Numerical model generation method for two-dimensional discontinuous sensitivity analysis of slope and related equipment

Abstract

The present application relates to the technical field of slope engineering, and particularly relates to a method for generating a two-dimensional non-continuous sensitivity analysis numerical model of a slope and related equipment. The method comprises the following steps: generating a two-dimensional geological profile by using surface, stratum and geological object information; constructing a lithology model by using spatial topological relations and a cutting closure algorithm; generating a fracture model and a joint model based on the lithology model; establishing an inheritance relationship among the three models to determine a shared part of a command stream file; selecting any one of the models as a parent model; constructing a child model according to sensitivity analysis requirements; and compiling a command stream file of the child model according to the inheritance relationship. Finally, the command stream file is converted in batches by using a two-dimensional non-continuous numerical calculation software to generate an executable sensitivity analysis numerical model, and efficient and accurate sensitivity evaluation of a geological model is achieved.

Description

Technical Field

[0001] This invention relates to the field of slope engineering technology, specifically to a method and related equipment for generating numerical models for two-dimensional discontinuous sensitivity analysis of slopes. Background Technology

[0002] In the field of slope stability analysis, two-dimensional discontinuous numerical simulation and sensitivity analysis are core technologies widely used in the industry. The modeling process typically requires adherence to the specific requirements of the computational software. Currently, the mainstream technical approaches fall into two categories: one involves manually constructing numerical models one by one, while the other utilizes custom modeling software such as Griddle for assistance. To improve modeling efficiency, existing research largely focuses on the direct conversion of engineering data (such as three-dimensional geological models or two-dimensional drawings) into computational models. For example, patent application CN111553007A discloses a method for converting a three-dimensional geological model of a slope into a two-dimensional calculation profile. The method uses closure processing with cutting lines to meet the material zoning closure requirements, but the generated "calculation profile" only has a geometric shape and lacks direct calculation functionality. Patent application CN111553007B further proposes a method for automatically generating multiple geometric conditions under multiple working condition combinations, but its results are still limited to the geometric part of the calculation model, do not involve specific calculation software, and cannot perform calculations. Patent application CN114021214A describes a method for generating a UDEC calculation model based on a geological profile map. Although it can perform calculations, it only supports a single software and cannot batch create multiple models required for sensitivity analysis. Overall, existing technologies, whether using manual construction or specific software assistance, require building numerical calculation models one by one, making it difficult to achieve batch automated construction of multiple calculation models from engineering data.

[0003] However, the aforementioned existing technologies have significant limitations: First, the models generated by existing conversion methods only represent the geometric part or are only applicable to a single software, failing to directly form a computable model containing complete information such as calculation parameters and boundary conditions, requiring additional manual intervention. Second, the need to build multiple computational models in batches (such as multi-condition models required for sensitivity analysis) is not effectively met, leading to inefficiency in scenarios requiring a large number of model calculations. Third, existing technologies lack sufficient support for multi-software compatibility, only generating computational files executable by specific software, limiting the model's versatility and cross-software reusability. These problems result in complex and time-consuming modeling processes in slope stability analysis, making it difficult to adapt to the batch analysis needs of multiple software and multiple conditions, becoming a key technical bottleneck restricting the improvement of numerical simulation efficiency and large-scale application. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and related equipment for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes, which addresses the shortcomings of the prior art. This method solves the problem that the prior art does not support compatibility with multiple software, can only generate calculation files that can be executed by specific software, and thus limits the model's versatility and cross-software reusability.

[0005] The objective of this invention is achieved through the following technical solutions: In a first aspect, the present invention provides a method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes, comprising: Obtain a two-dimensional geological profile of the slope in the target area; the two-dimensional geological profile should include at least information on the surface, strata, and geological objects. Based on the surface, strata and geological object information in the two-dimensional geological profile, lithological models of several material partitions are generated using spatial topological relationships and cutting and closing algorithms. Based on the lithological models, fracture models and joint models are generated. The inheritance relationship between the lithological models, fracture models and joint models is established. Based on the inheritance relationship, the shareable parts of each model command stream file are determined. Choose any one of the lithology model, fracture model, and joint model as the parent model, and construct a corresponding number of sensitivity analysis models as child models according to the content to be carried out in the sensitivity analysis. Based on the inheritance relationship between the parent and child models, each child model is compiled into a command stream file at once; Two-dimensional discontinuous numerical calculation software is used to convert the command stream files corresponding to each sub-model, thereby generating corresponding executable sensitivity analysis numerical models in batches.

[0006] As a further improvement of the present invention, the strata in the two-dimensional geological profile include the boundary lines of different lithologies, the boundary lines of different weathering degrees, and the boundary lines of different unloading types. The degree of weathering includes unweathered, slightly weathered, weakly weathered, strongly weathered, completely weathered, and residual soil; The unloading types include strong unloading, weak unloading, and deep unloading.

[0007] As a further improvement of the present invention, obtaining a two-dimensional geological profile of the slope of the target area includes: When the acquired two-dimensional geological profile is a dwg or dxf file, the attribute information and geometric information in the file are read directly; the attribute information includes the layer names of various boundary lines; the geometric information includes the boundary line node numbers and node coordinates; When the obtained two-dimensional geological profile is a text or image file, attribute information and geometric information are obtained using image recognition extraction technology.

[0008] As a further improvement of the present invention, a lithological model is generated using spatial topological relationships and a cutting and closing algorithm, and a fracture model and a joint model are generated based on the lithological model, including: Two-dimensional geological profiles are converted into lithological models containing several material partitions using spatial topological relationships and cutting closure algorithms. Add fractures to the lithology model to generate a fracture model, and then combine the fracture model with joints to obtain a joint model. When the lithological model is free of fractures, a joint model is generated based on the lithological model and the joints.

[0009] As a further improvement of the present invention, the joint model is added and generated according to the lithology model or fracture model in a random joint group generation manner; The random joint group generation method includes: generating random joint groups that conform to statistical characteristics using the Monte Carlo method based on the geometric statistical distribution type and parameters of joint length, spacing, dip angle and dip direction of each dominant joint group; The geometrical statistical distribution types include power-law distribution, Gaussian distribution, negative exponential distribution, normal distribution, log-normal distribution, uniform distribution, and Poisson distribution.

[0010] As a further improvement of the present invention, a corresponding number of sensitivity analysis models are constructed as sub-models based on the content to be subjected to sensitivity analysis, including: When the parent model is a lithological model, the sensitivity analysis includes grid size, water level, and parameters specified by different soil and rock constitutive models. When the parent model is a fracture model, the sensitivity analysis includes parameters specified by several joint constitutive models and different element combinations of several fractures. When the parent model is a joint model, the sensitivity analysis includes the geometric and statistical distribution parameters of joint length, spacing, dip angle, and dip direction of each dominant joint group in random joints, parameters specified by several joint constitutive models, and different element combinations of several dominant joint groups.

[0011] As a further improvement of the present invention, a corresponding number of sensitivity analysis models are constructed based on the content to be subjected to sensitivity analysis. The methods for constructing sensitivity analysis models include the following two approaches: The first approach is to directly create corresponding sensitivity analysis models in batches under the selected parent model based on the content to be analyzed. The second approach involves passing the same set of sensitivity analysis content to any parent model with an inheritance relationship, based on the inheritance relationship between the lithology model, fracture model, and joint model, to create corresponding sensitivity analysis models in batches.

[0012] Secondly, the present invention provides a numerical model generation system for two-dimensional discontinuous sensitivity analysis of slopes, used to implement the above-mentioned method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes, comprising: The data acquisition module is used to acquire two-dimensional geological profiles of the slopes in the target area; the two-dimensional geological profiles include at least information on the surface, strata, and geological objects. The model generation module is used to generate lithological models of several material partitions based on the surface, strata and geological object information in the two-dimensional geological profile map, using spatial topological relationships and cutting and closing algorithms. Based on the lithological models, fracture models and joint models are generated, the inheritance relationship between the lithological models, fracture models and joint models is established, and the shareable parts of each model command stream file are determined according to the inheritance relationship. The model processing module is used to select any one of the lithology model, fracture model, and joint model as the parent model, and construct a corresponding number of sensitivity analysis models as child models according to the content to be carried out in the sensitivity analysis. The model conversion module is used to compile each child model into a command stream file based on the inheritance relationship between the parent and child models; The numerical model generation module is used to convert the command stream files corresponding to each sub-model using two-dimensional discontinuous numerical computing software, thereby generating corresponding executable sensitivity analysis numerical models in batches.

[0013] Thirdly, the present invention provides a computer-readable storage medium for storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform the above-described method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes.

[0014] Fourthly, the present invention provides a computing device, comprising: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including steps for performing the steps in the above-described method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes.

[0015] The beneficial effects of this invention are as follows: This invention provides a method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes. By acquiring information on the surface, strata, and geological objects contained in a two-dimensional geological profile of the slope, a lithological model is generated using spatial topological relationships and a cutting and closing algorithm. Based on this, a fracture model and a joint model are constructed. An inheritance relationship among the three is established to determine the shareable parts of the command flow file, thereby achieving the reuse of geological parameters and improving modeling efficiency. Any model is selected as the parent model to construct a sensitivity analysis sub-model. The sub-model command flow file is compiled according to the inheritance relationship. Two-dimensional discontinuous numerical calculation software is used to batch convert and generate executable numerical models. This ensures the consistency of geological parameters between the sub-model and the parent model, and avoids repetitive modeling work by sharing parts. Each technical feature corresponds to an independent effect such as reducing modeling redundancy, improving parameter accuracy, and enhancing the targeting of analysis. Together, they achieve the standardization and automation of the geological model construction-analysis process in slope stability assessment, significantly improving modeling efficiency and analysis accuracy compared to existing technologies. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a method for batch generating numerical models for two-dimensional discontinuous sensitivity analysis of slopes, provided by an embodiment of the present invention. Figure 2 This is a schematic diagram of a two-dimensional geological profile provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the three-level model inheritance system based on two-dimensional geological profiles to generate lithology model, fracture model, and joint model, provided in an embodiment of the present invention. Figure 4 This is a schematic diagram of the batch generation of sensitivity analysis models based on a three-level model inheritance system for selecting sensitivity parameters, provided in an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating how a sensitivity analysis model is automatically compiled into a command stream file in batches according to a custom rule, as provided in an embodiment of the present invention. Figure 6 This is a schematic diagram illustrating how a command stream file is converted into a numerical calculation model required and executable by a selected two-dimensional discontinuous numerical calculation software, as provided in an embodiment of the present invention. Figure 7 This is an internal structural diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives and technical solutions of this invention clearer and easier to understand, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0019] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Example 1 In the discontinuous sensitivity analysis of slope engineering, traditional numerical model generation methods have many limitations: on the one hand, independent models need to be constructed for different geological elements such as lithology, fractures, and joints, and the lack of effective correlation between models leads to a large amount of repetitive modeling work and low efficiency; on the other hand, sensitivity analysis requires the generation of a large number of sub-models based on multiple parameter combinations, and existing methods are difficult to achieve rapid batch generation of sub-models, and the parameter transfer between parent and sub-models is prone to deviation, affecting the accuracy and reliability of the analysis results. In addition, the command flow files of different models are mostly independently compiled, and common content cannot be shared, further increasing the modeling cost and error risk. To solve the above problems, this embodiment proposes a numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes.

[0021] The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes mainly includes the following steps: obtaining a two-dimensional geological profile of the slope in the target area; the two-dimensional geological profile includes at least surface, strata, and geological object information; based on the surface, strata, and geological object information in the two-dimensional geological profile, generating a lithological model using spatial topological relationships and cutting closure algorithms; generating a fracture model and a joint model based on the lithological model; establishing the inheritance relationship between the lithological model, fracture model, and joint model; determining the shareable parts in the command flow files of each model based on the inheritance relationship; selecting any one of the lithological model, fracture model, and joint model as the parent model; constructing a corresponding number of sensitivity analysis models as child models according to the content to be sensitively analyzed; compiling each child model into a command flow file according to the inheritance relationship between the parent model and the child models; and using two-dimensional discontinuous numerical calculation software to convert the command flow files corresponding to each child model, thereby generating corresponding executable sensitivity analysis numerical models in batches.

[0022] The working principle of this embodiment is as follows: using a two-dimensional geological profile of the slope in the target area as the basic data source, the geological information is transformed into a structured lithological model through spatial topological relationships and cutting closure algorithms. Then, using the lithological model as a reference, fracture and joint models are generated, ensuring the spatial and parameter correlation between the models, i.e., inheritance. This inheritance relationship allows the command flow files of each model to share common content, reducing repetitive coding. After selecting the parent model based on sensitivity analysis, the child models only need to modify sensitive parameters; other parameters are inherited from the parent model, ensuring consistency between models. Finally, the batch processing function of the two-dimensional discontinuous numerical calculation software is used to convert the child model command flow files into executable models in batches, achieving efficient conversion from geological data to analysis models. Throughout the process, each step is closely linked, and the parameter transfer between the parent and child models is precise, ensuring the reliability of the models.

[0023] The selection of the target area needs to be determined based on the actual needs of the project, and may include slope engineering survey areas, potential disaster risk areas, etc. If the two-dimensional geological profile is in DWG or DXF file format, the attribute information such as layer names of various boundaries and the geometric information such as node numbers and node coordinates contained in the boundary can be directly read. The two-dimensional geological profile can also be in PDF or other text or image formats, in which case the corresponding image recognition and extraction technology can be used to obtain the attribute information such as text annotations of the corresponding boundaries and the geometric information such as nodes on the boundaries.

[0024] A two-dimensional geological profile of a slope should at least include the surface and strata, but may also include geological features such as water level and faults. The strata in the two-dimensional geological profile include boundaries between different lithologies, different degrees of weathering, and different unloading types. Weathering degrees include unweathered, slightly weathered, weakly weathered, strongly weathered, completely weathered, and residual soil; unloading types include strong unloading, weak unloading, and deep unloading.

[0025] Furthermore, spatial topological relationships and cutting closure algorithms are used to convert two-dimensional geological profiles into lithological models containing several material partitions; fractures are added to the lithological model to generate a fracture model, and joint models are obtained by combining the fracture model with joints; when the lithological model has no fractures, joint models are generated by combining the lithological model with joints.

[0026] During the generation of the lithological model, the lithology of the strata needs to be initially determined based on the relative age and spatial location of the lithological layers. For example, in recumbent folds, there may be alternating lithological boundaries between older and younger strata. In this case, the name of the alternating lithological boundary at the upper part represents the lithology of the layer immediately adjacent to the lower part of the boundary, and the name of the alternating lithological boundary at the lower part represents the lithology of the layer immediately adjacent to the upper part of the boundary. When identifying the corresponding material zones in the generated lithological model, it is necessary to comprehensively determine the lithological combination corresponding to the material by combining the boundary type and spatial relative relationship of the material zone. For example, if the lithology of material zone one has been initially determined to be limestone, and the upper boundary line is strongly weathered and the lower boundary line is weakly weathered, then according to the usual spatial logic of strongly weathered and weakly weathered, it is determined to be weakly weathered limestone. After automatically identifying the corresponding material zones in the generated lithological model in this embodiment, manual inspection and adjustment are supported through a visual interface.

[0027] In addition, when generating a fracture model based on a lithology model, if there are cases where the fracture does not cut through the rock mass, the original shape of the fracture can be maintained by introducing auxiliary lines that intersect with the fracture endpoints. The auxiliary lines are then assigned to fractures with higher joint constitutive parameters to maintain the continuity of the rock mass and generate a fracture model that conforms to the original fracture shape.

[0028] The joint model is generated by adding random joint groups based on the lithology model or fracture model. Specifically, the random joint group generation method includes: generating random joint groups that meet statistical characteristics using the Monte Carlo method based on the geometric statistical distribution type and parameters of the joint length, spacing, dip angle, and dip direction of each dominant joint group. The geometric statistical distribution can be selected from power-law distribution, Gaussian distribution, negative exponential distribution, normal distribution, log-normal distribution, uniform distribution, Poisson distribution, etc.

[0029] When a two-dimensional geological profile includes a water level, the water level line does not directly participate in the process of generating material partitions for lithology models, fracture models, and joint models. However, it records the material partitions through which the water level line passes, establishes the relationship between the water level and the material partitions, and facilitates the identification of different parts of the computational grid above and below the water level within the same material partition when generating the computational model, and then assigns differentiated values ​​to the groups.

[0030] The inheritance relationship among the lithology model, fracture model, and joint model means that the lithology model serves as the basic model, while the fracture and joint models are generated by combining fractures and joints on the basis of inheriting all the information of the lithology model. If fractures cannot be obtained, the joint model can be generated directly on the basis of the lithology model. If fractures can be obtained, the fracture model is first generated based on the lithology model, and then the joint model is generated by combining the fracture model with the joints.

[0031] Based on the content to be analyzed, a corresponding number of sensitivity analysis models are constructed as sub-models. These sub-models further include: when the parent model is a lithology model, the sensitivity analysis content includes grid size, water level, and parameters specified by various soil and rock constitutive models; when the parent model is a fracture model, the sensitivity analysis content includes parameters specified by several joint constitutive models and fracture combination methods; when the parent model is a joint model, the sensitivity analysis content includes geometric statistical distribution parameters such as joint length, spacing, dip angle, and dip direction of each dominant joint group in random joints, parameters specified by several joint constitutive models, and the combination methods of each dominant joint group.

[0032] Specifically, the sensitivity considerations for lithological model selection mainly include numerical parameters, such as mesh size, water level, and parameters specified by different soil and rock constitutive models, such as the friction angle specified by the Mohr-Coulomb elastoplastic constitutive model. Cohesion Tensile strength T, uniaxial compressive strength as specified by the Hoek-Brown elastoplastic constitutive model. Lithological index mi, geological strength index GSI, etc.

[0033] Preferably, the sensitivity parameters selected for the fracture model include numerical parameters and combined parameters; among which, the numerical parameters include parameters specified by various joint constitutive models, such as the friction angle specified by the Mohr-Coulomb joint constitutive model. Cohesion Tensile strength T, joint roughness coefficient JRC as specified by the Barton-Bandis joint constitutive model, joint wall compressive strength JCS, and residual friction angle. Common parameters include normal stiffness Kn and tangential stiffness Ks; combined parameters refer to different combinations of elements that can be considered sequentially, from considering one fracture to considering all fractures, when multiple fractures exist.

[0034] There are two methods for selecting sensitive content in the process of creating a batch sensitivity analysis model based on the selected sensitivity parameters: single-factor selection and multi-factor selection. Single-factor selection involves choosing only one sensitivity parameter from all available parameters, with multiple data points for that parameter, while keeping other unselected sensitivity parameters unchanged. Multi-factor selection allows selecting multiple sensitivity parameters from all available parameters, with each parameter having the same value as in the single-factor selection method, while keeping other unselected sensitivity parameters unchanged. If a numerical parameter is selected, batch data can be obtained using any of the following methods: sampling values ​​at uniform intervals within a specified range, sampling using a set probability distribution, or free selection. If a combined parameter is selected, batch data can be obtained by selecting any number of elements from all combinations of that parameter. Finally, the obtained batch data is automatically assigned to the corresponding model to generate the batch sensitivity analysis model.

[0035] If the selected parameters are sensitivity parameters for the lithology model, the corresponding sensitivity analysis model can be generated not only at the level below the lithology model, but also at the level below the fracture model and the joint model respectively; if the selected parameters are sensitivity parameters for the fracture model, the corresponding sensitivity analysis model can be generated not only at the level below the fracture model, but also at the level below the joint model.

[0036] There are two methods for constructing sensitivity analysis models: The first method is to directly create corresponding sensitivity analysis models in batches under the selected parent model according to the content to be sensitively analyzed; the second method is to pass the same set of sensitivity analysis content to any parent model with inheritance relationship according to the inheritance relationship between lithology model, fracture model and joint model, and create corresponding sensitivity analysis models in batches.

[0037] Additionally, it should be noted that the inheritance relationship between parent and child models is automatically constructed based on the parent-child relationship, including the following situations: when the content of the selected parent model is adjusted, not only will the child models of the next level of the selected parent model be adjusted accordingly, but the child models of other parent models that have an inheritance relationship with the selected parent model will also be adjusted synchronously.

[0038] The custom rules and generated content for the command flow differ depending on the parent model at the higher level of the sensitivity analysis model: the command flow file for the lithology model includes boundary conditions, material partition names, node coordinates of the material partitions, the geotechnical constitutive model and related parameters corresponding to the material partitions, and the computational grid within the material partitions; the command flow file for the fracture model, in addition to the command flow of the lithology model, should also include fracture numbers, node coordinates of the fractures, material partition numbers through which the fractures pass, joint constitutive models and related parameters of the fractures, and auxiliary line information; regardless of whether the joint model is generated based on the rock mass model or the fracture model, the command flow file for the joint model should, in addition to the command flow of the corresponding model, add the numbers of each dominant joint group under the random joint group, the geometric distribution under each dominant joint group, and the constitutive model and parameter information of the corresponding joints.

[0039] Two-dimensional discontinuous numerical calculation software can include UDEC (two-dimensional discrete element method), DDA (two-dimensional discontinuous deformation analysis method), and GDEM (finite element and discrete element coupled software).

[0040] The process of automatically converting command stream files into numerical calculation models can automatically extract relevant numbers, letters, symbols, and other information from the command stream files and rearrange and organize them according to the specific content requirements of the numerical calculation models that the selected calculation software can execute.

[0041] Example 2 Figure 1 This is a flowchart illustrating a method for batch generating numerical models for two-dimensional discontinuous sensitivity analysis of slopes, as provided in this embodiment of the invention. Figure 1 As shown, the batch generation method includes: S100, such as Figure 2 The two-dimensional geological profile shown includes the surface, the lithological boundaries of sandstone, mudstone and limestone with recumbent fold structures, the boundaries of completely weathered, strongly weathered and weakly weathered, and geological objects such as faults F1, F2 and F3. S200 automatically transforms two-dimensional geological profiles of slopes into lithological models containing multiple material partitions using spatial topological relationships and cutting / closing algorithms; among which, for example... Figure 2 The stratigraphic structure shown in the two-dimensional geological profile of the slope is a horizontal fold structure with alternating boundaries between old and new strata. Combined with the weathering degree boundary, a lithological model is generated that includes eight material zones: completely weathered sandstone, strongly weathered sandstone, weakly weathered sandstone, completely weathered mudstone, strongly weathered mudstone, weakly weathered mudstone, strongly weathered limestone, and weakly weathered limestone. Figure 2 The two-dimensional slope geological profile also includes faults F1, F2, and F3. Fault F1's two endpoints intersect the bottom boundary of the slope and the boundary between completely weathered and strongly weathered sections, meaning Fault F1 traverses all the material zones it passes through. Fault F2's two endpoints intersect the boundary between completely weathered and strongly weathered sections and Fault F1, respectively, meaning Fault F2, in combination with Fault F1, also traverses all the material zones it passes through. The lower endpoint of Fault F3 does not intersect with other boundaries, so a horizontal auxiliary line is introduced to intersect the lower endpoint of Fault F3 to maintain its original shape and achieve the goal of traversing all the material zones it passes through. This auxiliary line is used as a fault with a higher joint constitutive parameter value to maintain the continuity of the rock mass. By introducing this auxiliary line, a corresponding fault model is formed by jointly cutting along the lithological model. Supplementary data from other sources revealed three dominant joint groups, J1, J2, and J3, within the slope. All joint parameters exhibited a normal distribution. Specifically, J1 had a mean joint spacing and corresponding standard deviation of 0.5m and 0.1m, a mean length and corresponding standard deviation of 2m and 0.2m, and a mean dip angle and corresponding standard deviation of 12° and 2°, with the dip direction aligned with the slope's strike. J2 had a mean joint spacing and corresponding standard deviation of 1.5m and 0.2m, a mean length and corresponding standard deviation of 3m and 0.2m, and a mean dip angle and corresponding standard deviation of 27° and 2°, also aligned with the slope's strike. J3 had a mean joint spacing and corresponding standard deviation of 0.8m and 0.2m, a mean length and corresponding standard deviation of 2.2m and 0.2m, and a mean dip angle and corresponding standard deviation of 38° and 2°, also aligned with the slope's strike. Based on these joint distribution types and parameters, Monte Carlo methods were automatically adopted. The Carlo method generates random joint groups that conform to statistical characteristics. If the fractures F1, F2, and F3 are not considered, a joint model containing three dominant joint groups J1, J2, and J3 can be directly generated based on the lithological model. If the fractures F1, F2, and F3 are considered, a joint model containing three dominant joint groups J1, J2, and J3 is generated based on the fracture model according to the inheritance order.

[0042] S300, such as Figure 4 As shown, sensitivity analysis was performed on the lithology model, fracture model, and joint model using single-factor analysis. Among the sensitivity analysis parameters, the lithology parameter is the cohesion specified by the Mohr-Coulomb elastoplastic model in completely weathered sandstone, with a value range of 1 MPa to 5 MPa. Five sample values ​​were obtained sequentially in increments of 1 MPa. Then, five corresponding sensitivity analysis models were created in batches at the next level below the lithology model. Based on the inheritance relationship between the fracture model, joint model, and lithology model, the lithology parameter was passed to the fracture model and joint model to generate the corresponding next-level sensitivity analysis model.

[0043] like Figure 4 As shown, the fracture parameter in the sensitivity analysis is selected as the friction angle specified by the Mohr-Coulomb joint constitutive model in fracture F1, with a value range of 32° to 42°. Six sample values ​​are obtained in increments of 2°. Then, six corresponding sensitivity analysis models are created in batches at the next level below the fracture model. Based on the inheritance relationship between the fracture model and the joint model, the lithological parameters are passed to the joint model to generate the corresponding next-level sensitivity analysis model.

[0044] like Figure 4As shown, the joint parameter in the sensitivity analysis is the normal stiffness of joint group J1, with a value range of 1GPa to 10GPa. Ten sample values ​​are obtained in increments of 1GPa, and ten corresponding sensitivity analysis models are created in batches at the next level of the joint model. S400, such as Figure 5 As shown, the sensitivity analysis models are automatically batch-compiled into command flow files according to custom rules. If the parent model of the sensitivity analysis model is a lithological model, the command flow file includes boundary conditions, names of 8 material partitions, node coordinates of the 8 material partitions, geotechnical constitutive models and related parameters corresponding to the 8 material partitions, and computational grids within the material partitions. If the parent model of the sensitivity analysis model is a fracture model, the command flow file should also include 3 fracture numbers, node coordinates of the 3 fractures, material partition numbers traversed by the 3 fractures, joint constitutive models and related parameters of the 3 fractures, and auxiliary line information, based on the lithological model command flow. If the parent model of the sensitivity analysis model is a joint model, the corresponding command file can, depending on whether fracture is considered, add the numbers of 3 dominant joint groups, the geometric distribution under the 3 dominant joint groups, and the constitutive models and parameter information of the corresponding joints, based on the lithological model or fracture model.

[0045] S500, such as Figure 6 As shown, based on the specific content requirements of the calculation model files of the proposed two-dimensional discontinuous numerical calculation software type, such as the two-dimensional discrete element software UDEC, the two-dimensional discontinuous deformation analysis software DDA, and the finite element and discrete element coupled software GDEM, the relevant numbers, letters, symbols and other information in the command stream files are automatically extracted, rearranged and organized, and all command stream files are batched into numerical calculation models required and executable by the selected two-dimensional discontinuous numerical calculation software.

[0046] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved. This embodiment does not impose any limitations on these steps.

[0047] This embodiment automatically converts common and widely used two-dimensional geological profile data in slope engineering into a three-level model inheritance system: lithology model, fracture model, and joint model. This ensures the consistency of basic lithological information between models and the transferability of fracture and joint information, avoiding repetitive operations, reducing the probability of errors, and improving conversion efficiency. Based on the three-level model inheritance system, the efficiency of sensitivity parameter transfer is improved, repetitive operations are reduced, and a multi-dimensional sensitivity analysis system is quickly and systematically established. This helps relevant technical personnel to more comprehensively and effectively analyze the control parameters affecting slope stability. The built-in command flow conversion method can automatically and quickly convert sensitivity analysis models into command flow files executable by various continuous and non-continuous numerical calculation software in batches. This establishes a complete calculation model generation system and improves the compatibility of calculation models, replacing traditional manual conversion operations, improving conversion efficiency, reducing the error rate of manual writing, and allowing relevant technical personnel to focus their energy and time on subsequent calculation and analysis, thus liberating and developing productivity.

[0048] Example 3 Based on the numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes in Embodiments 1 and 2, this embodiment provides a numerical model generation system for two-dimensional discontinuous sensitivity analysis of slopes. The system includes: a data acquisition module, used to acquire a two-dimensional geological profile of the slope in the target area; the two-dimensional geological profile includes at least information on the surface, strata, and geological objects. The model generation module is used to generate a lithological model based on the surface, strata and geological object information in the two-dimensional geological profile map, using spatial topological relationships and cutting and closing algorithms. Based on the lithological model, a fracture model and a joint model are generated. The inheritance relationship between the lithological model, the fracture model and the joint model is established, and the shareable parts of each model command stream file are determined according to the inheritance relationship. The model processing module is used to select any one of the lithology model, fracture model, and joint model as the parent model, and construct a corresponding number of sensitivity analysis models as child models according to the content to be carried out in the sensitivity analysis. The model conversion module is used to compile each child model into a command stream file based on the inheritance relationship between the parent and child models; The numerical model generation module is used to convert the command stream files corresponding to each sub-model using two-dimensional discontinuous numerical computing software, thereby generating corresponding executable sensitivity analysis numerical models in batches.

[0049] Example 4 In another embodiment of the present invention, a computer-readable storage medium is provided as a storage component within a terminal device, the function of which is to store programs and data. It should be noted that the computer-readable storage medium here encompasses not only the built-in storage components of the terminal device but also extended storage components supported by the device. Essentially, it is a tangible medium capable of containing or storing programs that can be invoked by or in conjunction with an instruction execution system, device, or apparatus. This storage medium provides storage areas for the terminal's operating system and stores one or more instructions suitable for processor loading and execution, which can constitute one or more computer programs containing program code.

[0050] Specifically, examples of computer-readable storage media (a non-exclusive list) include: electrical connections with one or more wires, portable disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory, optical fibers, portable optical disc read-only memory, optical storage devices, magnetic storage devices, or any reasonable combination of the above types.

[0051] The storage medium may also include data signals propagated as part of a baseband portion or a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any reasonable combination of both. Furthermore, computer-readable storage medium may also refer to other readable media besides conventional readable storage media, capable of sending, propagating, or transmitting programs for use or operation by an instruction execution system, apparatus, or device. Program code on the storage medium can be transmitted via any suitable medium, including but not limited to wireless, wired, optical fiber, or any reasonable combination thereof.

[0052] The program code used to implement the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C. The execution modes of the program code include: running entirely on the user's computing device, running partially on the user's device as a standalone software package, running partially in a distributed manner on both the user's device and a remote computing device, or running entirely on a remote computing device or server. When a remote computing device is involved, the device can be connected to the user's computing device via any type of network such as a local area network (LAN) or a wide area network (WAN), or connected to an external computing device via the Internet through an Internet service provider.

[0053] The processor is capable of loading and executing one or more instructions stored in a computer-readable storage medium to implement the corresponding steps of the numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes described in Example 1.

[0054] Example 5 Figure 7This is a schematic diagram of a computer device provided according to an embodiment of the present invention.

[0055] Please see Figure 7 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the computational system constituting the method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes in this embodiment. To avoid repetition, these details are not elaborated here.

[0056] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 7 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0057] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, CPUs, graphics processing units (GPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, quantum computing-based data processing logic units, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0058] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or RAM of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0059] Furthermore, memory 62 may include both internal storage units and external storage devices of the computer device 60. Memory 62 is used to store computer programs and other programs and data required by the computer device. Memory 62 can also be used to temporarily store data that has been output or will be output.

[0060] Any references to memory, database, or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (Read-Only Memory). Memory includes ROM, magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0061] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

Claims

1. A method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes, characterized in that, include: Obtain a two-dimensional geological profile of the slope in the target area; the two-dimensional geological profile should include at least information on the surface, strata, and geological objects. Based on the surface, strata and geological object information in the two-dimensional geological profile, lithological models of several material partitions are generated using spatial topological relationships and cutting and closing algorithms. Based on the lithological models, fracture models and joint models are generated. The inheritance relationship between the lithological models, fracture models and joint models is established. Based on the inheritance relationship, the shareable parts of each model command stream file are determined. Choose any one of the lithology model, fracture model, and joint model as the parent model, and construct a corresponding number of sensitivity analysis models as child models according to the content to be carried out in the sensitivity analysis. Based on the inheritance relationship between the parent and child models, each child model is compiled into a command stream file at once; Two-dimensional discontinuous numerical calculation software is used to convert the command stream files corresponding to each sub-model, thereby generating corresponding executable sensitivity analysis numerical models in batches.

2. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 1, characterized in that, The strata in the two-dimensional geological profile include boundaries of different lithologies, different degrees of weathering, and different unloading types. The degree of weathering includes unweathered, slightly weathered, weakly weathered, strongly weathered, completely weathered, and residual soil; The unloading types include strong unloading, weak unloading, and deep unloading.

3. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 2, characterized in that, Obtain a two-dimensional geological profile of the slope in the target area, including: When the acquired two-dimensional geological profile is a dwg or dxf file, the attribute information and geometric information in the file are read directly; the attribute information includes the layer names of various boundary lines; the geometric information includes the boundary line node numbers and node coordinates; When the obtained two-dimensional geological profile is a text or image file, attribute information and geometric information are obtained using image recognition extraction technology.

4. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 1, characterized in that, A lithological model is generated using spatial topological relationships and a cutting closure algorithm. Based on the lithological model, a fracture model and a joint model are generated, including: Two-dimensional geological profiles are converted into lithological models containing several material partitions using spatial topological relationships and cutting closure algorithms. Add fractures to the lithology model to generate a fracture model, and then combine the fracture model with joints to obtain a joint model. When the lithological model is free of fractures, a joint model is generated based on the lithological model and the joints.

5. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 4, characterized in that, The joint model is added and generated according to the lithology model or fracture model in a random joint group generation method; The random joint group generation method includes: generating random joint groups that conform to statistical characteristics using the Monte Carlo method based on the geometric statistical distribution type and parameters of joint length, spacing, dip angle and dip direction of each dominant joint group; The geometrical statistical distribution types include power-law distribution, Gaussian distribution, negative exponential distribution, normal distribution, log-normal distribution, uniform distribution, and Poisson distribution.

6. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 1, characterized in that, Construct a corresponding number of sensitivity analysis models as sub-models based on the content to be analyzed, including: When the parent model is a lithological model, the sensitivity analysis includes grid size, water level, and parameters specified by different soil and rock constitutive models. When the parent model is a fracture model, the sensitivity analysis includes parameters specified by several joint constitutive models and different element combinations of several fractures. When the parent model is a joint model, the sensitivity analysis includes the geometrical statistical distribution parameters of each dominant joint group in the random joint, such as joint length, spacing, dip angle, and dip direction, as well as the parameters specified by several joint constitutive models and different element combinations of several dominant joint groups.

7. The method for generating a numerical model for two-dimensional discontinuous sensitivity analysis of slopes according to claim 6, characterized in that, Based on the content to be analyzed, construct a corresponding number of sensitivity analysis models. The methods for constructing sensitivity analysis models include the following two approaches: The first approach is to directly create corresponding sensitivity analysis models in batches under the selected parent model based on the content to be analyzed. The second approach involves passing the same set of sensitivity analysis content to any parent model with an inheritance relationship, based on the inheritance relationship between the lithology model, fracture model, and joint model, to create corresponding sensitivity analysis models in batches.

8. A numerical model generation system for two-dimensional discontinuous sensitivity analysis of slopes, used to implement the numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes as described in any one of claims 1 to 7, characterized in that, include: The data acquisition module is used to acquire two-dimensional geological profiles of the slopes in the target area; the two-dimensional geological profiles include at least information on the surface, strata, and geological objects. The model generation module is used to generate lithological models of several material partitions based on the surface, strata and geological object information in the two-dimensional geological profile map, using spatial topological relationships and cutting and closing algorithms. Based on the lithological models, fracture models and joint models are generated, the inheritance relationship between the lithological models, fracture models and joint models is established, and the shareable parts of each model command stream file are determined according to the inheritance relationship. The model processing module is used to select any one of the lithology model, fracture model, and joint model as the parent model, and construct a corresponding number of sensitivity analysis models as child models according to the content to be carried out in the sensitivity analysis. The model conversion module is used to compile each child model into a command stream file based on the inheritance relationship between the parent and child models; The numerical model generation module is used to convert the command stream files corresponding to each sub-model using two-dimensional discontinuous numerical computing software, thereby generating corresponding executable sensitivity analysis numerical models in batches.

9. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes as described in any one of claims 1 to 7.

10. A computing device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including steps for performing the steps in the numerical model generation method for two-dimensional discontinuous sensitivity analysis of slopes according to any one of claims 1 to 7.

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