A method for reconstructing the geometric model of columnar jointed rock mass based on field geological survey statistical data

Abstract

The present invention relates to a method for reconstructing a geometric model of a columnar jointed rock mass based on statistical data from on-site geological surveys. The method comprises the following steps: first, calculating the dip, inclination, column density, cross-sectional variation coefficient, joint thickness, transverse joint spacing, and transverse joint penetration rate based on the on-site survey data; then, generating uniformly distributed seed points within a plane region; randomly moving the seed points within a given circular range; generating a Voroni diagram from the seed points; calculating the variation coefficient until a seed point distribution with a specified variation coefficient is generated; then, removing shorter edges to generate a two-dimensional cross-sectional diagram; and finally, generating transverse joint planes along the longitudinal direction according to the penetration rate. The two-dimensional cross-sectional diagram is then stretched into a body, and the generated geometric model is sliced ​​using target geometric dimensions to ultimately generate a reconstructed geometric model of the columnar jointed rock mass. The method thus better combines the columnar jointed rock mass encountered in engineering on-site surveys with similar material models and numerical models used in scientific research.

Description

Technical Field

[0001] The invention relates to a method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data, belonging to a method for reconstructing a geometric model of a columnar joint. Background Art

[0002] In-situ tests on irregularly jointed rock masses are difficult to carry out due to the high cost of rock crushing. Therefore, similar materials with simple production, energy-saving and economical properties and easy control of joint parameters are often used for relevant tests, supplemented by numerical simulation methods to analyze the engineering mechanical properties of irregularly jointed rock masses.

[0003] At present, most similar material models and numerical models of columnar jointed rock masses use models with regular cross-sections such as regular quadrangular prisms and hexagonal prisms. This can greatly simplify the columnar jointed rock masses with complex and changeable geometric shapes. However, this deviates to a certain extent from the columnar jointed rock masses at the engineering site and cannot be well combined with the statistical data from the on-site geological survey. Therefore, it is urgent to propose a method that can fully utilize the statistical data from the on-site geological survey to reconstruct the geometric model of columnar jointed rock masses. Summary of the Invention

[0004] The present invention provides a method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data. The geometric model of the columnar jointed rock mass is constructed by multiple parameters. Using this geometric model, a similar material model and a numerical model can be established that can better reflect the geometric characteristics of the columnar jointed rock mass at the engineering site.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data comprises the following steps:

[0007] Step S1: Based on the known geological survey data, the dip DD, inclination DA, column density Q, and cross-sectional polygon variation coefficient C of the columnar jointed rock mass are obtained. v , joint thickness t, transverse joint spacing d and transverse joint penetration rate p;

[0008] Step S2: Generate a geometric model according to the target. The size of the generated geometric model is defined as L, W, and H. A rectangular area with a side length of 2L×2W is established. N c seed points, where N c =2L×2W×Q, establish a coordinate system with the center point of the rectangular area as the origin, record N c The two-dimensional coordinates of the seed point N ci (x i ,yi ), record the initial N c The distance between adjacent seed points of a seed point is defined as l;

[0009] Step S3: N uniformly distributed in the rectangular area c seed points within the radius r = l × C v Perform a random move within the range of the moving seed point, use the Delaunay triangulation algorithm to generate the Voronoi figure within the rectangular area, and calculate the coefficient of variation C of the polygon area within the rectangular area. vi ;

[0010] Step S4: Calculate the coefficient of variation C of the polygon area within the rectangular area vi The coefficient of variation of the cross-sectional polygon C v The relative difference is determined to determine whether the relative difference satisfies the preset relative error; if the preset relative error is satisfied, proceed to step S5; if the preset relative error is not satisfied, return to step S3;

[0011] Step S5: In the two-dimensional cross-section of the generated Voronoi figure, there are relatively short edges. The shorter edges are removed to obtain the polygon area variation coefficient C. vi and the two-dimensional cross-sectional diagram of columnar density Q, and according to the transverse joint spacing of the columnar jointed rock mass to be measured in the Z direction, the two-dimensional cross-sectional diagram is copied and translated in the range of Z = 0-2H along the Z axis;

[0012] Step S6: randomly select multiple polygons from each two-dimensional cross section generated by the copy and translation in step S5, remove the unselected polygons, and stretch the selected two-dimensional cross section along the Z axis into a body with a stretching length of 2H, thereby forming a columnar jointed rock mass geometric model with both columnar joints and transverse joints;

[0013] Step S7: Rotate a cuboid of target geometric model size based on the dip DD and dip angle DA obtained by analyzing the known geological survey data, use the cuboid of target geometric size to cut the columnar jointed rock mass geometric model obtained in step S6, delete the cuboid of target geometric size and geometric figures outside the cuboid of target geometric size, assign a joint thickness t to the cut geometric model, and generate a columnar jointed rock mass geometric model reconstructed based on the on-site geological survey data;

[0014] As a further preferred embodiment of the present invention, in step S1, the column density Q is calculated by dividing the number of polygons visible in the cross section of the geological survey site by the visible cross-sectional area;

[0015] As a further preferred embodiment of the present invention, the cross-sectional polygonal variation coefficient C v The calculation formula is

[0016]

[0017] In formula (1), SD is the standard deviation of the cross-sectional polygon area, MN is the mean cross-sectional polygon area, n is the total number of cross-sectional polygons, and A is the average cross-sectional polygon area. i is the area of ​​the i-th polygon;

[0018] As a further preferred embodiment of the present invention, in step S3, N uniformly distributed within the rectangular area c seed points within the radius r = l × C v Perform a random move within the range of , and the implementation of random move is as follows:

[0019] x ' i =x i =random(0,r)×cos(random(0,2π)) (2)

[0020] y' i =y i +random(0,r)×sin(random(0,2π)) (3).

[0021] As a further preferred embodiment of the present invention, in step S4, it is determined whether the relative difference satisfies the preset relative error. If not, the seed points uniformly distributed in the rectangular area are within the radius r=l×C v Continue to move randomly within the range of ×(100+i)%. If i>100, then take i=100, and generate the Voronoi figure according to the Delaunay triangulation algorithm based on the moved seed points;

[0022] As a further preferred embodiment of the present invention, in step S4, the polygon area variation coefficient C vi The coefficient of variation of the cross-sectional polygon C v The formula for calculating the relative difference is

[0023]

[0024] In formula (4), E i is the relative difference, C vi is the coefficient of variation of polygon area, C v is the coefficient of variation of the cross-sectional polygon;

[0025] As a further preferred embodiment of the present invention, in step S5, the method for removing the shorter side in the two-dimensional cross-sectional image is to merge the two end points of the shorter side, wherein the shorter side is defined as a=n×l;

[0026] As a further preferred embodiment of the present invention, in step S6, a plurality of polygons are randomly selected from the two-dimensional cross section obtained in step S5, and the number of the selected polygons is A=N. c ×p;

[0027] As a further preferred embodiment of the present invention, in step S7, the method for generating the cuboid of the target geometric model is to generate a L×W×H cuboid with the origin as the center point, rotate the cuboid clockwise around the Z axis in the XY plane with the origin as the center by an angle DD, and then rotate the cuboid clockwise around the X axis in the YZ plane with the origin as the center by an angle DA;

[0028] As a further preferred embodiment of the present invention, the cuboid of the target geometric model in step S7 is cut into the columnar jointed rock mass geometric model in step S6 by using a Boolean operation-segmentation method;

[0029] The joint thickness of the cut geometry is given by stretching all faces of the geometry along the normal direction.

[0030] Through the above technical solution, compared with the existing technology, the present invention has the following beneficial effects:

[0031] 1. Compared with traditional methods, the method for reconstructing the geometric model of columnar jointed rock mass provided by the present invention contains a large amount of geological exploration statistical data, which is convenient for making similar material models and constructing numerical models;

[0032] 2. In the process of generating a two-dimensional cross-sectional image, the present invention first generates regular seed points and then allows the seed points to move randomly within a specified range. The random range is controllable and consistent with the hypothesis that regular hexagonal columnar joints are generated under ideal conditions due to cooling and contraction of columnar jointed rock masses, but the actual situation is not ideal and naturally irregular columnar joints are generated.

[0033] 3. The method for reconstructing the geometric model of columnar jointed rock mass provided in this application also takes transverse joints into account in the generated rock mass model, which can better simulate natural irregular columnar jointed rock mass. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The present invention will be further described below with reference to the accompanying drawings and examples.

[0035] Figure 1 It is an overall flow chart of a preferred embodiment provided by the present invention;

[0036] Figure 2 It is a rectangular area where seed points are evenly distributed in step S2 of the preferred embodiment provided by the present invention;

[0037] Figure 3The Voronoi diagram generated by uniformly distributing seed points in step S2 of the preferred embodiment provided by the present invention;

[0038] Figure 4 Schematic diagram of random movement of seed points in step S3 of a preferred embodiment provided by the present invention;

[0039] Figure 5 The preferred embodiment provided by the present invention satisfies the polygon area variation coefficient C in step S5. vi and a two-dimensional cross-sectional diagram of the column density Q;

[0040] Figure 6 This is a schematic diagram of removing shorter edges in step S5 of a preferred embodiment provided by the present invention;

[0041] Figure 7 It is the two-dimensional cross-sectional view that does not contain shorter sides and satisfies the polygonal variation coefficient and column density, which is finally determined in step S5 of the preferred embodiment provided by the present invention;

[0042] Figure 8 The preferred embodiment of the present invention eliminates the transverse joint surface generated by the unselected polygons;

[0043] Figure 9 In the preferred embodiment provided by the present invention, in step S6, a geometric model of a columnar jointed rock mass having both columnar joints and transverse joints is generated;

[0044] Figure 10a-Figure 10b This is a schematic diagram of the inclination and tilt rotation of the rectangular parallelepiped used for sectioning in step S7 of the preferred embodiment provided by the present invention, wherein Figure 10a is a schematic diagram of inclination rotation, Figure 10b is a schematic diagram of tilt rotation;

[0045] Figure 11 A schematic diagram of the joint skeleton of a columnar jointed rock mass reconstructed based on on-site geological survey statistical data is generated by a preferred embodiment of the present invention;

[0046] Figure 12 The geometric model of columnar jointed rock mass reconstructed based on on-site geological survey data is generated by the preferred embodiment provided by the present invention. DETAILED DESCRIPTION

[0047] The present invention will now be described in further detail with reference to the accompanying drawings.

[0048] As explained in the background technology, most of the current methods for simplifying columnar jointed rock masses with complex and changeable geometric shapes will cause deviations from the columnar jointed rock masses at the actual engineering site. Therefore, this application provides a method for reconstructing the geometric model of columnar jointed rock masses based on on-site geological survey statistical data. It uses more available parameters to construct a geometric model that is closer to the geometric characteristics of the columnar jointed rock masses at the engineering site, so as to improve the research accuracy on the engineering mechanical properties of jointed rock masses.

[0049] Next, we will explain the reconstruction method, including Figure 1 Steps shown:

[0050] Step S1: Based on the known geological survey data, the dip DD, inclination DA, column density Q, and cross-sectional polygon variation coefficient C of the columnar jointed rock mass are obtained. v , joint thickness t, transverse joint spacing d and transverse joint penetration rate p;

[0051] The column density Q is calculated by dividing the number of polygons visible in the cross section of the geological survey site by the visible cross-sectional area;

[0052] Coefficient of variation of cross-sectional polygon C v The calculation formula is

[0053]

[0054] In formula (1), SD is the standard deviation of the cross-sectional polygon area, MN is the mean cross-sectional polygon area, n is the total number of cross-sectional polygons, and A is the average cross-sectional polygon area. i is the area of ​​the i-th polygon.

[0055] Remove the column density Q and the cross-sectional polygonal variation coefficient C v The remaining parameters are averaged based on on-site geological survey data. If one or some data cannot be obtained, the engineering analogy method is used to select them.

[0056] Step S2: Generate a geometric model according to the target. The size of the generated geometric model is defined as L, W, and H. A rectangular area with a side length of 2L×2W is established. N c seed points, where N c =2L×2W×Q, establish a coordinate system with the center point of the rectangular area as the origin, record N c The 2D coordinates of the seed points Record initial N c The distance between adjacent seed points of a seed point is defined as l;

[0057] Step S3: N uniformly distributed in the rectangular area c seed points within the radius r = l × C v Perform a random move within the range of the moving seed point, use the Delaunay triangulation algorithm to generate the Voronoi figure within the rectangular area, and calculate the coefficient of variation C of the polygon area within the rectangular area. vi ;

[0058] The random movement is implemented as follows:

[0059] x' i =x i =random(0,r)×cos(random(0,2π)) (2)

[0060] y' i =y i +random(0,r)×sin(random(0,2π)) (3).

[0061] Step S4: Calculate the coefficient of variation C of the polygon area within the rectangular area vi The coefficient of variation of the cross-sectional polygon C v The relative difference is used to determine whether the relative difference meets the preset relative error; here, the polygon area variation coefficient C vi The coefficient of variation of the cross-sectional polygon C v The formula for calculating the relative difference is

[0062]

[0063] In formula (4), E i is the relative difference, C vi is the coefficient of variation of polygon area, C v is the coefficient of variation of the cross-sectional polygon;

[0064] If the preset relative error is satisfied, proceed to step S5. If the preset relative error is not satisfied, return to step S3. Specifically, the seed points uniformly distributed in the rectangular area are within the radius r = l × C v Random movement is continued within the range of ×(100+i)%, wherein if i>100, i=100 is taken, and the Voronoi graph is generated according to the Delaunay triangulation algorithm based on the seed points after movement.

[0065] Step S5: In the two-dimensional cross-sectional view of the generated Voronoi figure, there are relatively short edges, which brings great difficulties to the subsequent meshing of numerical simulations and the preparation of similar material models. Therefore, it is necessary to remove the shorter edges and obtain the polygon area variation coefficient C. viand the two-dimensional cross-sectional diagram of columnar density Q, and according to the transverse joint spacing of the columnar jointed rock mass to be measured in the Z direction, the two-dimensional cross-sectional diagram is copied and translated in the range of Z = 0-2H along the Z axis;

[0066] The method for eliminating the shorter side in the two-dimensional cross-sectional view is to merge the two endpoints of the short side, wherein the short side is defined as a=n×l, and n can be defined according to specific circumstances.

[0067] Step S6: Randomly select A=N from each two-dimensional cross section generated by the copy translation in step S5 c ×p (the product of the penetration rate and the number of polygons, rounded to an integer) polygons, eliminating the unselected polygons, stretching the selected two-dimensional cross-section along the Z axis into a body with a stretching length of 2H, and forming a columnar jointed rock mass geometric model with both columnar joints and transverse joints;

[0068] Step S7: Rotate a cuboid of the target geometric model size based on the inclination DD and dip angle DA obtained by analyzing the known geological survey data. The specific generation method is as follows: generate a cuboid of L×W×H with the origin as the center point, rotate the cuboid clockwise around the Z axis in the XY plane with the origin as the center by the inclination angle DD, and then rotate the cuboid clockwise around the X axis in the YZ plane with the origin as the center by the angle DA;

[0069] The target geometric size cuboid is used to cut the columnar jointed rock mass geometric model in step S6 using the Boolean operation-segmentation method, and the target geometric size cuboid and the geometric figures outside the target geometric size cuboid are deleted. All the faces in the geometric model are stretched up and down along the normal direction. This enables the assignment of joint thickness and ultimately generates a geometric model of columnar jointed rock mass reconstructed based on on-site geological survey data.

[0070] Example:

[0071] In order to better illustrate the superiority of the above reconstruction method, this application provides a specific case analysis. First, the reconstruction model size is 1m×1m×1m, and seven geometric parameters are selected, as shown in the following table:

[0072] Table 1

[0073]

[0074] Combining the concept of unit body representation in rock mechanics and related research, the size of the geometric model is selected as 1m×1m×1m. Figure 2 As shown, the selected rectangular area is 2m×2m, and the number of seed points is N c =2m×2m×10.02m -2= 40.08, taking 40 seed points, l is 0.29m, the corresponding Voronoi diagram is as follows Figure 3 As shown;

[0075] According to the cross-sectional variation coefficient C v , let various seed points be within the radius r=l×C v =0.29×35.1%=0.1018m, and then generate the following triangles in the rectangular area using the Delaunay triangulation algorithm based on the seed points after the movement. Figure 4 The Voronoi graph shown calculates the coefficient of variation C of the polygon area within the region vi .

[0076] Calculate the coefficient of variation C of the generated Voronoi diagram vi and the cross-sectional coefficient of variation C v The relative difference Determine whether it meets the preset relative difference E. Combined with the research on related columnar jointed rock mass, in order to reduce the number of random movements of uniform seed points and ensure the accuracy of the geometric model of columnar jointed rock mass, the preset error is selected as 10%. Determine the two-dimensional cross-sectional diagram that meets the polygonal variation coefficient and column density. The two-dimensional cross-sectional diagram that meets the polygonal variation coefficient and column density is as follows: Figure 5 shown.

[0077] In the two-dimensional cross-sectional diagram, define a = n × l = 0.2 × 0.29 = 0.058m (n is 0.2) as the shorter side, merge the two endpoints of the shorter side, and eliminate the schematic diagram as shown in FIG. Figure 6 As shown, the final generated two-dimensional cross-section diagram that does not contain shorter sides and satisfies the polygonal variation coefficient and column density is as follows Figure 7 shown.

[0078] According to the horizontal joint spacing of the vertical plane, the two-dimensional cross-section is copied and translated in the Z direction (perpendicular to the direction of the two-dimensional cross-section) within the range of Z=0-2H. In the two-dimensional cross-section copied by translation, A=N are randomly selected. c ×p=40×34.2%=13.68 polygons (rounded to 14), remove the unselected polygons, such as Figure 8 shown.

[0079] The two-dimensional cross-section is stretched into a body along the Z axis with a stretching length of 2H = 2m, forming a geometric model of a columnar jointed rock mass with both columnar joints and transverse joints, as shown in Figure 9 shown.

[0080] like Figure 10a-Figure 10bAs shown in the figure, a 1m×1m×1m cuboid is generated with the origin as the center point, and the cuboid is rotated clockwise around the Z axis in the XY plane with the origin as the center by DD-12.3°. Then the cuboid is rotated clockwise around the X axis in the YZ plane with the origin as the center by DA-73.2°. The columnar jointed rock geometry model is cut (Boolean operation-split) with the cuboid, and the geometry outside the cuboid is deleted. All faces in the geometry model are stretched up and down along the normal direction. into a body, thereby achieving the imparting of joint thickness, and the internal joints such as Figure 11 As shown in the figure, the geometric model of columnar jointed rock mass reconstructed based on the field geological survey data is finally generated. Figure 12 shown.

[0081] In summary, this application first calculates the inclination, dip, column density, cross-sectional variation coefficient, joint thickness, transverse joint spacing, and transverse joint penetration rate based on the field survey data; generates uniformly distributed seed points in the plane area, gives a circular range and allows the seed points to move randomly within the range, calculates the variation coefficient until the seed point distribution with the specified variation coefficient is generated, removes the shorter edges, and generates a two-dimensional cross-sectional figure; generates transverse joint surfaces along the longitudinal direction according to the penetration rate, and stretches the two-dimensional cross-sectional figure into a body, uses the target geometric dimensions to cut the generated geometric model, and finally generates a reconstructed columnar jointed rock mass geometric model. This can better combine the columnar jointed rock mass encountered in the engineering field survey with similar material models and numerical models used in scientific research.

[0082] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such herein, will not be interpreted in an idealized or overly formal sense.

[0083] With the above-described preferred embodiments of the present invention as a guide, and with reference to the above description, relevant personnel are fully capable of making various changes and modifications without departing from the technical scope of this invention. The technical scope of this invention is not limited to the contents of the specification and must be determined according to the scope of the claims.

Claims

1. A method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data, characterized by: The specific steps include: Step S1: Based on the known geological survey data, the dip DD, inclination DA, column density Q, and cross-sectional polygon variation coefficient C of the columnar jointed rock mass are obtained. v , joint thickness t, transverse joint spacing d and transverse joint penetration rate p; Step S2: Generate a geometric model according to the target. The size of the generated geometric model is defined as L, W, and H. A rectangular area with a side length of 2L×2W is established. N c seed points, where N c =2L×2W×Q, establish a coordinate system with the center point of the rectangular area as the origin, record N c The 2D coordinates of the seed points Record initial N c The distance between adjacent seed points of a seed point is defined as l; Step S3: N uniformly distributed in the rectangular area c seed points within the radius r = l × C v Perform a random move within the range of the moving seed point, use the Delaunay triangulation algorithm to generate the Voronoi figure within the rectangular area, and calculate the coefficient of variation C of the polygon area within the rectangular area. vi ; Step S4: Calculate the coefficient of variation C of the polygon area within the rectangular area vi The coefficient of variation of the cross-sectional polygon C v The relative difference is determined to determine whether the relative difference satisfies the preset relative error; if the preset relative error is satisfied, proceed to step S5; if the preset relative error is not satisfied, return to step S3; Step S5: In the two-dimensional cross-section of the generated Voronoi figure, there are relatively short edges. The shorter edges are removed to obtain the polygon area variation coefficient C. vi and the two-dimensional cross-sectional diagram of columnar density Q, and according to the transverse joint spacing of the columnar jointed rock mass to be measured in the Z direction, the two-dimensional cross-sectional diagram is copied and translated in the range of Z = 0-2H along the Z axis; Step S6: randomly select multiple polygons from each two-dimensional cross section generated by the copy and translation in step S5, remove the unselected polygons, and stretch the selected two-dimensional cross section along the Z axis into a body with a stretching length of 2H, thereby forming a columnar jointed rock mass geometric model with both columnar joints and transverse joints; Step S7: Rotate a cuboid of the target geometric model size based on the inclination DD and dip angle DA obtained from the analysis of known geological survey data, use the cuboid of the target geometric size to cut the columnar jointed rock mass geometric model in step S6, delete the cuboid of the target geometric size and the geometric figures outside the range of the cuboid of the target geometric size, assign the joint thickness t to the geometric model after cutting, and generate a columnar jointed rock mass geometric model reconstructed based on the on-site geological survey data.

2. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 1, characterized in that: In step S1 , the column density Q is calculated by dividing the number of polygons visible in the cross section of the geological survey site by the visible cross-sectional area.

3. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 2, characterized in that: Coefficient of variation of cross-sectional polygon C v The calculation formula is In formula (1), SD is the standard deviation of the polygonal area of ​​the cross section, MN is the mean polygonal area of ​​the cross section, n is the total number of polygons in the cross section, and A is the i is the area of ​​the i-th polygon.

4. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 3, characterized in that: In step S3, N is evenly distributed in the rectangular area. c seed points within the radius r = l × C v Perform a random move within the range of , and the implementation of random move is as follows: x i '=x i =random(0,r)×cos(random(0,2π)) (2) y i '=y i +random(0,r)×sin(random(0,2π)) (3)。 5. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 4, characterized in that: In step S4, it is determined whether the relative difference meets the preset relative error. If not, the seed points uniformly distributed in the rectangular area are within the radius r = l × C v The random movement is continued within the range of ×(100+i)%, wherein if i>100, i=100 is taken, and the Voronoi figure is generated according to the Delaunay triangulation algorithm of the seed point after the movement.

6. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 5, characterized in that: In step S4, the polygon area variation coefficient C vi The coefficient of variation of the cross-sectional polygon C v The formula for calculating the relative difference is In formula (4), E i is the relative difference, C vi is the coefficient of variation of polygon area, C v is the coefficient of variation of the cross-sectional polygon.

7. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 6, characterized in that: In step S5 , the method for removing the shorter side in the two-dimensional cross-sectional image is to merge the two endpoints of the shorter side, wherein the shorter side is defined as a=n×l.

8. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 7, characterized in that: In step S6, a plurality of polygons are randomly selected from each two-dimensional cross section generated by copying and translating in step S5, and the number of polygons selected is A=N. c ×p.

9. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 8, characterized in that: In step S7, the method for generating the cuboid of the target geometric model is to generate an L×W×H cuboid with the origin as the center point, rotate the cuboid clockwise around the Z axis in the XY plane with the origin as the center by an angle DD, and then rotate the cuboid clockwise around the X axis in the YZ plane with the origin as the center by an angle DA.

10. The method for reconstructing a geometric model of a columnar jointed rock mass based on on-site geological survey statistical data according to claim 9, characterized in that: In step S7, the cuboid of the target geometric model is cut into the columnar jointed rock mass geometric model in step S6 by using a Boolean operation-segmentation method; The joint thickness of the cut geometry is given by stretching all faces of the geometry along the normal direction.

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