A multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass

Abstract

The present invention proposes a multi-scale DFN-DEM equivalent modeling method for non-grade jointed rock mass, which relates to the field of geotechnical engineering technology. The specific scheme is: according to the collected multi-source heterogeneous data, the spatial distribution morphology of the structural surface is analyzed, and a spatial distribution model of different joint scales is established; based on the spatial distribution model of different joint scales, DFN is performed. i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group; multi-scale DFN for ungraded jointed rock mass i The mechanical parameters of the model group were analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-graded jointed rock mass was completed, thus solving the limitations of in-situ testing in reflecting the mechanical behavior of jointed rock mass.

Description

Technical Field

[0001] The invention belongs to the technical field of geotechnical engineering, and in particular relates to a multi-scale DFN-DEM equivalent modeling method for non-grade jointed rock mass. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The mechanical properties of rock mass are closely related to the structural planes, structures and the environment in which they occur. There are various geological interfaces in the rock mass, including material differentiation planes and discontinuity planes. As an important structural plane in the rock mass, the existence of joints makes the rock mass exhibit anisotropic characteristics under the action of external loads, and can also cause the size effect of the rock mass; in addition, the scale of the structural plane also has a significant impact on the mechanical properties of the rock mass. Practice has proved that the degree of influence of the structural plane on the mechanical properties and stability of the rock mass depends first on the ductility and scale of the structural plane; the Institute of Geology, Chinese Academy of Sciences divides the scale of the structural plane into five levels, among which the fourth-level structural plane has poor ductility, generally joints and foliations within a range of several meters to tens of meters, which only cut the rock mass into blocks within a small range; different combinations of these structural planes can cut the rock mass into structures of various shapes and sizes, which is one of the key issues in the study of rock mass structure, and the fifth-level structural plane is some tiny cracks with extremely poor ductility, which mainly affects the mechanical properties of the rock block. The destruction of the rock block is random due to the existence of microcracks.

[0004] In engineering design, rock mass quality evaluation is the basic work of rock mechanics and engineering applications; rock joint mechanics tests require testing of a large number of specimens of different shapes, which usually contain various joint structures, and various stress path loading and unloading tests are carried out under specific stress levels; due to the requirements of the test equipment on the specimen size and the limitations of the test costs, it is usually impossible to use this method on a large scale; although in-situ tests on rock masses can truly reflect the mechanical behavior of jointed rock masses, the application of this method is also greatly restricted due to the difficulty and high cost of in-situ testing; therefore, the existing methods of reflecting the mechanical behavior of jointed rock masses have many limitations in application, and are not suitable and robust enough. Summary of the invention

[0005] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass. Based on the regional adaptive correction algorithm of Markov chain Monte Carlo, a multi-scale DFN grid model of non-hierarchical jointed rock mass that truly reflects the geometric characteristics of engineering jointed rock mass is established. Based on the concept of rock mass characterization unit REV, the influence of mechanical properties of joints of different scales is equivalent, and a multi-scale DFN-DEM equivalent model of non-hierarchical jointed rock mass is established, thereby solving the limitations of in-situ testing in reflecting the mechanical behavior of jointed rock mass.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0007] A first aspect of the present invention provides a multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass.

[0008] A multi-scale DFN-DEM equivalent modeling method for non-grade jointed rock mass, including:

[0009] According to the collected multi-source heterogeneous data, the spatial distribution of the structural surface is analyzed, and the spatial distribution model of different joint scales is established;

[0010] Based on the spatial distribution model of different joint scales, DFN is carried out i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group;

[0011] Multi-scale DFN for rock masses with uneven joints i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-grade jointed rock mass is completed.

[0012] Furthermore, the multi-source heterogeneous data include rock mass structural surface information, binocular stereo photography measurement, borehole television, and advanced geological forecast multi-source information.

[0013] Furthermore, the spatial distribution of the analysis structure surface is specifically as follows:

[0014] The continuously collected tunnel face images are processed and feature extracted to obtain rock mass structural surface information. The tunnel structural surface information dynamic tracking and analysis method that combines binocular stereo photography measurement, borehole television, and advanced geological forecast multi-source information fusion can obtain the real spatial distribution of the structural surface.

[0015] Furthermore, the establishment of spatial distribution models of different joint scales is based on the real spatial distribution morphology of structural surfaces, analyzing the occurrence, engineering scale, and spatial distribution morphology of rock joints to establish spatial distribution models of different joint scales.

[0016] Furthermore, the DFN i Parameter entry is from small scale DFN1 to large scale DFN i Input of non-grade joint parameters.

[0017] Furthermore, the regional adaptive correction by Markov chain Monte Carlo is specifically performed in the following steps:

[0018] From a random initial state i Start;

[0019] Randomly select a target state j , calculate the measure: α ij =min(s j p ji 、s i p ij , 1), if > 0.5, the state transfer is accepted, otherwise it is rejected; after multiple iterations, the Markov chain converges to the ideal static distribution s, that is, the target joint distribution;

[0020] The joints [S] within the range of one times the tunnel diameter in the surrounding rock area are traversed, that is, the real joint group distribution within the tunnel face area; thereby, a deterministic-stochastic joint adaptive dynamic network model based on the MCMC algorithm is constructed.

[0021] Furthermore, the multi-scale DFN for non-grade jointed rock mass i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties. This is a process of realizing the equivalent mechanical properties of jointed rock mass by using the concept of rock mass characterization unit volume REV.

[0022] A second aspect of the present invention provides a multi-scale DFN-DEM equivalent modeling system for non-hierarchical jointed rock masses.

[0023] A multi-scale DFN-DEM equivalent modeling system for non-grade jointed rock mass, including a spread construction module, a DFN i Modeling modules and equivalent modeling modules:

[0024] The distribution construction module is configured to: analyze the spatial distribution morphology of the structural surface based on the collected multi-source heterogeneous data and establish spatial distribution models of different joint scales;

[0025] DFN i The modeling module is configured to: perform DFN based on spatial distribution models of different joint scales i Parameter entry, construction of non-hierarchical DFNi The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group;

[0026] The equivalent modeling module is configured as follows: Multi-scale DFN for ungraded jointed rock mass i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-grade jointed rock mass is completed.

[0027] The third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass as described in the first aspect of the present invention.

[0028] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass as described in the first aspect of the present invention are implemented.

[0029] One or more of the above technical solutions have the following beneficial effects:

[0030] The present invention establishes a multi-scale DFN for non-hierarchical jointed rock mass by acquiring the spatial distribution morphology and the regional adaptive correction algorithm of Markov chain Monte Carlo. i Model group, which truly reflects the geometric characteristics of engineering jointed rock mass.

[0031] Based on the concept of rock mass characterization unit REV, the influence of joint mechanical properties at different scales is equivalent, and a multi-scale DFN-DEM equivalent model of rock mass with non-graded joints is established.

[0032] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0034] Figure 1 FIG. 1 is a schematic diagram of a method of the first embodiment.

[0035] Figure 2 Schematic diagram of the mechanical equivalent process of the engineering-scale single-joint model of the first embodiment. DETAILED DESCRIPTION

[0036] It should be noted that the following detailed descriptions are illustrative and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in the present invention have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0037] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0038] Glossary:

[0039] DFN: Discrete Fracture Network is a mathematical model that describes the distribution and relationship of fractures in rocks. The discrete fracture network abstracts the fractures in rocks into discrete elements, such as line segments or patches, and establishes geometric and mechanical connections between them. Such a model can be used to study the distribution, morphology, and connection of fractures in rocks and their effects on the mechanical properties of rocks.

[0040] DEM: Discrete Element Method (DEM) is a numerical simulation method used to study the behavior and deformation of granular materials (such as rocks) under mechanical action.

[0041] REV: Representative Elementary Volume; within the same statistically homogeneous area of ​​rock mass structure, when the rock mass size is small, the distribution of cracks therein will be relatively different, and thus the rock mass properties will have obvious fluctuations. This difference will gradually weaken as the rock mass size increases. When the rock mass size is greater than a certain critical value, the rock mass properties will no longer change with the increase in rock mass size. This critical value is called the REV size.

[0042] The present invention proposes a multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass. The method can flexibly simulate the geometric and mechanical properties of randomly distributed joints. It is a virtual laboratory that performs numerical simulation tests on equivalent jointed rock mass composed of joints and rocks. Its key technologies include establishing a three-dimensional network model of the actual structural surface of the reaction engineering and establishing an equivalent rock mass mechanics calculation model. The method uses the concept of rock mass characterization unit body REV to equivalently affect the influence of microcracks on the mechanical properties of the rock mass and the engineering effect of equivalent medium-scale larger cracks.

[0043] Embodiment 1

[0044] In one or more embodiments, a multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass is disclosed, such as Figure 1 As shown, the following steps are included:

[0045] Step S1: Based on the collected multi-source heterogeneous data, the spatial distribution morphology of the structural surface is analyzed and spatial distribution models of different joint scales are established.

[0046] Specifically, image processing and feature extraction are performed on the tunnel face images continuously collected at the engineering site to achieve a series of image processing and effect enhancement of the fractured rock mass of the tunnel face, as well as feature extraction and automatic interpretation of structural surfaces with different characteristic attributes. The image characteristics of the fractured rock mass are fully considered, and grayscale transformation, edge sharpening, secondary filtering and other operations can be performed to obtain an image that is easy to identify. Based on the morphological edge detection algorithm and the Hough transform principle, targeted feature extraction of the rock mass structure is achieved, and multi-parameter attribute characterization of the structural surfaces in the rock mass is carried out using parameters such as fracture ratio, fractal dimension, surface density, joint spacing, joint trace length, and joint apparent inclination.

[0047] Combining binocular stereo photography measurement, borehole television, scanning, advanced geological forecast and other multi-source heterogeneous data, the rock joint occurrence, engineering scale and spatial distribution are analyzed, and spatial distribution models of different joint scales are constructed. The model here is a collection of structural surface data including occurrence, size, angle with the tunnel axis, position, ductility and other data.

[0048] Step S2: DFN based on spatial distribution models of different joint scales i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group.

[0049] Here, the DFN model can be established through 3DEC software. 3DEC is the abbreviation of 3 Dimension Distinct Element Code, which is a three-dimensional discrete element method program. As the name implies, 3DEC is a computational analysis program based on the discrete element method as the basic theory to describe the mechanical behavior of discrete media. The so-called discrete medium can be defined as a collection of continuous media, and continuous media interact with each other through non-continuous characteristics. 3DEC is a numerical program that can perform computational analysis on the mechanical behavior of discrete media. The program uses the finite difference method and can simulate the non-continuous mechanical behavior of the contact surface from a mechanical point of view. Therefore, it has a strong universal analysis capability within the scope of continuous medium mechanics. The DFN function in the software has a powerful discrete network model generation capability, which is an indispensable tool for rock deformation, destruction, discrete fracture network simulation and other analyses. Specifically, the acquired rock mass distribution information is input into the 3DEC software to realize non-hierarchical DFN. i Parameter input, the input parameters include model size, geometric occurrence (dip, dip angle) of the structural surface, structural surface density, structural surface size distribution, roughness, etc., by adjusting the model from small-scale DFN1 to large-scale DFN i The ungraded joint parameters are input to complete the establishment of ungraded joint rock mass DFN reflecting the real rock mass structural surface. i Model group.

[0050] The established DFN model group was verified by setting up several inspection planes in three directions (X, Y, and Z) of the DFN model and obtaining its P 21 Value, and the P of the actual structure surface of the project 21 The values ​​are compared and the verification is passed if similar and unified results are achieved. If the verification fails, the Markov chain Monte Carlo algorithm (MCMC) is used to establish a deterministic-stochastic joint adaptive dynamic network model.

[0051] The Markov Chain Monte Carlo algorithm (MCMC) is implemented by assuming that the joint surface s =( s 1, s 2,..., s M ) is the real distribution near the tunnel face. If we want to construct a Markov chain containing this distribution, then the Markov chain has M states, its transfer matrix P Medium Element P ij Represents the state i To status j The probability of , the steps are as follows:

[0052] 1) From a random initial state iStarting from, the DFN model generated by conventional Monte Carlo.

[0053] 2) Randomly select a target state j (The actual distribution state value of the joint group is selected here), calculate the measure (acceptance probability): α ij =min(s j p ji 、s i p ij , 1), if > 0.5, then the state transfer is accepted, otherwise it is rejected. After multiple iterations, the Markov chain converges to the ideal static distribution s, that is, the target joint distribution.

[0054] 3) Traverse the joints [S] within the range of one times the tunnel diameter in the surrounding rock area, that is, the real joint group distribution within the tunnel face area. Thus, a deterministic-stochastic joint adaptive dynamic network model based on the MCMC algorithm is constructed.

[0055] Step S3: Multi-scale DFN for ungraded jointed rock mass i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-grade jointed rock mass is completed.

[0056] Specifically, Figure 2 As shown in the figure, according to the multi-scale DFN of jointed rock mass constructed in the previous step i Model group division sequence, different levels of DFN are marked as DFN si , i =(1,2,..., n ), REV si For the corresponding size model DFN si Characterize the unit body; this SRM model can be divided into a series of different size models: DFN= (DFN s1 , DFN s2 ,..., DFN sn ), where DFN s1 Model representation contains only dimensions < L 1 block-level joints, the same DFN s2 Model means only the size between L 1~ L The 2 blocks are graded joints.

[0057] After the full-scale DFN model is partitioned, it is homogenized using the REV concept of the sub-scale DFN model; for example, REV s1 The mechanical properties can be used to show that the removal of DFN s1 Small cracks (i.e. crack length ≤ L 1) and the equivalent continuum material formed by intact rocks; similarly, the next scale level, REVs2 The mechanical properties of DFN can be used to represent s2 The slightly larger crack defined L 1<crack length≤ L 2) and by REV s1 The equivalent continuum material represented by the definition of "intact rock" is formed by the equivalent continuum material. si The mechanical properties can be used to show that the removal of DFN si The equivalent continuum material formed by the cracks and the "intact rock", the mechanical properties of the intact rock are determined by REV s(i−1) The equivalent continuum material definition represented by REV sn Represents an equivalent continuum material formed by all fractures and intact rock.

[0058] The acquisition of REV equivalent continuous medium is obtained by uniaxial compression experiment of SRM model formed by combining DFN model of each scale with complete rock with relevant equivalent properties. The mechanical properties of rock mass have size effect. With the increase of model size, the mechanical properties of rock mass tend to be stable. At this time, the model size is the REV size of rock mass. The equivalent analysis is carried out step by step. Finally, DFN sn With the grant of rev s(n-1) The complete rock mass with equivalent continuous medium properties is combined to finally realize an equivalent model with only a single joint at engineering scale.

[0059] Taking the DFN model of 50×50×50cm and three scales as an example, the specific steps of using REV to perform mechanical equivalence on the DFN models of different sizes are as follows: s1 A series of cubic specimens with widths ranging from 2m to 18m were sampled at different spatial locations of the DFN model. Uniaxial compression tests were performed on each specimen in three loading directions (X, Y, and Z). After obtaining the stress-strain curve, the mechanical parameters such as the uniaxial compressive strength, Poisson's ratio, and Young's modulus of different sizes in each direction were estimated and statistically analyzed. The stabilized parameters were used as REV s1 Mechanical properties of equivalent continuum materials.

[0060] In the UCS (Uniaxial Compressive Strength) simulation, the axial load is applied to one model face through a constant vertical velocity, while the opposite face of the model is subjected to the same loading conditions in all three loading directions to study the deformation and strength anisotropy of the specimen. The vertical velocity is applied directly to the grid points on the model surface. The axial and transverse strains are monitored through multiple pairs of monitoring grid points, and the strains are calculated by averaging the grid displacements using a software script. Nine points are arranged on each surface of the block to monitor the axial and transverse displacements in the three loading directions.

[0061] In DFN iDFN was removed from the model group s1 This set of cracks will obtain the REV s1 Mechanical properties of equivalent continuum materials (i.e., UCS, E ,υ, C and ) is assigned to REV s2 Designated as equivalent to "intact rock" in the analysis. REV s1 The mechanical properties of REV s2 The equivalent "intact rock" properties are assigned in the analysis. The intact rock mass is now reassigned the same as the DFN removed. s1 The model group combines to form the SRM s1 DFN is hidden s 1 This set of cracks achieves the purpose of simplification while taking into account DFN s1 The influence on the mechanical properties of jointed rock mass. From then on, the first step of the equivalent process is completed.

[0062] Similarly, for the mesoscale DFN s2 , the sampling width is between 4 and 26m. In the process of equivalence of the middle scale, REV is also used to replace its properties. After completing the extraction of the first two properties, DFN s3 The processing of large structural surfaces is just to determine the required size requirements and convert the SRM obtained in the previous step s2 The relevant mechanical parameters of the rock mass are assigned to the complete rock mass of this size and finally compared with DFN s3 Combined, we get the model SRM s3 Only the last set of cracks is left, and the equivalent rock mass of the first two sets of cracks is considered, and finally the single joint model with only engineering scale is established.

[0063] Embodiment 2

[0064] In one or more embodiments, a multi-scale DFN-DEM equivalent modeling system for non-hierarchical jointed rock mass is disclosed, including a spread construction module, a DFN i Modeling modules and equivalent modeling modules:

[0065] The distribution construction module is configured to: analyze the spatial distribution morphology of the structural surface based on the collected multi-source heterogeneous data and establish spatial distribution models of different joint scales;

[0066] DFN i The modeling module is configured to: perform DFN based on spatial distribution models of different joint scales i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group;

[0067] The equivalent modeling module is configured to analyze the mechanical parameters of the multi-scale DFNi model group of non-hierarchical jointed rock mass, obtain the equivalent rock mass mechanical properties, and complete the multi-scale DFN-DEM equivalent rock mass modeling of non-hierarchical jointed rock mass.

[0068] Embodiment 3

[0069] The purpose of this embodiment is to provide a computer-readable storage medium.

[0070] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in a multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass as described in the first embodiment of the present disclosure.

[0071] Embodiment 4

[0072] The purpose of this embodiment is to provide an electronic device.

[0073] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass as described in the first embodiment of the present disclosure are implemented.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass, characterized in that: include: According to the collected multi-source heterogeneous data, the spatial distribution of the structural surface is analyzed, and the spatial distribution model of different joint scales is established; Based on the spatial distribution model of different joint scales, DFN is carried out i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group; Multi-scale DFN for rock masses with uneven joints i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-grade jointed rock mass is completed; The establishment of spatial distribution models of different joint scales is based on the real spatial distribution morphology of the structural surface, analyzing the occurrence, engineering scale, and spatial distribution morphology of rock joints, and establishing spatial distribution models of different joint scales; The specific steps of the regional adaptive correction by Markov chain Monte Carlo are as follows: From a random initial state i Start; Randomly select a target state j , calculate the measure: α ij =min(s j p ji 、s i p ij , 1), if > 0.5, the state transfer is accepted, otherwise it is rejected; after multiple iterations, the Markov chain converges to the ideal static distribution s and obtains the target joint distribution, where s i 、s j Respectively represent the state of the joint surface i and status j , P ij Represents the state i To status j The probability of Traverse the joints [S] within the range of one times the tunnel diameter in the surrounding rock area, that is, the real joint group distribution within the tunnel face area; thereby construct a deterministic-stochastic joint adaptive dynamic network model based on the MCMC algorithm; The multi-scale DFN for non-grade jointed rock mass i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties. This is a process of realizing the equivalent mechanical properties of jointed rock mass by using the concept of rock mass characterization unit volume REV.

2. A multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass according to claim 1, characterized in that: The multi-source heterogeneous data include rock mass structural surface information, binocular stereo photography measurement, borehole television, and advanced geological forecast multi-source information.

3. A multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass according to claim 1, characterized in that: The spatial distribution form of the analysis structure surface is specifically: The continuously collected tunnel face images are processed and feature extracted to obtain rock mass structural surface information. The tunnel structural surface information dynamic tracking and analysis method that combines binocular stereo photography measurement, borehole television, and advanced geological forecast multi-source information fusion can obtain the real spatial distribution of the structural surface.

4. A multi-scale DFN-DEM equivalent modeling method for non-hierarchical jointed rock mass according to claim 1, characterized in that: The DFN i Parameter entry is from small scale DFN1 to large scale DFN i Input of non-grade joint parameters.

5. A multi-scale DFN-DEM equivalent modeling system for non-hierarchical jointed rock mass, characterized by: The method according to any one of claims 1 to 4 is used, comprising deploying a construction module, a DFN i Modeling modules and equivalent modeling modules: The distribution construction module is configured to: analyze the spatial distribution morphology of the structural surface based on the collected multi-source heterogeneous data and establish spatial distribution models of different joint scales; DFN i The modeling module is configured to: perform DFN based on spatial distribution models of different joint scales i Parameter entry, construction of non-hierarchical DFN i The model group, through the regional adaptive correction of Markov chain Monte Carlo, finally obtains the multi-scale DFN of non-grade jointed rock mass i Model group; The equivalent modeling module is configured as follows: Multi-scale DFN for ungraded jointed rock mass i The mechanical parameters of the model group are analyzed to obtain the equivalent rock mechanical properties, and the multi-scale DFN-DEM equivalent rock modeling of non-grade jointed rock mass is completed.

6. An electronic device, comprising: a memory for non-transitory storage of computer readable instructions; as well as a processor for executing the computer readable instructions, When the computer-readable instructions are executed by the processor, the method described in any one of claims 1 to 4 is executed.

7. A storage medium, characterized in that it non-temporarily stores computer-readable instructions, wherein: When the non-transitory computer-readable instructions are executed by a computer, the instructions of the method according to any one of claims 1 to 4 are executed.

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