A honeycomb reef limestone numerical model coupling generation method

Abstract

The application provides a honeycomb reef limestone numerical model coupling generation method, comprising the following steps: S1, the structural characteristics of a honeycomb reef limestone sample are characterized as a plurality of n-polygon unit bodies, and geometric parameters of the unit bodies are determined; S2, a pore radius is determined; S3, a three-dimensional geometric model of the unit bodies is established by using finite element software; S4, the three-dimensional geometric model of the unit bodies is subjected to particle filling by using discrete element software; S5, the unit bodies are copied, arranged and combined to form a three-dimensional geometric model of a complete sample; S6, a radial pore structure is generated in the three-dimensional geometric model of the complete sample by using pore particles, and the radius of the pore particles is equal to the pore radius in step S2; and S7, the pore structure is deleted, and contact properties are applied to the particles of the three-dimensional geometric model of the complete sample. The application can perform three-dimensional fine modeling on the skeleton structure of the honeycomb reef limestone, and provide an accurate model for the study of the meso-mechanical characteristics of the reef limestone and the simulation calculation of the bearing capacity of an actual engineering foundation.

Description

Technical Field

[0001] This invention relates to the field of reef limestone modeling technology, and specifically to a method for coupled generation of a numerical model of honeycomb reef limestone. Background Technology

[0002] Reef limestone is a unique type of biogenic limestone formed from the remains of reef-building organisms that died and underwent transport and deposition processes and complex biochemical reactions in a marine environment. Due to its unique biogenic diagenetic mechanism, its structure and properties differ from terrestrial rocks. On the one hand, reef limestone retains the pores of the original biogenic calcareous framework; on the other hand, the calcium carbonate components are dissolved by CO2 or microorganisms in the water, forming pores and defects. The mineral composition, pore structure, and morphological characteristics of reef limestone control its macroscopic mechanical behavior, exhibiting characteristics of high porosity, low strength, and brittleness. From a macroscopic mechanical perspective, the strength of rock materials is closely related to their heterogeneity. Currently, domestic and international scholars have conducted extensive laboratory experiments and numerical analysis studies on the mechanical properties of reef limestone.

[0003] The current numerical modeling methods for reef limestone have the following problems: (1) Reef limestone has high porosity and its structure has the characteristics of a regular biological skeleton. As a method for simulating continuous media, the finite element method cannot well simulate the discrete pore structure inside it. Moreover, as a brittle rock, the finite element method cannot well simulate the failure mode of reef limestone. The discrete element method only generates simple strip-shaped pores or local voids or only adjusts the parameters to make them conform to the mechanical properties of the actual sample. It does not take into account the "radioactive" pore structure of reef limestone, a biological skeleton rock. (2) Most of the existing discrete element models of reef limestone are two-dimensional models. Therefore, they cannot well characterize the actual three-dimensional pore structure of reef limestone and truly reflect the failure mechanism of reef limestone at the three-dimensional level. They also cannot study the law of the influence of pore structure on its mechanical properties. (3) In actual engineering, the numerical model calculation of reef limestone often ignores the influence of pores. The non-uniform pores in reef limestone often lead to a series of problems such as pile foundation settlement and bearing capacity reduction. Therefore, achieving detailed modeling of reef limestone is also very necessary for engineering design. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by providing a numerical model coupling generation method for honeycomb reef limestone. This method can perform three-dimensional fine modeling of the honeycomb-like skeleton structure of reef limestone, providing an accurate model for the study of the micromechanical properties of reef limestone and the simulation calculation of the bearing capacity of actual engineering foundations.

[0005] To address the aforementioned technical problems, this invention provides a method for coupled generation of a numerical model of honeycomb reef limestone, comprising:

[0006] S1. The structural characteristics of the honeycomb-shaped reef limestone sample are characterized into multiple n-sided unit cells. Each unit cell includes an n-sided skeleton wall, an n-sided room-column structure located inside the skeleton wall, and a radial fiber sheet structure connecting the room-column structure and the skeleton wall. The geometric parameters of the unit cells are determined and used as the basis for modeling.

[0007] S2. Determine the pore radius based on the CT scan images of the reef limestone sample;

[0008] S3. Based on the geometric parameters of the unit, use SOILDWORKS software to establish a three-dimensional geometric model of the unit;

[0009] S4. Use discrete element software to fill the three-dimensional geometric model of the unit cell with particles;

[0010] S5. The unit cells are copied, arranged, and combined to form a complete three-dimensional geometric model of the sample.

[0011] S6. Using porous particles, a radial pore structure is generated in the three-dimensional geometric model of the complete sample. The radius of the porous particles is equal to the pore radius in step S2.

[0012] S7. Delete the pore structure and apply contact properties to the particles of the three-dimensional geometric model of the complete sample.

[0013] Further, step S3 includes: using finite element software to establish a three-dimensional geometric model of the unit body. In the three-dimensional geometric model of the unit body, the skeleton wall, the room column structure, and the fiber sheet structure are three independent components, and the three independent components are exported separately.

[0014] Further, step S4 includes: importing the three independent components exported in step S3 into the discrete element software, filling the three-dimensional geometric model of the unit with particles, extracting the coordinate information of the particles after the particles are balanced, grouping the particles according to the different regions where the three independent components are located, dividing the particles into skeleton wall particles, fiber structure particles and room column particles, and outputting the radius, position coordinates and grouping information of each particle.

[0015] Further, step S5 includes: calculating the position coordinates of all replicated particles based on the radius, position coordinates and grouping information of each particle; replicating the three-dimensional geometric model of the unit multiple times and arranging and combining them; and deleting the redundant parts according to the actual shape of the reef limestone sample to form a complete three-dimensional geometric model of the sample.

[0016] Further, step S6 includes:

[0017] S61. Define the particles located at the boundary of the room column particles as pore seeds. The pore seeds grow from the particles located at the boundary of the room column particles as the starting point and the direction from the center of the room column structure to the center of the pore seeds as the growth direction, continuously generating pore particles. The radius of the pore particles is equal to the pore radius in step S2.

[0018] S62. Update the contact information of porous particles in real time. When it is detected that a porous particle is in contact with a fiber structure particle, delete the fiber structure particle that is in contact with the porous particle. When it is detected that a porous particle is in contact with a skeleton wall particle or a porous particle is in contact with the model boundary, stop the growth of the current porous seed.

[0019] Furthermore, in step S61, the growth spacing of the porous particles is smaller than the pore radius.

[0020] Furthermore, in step S61, the velocity of the generated porous particles is set to 0.

[0021] Further, step S2 includes:

[0022] S21. Perform image enhancement, filtering and noise reduction and threshold segmentation preprocessing on the CT scan image to obtain image voxel information of pores and matrix skeleton, and extract the (x,y) coordinates and gray values ​​of each pixel in the CT scan image.

[0023] S22. Using the fast watershed algorithm, calculate the pore radius with the highest relative frequency. The pore radius with the highest relative frequency is taken as the pore radius of the reef limestone sample.

[0024] Further, step S21 includes:

[0025] The grayscale value of each pixel in the CT scan image is compared with the pixel grayscale threshold. If it is higher than the pixel grayscale threshold, the grayscale value of the pixel is enhanced; otherwise, the grayscale value of the pixel is set to 0.

[0026] In ImageJ, the filter radius is set to 2, and median filtering is used to eliminate system noise generated during CT scanning.

[0027] Use ImageJ to extract pixel information from CT scan images, save the (x,y) coordinates and grayscale value of each pixel, and output a CSV file.

[0028] Further, step S22 includes:

[0029] Based on the (x,y) coordinates and gray values ​​of each pixel in step S21, the gray values ​​of different pixels are represented by different heights to form a contour map. The boundary of the local minimum value is the boundary of the pore structure. The pores are segmented and quantitatively analyzed using the fast watershed algorithm in Matlab. The radius of the pore structure is statistically analyzed using ImageJ on the processed CT scan image, and the radius of the pore with the highest relative frequency is calculated.

[0030] The beneficial effects of this invention are as follows: This invention characterizes reef limestone samples as structures composed of hexagonal unit cells, extracts their geometric parameters, establishes a geometric model using SOILDWORKS, imports this model into discrete element method (DEM) software to generate unit cells composed of particles, and uses a self-developed FILE function to copy and arrange these unit cells. Based on the pore structure radius parameters obtained from CT scan images of the reef limestone, the self-developed FILE function generates a radial pore structure similar to the actual sample, thus achieving a refined simulation of the microstructure of the reef limestone. In the splitting tests of related studies, the tensile strength of this well-porosity reef limestone is generally 0.6–0.82 MPa. The numerical model of this invention achieves a peak tensile strength of 0.67 MPa, and the failure mode of the sample is tensile failure at the cemented surface. This demonstrates that this invention can not only accurately characterize the microstructure of reef limestone but also accurately simulate its mechanical properties and failure modes. The reef limestone model of this invention can be widely used in the study of the micromechanical properties of reef limestone and in the simulation calculation of the bearing capacity of actual engineering foundations. Attached Figure Description

[0031] Figure 1 This is a flowchart of the present invention.

[0032] Figure 2 This diagram illustrates the characterization and extraction process of the reef limestone sample in this invention.

[0033] Figure 3 This is a schematic diagram of the three-dimensional geometric model of the unit body of the present invention.

[0034] Figure 4 This is a top view of the three-dimensional geometric model of the unit body of the present invention.

[0035] Figure 5 This is a three-dimensional geometric model diagram of the particle filling process using discrete element method software according to the present invention.

[0036] Figure 6 This is a three-dimensional geometric model diagram of the unit cells after being copied, arranged, and combined according to the present invention.

[0037] Figure 7 This is a sampling diagram of the present invention.

[0038] Figure 8This is a schematic diagram illustrating the principle of generating porous particles according to the present invention.

[0039] Figure 9 This is a schematic diagram of the model of the hidden fibrous structure particles after the porous particles of the present invention are generated.

[0040] Figure 10 This is a comparison diagram of the pore structure of the three-dimensional geometric model of the present invention and the pore structure of the actual CT scan of the reef limestone.

[0041] Figure 11 The particle displacement cloud map used in this invention is from the Brazilian splitting numerical test.

[0042] Figure 12 This is a graph showing the relationship between tensile strength and strain of the reef limestone sample of this invention.

[0043] Figure reference numerals: 1. Skeletal wall; 2. Fiber sheet structure; 3. Room column structure; 4. Pore seed; 5. Pore particle; 6. Skeletal wall particle; 7. Fiber structure particle; 8. Room column particle. Detailed Implementation

[0044] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0045] like Figure 1 As shown, this invention provides a method for coupled generation of a numerical model of honeycomb reef limestone, comprising:

[0046] S1, such as Figure 2 As shown, the structure of the honeycomb reef limestone sample is simplified and characterized into multiple n-sided unit cells. Each unit cell includes an n-sided skeleton wall 1, an n-sided room column structure 3 located inside the skeleton wall 1, and a radial fiber sheet structure 2 connecting the room column structure 3 and the skeleton wall 1. The geometric parameters of the unit cells are determined and used as the basis for modeling.

[0047] In this embodiment, n=6, and each unit cell is adjacent to six unit cells. This embodiment is mainly to study the influence of the pore structure of honeycomb reef limestone on its mechanical properties. The reef limestone sample can be regarded as being composed of multiple identical unit cells, and the geometric parameters of the unit cells can be determined based on the average value of the geometric parameters of all unit cells to simplify the modeling process.

[0048] S2. Determine the pore radius based on CT scan images of the reef limestone sample; specifically including:

[0049] S21. Perform image enhancement, filtering and noise reduction, and threshold segmentation preprocessing on the CT scan images to obtain image voxel information of pores and matrix skeleton, and extract the (x,y) coordinates and gray values ​​of each pixel in the CT scan images; specifically including:

[0050] The grayscale value of each pixel in the CT scan image is compared with a pixel grayscale threshold. If the value is higher than the threshold, the grayscale value of that pixel is enhanced; otherwise, the grayscale value of that pixel is set to 0. Figure 10 As shown, the image on the left is the enhanced CT scan image, with black representing the pore structure.

[0051] In ImageJ, the filter radius is set to 2, and median filtering is used to eliminate system noise generated during CT scanning.

[0052] Use ImageJ to extract pixel information from CT scan images, save the (x,y) coordinates and grayscale value of each pixel, and output a CSV file.

[0053] S22. Using the fast watershed algorithm, calculate the pore radius with the highest relative frequency. The pore radius with the highest relative frequency is taken as the pore radius of the reef limestone sample; specifically including:

[0054] Based on the (x,y) coordinates and gray values ​​of each pixel in step S21, the gray values ​​of different pixels are represented by different heights to form a contour map. The boundary of the local minimum value is the boundary of the pore structure. The pores are segmented and quantitatively analyzed using the fast watershed algorithm in Matlab. The radius of the pore structure is statistically analyzed using ImageJ on the processed CT scan image, and the radius of the pore with the highest relative frequency is calculated.

[0055] S3. Based on the geometric parameters of the element, establish a three-dimensional geometric model of the element using finite element software; specifically including:

[0056] like Figure 3 , 4 As shown, a three-dimensional geometric model of the unit is established using the software SOILDWORKS. In the three-dimensional geometric model of the unit, the skeleton wall 1, the room column structure 3, and the fiber sheet structure 2 are set as three independent components, and the three independent components are exported as STL files respectively.

[0057] S4. Use discrete element method (DEM) software to fill the 3D geometric model of the unit cell with particles; specifically including:

[0058] Import the STL files of the three independent components exported in step S3 into the discrete element method software FLAC3D. Fill the three-dimensional geometric model of the unit cell with spherical particles. After the particles are balanced, extract their coordinate information. Group the particles according to the different regions where the three independent components are located, classifying them into skeleton wall particles (6), fiber structure particles (7), and room column particles (8). Figure 5 As shown, the output shows the radius, position coordinates, and grouping information of each particle, and saves it as a TXT file.

[0059] S5. The unit cells are replicated, arranged, and combined to form a complete three-dimensional geometric model of the specimen; specifically including:

[0060] The radius, position coordinates, and grouping information of the particles in the TXT file are read. The position coordinates of all copied particles are calculated. The 3D geometric model of the unit cell is copied multiple times, and then arranged and combined to obtain the following result: Figure 6 The structure shown; as Figure 7 As shown, the redundant parts were removed based on the actual shape of the reef limestone sample to form a complete three-dimensional geometric model of the sample.

[0061] S6. Using porous particles 5, a radial pore structure is generated in the three-dimensional geometric model of the complete sample. The radius of the porous particles 5 is equal to the pore radius in step S2. Specifically, this includes:

[0062] S61, such as Figure 8 As shown, the particles located at the boundary in the room column particles 8 are defined as pore seeds 4. The pore seeds 4 grow from the particles located at the boundary in the room column particles 8 as the starting point and the direction from the center of the room column structure 3 to the center of the pore seeds 4 as the growth direction, continuously generating pore particles 5. The radius of the pore particles 5 is equal to the pore radius in step S2.

[0063] Among them, the growth spacing of the porous particles 5 is smaller than the pore radius to prevent the particles from just avoiding the wall during the generation process, thus making it impossible to detect the 'ball-facet' contact and preventing the program from stopping; the speed of the generated porous particles 5 is all set to 0 to prevent the growth of the porous particles 5 from disturbing the structure of the entire model, ensuring the stability and accuracy of the model.

[0064] S62. Update the contact information of porous particles 5 in real time. When contact between porous particles 5 and fibrous structure particles 7 is detected, delete the fibrous structure particles 7 that are in contact with porous particles 5. When contact between porous particles 5 and skeleton wall particles 6 or between porous particles 5 and the model boundary is detected, stop the growth of the current porous seed 4. Figure 9 The image shows a schematic diagram of the structure of the porous particles 5 after generation. It can be seen that the porous particles 5 are radially arranged. Figure 97. Fiber structure particles are hidden within.

[0065] S7. Delete the pore structure and apply different contact properties to the skeleton wall particles 6 and fiber structure particles 7 of the three-dimensional geometric model of the complete sample. For example... Figure 10 As shown, Figure 10 The structure on the right is a three-dimensional geometric model of the complete sample. As can be seen, the three-dimensional geometric model generated by this invention is similar to the structure of the image obtained by CT scan.

[0066] The Brazilian splitting test was then performed on the three-dimensional geometric model generated by this invention:

[0067] In the discrete element method software FLAC3D, two loading planes are generated radially on the three-dimensional geometric model of the complete specimen to simulate the loading mode of the actual Brazilian splitting test. Relative loading velocities are applied to the loading plates, and the stress-strain condition of the specimen is recorded. The tensile strength of the three-dimensional geometric model is obtained through calculation and processing. The calculation results are as follows: Figure 12 As shown, the simulation results demonstrate that the tensile strength of the three-dimensional geometric model is 0.73 MPa, which is consistent with the tensile strength range of 0.6–0.82 MPa observed in relevant reef limestone mechanical tests. Figure 11 As shown, the failure mode of the three-dimensional geometric model is also tensile failure at the cemented surface. It can be seen that the present invention can not only accurately characterize the micropore structure of the reef limestone test, but also accurately simulate the mechanical properties and failure mode of the reef limestone.

[0068] This invention characterizes reef limestone samples as structures composed of hexagonal unit cells, extracts their geometric parameters, establishes a geometric model using SOILDWORKS, imports this model into discrete element method (DEM) software to generate unit cells composed of particles, and uses a custom-designed FILE function to replicate and arrange these unit cells. Based on pore structure radius parameters obtained from CT scan images of the reef limestone, the custom-designed FILE function generates a radial pore structure similar to the actual sample, thus achieving a refined simulation of the microstructure of the reef limestone. In splitting tests of related studies, the tensile strength of this well-porosity reef limestone is generally 0.6–0.82 MPa. The numerical model of this invention achieves a peak tensile strength of 0.67 MPa, and the failure mode of the sample is tensile failure at the cemented surface. This demonstrates that this invention can not only accurately characterize the microstructure of reef limestone but also accurately simulate its mechanical properties and failure modes. The reef limestone model of this invention can be widely used in the study of the micromechanical properties of reef limestone and in the simulation calculation of bearing capacity of actual engineering foundations.

[0069] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for coupled generation of a numerical model of honeycomb reef limestone, characterized in that, include: S1. The structural characteristics of the honeycomb-shaped reef limestone sample are characterized into multiple n-sided unit cells. Each unit cell includes an n-sided skeleton wall, an n-sided room-column structure located inside the skeleton wall, and a radial fiber sheet structure connecting the room-column structure and the skeleton wall. The geometric parameters of the unit cells are determined and used as the basis for modeling. S2. Determine the pore radius based on the CT scan images of the reef limestone sample; S3. Based on the geometric parameters of the element, use finite element software to establish a three-dimensional geometric model of the element; S4. Use discrete element software to fill the three-dimensional geometric model of the unit cell with particles; S5. The unit cells are copied, arranged, and combined to form a complete three-dimensional geometric model of the sample. S6. Using porous particles, a radial pore structure is generated in the three-dimensional geometric model of the complete sample. The radius of the porous particles is equal to the pore radius in step S2. S7. Remove the pore structure and apply contact properties to the particles of the three-dimensional geometric model of the complete sample. Step S3 includes: using finite element software to establish a three-dimensional geometric model of the unit body. In the three-dimensional geometric model of the unit body, the skeleton wall, the room column structure, and the fiber sheet structure are three independent components, and the three independent components are exported separately. Step S4 includes: importing the three independent components exported in step S3 into the discrete element software, filling the three-dimensional geometric model of the unit with particles, extracting the coordinate information of the particles after the particles are balanced, grouping the particles according to the different regions where the three independent components are located, dividing the particles into skeleton wall particles, fiber structure particles and room column particles, and outputting the radius, position coordinates and grouping information of each particle.

2. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 1, characterized in that, Step S5 includes: calculating the position coordinates of all replicated particles based on the radius, position coordinates and grouping information of each particle; replicating the three-dimensional geometric model of the unit multiple times and arranging and combining them; and deleting the redundant parts according to the actual shape of the reef limestone sample to form a complete three-dimensional geometric model of the sample.

3. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 1, characterized in that, Step S6 includes: S61. Define the particles located at the boundary of the room column particles as pore seeds. The pore seeds grow from the particles located at the boundary of the room column particles as the starting point and the direction from the center of the room column structure to the center of the pore seeds as the growth direction, continuously generating pore particles. The radius of the pore particles is equal to the pore radius in step S2. S62. Update the contact information of porous particles in real time. When it is detected that a porous particle is in contact with a fiber structure particle, delete the fiber structure particle that is in contact with the porous particle. When it is detected that a porous particle is in contact with a skeleton wall particle or a porous particle is in contact with the model boundary, stop the growth of the current porous seed.

4. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 3, characterized in that, In step S61, the growth spacing of the porous particles is smaller than the pore radius.

5. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 3, characterized in that, In step S61, the velocity of the generated porous particles is set to 0.

6. The method for coupling and generating a numerical model of honeycomb reef limestone according to any one of claims 1 to 5, characterized in that, Step S2 includes: S21. Perform image enhancement, filtering and noise reduction and threshold segmentation preprocessing on the CT scan image to obtain image voxel information of pores and matrix skeleton, and extract the (x,y) coordinates and gray values ​​of each pixel in the CT scan image. S22. Using the fast watershed algorithm, calculate the pore radius with the highest relative frequency. The pore radius with the highest relative frequency is taken as the pore radius of the reef limestone sample.

7. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 6, characterized in that, Step S21 includes: The grayscale value of each pixel in the CT scan image is compared with the pixel grayscale threshold. If it is higher than the pixel grayscale threshold, the grayscale value of the pixel is enhanced; otherwise, the grayscale value of the pixel is set to 0. In ImageJ, the filter radius is set to 2, and median filtering is used to eliminate system noise generated during CT scanning. Use ImageJ to extract pixel information from CT scan images, save the (x,y) coordinates and grayscale value of each pixel, and output a CSV file.

8. The method for coupling and generating a numerical model of honeycomb reef limestone according to claim 6, characterized in that, Step S22 includes: Based on the (x,y) coordinates and gray values ​​of each pixel in step S21, the gray values ​​of different pixels are represented by different heights to form a contour map. The boundary of the local minimum value is the boundary of the pore structure. The pores are segmented and quantitatively analyzed using the fast watershed algorithm in Matlab. The radius of the pore structure is statistically analyzed using ImageJ on the processed CT scan image, and the radius of the pore with the highest relative frequency is calculated.

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