Method for analyzing deformation of soil pore structure under uniaxial compaction

Abstract

The application belongs to the technical field of soil science, and discloses a method for analyzing deformation of soil pore structure under uniaxial compaction, which comprises the following steps: collecting a soil sample; performing CT scanning on the soil sample to obtain a first image slice; performing uniaxial compaction on the soil sample, and performing CT scanning on the compacted soil sample to obtain a second image slice; performing image processing on the first image slice and the second image slice to obtain a binary image, and analyzing changes in soil pore characteristic parameters before and after compaction; obtaining a pre-compaction binary image and a post-compaction binary image of biological pores according to the first image slice and the second image slice; and calculating changes in biological pore characteristic parameters before and after compaction according to the pre-compaction binary image and the post-compaction binary image, and evaluating stability of biological pores in the compaction process. The method can quantitatively analyze deformation of soil pore structure under uniaxial compaction.

Description

Technical Field

[0001] This invention belongs to the field of soil science and technology, specifically relating to a method for analyzing soil pore structure deformation under uniaxial compaction. Background Technology

[0002] Soil compaction essentially involves the rearrangement of soil particles, leading to an increase in soil bulk density and a decrease in porosity. The deformation of the pore structure caused by soil compaction further hinders water and air transport, root growth, and affects processes such as redox reactions and greenhouse gas emissions in the soil. Soil compaction has become one of the main forms of global soil degradation. Soil compaction primarily affects the macropore structure of the soil; the degree of pore deformation is related to factors such as applied stress, initial pore structure, and soil moisture. Specifically, soil pores with different initial structures exhibit different deformation patterns during compaction. For example, biological pores are relatively stable during compaction; tubular biological pores can maintain their morphological stability under stress, preserving the soil's aeration and drainage functions, and have high application potential in mitigating compaction risks.

[0003] Traditional methods struggle to quantify the deformation of soil pores during compaction and the stabilizing role of biological pores. X-ray computed tomography (CT) has been widely used to quantify soil pore structure. However, the deformation of the microscopic pore structure of farmland soils under uniaxial compaction has not yet been systematically analyzed, especially the stability of tubular biological pores during compaction.

[0004] Therefore, it is not currently possible to quantitatively analyze the deformation of soil pore structure under uniaxial compaction. Summary of the Invention

[0005] The purpose of this invention is to provide a method for analyzing soil pore structure deformation under uniaxial compaction, which can quantitatively analyze the soil pore structure deformation under uniaxial compaction.

[0006] The first aspect of this invention discloses a method for analyzing soil pore structure deformation under uniaxial compaction, comprising:

[0007] Collect soil samples;

[0008] The soil sample was subjected to a CT scan to obtain a first image slice;

[0009] The soil sample was uniaxially compacted, and the compacted soil sample was then CT scanned to obtain a second image slice.

[0010] Image processing is performed on the first image slice and the second image slice to obtain a binarized image. The changes in soil pore characteristic parameters before and after compaction are analyzed based on the binarized image.

[0011] Based on the first image slice and the second image slice, obtain the pre-compaction binarized image and the post-compaction binarized image of the biological pores;

[0012] The changes in biological porosity characteristic parameters before and after compaction are calculated based on the binarized images before and after compaction, and the stability of biological porosity during the compaction process is evaluated.

[0013] In some embodiments, prior to performing a CT scan on the soil sample, the method further includes:

[0014] Filter paper is wrapped around the bottom of the soil sample and placed in a sandbox to saturate it. After the soil sample is saturated, the suction value of the sandbox is adjusted to a preset value so that the soil sample is under the same suction.

[0015] In some embodiments, image processing is performed on the first image slice and the second image slice to obtain a binarized image. Based on the binarized image, the changes in soil pore characteristic parameters before and after compaction are analyzed, including:

[0016] Perform image preprocessing on the first image slice and the second image slice;

[0017] The central region is selected as the region of interest in the preprocessed first and second image slices to obtain the target image;

[0018] The target image is segmented using a single threshold segmentation method to obtain a binarized image.

[0019] Based on the binarized image, the changes in soil pore characteristic parameters before and after compaction are calculated. These soil pore characteristic parameters include soil macroporosity, pore connectivity, and soil pore size distribution.

[0020] In some embodiments, before selecting the central region as the region of interest in the preprocessed first and second image slices, the following preprocessing steps are further included:

[0021] Adjust the brightness and contrast of the first image slice and the second image slice; use median filtering to reduce noise in the first image slice and the second image slice.

[0022] In some embodiments, calculating the changes in pore characteristic parameters before and after compaction based on the binarized image includes:

[0023] Based on the binarized image, the changes in soil macroporosity before and after compaction were calculated using the volume fraction module in Avizo software, the changes in pore connectivity before and after compaction were calculated using the connectivity module in Avizo software, and the changes in soil pore size distribution before and after compaction were calculated using the thickness module in Avizo software.

[0024] In some embodiments, after uniaxial compaction of the soil sample and CT scanning of the compacted soil sample to obtain a second image slice, the method further includes:

[0025] The compacted soil sample was dried and weighed to obtain the soil sample mass.

[0026] Based on the sample mass and the deformation data of the soil sample before and after compaction, the changes in soil bulk density and soil porosity before and after compaction are calculated.

[0027] In some embodiments, obtaining a pre-compaction binarized image and a post-compaction binarized image of biological pores based on the first image slice and the second image slice includes:

[0028] Based on the first image slice and the second image slice, determine the biological pores that meet the requirements;

[0029] Biological pores were separated from the first image slice and the second image slice using the region growing method in VG Studio software, and the binarized image before compaction and the binarized image after compaction were obtained respectively.

[0030] In some embodiments, determining the required biological porosity based on the first image slice and the second image slice includes:

[0031] In the first image slice, biological pores that meet the requirements are identified visually based on their morphological characteristics. Based on the position and trend of the biological pores in the first image slice, the corresponding biological pores are identified in the second image slice.

[0032] In some embodiments, the biological porosity characteristic parameters are the volume, length, and pore size of the biological pores. The step of calculating the changes in the biological porosity characteristic parameters before and after compaction based on the pre-compaction binarized image and the post-compaction binarized image, and evaluating the stability of the biological porosity during the compaction process, includes:

[0033] For the same biological pore, the pre-compaction binarized image and the post-compaction binarized image are compared using the volume rendering module of Avizo software to compare the three-dimensional structure of the biological pore before and after compaction. The volume fraction module of Avizo software is used to calculate the change in porosity of the biological pore before and after compaction. The thickness module of Avizo software is used to calculate the change in pore diameter of the biological pore before and after compaction based on the three-dimensional structure. The skeleton module of Avizo software is used to generate a biological pore skeleton, and the change in pore length of the biological pore before and after compaction is calculated based on the biological pore skeleton.

[0034] In some embodiments, after generating a biological porous skeleton using the skeleton module of Avizo software, the method further includes:

[0035] Biological pores with an angle of less than 30° between the biological pore framework and the z-axis are classified as longitudinal biological pores, and biological pores with an angle of greater than 60° between the biological pore framework and the z-axis are classified as transverse biological pores. The influence of biological pore angle on pore deformation is analyzed.

[0036] The beneficial effects of this invention lie in the fact that by performing CT scans on soil samples before and after compaction, three-dimensional images of the soil structure are obtained non-destructively. The changes in macroporosity, pore connectivity, and pore size distribution of the same soil sample before and after uniaxial compaction are calculated, quantifying the impact of uniaxial compaction on the soil pore structure. By extracting naturally formed biological pores in the soil, and calculating the changes in characteristic parameters related to biological pores before and after compaction based on the binarized images of the biological pores before and after compaction, the stability and deformation patterns of biological pores under uniaxial compaction are quantitatively evaluated. This comprehensively achieves a quantitative analysis of the soil pore deformation patterns under uniaxial compaction. Attached Figure Description

[0037] The accompanying drawings illustrate specific examples of the technical solutions described in this invention and, together with the detailed embodiments, form part of the specification, serving to explain the technical solutions, principles, and effects of this invention.

[0038] Unless otherwise specified or defined, the same reference numerals in different figures represent the same or similar technical features, and different reference numerals may be used to represent the same or similar technical features.

[0039] Figure 1 This is a flowchart of a method for analyzing soil pore structure deformation under uniaxial compaction, as disclosed in an embodiment of the present invention.

[0040] Figure 2 These are comparison images of soil samples before and after compaction in an embodiment of the present invention;

[0041] Figure 3 This is a three-dimensional image of pore deformation under uniaxial compaction according to an embodiment of the present invention;

[0042] Figure 4 This is a detailed flowchart of step S400 in an embodiment of the present invention;

[0043] Figure 5 This is a schematic diagram of the biological pores before and after compaction in an embodiment of the present invention.

[0044] Figure 6 This is a three-dimensional image of biological pores and their skeletal deformation under uniaxial compaction according to an embodiment of the present invention. Detailed Implementation

[0045] Unless otherwise specified or defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. When combined with the technical solutions of the invention in a real-world scenario, all technical and scientific terms used herein may also have meanings corresponding to the purpose of achieving the technical solutions of the invention. The terms "first," "second," etc., used herein are merely for distinguishing names and do not represent a specific number or order. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0046] It should be noted that when a component is considered "fixed" to another component, it can be directly fixed to the other component or there can be an intervening component; when a component is considered "connected" to another component, it can be directly connected to the other component or there can be an intervening component; when a component is considered "mounted" on another component, it can be directly mounted on the other component or there can be an intervening component; when a component is considered "placed" on another component, it can be directly placed on the other component or there can be an intervening component.

[0047] Unless otherwise specified or defined, the terms "described" or "the" as used herein refer to the technical features or technical content mentioned or described prior to the relevant section, which may be the same as or similar to the technical features or technical content mentioned herein. Furthermore, the terms "comprising" and "having," and any variations thereof, as used herein, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0048] This invention proposes a method for analyzing soil pore structure deformation under uniaxial compaction. It can calculate the changes in soil macroporosity, pore connectivity, and soil pore size distribution before and after compaction, and quantitatively analyze the stability of biological pores during the compaction process, thus realizing the quantitative analysis of soil pore deformation law under uniaxial compaction.

[0049] This invention uses farmland soil as an example. Through non-destructive CT scanning technology, it compares the pore deformation of undisturbed farmland soil before and after uniaxial compaction. Furthermore, it extracts naturally formed biological pores in the field soil to quantitatively analyze the stability of these pores during the compaction process. It should be emphasized that the analytical method of this invention is not limited to farmland soil; it can also be used to analyze soil pore structure deformation in other types of soil.

[0050] To facilitate understanding of the present invention, specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings.

[0051] like Figure 1 As shown, the method includes the following steps:

[0052] Step S100: Collect soil samples;

[0053] The soil sample in this embodiment is an undisturbed topsoil sample from farmland. The collection process is as follows: a PC tube with a height of 5.5 cm and an outer diameter of 5 cm, with one end ground into a blade, is used to collect the undisturbed topsoil sample from the field. The undisturbed soil sample is then wrapped with plastic wrap to facilitate CT scanning of the soil sample.

[0054] Step S200: Perform a CT scan on the soil sample to obtain the first image slice;

[0055] To ensure that soil samples are subjected to the same suction under uniaxial pressure, and to compare the deformation patterns of different soil samples, this embodiment involves wrapping filter paper around the bottom of the soil sample before CT scanning and saturating it in a sandbox. Once the soil sample is saturated, the suction of the sandbox is adjusted to a preset value to ensure that the soil samples are subjected to the same suction value. Then, industrial CT scanning is used to reconstruct the soil sample, resulting in a TIFF format grayscale image slice, which is the first image slice.

[0056] Step S300: The soil sample is uniaxially compacted, and the compacted soil sample is CT scanned to obtain a second image slice;

[0057] A uniaxial compaction test was conducted on the soil sample using a universal testing machine. After the uniaxial compaction test was completed, the compacted soil sample was CT scanned and reconstructed to obtain a second image slice.

[0058] Specifically, a uniaxial compaction test was conducted on the soil using a universal testing machine. A load greater than the soil pre-compression stress was applied to the universal testing machine, for example, loads of 200 kPa and 400 kPa were applied to the soil samples for 4 hours. Finally, the stress was adjusted back to 1 kPa for 0.5 hours to allow the soil to naturally rebound. The compacted soil samples were then subjected to CT scanning. After reconstruction, TIFF format grayscale image slices of the compacted soil samples were obtained, i.e., the second image slice.

[0059] Furthermore, in this embodiment, after uniaxial compaction of the soil sample, such as Figure 2As shown, the deformation of the soil after stress removal was also measured to obtain the volume of the compacted soil, and the changes in soil bulk density and porosity before and after compaction were calculated. Specifically, the height of the compacted soil sample was first measured, then the soil sample was dried and weighed, and the changes in soil bulk density and porosity before and after compaction were calculated based on the sample mass and measurement data.

[0060] The formula for calculating the soil bulk density before compaction is: The formula for calculating the bulk density of compacted soil is: The formula for calculating soil porosity before compaction is: The formula for calculating the porosity of compacted soil is: Where m is the mass of the soil sample in g; H is the height of the soil sample in cm; d is the degree of soil settlement after stress removal in cm; r is the radius of the soil sample in cm; ρ s The particle density of a soil sample is the ratio of the mass of soil particles to their volume, expressed in g / cm³. 3 .

[0061] Step S400: Perform image processing on the first image slice and the second image slice to obtain a binarized image, and analyze the changes in soil pore characteristic parameters before and after compaction based on the binarized image;

[0062] Three-dimensional images of pore deformation under uniaxial compression are shown below. Figure 3 As shown, for the first and second image slices, soil pores are selected using Image and Avizo software, the three-dimensional structure of the pores is rendered, and the changes in soil macroporosity and soil pore size distribution before and after compaction are calculated.

[0063] like Figure 4 As shown, the specific steps of this embodiment include:

[0064] Step S410: Perform image preprocessing on the first image slice and the second image slice;

[0065] The first and second image slices are imported into ImageJ software. The brightness and contrast of the first and second image slices are adjusted using ImageJ software (Image-adjust-Brightness / Contrast). Median filtering is then applied to the first and second image slices to reduce noise, thereby improving the quality of the target image and thus improving the accuracy of the analysis.

[0066] Step S420: Select the central region as the region of interest in the preprocessed first and second image slices to obtain the target image;

[0067] By selecting the central region as the Region of Interest (ROI) for further image processing, the impact of uniaxial pressure on the real-time PC tube wall can be reduced. Specifically, a certain range is selected at the center of the first image slice and the center of the second image slice to obtain the target image.

[0068] Step S430: Use a single threshold segmentation method to perform threshold segmentation on the target image to obtain a binarized image;

[0069] Specifically, the single threshold segmentation method in ImageJ software is used to perform threshold segmentation on the target image to obtain a binarized image of the target image.

[0070] Step S440: Based on the binarized image, calculate the changes in soil pore characteristic parameters before and after compaction. Soil pore characteristic parameters include soil macroporosity, pore connectivity, and soil pore size distribution.

[0071] Based on the binarized image, the changes in soil macroporosity before and after compaction were calculated using the Volume Fraction module in Avizo software, the changes in pore connectivity before and after compaction were calculated using the Axis Connecticity module in Avizo software, and the changes in soil pore size distribution before and after compaction were calculated using the Thickness module in Avizo software.

[0072] Step S500: Based on the first image slice and the second image slice, obtain the binarized image of the biological pores before compaction and the binarized image after compaction;

[0073] First, identify the biological pores that meet the requirements in the first and second image slices, such as relatively complete, regularly shaped, and representative biological pores. Then, separate the images corresponding to the biological pores in the first and second image slices to obtain the pre-compaction binarized image and the post-compaction binarized image of the biological pores.

[0074] In this embodiment, the specific process of determining the required biological pores in the first and second image slices is as follows: In the first image slice, based on the morphological characteristics of the biological pores (such as tubular shape and relatively continuous structure), the required biological pores are visually identified. For example, by observing a soil sample, relatively complete and regularly shaped biological pores in the grayscale image are visually identified. Based on the position and trend of the biological pores in the first image slice, the corresponding biological pores are found in the second image slice, i.e., the same biological pores after compaction. Please refer to [reference needed] for biological pores before and after compaction. Figure 5 .

[0075] Then, based on the first and second image slices, the region growing method in VG Studio, combined with manual selection, was used to separate representative soil biological pores from the first and second image slices, obtaining binarized images before and after compaction. VG Studio's region growing method can automatically identify the boundaries between target pores and the surrounding soil matrix, and allows for interactive operation, avoiding the simultaneous selection of target biological pores and adjacent non-biological pores, ultimately obtaining a binarized image of the biological pores.

[0076] Step S600: Calculate the changes in biological porosity characteristic parameters before and after compaction based on the binarized images before and after compaction, and evaluate the stability of biological porosity during the compaction process.

[0077] Biological pore characteristic parameters typically include the volume, length, pore diameter, and angle of biological pores.

[0078] Three-dimensional images of biological porosity deformation under uniaxial compaction are shown below. Figure 6 As shown, for the same biological pore before and after compaction, the changes in volume, length, and pore size of the biological pore before and after compaction are calculated based on the binarized images before and after compaction, respectively, to assess the stability of the original biological pore in the field.

[0079] Specifically, for the same biological pore in the pre-compaction binarized image and the post-compaction binarized image, the volume rendering module of Avizo software is used to generate and visualize the three-dimensional structure of the biological pore before and after compaction. The volume fraction module of Avizo software is used to calculate the change of biological porosity before and after compaction based on the three-dimensional structure. The thickness module of Avizo software is used to calculate the pore size distribution of the biological pore based on the three-dimensional structure. The pore size weighted average is used as the pore size of the biological pore, and the change of biological pore size before and after compaction is calculated. The skeleton module of Avizo software is used to obtain the biological pore skeleton, and the change of biological pore length before and after compaction is calculated based on the biological pore skeleton.

[0080] In this embodiment, after obtaining the biological pore skeleton using the skeleton module of Avizo software, the biological pores are further classified to analyze the response of the biological pore angle to uniaxial compaction. Specifically, considering that the pore deformation under stress is related to the pore angle, biological pores with an angle less than 30° between the biological pore skeleton and the z-axis are classified as longitudinal biological pores, and biological pores with an angle greater than 60° between the biological pore skeleton and the z-axis are classified as transverse biological pores.

[0081] In some embodiments, the percentage change in biological porosity characteristic parameters before and after compaction is used instead of the absolute change in biological porosity characteristic parameters to analyze the variation law of biological porosity characteristics before and after compaction.

[0082] In summary, this embodiment compacted soil samples under specific matric potential and measured the soil sample settlement using a universal testing machine. Three-dimensional images of the soil structure were non-destructively acquired using CT scanning technology. Further image processing separated soil particles and pores, and the changes in soil pore structure parameters before and after uniaxial compaction of the same soil sample were calculated. Based on visual inspection and zone growth methods, biological pores at different angles were selected to quantitatively evaluate the stability and deformation patterns of biological pores during uniaxial compaction. Thus, the impact of uniaxial compaction on the undisturbed soil pores in farmland was analyzed using non-destructive CT scanning technology. Naturally formed biological pores in farmland soil were extracted, enabling a quantitative analysis of the stability of biological pores during the compaction process, aiming to provide a scientific basis for mitigating mechanical compaction in the field.

[0083] The purpose of the above embodiments is to reproduce and derive the technical solution of the present invention by way of example, and to fully describe the technical solution, purpose and effect of the present invention. The purpose is to enable the public to have a more thorough and comprehensive understanding of the disclosure of the present invention, and not to limit the scope of protection of the present invention.

[0084] The above embodiments are not an exhaustive list based on the present invention, and there may be many other embodiments not listed. Any substitutions and improvements made without departing from the concept of the present invention are within the protection scope of the present invention.

Claims

1. A method for analyzing soil pore structure deformation under uniaxial compaction, characterized in that, include: Collect soil samples; The soil sample was subjected to a CT scan to obtain a first image slice; The soil sample was uniaxially compacted, and the compacted soil sample was then CT scanned to obtain a second image slice. Image processing is performed on the first image slice and the second image slice to obtain a binarized image. The changes in soil pore characteristic parameters before and after compaction are analyzed based on the binarized image. Based on the first image slice and the second image slice, obtain the pre-compaction binarized image and the post-compaction binarized image of the biological pores; The changes in bioporous characteristic parameters before and after compaction are calculated based on the binarized images before and after compaction, and the stability of bioporous pores during the compaction process is evaluated. The biological porosity characteristic parameters are the volume, length, and pore size of the biological pores. The calculation of the changes in the biological porosity characteristic parameters before and after compaction based on the pre-compaction binarized image and the post-compaction binarized image, and the evaluation of the stability of the biological porosity during the compaction process, includes: For the same biological pore, the pre-compaction binarized image and the post-compaction binarized image are compared using the volume rendering module of Avizo software to compare the three-dimensional structure of the biological pore before and after compaction. The volume fraction module of Avizo software is used to calculate the change in porosity of the biological pore before and after compaction. The thickness module of Avizo software is used to calculate the change in pore diameter of the biological pore before and after compaction based on the three-dimensional structure. The skeleton module of Avizo software is used to generate a biological pore skeleton, and the change in pore length of the biological pore before and after compaction is calculated based on the biological pore skeleton.

2. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 1, characterized in that, Before performing a CT scan on the soil sample, the procedure also includes: Filter paper is wrapped around the bottom of the soil sample and placed in a sandbox to saturate it. After the soil sample is saturated, the suction value of the sandbox is adjusted to a preset value so that the soil sample is under the same suction.

3. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 1, characterized in that, Image processing is performed on the first image slice and the second image slice to obtain a binarized image. Based on the binarized image, the changes in soil pore characteristic parameters before and after compaction are analyzed, including: Perform image preprocessing on the first image slice and the second image slice; The central region is selected as the region of interest in the preprocessed first and second image slices to obtain the target image; The target image is segmented using a single threshold segmentation method to obtain a binarized image. Based on the binarized image, the changes in soil pore characteristic parameters before and after compaction are calculated. These soil pore characteristic parameters include soil macroporosity, pore connectivity, and soil pore size distribution.

4. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 3, characterized in that, Before selecting the central region as the region of interest in the preprocessed first and second image slices, the following preprocessing steps are included: Adjust the brightness and contrast of the first image slice and the second image slice; Median filtering is used to reduce noise in the first image slice and the second image slice.

5. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 3, characterized in that, The calculation of changes in soil pore characteristic parameters before and after compaction based on the binarized image includes: Based on the binarized image, the changes in soil macroporosity before and after compaction were calculated using the volume fraction module in Avizo software, the changes in pore connectivity before and after compaction were calculated using the connectivity module in Avizo software, and the changes in soil pore size distribution before and after compaction were calculated using the thickness module in Avizo software.

6. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 1, characterized in that, After uniaxial compaction of the soil sample and CT scanning of the compacted soil sample to obtain a second image slice, the process further includes drying and weighing the compacted soil sample to obtain the soil sample mass. Based on the soil sample mass and the deformation data of the soil sample before and after compaction, the changes in soil bulk density and soil porosity before and after compaction are calculated.

7. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 1, characterized in that, The step of obtaining a pre-compaction binarized image and a post-compaction binarized image of biological pores based on the first image slice and the second image slice includes: Based on the first image slice and the second image slice, determine the biological pores that meet the requirements; Biological pores were separated from the first image slice and the second image slice using the region growing method in VG Studio software, and the binarized image before compaction and the binarized image after compaction were obtained respectively.

8. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 7, characterized in that, The step of determining the required biological pores based on the first image slice and the second image slice includes: In the first image slice, biological pores that meet the requirements are identified visually based on their morphological characteristics. Based on the position and trend of the biological pores in the first image slice, the corresponding biological pores are identified in the second image slice.

9. The method for analyzing soil pore structure deformation under uniaxial compaction as described in claim 1, characterized in that, After generating a biological porous framework using the framework module of Avizo software, the following steps are also included: Biological pores with an angle of less than 30° between the biological pore framework and the z-axis are classified as longitudinal biological pores, and biological pores with an angle of greater than 60° between the biological pore framework and the z-axis are classified as transverse biological pores. The influence of biological pore angle on pore deformation is analyzed.

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