus obtaining the impact and flow depth of the landslide. PFC3D software was also used to obtain the deformation characteristics and magnitude of the structures at various moments during the interaction between the landslide and the structures, as well as the magnitude of the contact forces between the landslide particles and the structures.

[0064] Monitoring particle velocity and displacement data directly reflects the dynamic characteristics of a landslide during its sliding process, including information such as the movement mode, velocity, and displacement of the landslide mass. This data allows for detailed analysis of the impact effects when the landslide comes into contact with structures, such as the transfer of kinetic energy, the extent of the disaster's impact, and the stress on the structures. Monitoring particle data helps simulate the entrainment effect of landslides and its interaction with structures. Monitoring particle displacement and velocity data helps quantify the impact of entrained particles on building models during landslides. It also provides data support for detailed analysis of the interaction process between the entrained landslide mass and engineering structures.

[0065] Furthermore, step S4 involves using PFC3D software to create a three-dimensional model of the landslide. The specific process is as follows:

[0066] (1) Establishing a landslide bed model: Using the post-disaster digital elevation data obtained through ArcGIS software, the boundary range of the model to be built was determined. The raster clipping function in ArcGIS software was used to clip the digital elevation data to the required modeling range, obtaining the necessary landslide bed data. After data processing, the data was exported to a TIF file format supported by GlobalMapper. Subsequently, GlobalMapper software was used to convert the TIF format terrain data into a DEM format file recognizable by 3DMax software. 3D modeling of the DEM data was performed using 3DMax software, and finally, the model was exported to an STL format file supported by PFC3D software, laying the foundation for subsequent simulation analysis and modeling work.

[0067] (2) Simultaneously process the digital elevation data before the disaster, and determine the extent of the three areas—the landslide source area, the flow area, and the accumulation area—from the post-disaster site survey. Using the raster clipping function, cut out the digital elevation data of the landslide source area and the flow area before the disaster, and then export them to an STL format recognizable by PFC3D software through the same steps described above. Import the digital elevation data of the slide bed after the disaster, as well as the STL files of the digital elevation data of the landslide source area and the flow area before the disaster, into PFC3D software using the geometry import command, and generate the wall boundary using the wallimport command. In this way, there will be a topographic difference between the landslide source area and the flow area before and after the disaster, and this topographic difference is the sliding body of the sliding part. Use the ball distribute box command to generate particles in the cubic space near the space of the landslide source area, and then use the ball delete command to delete the particles below the slide bed in the lower part of the landslide source area and the particles above the upper boundary, leaving only the particles between the topographic differences. This achieves the purpose of using particles to replace the sliding body in the landslide source area.

[0068] Furthermore, due to the large area of ​​the flow zone, if the same particle generation method as the source zone is used, the number of particles generated would be several million, which would be difficult for a computer to process successfully. Therefore, the "ball distribute range" command is used to generate particles below the upper boundary of the flow zone, and then the "ball delete" command is used to delete the particles below the lower slide bed in the flow zone. This achieves the operation of using particles to replace the sliding bodies within the topographic difference of the flow zone, and the number of particles processed is around several hundred thousand, which can be achieved by a computer. After the sliding body particles are generated, the microscopic parameters of the sliding body particles are assigned according to the parameter calibration results of step S2. Based on the different geological characteristics of the two regions, the porosity ratio, friction angle, friction coefficient, damping coefficient, and other parameters of the sliding body particles are set accordingly, completing the construction of the three-dimensional model and the sampling steps of the sliding body particles.

[0069] (3) Perform mechanical servo operation on particles: Considering that the particles generated in PFC3D software are randomly distributed and there may be overlap between particles, by applying a servo mechanism, the force between particles can be evenly distributed, so that the particle system can reach a state of mechanical equilibrium, ensuring that the interaction force between particles conforms to the actual physical law, and completing the modeling process of all slope models.

[0070] Furthermore, in step S5, the results of the PFC simulation are compared with the actual situation on site, including:

[0071] 1) Compare the spatial location of the simulated landslide particle impact range with the on-site post-disaster information determined in step S3, especially whether the simulated accumulation area range is consistent with the actual site, to ensure that the particles in the simulated accumulation area account for more than 80% of the actual post-disaster accumulation area.

[0072] 2) At the same time, the distribution of the landslide body in the flow area after the disaster is determined by the digital elevation data before and after the disaster, and the distribution of particle accumulation in the flow area after simulation is compared with the distribution of the landslide body.

[0073] 3) Compare the simulated accumulation depth of the sliding particles in the accumulation area with the actual field conditions to ensure that the simulated average accumulation depth is consistent with the actual field average accumulation depth.

[0074] Repeat the above comparison process until the simulation results match the actual situation on site, and determine the values ​​of the friction coefficient and damping coefficient parameters at this point.

[0075] Furthermore, in step S6, the specific steps for establishing the three-dimensional frame model of the substructure—the building model—using PFC3D software are as follows:

[0076] (1) First, based on the dimensional information of the local buildings obtained in step S1, including the length, width, height, and number of floors, a model is established. Based on the dimensional data of the beams and load-bearing columns, and according to the structural characteristics of the building, corresponding geometric parameters are set. After determining the dimensions and material information, the coordinate position of the building in the PFC model is determined using the results of the site survey. First, the coordinate origin of the building foundation is determined. In PFC, the loop statement and the Ball create command are used to generate regularly arranged particles in a loop, generating the foundation at the building location. Because the local terrain is not flat, and the building foundation has a constraining effect on the building frame, the foundation is generated first, and then the building model is built on top of the foundation.

[0077] (2) Based on the material information of the building beams and load-bearing columns obtained from the on-site survey, parameters were assigned to the particles. Contact models were set up between the column and beam particles respectively. The cmat default model command was used to set the contact model between the beam and column particles as a linear pbond parallel bonded contact model. This particle contact model can be used to represent the mechanical behavior of the bonding material (bonding of cement aggregate), therefore this contact model was selected as the contact model between the building particles. For the connection between the beam and the load-bearing column, appropriate constraints were applied by adjusting parameters such as the friction coefficient (friction), cohesion (pb_coh), and friction angle (pb_fa) between the particles. For the contact between the load-bearing column and the foundation, the particles at the contact point were fixed using the ball fix command, thereby realizing the constraint effect of the foundation on the load-bearing column. Finally, gravity loading was applied, and the entire building model was brought to mechanical equilibrium through mechanical servo operation, completing the modeling process of the entire building.

[0078] After PFC modeling is completed, this invention uses the built-in Ball history command to select particles at different locations in the landslide source and flow zones of the entire landslide model and designate them as monitoring particles. This is used to monitor the kinematic characteristics of the landslide body during slope instability in detail. For example, Excel data on particle velocity, displacement, and energy changes over time is generated for subsequent detailed analysis. By analyzing this data, the deposition morphology, flow depth, and particle velocity data at the moment the landslide body reaches the structure are recorded to calculate the impact energy when it interacts with the structure. Simultaneously, by setting the particle properties in the PFC software, the landslide body can be set to Ball displacement and Ball contact force options to obtain particle deformation data and contact force magnitude when the landslide body interacts with the underlying structure. This data allows for detailed analysis of the interaction process between the landslide body and the structure.

[0079] In this invention, the three-dimensional landslide model incorporates the surrounding terrain of the slope, rather than being a single cross-section. The impact of slope instability is not limited to objects on a single cross-section, but rather arises from the convergence of forces from the upper landslide source area and their subsequent impact on the lower slope. Furthermore, the landslide instability is not a complete collapse, but rather the instability of the upper landslide source area triggers sliding in the flow zone, which is more consistent with reality.

[0080] Example

[0081] This study presents a landslide case in Zhejiang Province. The landslide has a longitudinal length of 850-1200m, a lateral width of approximately 100-340m, and a volume of approximately 400,000 m³. 3 .

[0082] S1: Digital topographic data of the study area before and after the disaster were obtained using the 91 Satellite Assistant software and relevant data websites. Dimensional information and impact conditions of post-disaster building structures were also collected. On-site investigation results indicate that the surface layer (0-4.5 meters) of the landslide body is a layer of gravelly cohesive soil, with a lower layer of fragmented rock. The original rock lithology is porphyritic fine-grained granite, which is hard and dense. Affected by faulting and sliding displacement, the rocks in the landslide area are extremely fragmented, exhibiting a fractured to fragmented shape, with block diameters mainly concentrated between 0.3 and 0.8 meters, and mostly in the form of regular oblique cuboids. The rock samples used are porphyritic fine-grained granite, with the following macroscopic parameters: elastic modulus E = 56 GPa (the tensile elastic modulus of this rock is equal to its compressive elastic modulus), Poisson's ratio μ = 0.18, and density ρ = 2700 g / cm³. 3 In the uniaxial compression test, the standard value of the saturated compressive strength of the rock was found to be 110.29 MPa.

[0083] S2: The macroscopic parameters of the local soil and rock mass obtained in step S1 are calibrated using PFC2D software.

[0084] The specific results of the macro-micro parameter calibration are as follows:

[0085] (1) The relationship between the tensile modulus (peak value / peak strain) and the effective modulus of parallel bond Pb_emod obtained by uniaxial tensile test is as follows:

[0086] E t =1.0892x + 0.0146

[0087] In the formula E t The tensile modulus of elasticity is expressed in GPa; x represents the actual Pb_emod value used / 1e 9 At this point, the tensile modulus is 56 GPa. Substituting this into the above formula, we can find that x is approximately 51.40 GPa, meaning the effective modulus of parallel bonding, Pb_emod, should be 51.40 GPa.

[0088] (2) The relationship between the compressive elastic modulus and the linear effective contact modulus (emod) obtained through uniaxial compression experiments is as follows:

[0089] E c =0.3934x + 2.2347

[0090] In the formula E c This is the compressive modulus, expressed in GPa; here, x is the actual emod value used / 1e 9 The compressive elastic modulus is 56 GPa. Substituting this into the above formula, we can find that x is approximately 136.668 GPa, meaning the linear contact modulus emod should be 136.668 GPa.

[0091] (3) The relationship between Poisson's ratio and stiffness ratio (Kratio) obtained through biaxial compression experiments is as follows:

[0092] μ = 0.1710x - 0.0624

[0093] In the formula, μ is the macroscopic Poisson's ratio, and x is the stiffness ratio. Substituting the Poisson's ratio of 0.18, we get the stiffness ratio (kratio) as 1.418.

[0094] S3: Through on-site investigation combined with satellite remote sensing imagery, the landslide area was delineated, including the specific distribution of the source area, flow area, and deposition area. In ArcGIS software, raster clipping was used to extract elevation data of the landslide body and slide bed areas, providing the necessary topographic data foundation for subsequent 3D modeling.

[0095] S4: Export the data processed in step S3 to a TIF file format supported by GlobalMapper using ArcGIS software. Then, use GlobalMapper to convert the TIF format terrain data into a DEM format file recognizable by 3DMax software. Perform 3D modeling on the DEM data using 3DMax software, and finally export the 3D terrain model created in 3DMax software to an STL format file supported by PFC3D software.

[0096] (1) After importing the STL format file of the terrain into PFC3D software, a landslide terrain model was constructed using the Ball-Wall method. The terrain of the sliding bed and sliding body was set as Wall boundary conditions, while the source area and flow area were filled with particles (Balls). In the source area, the particle radius was set to 1.0-2.0 meters, while in the flow area, the particle radius was set to 1.0-2.5 meters. Based on the parameter calibration results, the micro-parameters were assigned to the particles, ultimately generating 44,656 particles.

[0097] (2) A servo mechanism is introduced to ensure uniform force distribution within the particles. Parameters are assigned to this mechanism to prepare for sliding. Gravitational acceleration is applied, the friction coefficient between the particles and the slide bed in the sliding source area is 0.05, the damping coefficient between particles in the sliding source area is 0.1, and the internal friction angle between particles in the sliding source area is set to 25°. The friction coefficient between the particles and the slide bed in the flow area is set to 0.1, the damping coefficient between particles in the flow area is 0.3, the internal friction angle between particles in the flow area is 45°, and the time step of the landslide model is set to 5e. -4 s.

[0098] S5: Compare the results obtained from the PFC simulation, specifically the influence range of the sliding particles, with the post-disaster plan view (e.g., Figure 7As shown in the figure, a landslide accumulation area profile was selected, and the accumulation thickness at the corresponding location in the simulation results was extracted and compared with the actual accumulation thickness obtained from the field survey (i.e., the average accumulation depth of 12m). By subtracting the post-disaster digital elevation data from the pre-disaster digital elevation data using post-disaster digital elevation data, raster data showing the elevation changes in the area before and after the disaster can be obtained. The coordinate information of the particles obtained from the model simulation was imported into ArcGIS software, and the differences in the sliding range and accumulation characteristics between the simulated particle accumulation distribution and the elevation change raster data based on the simulation and measured results were compared.

[0099] The parameters in the PFC model were adjusted in reverse based on the above comparison results, focusing on the friction coefficient between the sliding particles and the slide bed, as well as the damping coefficient between the particles. Verification was conducted from multiple perspectives until the simulation results matched the actual field conditions, thus determining the numerical values ​​of the friction coefficient and damping coefficient parameters in the model.

[0100] S6: The specific steps for creating a building model using PFC3D software are as follows:

[0101] (1) The dimensions of the building are obtained as follows: length 12m, width 5m, and height 7m. The dimensions of the beams and load-bearing columns are 40cm × 40cm. The walls are brick-concrete structure, and the beams and load-bearing columns are made of reinforced concrete. After determining the dimensions and material information, the Ball create command is used in PFC to generate regularly arranged particles. A foundation is generated at the location of the building, and the building model is then built on the foundation. Considering the building size requirements, the radius of the generated particles is set to 0.1m, and two columns of particles are arranged horizontally and vertically to ensure that the arrangement of each particle meets the on-site size requirements, i.e., the effect of 40cm × 40cm.

[0102] (2) After establishing the frame model, assign corresponding parameters to the foundation, beams, and load-bearing columns, and define the contact characteristics between particles. Based on the actual properties of the materials, set the density of the building particles to 2400 kg / m³. 3 The coefficient of friction is set to 0.5. The contact model between particles is set to a parallel bonded contact model, and the cohesion is set to 1×10⁻⁶. 10 Pa, friction angle set to 30°, gravitational acceleration set to 10 m / s² 2 Finally, mechanical servoing is performed to bring the particles into a state of mechanical equilibrium.

[0103] S7: After the parameters are determined, use the built-in Ball history command to set monitoring particles at different locations in the landslide source area and flow area of ​​the 3D landslide model to monitor the changes in velocity and displacement of the landslide body over time. This provides data support for subsequent analysis of the interaction between the landslide body and structures. Figure 1 As shown, the first column displays the changes in particle velocity and displacement over time in the slip source region, and the second column displays the changes in particle velocity and displacement over time in the flow region. #1, #2, #3, and #4 in the legend represent particles at different locations in the slip source and flow regions, respectively. Four particles were selected in the slip source region, and four particles were also selected in the flow region. A schematic diagram of the monitored particles is shown below. Figure 6 .

[0104] After the slope instability simulation began, to study the motion characteristics and deposition effects of the landslide at various times, nine time points (T=0s, 5s, 10s, 20s, 30s, 60s, 80s, 100s, and 120s) were selected to analyze its motion characteristics. To better observe the changes in the profile morphology of the landslide mass during the sliding process, the simulation results of the profile motion morphology were selected. This profile allows for a direct observation of the entrainment effect between particles in the landslide source area and particles in the flow area. The final deposition effect is that particles from the landslide source area and particles from the flow area are mixed together and deposited. Particles in the scraped area move under the combined action of the forward thrust and entrainment of particles in the landslide source area, and then collectively exert their effect on the structure, such as... Figure 2 As shown, Figure 2 The blue area represents particles in the flow zone, the red area represents particles in the slip source zone, and the overlapping area of ​​red and blue represents particles in the scraping zone. Furthermore, the impact of the sliding body on the underlying structure can be visually observed, and its deformation at different times can be obtained, such as... Figure 3 , Figure 4 As shown.

[0105] Furthermore, by setting the ball displacement and ball contact force properties of the particles, the deformation data and the changes in contact force between the sliding body and the building at various moments during the interaction between the sliding body and the building were obtained. The structural displacement of the building after being impacted by the sliding body is shown below. Figure 5 As shown, the deformation and displacement of various parts of the building can be observed through the building model, thus allowing for a direct observation of the interaction between the sliding body and the building.

[0106] Simulation results provide a clear visual representation of the kinematic characteristics of the landslide body at different times during slope instability, considering the entrainment effect. This includes the landslide body's displacement, velocity, and other dynamic behaviors, which can be used to calculate the impact energy when the landslide body reaches the building. Furthermore, the simulation results clearly demonstrate the interaction between the landslide body and the building structure, revealing the impact process and deformation of the building frame. These dynamic analyses provide crucial theoretical basis and technical support for assessing the scope of disaster impact and developing disaster prevention and mitigation strategies.

[0107] Any aspects not covered in this invention are applicable to existing technologies.

Claims

1. A method for analyzing slope-engineering structure interaction considering the PFC entrainment effect, characterized in that, The steps of the method are as follows: S1: Acquire digital elevation model (DEM) data, satellite imagery data, spatial data of the slope and surrounding area before and after the disaster, as well as basic mechanical parameters of the local soil and rock mass, dimensional information and geometry of the substructure of the local slope, and information on the components used in the substructure, including material type and component size. S2: Using the basic mechanical parameter data of the soil and rock mass obtained in step S1, the micro-parameters of the soil and rock mass are calibrated using discrete element PFC software; S3: Based on the digital elevation model (DEM) data and satellite imagery data obtained in step S1, analyze and determine the spatial distribution of the landslide source area, flow area, and deposition area after the disaster. S4: Based on the digital elevation model (DEM) data of the slope obtained in step S1, the spatial distribution of each zone determined in step S3, and the micro-parameters determined in step S2, a three-dimensional model of the slope and surrounding terrain is performed to obtain a three-dimensional landslide model: First, a sliding bed model of the landslide is established; then, sliding particles are generated in the source area and the flow area to replace the surface soil. The particles in the source area represent the initial particles after the landslide collapse, while the particles in the flow area are used to simulate the dynamic behavior of the rock and soil during the landslide flow, reflecting the movement characteristics and interactions of the landslide body. Damping effects are added between particles in the slip source area and the flow area, and friction is added between particles in the slip source area and the flow area and the slide bed to simulate a real sliding effect. S5: Correct the 3D landslide model: Use PFC3D software to simulate the landslide after the disaster. Compare the simulation results with the actual situation on site, and adjust the parameters of the model in PFC in reverse, including the friction coefficient between the sliding particles and the sliding bed surface and the damping coefficient between the sliding particles; until the simulation results match the actual situation on site determined in step S3, thereby determining the values ​​of the friction coefficient and damping coefficient parameters, and obtaining the corrected 3D landslide model; S6: After establishing the corrected three-dimensional landslide model, use PFC3D software to establish a three-dimensional frame model of the substructure. Generate the corresponding building model particles in PFC3D software to ensure that the size, shape and distribution of the building model particles can accurately match the actual situation on site. S7: After modeling the landslide and its substructure, monitoring particles were installed at different locations in the upper, middle, and lower parts of the landslide source and flow zones. These monitoring particles effectively represent the motion characteristics of the landslide body within the overall study area, allowing for a detailed analysis of the landslide's kinematic characteristics. The slope instability is not a single object on a single profile, but rather the impact of the upper landslide source zone on the lower structures. Landslide instability is not a complete collapse, but rather the instability of the upper landslide source zone that drives the flow zone to slide. The landslide instability process was numerically simulated using PFC3D software, simulating the entrainment effect on the flow zone particles during the landslide's descent, causing the particles to move downwards with the landslide and ultimately impact the lower structures, thus obtaining the impact and flow depth of the landslide. PFC3D software was also used to obtain the deformation characteristics and magnitude of the structures at various moments during the interaction between the landslide and the structures, as well as the magnitude of the contact forces between the landslide particles and the structures.

2. The method according to claim 1, characterized in that, The results of PFC3D software simulation are compared with the actual on-site situation, including the following: 1) Compare the spatial location of the landslide particle impact range obtained from the simulation with the on-site post-disaster information determined in step S3 to confirm whether the range of the accumulation area obtained from the simulation is consistent with the actual situation. 2) At the same time, the distribution of the landslide body in the flow area after the disaster was determined by the digital elevation data before and after the disaster, and the distribution of particle accumulation in the flow area after the simulation was compared with the distribution of the landslide body. 3) Compare the simulated accumulation depth of the sliding particles in the accumulation area with the actual field conditions to ensure that the simulated average accumulation depth is consistent with the actual average accumulation depth on site. Once the above conditions are met, the simulation results are considered to be consistent with the actual situation on site, and the values ​​of the friction coefficient and damping coefficient parameters are determined.

3. The method according to claim 1, characterized in that, The friction coefficients between the particles and the slide bed in the slip source zone and the flow zone are 0.05 and 0.1, respectively. The damping coefficient between particles in the slip source zone is 0.1, and the damping coefficient between particles in the flow zone is 0.

3. The internal friction angle of the particles in the slip source zone is 25°, and the internal friction angle of the particles in the flow zone is 45°. The friction coefficient of the building particles is set to 0.

5.

4. The method according to claim 1, characterized in that, The analysis process of the dynamic process of the interaction between landslide and building, impact effect and its impact on the structural safety of building is as follows: In this process, the velocity, displacement, friction loss energy and accumulation effect at different times including flow depth of particles are monitored. According to the flow process at different times, it is determined whether the particles in the landslide source area carry the particles in the flow area together. If they move together, the entrainment effect occurs. The data of monitored particles are used to simulate the entrainment effect of landslide and its interaction with building, and to quantify the impact of the particles entrained by the landslide on the building model. The simulation results of the cross-sectional motion pattern of the sliding body during the sliding process show that the accumulation effect formed by the entrainment effect between the particles in the sliding source area and the particles in the flow area is that the particles in the sliding source area and the particles in the scraping area are mixed together and accumulated together; the particles in the scraping area are particles that move under the combined action of the forward push and entrainment of the particles in the sliding source area and jointly exert an effect on the building.

5. The method according to claim 1, characterized in that, In step S5, the specific steps for establishing the three-dimensional frame model of the substructure using PFC3D software are as follows: 1) Based on the dimensional and geometric information of the local slope substructure obtained in step S1, and the relevant information of the components used in the substructure, including the length, width, height, and number of stories of the building, and the dimensions of the components, a three-dimensional frame model of the substructure is established: Based on the dimensional data of the beams and load-bearing columns, and according to the structural characteristics of the building, the corresponding geometric parameters are set; The coordinates of the building in the PFC model were then determined using the results of the on-site survey. Determine the coordinate origin of the building foundation at the location of the building. Use the loop statement and the Ball create command in PFC3D software to generate regularly arranged particles in a loop. Generate the foundation at the location of the building. Then build the building model on the foundation. The building foundation has a constraining effect on the building frame. 2) Based on the material information of the building beams and load-bearing columns obtained from the on-site survey, parameters are assigned to the particles. The cmatdefault model command is used to set the contact model between the beam and column particles as a linear pbond parallel bonded contact model. For the connection between the beam and the load-bearing column, constraint conditions are applied by adjusting the friction coefficient, cohesion, and friction angle between the particles. For the contact between the load-bearing column and the foundation, the ball fix command is used to fix the particles at the contact point, thereby realizing the constraint effect of the foundation on the load-bearing column. Finally, gravity loading is applied, and the entire building model is brought to mechanical equilibrium through mechanical servo operation, completing the modeling process of the entire building.

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