Parameterization design and optimization method for side slope protection net based on live-action three-dimensional model

Abstract

The invention relates to the crossing technical field of civil engineering and computer graphics, in particular to a side slope protection net parameterization design and optimization method based on a live-action three-dimensional model, which comprises the following steps: collecting target side slope area data, and constructing a live-action three-dimensional terrain model; constructing a protective net three-dimensional geometric curved surface model based on the live-action three-dimensional terrain model; constructing a discrete element model oriented to kinetic analysis; constructing a dynamic simulation environment, and carrying out dynamic simulation; and performing multi-target iterative optimization based on a dynamic simulation result. Through the steps, the invention provides a novel slope protection net design and optimization method integrating high-fidelity modeling, dynamic interactive design, high-precision simulation and multi-objective optimization.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of civil engineering and computer graphics, and in particular to a parametric design and optimization method for slope protection nets based on real-world 3D models. Background Technology

[0002] High-precision real-scene 3D modeling technology, by integrating methods such as UAV oblique photography and 3D laser scanning, can quickly and accurately reconstruct the topography and geological structure of slopes, and has gradually become a core tool for slope geological disaster prevention and control. However, the application of this technology still faces the following problems: 1) Design is out of touch with reality. Traditional designs are mostly based on two-dimensional drawings or simplified three-dimensional terrain. The protective net model cannot accurately reflect its true spatial form under complex terrain, resulting in inaccurate estimation of engineering quantities and deviations between the protective effect and expectations.

[0003] 2) Fragmented design process, resulting in low efficiency. The deployment, modeling, simulation analysis, and scheme evaluation of the protective net are usually completed step by step by different software, making data import and export cumbersome and creating information barriers; scheme adjustments often require starting from scratch, resulting in long iteration cycles and making it difficult to quickly compare multiple schemes.

[0004] 3) Lack of quantitative assessment and scientific decision-making basis. The evaluation of the merits of protection solutions relies heavily on the experience of engineers, lacking a comprehensive quantitative assessment of multiple key indicators such as security, reliability, and economy; it is difficult to scientifically weigh multiple mutually restrictive objectives (such as: increasing the interception rate may increase costs), making it difficult to find the optimal solution.

[0005] 4) Insufficient accuracy of simulation models. Traditional rockfall simulation models are relatively crude in simulating the rockfall source area and the flexible structure of the protective net, making it difficult to realistically reflect the interaction mechanism between rockfalls and complex terrain and flexible protective nets.

[0006] As one of the mainstream discrete element methods, particle discrete element method requires the generation of block or surface structure elements from spherical particles based on a complex 3D model during preprocessing. This process is quite cumbersome. However, by using a parameterized and visualized framework to achieve dynamic control of particle element production, the preprocessing of discrete element simulation can be transformed from an experience-based approach to an efficient, accurate, and explorable intelligent design process. Summary of the Invention

[0007] The purpose of this invention is to address the shortcomings of the aforementioned background technology by providing a new design and optimization scheme for slope protection nets that integrates high-fidelity modeling, dynamic interactive design, high-precision simulation, and multi-objective optimization.

[0008] To achieve the above objectives, this invention provides a parametric design and optimization method for slope protection nets based on a real-world 3D model, comprising the following steps: S1: Collect data on the target slope area and construct a realistic 3D terrain model; S2, based on the real-world 3D terrain model, plans the 2D plane alignment of the protective net, projects the 2D plane alignment onto the surface of the real-world 3D terrain model, generates the bottom installation baseline of the protective net that accurately fits the undulations of the ground, and extends along the slope normal or gravity direction of each point on the baseline according to the preset height parameters of the protective net to generate the top boundary line, and connects the bottom installation baseline and the top boundary line to form a curved surface, constructing a 3D geometric curved surface model of the protective net that is completely coupled with the real terrain; S3, construct a discrete element model for dynamic analysis, including a protective net discrete element model and a rockfall source area discrete element model. The protective net discrete element model is divided according to the components and each component is assigned corresponding physical and mechanical parameters. The rockfall source area discrete element model generates rockfall particles in the corresponding space. S4: Construct a dynamic simulation environment, configure the gravity field and contact models between various objects, perform dynamic simulation, record and analyze the simulation results; the contact models include the contact model between the falling rock and the slope, the contact model between falling rocks, and the contact model between the falling rock and the protective net. S5, based on the results of dynamic simulation, performs multi-objective iterative optimization to obtain a series of different design schemes and corresponding design evaluation indicators. Selecting one of the design schemes completes the parametric design and optimization of the slope protection net.

[0009] Furthermore, in S1, the acquired 3D point cloud or image data of the target slope area is processed to generate a 3D point cloud data model with reasonable density and accuracy. The 3D point cloud data model is constructed into a triangular mesh model with real geographic coordinates and elevation information, and real texture mapping is performed to obtain a real 3D terrain model of the slope surface that is completely consistent with the actual landform.

[0010] Furthermore, in S2, based on engineering design specifications, geological hazard risk assessment results, and terrain analysis results, one or more protective nets are planned and laid out in the two-dimensional top view or three-dimensional view of the real-scene three-dimensional terrain model to determine the direction of the protective nets on the horizontal plane.

[0011] Furthermore, in S2, the two-dimensional planar lines are stretched along a direction perpendicular to the horizontal plane to construct one or more vertical virtual projection planes. The intersection of the virtual projection planes and the real three-dimensional terrain model is calculated, resulting in one or more spatial three-dimensional intersection lines that accurately fit the undulations of the real surface. The bottom installation baseline of the protective net on the real terrain is obtained. Taking the bottom installation baseline as the starting edge, according to the design height of the protective net, a specified distance is extended upward along the slope normal direction or gravity direction of each baseline point to generate the top boundary line of the protective net. The bottom installation baseline and the top boundary line are connected to generate a three-dimensional geometric surface model of the protective net.

[0012] Furthermore, when constructing the discrete element model of the protective net in S3, the model parameters are defined. , This indicates the chord-length spacing of the particles along the bottom mounting baseline. This indicates the spacing between particles in the vertical direction. Indicates the vertical particle hierarchy. Indicates the height of the supporting column. This indicates the frequency of the support columns' placement. Represents the visual radius of the particle; The continuous bottom mounting baseline is discretized into a set of ordered reference points, and the reference points are repeatedly translated vertically to construct the lateral particle rows. Each reference point is used to generate a vertical column of particles independently, thus constructing a vertical particle column. All horizontal particle rows and vertical particle columns are combined to obtain a complete protective net particle matrix.

[0013] Furthermore, when constructing the supporting columns, based on the generated set of reference points, parameters are used... The step size is used to determine each pair of reference points corresponding to two adjacent support columns, so that each pair of reference points is spaced by a horizontal distance. The vertical spacing and height of the column particles are the same as those of the protective net itself.

[0014] Furthermore, in S4, for the rockfall-slope contact model, the slope surface terrain is set as a rigid boundary to prevent rocks from crossing it. In each iteration step, the condition of each rockfall particle is determined. Whether it is located inside the closed grid of the slope, if it is inside, it is moved out using the following formula: ; in, This indicates the coordinates of the center point of the falling rock particles. These are the coordinates of the point on the slope surface closest to the center of the fallen rock particle. It is the shortest vector that pushes the center point of the falling rock out of the entity; the bouncing behavior of the falling rock is controlled by the elasticity solver. When a collision is detected, the elasticity solver reverses the component of the falling rock's velocity vector perpendicular to the collision surface, and simultaneously sets the coefficient of restitution. Friction is simulated by attenuating the tangential velocity component after a collision, and a coefficient of dynamic friction is introduced. The higher the coefficient of kinetic friction, the faster the tangential velocity decays, and the more likely the falling rock is to stop sliding. For the rockfall contact model, multiple rocks are allowed to collide and bounce off each other. For any two rockfall particles... and Calculate the coordinates of their center points. and Distance between A collision is considered to have occurred if the following conditions are met: ; in and These are rock fragments and The radius; For the contact model between falling rocks and protective netting, the contact mechanics relationship between the falling rock particles and the discrete element model of the protective netting is defined to simulate the process of energy being transferred through the wire mesh to the pressure relief ring and the supporting structure when an impact occurs.

[0015] Furthermore, when performing precise dynamic simulations in S4, the protective net is discretized into a flexible structure composed of a large number of particles connected through a contact model, and given realistic material mechanical parameters; multiple spherical particles are rigidly bonded together using particle cluster technology to construct a non-spherical block model that can reflect the irregular shape, mass, center of mass, and moment of inertia of real falling rocks; the slope is set as a boundary wall with realistic contact stiffness, friction coefficient, and restitution coefficient.

[0016] Furthermore, S3 sets three dimensions of design evaluation indicators: safety indicators, reliability indicators, and economic indicators; The safety index is the interception rate calculated based on the number or mass of the intercepted rocks; the reliability index is the impact energy margin obtained by comparing the simulated maximum impact energy with the energy absorption level of the protective net design; and the economic index is the unit protection cost calculated based on the geometric parameters of the protective net and the unit price of the materials.

[0017] Furthermore, in S5, the key design parameters of the protective net are used as input variables, and the design evaluation index is used as the output target. A parameterized optimization model is established, the input variables are adjusted, and S2 to S5 are repeated to obtain multiple design schemes and corresponding design evaluation indexes, and the Pareto optimal solution is selected from them.

[0018] The above-described solution of the present invention has the following beneficial effects: The parametric design and optimization method for slope protection nets based on real-scene 3D models provided by this invention improves the accuracy and realism of protection net design: the protection net model generated is directly based on a high-precision real-scene 3D model and is fully coupled with the real terrain, ensuring the accuracy of the design and avoiding the "distortion" problem of traditional 2D design. This invention improves the fidelity of simulation: high-precision modeling of the entire chain from terrain and protective netting to rockfall source areas ensures the input quality of dynamic simulation, thereby obtaining simulation results that are closer to the real physical process, and providing a solid foundation for the reliability verification of the scheme; This invention achieves scientific and optimized decision-making: it establishes a three-in-one quantitative evaluation system of "safety-reliability-economy" and introduces a multi-objective optimization method, which can make trade-off decisions from a series of Pareto optimal solutions, thus moving away from simple empirical design and finding the best balance between safety and cost. This invention enables dynamic interaction and efficiency improvement in design: through parameterization and automation, any adjustment to design parameters can trigger instant model updates and rapid feedback of results, which can shorten the design iteration cycle of several days or even weeks to several minutes or hours, greatly improving design efficiency. Other beneficial effects of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0019] Figure 1 This is a flowchart of the steps of the present invention; Figure 2 This is a schematic diagram of the two-dimensional planar line position of the present invention; Figure 3 This is a schematic diagram of the virtual projection plane of the present invention; Figure 4 This is a schematic diagram of the baseline for installing the bottom of the protective netting according to the present invention; Figure 5 This is a schematic diagram of the projection of the interception position of the protective net entity onto a three-dimensional terrain according to the present invention; Figure 6 This is a schematic diagram of the protective mesh particle matrix of the present invention; Figure 7 This is a schematic diagram of the column reference point set of the present invention. Detailed Implementation

[0020] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. This disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0021] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0022] It should also be noted that the illustrations provided in the following embodiments are merely schematic representations of the basic concept of this disclosure. The illustrations only show components relevant to this disclosure and are not drawn according to the actual number, shape, and size of components in implementation. In actual implementation, the type, quantity, and proportion of each component can be arbitrarily changed, and the component layout may be more complex. Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0023] like Figure 1 As shown, embodiments of the present invention provide a parametric design and optimization method for slope protection nets based on a real-world 3D model. Taking a typical rock slope as the research object, this method can also be used for parametric design and optimization of slope protection nets for other types of slopes. The method specifically includes the following steps: S1 collects data on the target slope area and constructs a high-precision real-scene 3D terrain model.

[0024] In this step, high-precision 3D point cloud or image data of the target slope area is first acquired, and then the data is processed to generate a real-world 3D terrain model of the slope surface that is consistent with the real landform, which serves as the digital model base for all subsequent steps.

[0025] For example, high-precision 3D point cloud data or image data can be acquired by using a drone equipped with a high-resolution oblique photography camera to collect data on a target slope area. The drone needs to follow a preset flight path to collect multi-angle, high-overlap 3D (laser) point cloud data or image data of the slope to ensure no data blind spots.

[0026] When processing the data, the collected data is imported into the corresponding processing software. The software performs operations such as aerial triangulation encryption, multi-view image matching or point cloud registration, and noise reduction on the collected data to generate a high-density, high-precision 3D point cloud data model. The 3D point cloud data model is then constructed into a triangular mesh model with real geographic coordinates and elevation information, and real texture mapping is performed to finally obtain a slope surface real-scene 3D terrain model that is completely consistent with the actual landform.

[0027] S2, based on a real-world 3D terrain model, constructs a 3D geometric model of the protective net.

[0028] In this step, the two-dimensional planar alignment of the protective net is first planned and operated in the software. Then, the two-dimensional planar alignment is projected onto the surface of the real-world three-dimensional terrain model to generate a precise spatial three-dimensional protective net bottom installation baseline that fits the undulations of the ground. Based on this baseline, and according to the preset protective net height parameters, the top boundary line is generated by extending along the slope normal or gravity direction at each point on the baseline. The bottom installation baseline and the top boundary line are then connected to form a curved surface, constructing a three-dimensional geometric curved surface model of the protective net that is fully coupled with the real terrain.

[0029] For example, this step can be completed in the 3D modeling software Rhinoceros (hereinafter referred to as Rhino) and its parametric plugin Grasshopper. First, import the real-world 3D terrain model generated by S1 (usually in .obj or .osgb format) into Rhino. Perform elevation, slope, and aspect analysis on the model, generating visualization files (such as elevation rendering maps, contour maps, etc.). Based on engineering design specifications, geological hazard risk assessment results (such as potential rockfall source areas, trajectory predictions), and terrain analysis results, preliminarily plan and lay out the 2D planar alignment of one or more protective nets in the 2D top view or 3D view of the model, determining the orientation of the protective nets on the horizontal plane, such as... Figure 2 As shown.

[0030] The obtained two-dimensional planar alignment is then precisely projected onto the surface of the real-world three-dimensional terrain model to initially determine the bottom installation position of the protective netting. Specifically, as follows... Figure 3As shown, the two-dimensional plane line position Along the vertical plane (i.e.) Stretch along the axis to construct one or more vertical virtual projection planes. Calculate the virtual projection plane. With real-world 3D terrain model The intersection of these lines results in one or more spatial three-dimensional intersection lines that precisely conform to the undulations of the actual ground surface. These intersection lines serve as the baseline for the bottom installation of the protective netting structure on the real terrain. ,like Figure 4 As shown.

[0031] More specifically, in this embodiment, the point coordinates read from the 3D point cloud data model are: ,in , It is the total number of points. Let it be. Coordinates are Set initial value The generated 3D point set can be represented as , where each point The coordinates are These points are all located in of On a plane. The generated two-dimensional plane lines. It is a piecewise linear curve connecting these points.

[0032] Two-dimensional plane line position When stretching along a direction perpendicular to the horizontal plane, let the stretching height be... ,Pick The stretching vector is The first stretched surface generated It can be represented as: ; in, It is along Curve parameters, It is a parameter in the stretching direction, and The first stretched surface It can be regarded as being based on As the bottom line, along Extending in the positive direction of the axis The vertical plane of the height.

[0033] Two-dimensional plane line position along Directional translation, let The translation distance in the direction is ,and The translation vector is The translated curve It can be represented as Therefore, similarly, the generated second stretched surface It can be represented as: ; in, Is with Another parallel vertical plane, in Offset in axial direction The distance.

[0034] The continuous first stretched surface S1 and the second stretched surface S2 are converted into meshes, and these two meshes are represented as follows: and ,and , The terrain mesh of a realistic 3D terrain model can be represented as... ,calculate and The intersection of these lines results in a series of discontinuous line segments: ; These line segments need to be connected to form one or more continuous polylines, known as the bottom mounting baseline: ; Similarly, calculation and The intersection of these points ultimately yields: ; ; in, It is a projection of the physical interception location of the protective net onto the three-dimensional terrain, through and To quickly construct a physical protective network that simulates the interception effect of a protective network, such as... Figure 5 As shown.

[0035] Finally, starting from the bottom installation baseline, and based on the design height of the protective netting, extend upwards a specified distance along the slope normal or gravity direction at each baseline point to generate the top boundary line of the protective netting. Connect the bottom installation baseline and the top boundary line to generate one or more three-dimensional geometric surface models of the protective netting that are fully coupled to the real terrain and have a specified height and orientation. This model realistically reflects the shape and position of the protective netting in space.

[0036] S3, Construct a discrete element model (DEM) for dynamic analysis.

[0037] In this step, the 3D geometric surface model of the protective netting, and the rockfall source area model dynamically and automatically generated on the real-world 3D terrain model using adjustable parameters (such as slope, curvature threshold, etc.), are both converted into discrete element models composed of discrete particles. Specifically, the 3D geometric surface model of the protective netting is divided according to its components (such as supporting columns, wire mesh, etc.) to generate discrete element models separately, and each component is assigned independent physical and mechanical parameters; the rockfall source area model generates one or more rockfall particles in the corresponding space using a volume-filling algorithm.

[0038] It should be noted that the generation of the rockfall source area model can be divided into the following steps: First, determine the rockfall area based on geological survey data, surface weathering information, and the location of the main controlling structural planes. Second, obtain multiple closed mesh entities of the rockfall area through mesh Boolean operations based on the rockfall area and the location of the structural planes. Third, discretize the continuous mesh entities into a three-dimensional mesh, which is composed of many tiny cubic units, called "voxels". Fourth, generate spheres with the center points of all selected voxels as the sphere centers and half the size of the voxels as the radius, resulting in a sphere-particle combination. This sphere-particle combination is then converted into a discrete element model.

[0039] More specifically, in this embodiment, when constructing the discrete element model of the protective net, model parameters are defined. ,in This indicates the chord length spacing (horizontal spacing) of the particles along the bottom mounting baseline. This indicates the spacing between particles in the vertical direction (vertical spacing). Indicates the vertical particle hierarchy. Indicates the height of the supporting column. Indicates the frequency of the support column installation (per (One support column is set at each reference point). This represents the visual radius of the particle.

[0040] Continuous bottom mounting baseline Discretize into a set of ordered reference points : ; The generation of this set of points satisfies: , that is, the starting point; for any ,point It is on the curve From Moving forward The point obtained by the chord length distance, i.e. ,in This represents the integer index of the reference point. It is understandable that... The 0th row of particles constitutes the entire protective net, that is, the bottommost row of particles.

[0041] When constructing the other granular rows of the protective net, it is done by repeatedly vertically translating the reference point row. Therefore, for each vertical level index... Generate a corresponding horizontal granular row. Obviously, line 0 The reference point set itself, .set up for Unit vector of the axis The vector of a single vertical translation .therefore, By base row each point translates upwards times The distance is obtained, as follows: ; All horizontal particle rows The union of these points constitutes a complete set of horizontal protection points.

[0042] For vertical particle columns, each reference point is considered as the starting point of a "pillar," and each vertical particle column is generated independently. any reference point in , take it as the first The starting point for the generation of particles. Therefore, the first... A column of particles is also a set of points, extending from a reference point along... by Step size, repeat The secondary generation is as follows: ; All vertical particle columns The union of these also constitutes a complete set of vertical protection points.

[0043] Clearly, the combination of horizontal particle rows and vertical particle columns results in a complete protective mesh particle matrix. ,like Figure 6 As shown. Let any particle By its horizontal index and vertical index The coordinates of a point can be generated by the following function, which is uniquely defined: ; Therefore, the complete protective net particle matrix This can be expressed in set theory as: ; This allows the protective netting to be broken down and constructed from its constituent particles.

[0044] When constructing the supporting columns, based on the generated set of reference points , with parameters The step size is used to determine each pair of reference points corresponding to two adjacent support columns, so that each pair of reference points is spaced by a horizontal distance. Therefore, the first pair of reference points is... The second pair of base points is And so on, the first For the reference point ( (Counting from 0) , reference point pair It can also be expressed using set theory: ; in, It is the set of natural numbers (including 0). Each element in the equation is an ordered pair containing two particles, which restricts the position and outer diameter of the column, etc.

[0045] The vertical spacing and height of the column particles are the same as those of the main wire mesh, meaning that for any column reference point... Its corresponding vertical particle sequence Generated by the following function: ; Therefore, for each column reference point (i.e., the particle in the ordered pair), a starting point is generated, with... The step size extends upwards to the height. The point set, such as Figure 7 As shown. The complete point set of all column particles. It is the sequence of all individual column particles. The union of .

[0046] Furthermore, to facilitate the import of these geometric entities into computational scripts (such as Python), this embodiment further transforms the aforementioned mathematical set into an ordered list or array. Specifically, the point set... Convert it into a one-dimensional list, with the following structure: ; Each element in this list is a three-dimensional coordinate point. The total length of the list is For the set of column particles, it is transformed into a two-dimensional list, where each sublist represents an independent column, with the following structure: ; in yes The first in The point, i.e. the th point Each point serves as a reference point for the column.

[0047] for Each point in , build a For the center of the ball, The union of all spheres with radius r forms a visual model of the discrete elements of the protective net.

[0048] S4 constructs a dynamic simulation environment, configures the gravity field and contact models between various objects, performs dynamic simulation, simulates the entire process of falling rocks starting from the rockfall source area, moving along the slope until impacting the protective net, records and analyzes the simulation results, and extracts key data such as the trajectory of the falling rocks, the impact location, and the impact energy.

[0049] It should be noted that the contact models between various objects include those between falling rocks and the slope, between falling rocks themselves, and between falling rocks and the protective netting. Considering real-world conditions, these contact models are set up differently. For example, for the bouncing behavior of falling rocks, this embodiment uses a bounce solver based on explicit dynamics for simulation. This solver can maintain the system's kinetic energy and accurately simulate elastic collisions and momentum transfer between rigid bodies. By setting a series of physical targets such as gravity, solid collisions, and spherical collisions, and inputting them into the bounce solver, a high-fidelity dynamic simulation of the entire process of falling rocks from instability initiation, movement along the slope, to final impact with the protective structure can be performed.

[0050] For the rockfall-slope contact model, points representing the rockfall and solids representing the slope's closed mesh are connected to a SolidPointCollide component, setting the slope surface terrain as a rigid boundary to prevent rocks from crossing. In each iteration step, the component determines the characteristics of each rockfall particle. Whether it is located inside the closed grid of the slope, if it is inside, it is moved out using the following formula: ; in, This indicates the coordinates of the center point of the falling rock particles. It is the point on the slope surface closest to the center of the fallen rock particle. It is the shortest vector that "pushes" the center point of the falling rock particles out of the entity.

[0051] The bouncing behavior of falling rocks is controlled by the Bouncy Solve. When a collision is detected, the Bouncy Solve reverses the component of the falling rock's velocity vector perpendicular to the collision surface and sets the coefficient of restitution. It is a parameter between 0 and 1. This indicates a completely inelastic collision (no bounce). This represents a perfectly elastic collision. Friction is simulated by attenuating the tangential velocity component after the collision, further incorporating the coefficient of kinetic friction. The coefficient of dynamic friction is a parameter between 0 and 1. The larger the coefficient of dynamic friction, the faster the tangential velocity decays, and the more likely the falling rock is to stop sliding.

[0052] For the rockfall-to-rockfall contact model, Points representing the rocks are connected to the SphereCollide component, allowing multiple rocks to collide and bounce off each other. For any two rockfall particles... and This component calculates their center point coordinates. and The distance between them. A collision (overlap) is determined to have occurred if the following conditions are met: ; in and These are rock fragments and The radius.

[0053] For the contact model between falling rocks and protective netting, the contact mechanics relationship between the falling rock particles and the discrete element model of the protective netting is defined to accurately simulate the relatively complex process of energy transfer through the wire mesh to the pressure-reducing ring and supporting structure during impact. Therefore, Points representing falling rocks and Solids representing the protective netting are connected to the SolidPointCollide component to simulate the impact between the falling rocks and the protective netting.

[0054] During simulation, the dynamics solver is activated. Starting from time zero, it iteratively calculates the force, acceleration, velocity, and displacement of all particles within each tiny time step until all particles stop moving or exceed the calculation boundary. The falling rock trajectories obtained from multiple simulations are superimposed to form a three-dimensional trajectory envelope. This envelope is then spatially compared with the discrete element model (or three-dimensional geometric surface model) of the protective net to assess whether the deployment location of the protective net can effectively intercept most high-risk falling rock trajectories. If it cannot effectively intercept the falling rocks, the process returns to S1 to redesign the protective net.

[0055] Then, higher-precision model optimization and simulation are performed. The protective netting is discretized into a flexible structure composed of a large number of particles connected by contact models (such as linear springs or parallel connection models), and given realistic material mechanical parameters (such as the elastic modulus of steel wire, yield strength, force-displacement curve of pressure-reducing rings, etc.). Multiple spherical particles are rigidly bonded together using particle cluster technology to construct a non-spherical block model that can reflect the irregular shape, mass, center of mass, and moment of inertia of real falling rocks. The slope is set as a boundary wall with realistic contact stiffness, friction coefficient, and coefficient of restitution.

[0056] Based on further optimization of the model, a complete dynamic simulation calculation is performed. The software will iteratively solve the motion of the falling rock and the complex nonlinear interaction between the rock and the slope and the protective net within a small time step based on Newton's second law. The simulation results will be recorded and analyzed to extract key data such as the trajectory of the falling rock, the impact location, and the impact energy.

[0057] S5, based on the results of dynamic simulation, performs multi-objective iterative optimization to obtain a series of different design schemes and their corresponding design evaluation indicators, and selects the corresponding design scheme to complete the parametric design and optimization of the slope protection net.

[0058] In this step, design evaluation indicators are calculated across at least three dimensions: safety, reliability, and economic efficiency. The safety indicator is the interception rate calculated based on the number or mass of intercepted rocks; the reliability indicator is the impact energy margin obtained by comparing the simulated maximum impact energy with the energy absorption level of the protective net; and the economic indicator is the unit protection cost calculated based on the geometric parameters of the protective net and the unit price of materials. The key design parameters of the protective net are then used as input variables, and the design evaluation indicators are used as output targets to establish a parametric optimization model. The input variables are systematically adjusted, and steps S2 to S5 are repeated to obtain multiple design schemes and their corresponding design evaluation indicators. From these, the Pareto optimal solution is selected, providing a scientific basis for the final decision.

[0059] More specifically, in this embodiment, the interception rate is calculated as the percentage of the number (or total mass) of rocks successfully intercepted by the protective netting out of the total number (or total mass) of rocks originating from the rockfall source area. By analyzing the final resting position of the rocks, the number of rocks that landed above the protective netting (intercepted) and those that penetrated / crossed / bypassed the netting are counted. The interception rate is calculated using the formula: Interception Rate = (Number of Intercepted Rocks / Total Number of Rocks). 100% calculations are performed. This indicator directly reflects the effectiveness of the protective netting deployment location.

[0060] The impact energy margin is calculated as the difference or ratio between the design nominal energy absorption level of the protective net and the maximum impact energy it withstands in the simulation. This is achieved by comparing the maximum single impact energy or cumulative impact energy obtained from the simulation with the rated energy absorption level (e.g., 3000kJ) provided by the national standard or manufacturer for the selected protective net model. This indicator is used to determine the rationality of the protective net selection and the safety of the structure.

[0061] The unit protection cost is calculated based on the material and construction costs required to achieve the current protection effect. A cost estimation function is established based on the design parameters of the protective netting scheme (such as total netting length, height, post spacing, wire diameter, number of pressure-reducing rings, etc.), combined with material unit prices and construction rates. This indicator is used to compare the economics of different design schemes.

[0062] The inputs to the parametric optimization model are the key design parameters of the protective netting, including input variables such as installation baseline coordinates, netting height, post spacing, and material type. The optimization objectives of the parametric optimization model are: interception rate, impact energy margin, and unit protection cost. During the optimization process, a multi-scheme comparative analysis (parametric study) is performed. By systematically adjusting the input variables and running multiple sets of simulations, a series of different design schemes and their corresponding design evaluation indicators are obtained.

[0063] When making multi-objective trade-off decisions, the "interception rate," "impact energy margin," and "unit protection cost" of all options are plotted on a multi-dimensional coordinate system to form a design solution space. Based on the specific requirements of the project (such as risk level and budget constraints), one or more Pareto optimal solutions are selected from the solution space.

[0064] In practice, the optimization results of the design evaluation indicators are presented in the form of a three-dimensional scatter plot. The three axes represent the three optimization objectives, and all "non-dominated solutions" (i.e., Pareto fronts) can be clearly seen on the three-dimensional scatter plot. Decision-makers make choices based on external constraints and value judgments. For example, they can choose the lowest-cost solution among those with an interception rate of over 98%; or, within a budget limit of 2 million, they can choose the solution with the best overall performance in terms of interception rate and energy impact margin. This allows for a final design decision that balances safety, reliability, and economy, enabling efficient, accurate, and scientific completion of the design and optimization of slope protection nets.

[0065] Based on the same inventive concept, this embodiment also provides a parametric design and optimization system for slope protection nets based on a real-world 3D model, including a model building module, a discrete element transformation module, a dynamic simulation module, and an optimization decision module. The model building module generates a real-world 3D terrain model of the slope surface consistent with the actual landform, and then generates a 3D geometric model of the protection net. The discrete element transformation module generates a discrete element model from the 3D geometric model of the protection net for dynamic simulation. The dynamic simulation module constructs a dynamic simulation environment, configures the gravity field and contact models between various objects, and performs dynamic simulation on the discrete element model. The optimization decision module calculates design evaluation indicators, performs multi-objective iterative optimization, and obtains a series of different design schemes and their corresponding design evaluation indicators.

[0066] The system provided by this invention has the same inventive concept and beneficial effects as the aforementioned method, which will not be repeated here.

[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for parameterized design and optimization of slope protection net based on real scene three-dimensional model, characterized in that, The method comprises the following steps: S1, collecting target slope region data, and constructing a real scene three-dimensional terrain model; S2, based on the real scene three-dimensional terrain model, planning a two-dimensional plane line position of the protective net, projecting the two-dimensional plane line position to the surface of the real scene three-dimensional terrain model, generating a bottom installation baseline of the protective net accurately fitted to the ground surface, extending along the slope normal direction or gravity direction of each point position on the baseline according to a preset protective net height parameter, generating a top boundary line, and connecting the bottom installation baseline and the top boundary line to form a curved surface, thereby constructing a three-dimensional geometric curved surface model of the protective net completely coupled with the real terrain; S3, constructing a discrete element model for dynamic analysis, including a protective net discrete element model and a rockfall source area discrete element model, the protective net discrete element model being divided according to components and each component being given corresponding physical and mechanical parameters, and the rockfall source area discrete element model generating rockfall particles in the corresponding space; S4, constructing a dynamic simulation environment, configuring a gravity field and a contact model between objects, performing dynamic simulation, and recording and analyzing simulation results; the contact model includes a contact model between rockfalls and slope bodies, a contact model between rockfalls, and a contact model between rockfalls and protective nets; S5, based on the dynamic simulation results, performing multi-objective iterative optimization to obtain a series of different design schemes and corresponding design evaluation indexes, selecting a design scheme, and completing parameterized design and optimization of the slope protective net.

2. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 1, characterized in that, In S1, the obtained three-dimensional point cloud or image data of the target slope region is processed to generate a three-dimensional point cloud data model with reasonable density and accuracy, the three-dimensional point cloud data model is constructed into a triangular mesh model with real geographic coordinates and elevation information, real texture mapping is performed, and a slope surface real scene three-dimensional terrain model completely consistent with the actual topography is obtained.

3. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 1, characterized in that, In S2, according to the engineering design specification, the geological disaster risk assessment result and the terrain analysis result, one or more two-dimensional plane line positions of the protective net are planned and laid out in the two-dimensional plan view or the three-dimensional view of the real scene three-dimensional terrain model to determine the trend of the protective net in the horizontal plane.

4. The method according to claim 3, wherein, In S2, the two-dimensional plane line position is stretched in the direction perpendicular to the horizontal plane to construct one or more vertical virtual projection planes, the intersection of the virtual projection planes and the real scene three-dimensional terrain model is calculated, the result is one or more spatial three-dimensional intersection lines accurately fitted to the real ground surface, the bottom installation baseline of the protective net on the real terrain is obtained, the top boundary line of the protective net is generated by extending a specified distance upward along the slope normal direction or gravity direction of each baseline point position according to the design height of the protective net, and the three-dimensional geometric curved surface model of the protective net is generated by connecting the bottom installation baseline and the top boundary line.

5. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 1, characterized in that, In the construction of the protective network discrete element model in S3, the model parameters are defined , represents the chord length interval of the particles along the bottom-mounted baseline, represents the vertical interval of the particles, represents the vertical level of the particles, represents the height of the support column, represents the layout interval frequency of the support column, represents the visualization radius of the particles; The continuous bottom installation baseline is discretized into a set of ordered reference points, and the reference points are repeatedly vertically translated to construct transverse particle rows; Each reference point independently generates each column of vertical particles to construct longitudinal particle columns, and the complete protective net particle matrix is obtained by combining all the transverse particle rows and the longitudinal particle columns.

6. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 5, characterized in that, In constructing the support column, based on the generated reference point set, each pair of reference points corresponding to two adjacent support columns is determined with a parameter as the step length, so that each pair of reference points is spaced apart by a horizontal interval , and the vertical interval and height of the column particles are the same as those of the protective net itself.

7. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 1, characterized in that, In S4, for the rockfall-slope contact model, the slope surface is set as a rigid boundary to prevent rocks from crossing. In each iteration step, each rockfall particle is analyzed. Whether it is located inside the closed grid of the slope, if it is inside, it is moved out using the following formula: ； wherein, represents the coordinates of the center point of the rockfall particle, is the coordinates of the point on the slope surface topography closest to the center point of the rockfall particle, is the shortest vector that pushes the center point of the rockfall particle out of the solid; the bouncing behavior of the rockfall is controlled by a spring force solver that, when a collision is detected, reverses the component of the rockfall velocity vector perpendicular to the collision face while setting a restitution coefficient ; friction is simulated by decaying the tangential velocity component after a collision, introducing a dynamic friction coefficient , the greater the dynamic friction coefficient, the faster the tangential velocity decays, the more the rockfall tends to stop sliding; For the rockfall and rockfall contact model, a plurality of rockfalls are set to collide with each other and bounce off. For any two rockfall particles and , the distance between their center point coordinates and is calculated ; if the following conditions are met, it is determined that a collision has occurred: ； wherein and are the radii of the rockfall particles and respectively. For the model of rockfall impacting the protection net, the contact mechanics between the rockfall particle and the protection net is defined, and the process of energy transmission from the impacting rockfall to the supporting structure through the protection net is simulated.

8. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 7, characterized in that, In S4, the protection net is discretized into a flexible structure connected by a large number of particles through a contact model, and real material mechanics parameters are assigned; the particle cluster technology is used to rigidly bond multiple spherical particles to construct a non-spherical block model that can reflect the real irregular shape, mass, center of mass, and moment of inertia of the rockfall; the slope surface is set as a boundary wall with real contact stiffness, friction coefficient, and restitution coefficient.

9. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 1, characterized in that, In S3, three-dimensional design evaluation indicators are set: safety indicators, reliability indicators, and economic indicators; The safety indicators are the interception rate calculated according to the number or mass of intercepted rockfalls; the reliability indicators are the impact energy margin obtained by comparing the maximum impact energy and the design energy absorption level of the protection net; The economic indicators are the unit protection cost calculated according to the geometric parameters of the protection net and the material unit price.

10. The real-scene three-dimensional model based parameterized design and optimization method of slope protection net according to claim 9, characterized in that, In S5, the key design parameters of the protection net are taken as input variables, and the design evaluation indicators are taken as output targets to establish a parameterized optimization model. The input variables are adjusted, and S2 to S5 are repeatedly executed to obtain multiple design schemes and corresponding design evaluation indicators, and the Pareto optimal solution is selected from them.

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