A method and system for quantitatively analyzing a full-scale microstructure of a chloridic silt clay

Abstract

This invention discloses a method and system for quantitative analysis of the full-scale microstructure of chloride-containing silty clay, belonging to the field of geotechnical materials mechanics. The method first prepares standard samples and performs CT and NMR tests to obtain microscopic two-dimensional images and microscopic relaxation time distributions. Micrometer-level pore characteristic parameters are extracted based on image processing, and nanometer-level pore characteristic parameters are inverted based on the relaxation mechanism. The two types of parameters are compared and fused, and overlapping data are corrected to generate a full-scale pore size distribution curve covering the nanometer to micrometer scales. The pore size fractal dimension is then calculated through piecewise fitting. This invention integrates the complementary advantages of CT and NMR technologies, overcoming the limitations of single-scale analysis, and achieving integrated, full-scale characterization of the microstructure of saline soils, providing a reliable tool for revealing the evolution mechanism of their macroscopic mechanical properties.

Description

Technical Field

[0001] This invention relates to the field of geotechnical materials mechanics, and in particular to a method and system for quantitative analysis of the full-scale microstructure of chloride-containing silty clay. Background Technology

[0002] Saline soils, especially marine saline soils dominated by chloride salts, are widely distributed in coastal areas and exhibit significant uniqueness and complexity in their engineering properties. Due to the influence of soluble salts, the mechanical behavior and stability of this type of soil differ significantly from those of general cohesive soils. The dissolution of chloride salts weakens the cementation between soil particles, leading to soil softening and reduced bearing capacity, making it more prone to instability, especially under water conditions. Furthermore, the dissolution-crystallization cycle of chloride salts can trigger repeated expansion and contraction of the soil, thereby inducing uneven foundation settlement and cracking of pavement structures. In low-temperature environments, the presence of chloride salts lowers the freezing point of water in the soil, exacerbating freeze-thaw cycles and further damaging the internal structure of the soil. Simultaneously, chloride salts may alter the permeability characteristics of the soil, promoting pore expansion and increased permeability, increasing the risk of piping and groundwater contamination. These problems pose serious challenges to foundation treatment, road engineering, and the construction and long-term safe operation of water conservancy facilities.

[0003] To ensure the smooth implementation and safe operation of engineering projects in saline-alkali soil areas, it is necessary to deeply reveal the mechanisms underlying the changes in their mechanical properties. Elucidating these mechanisms requires a systematic understanding of the microstructure of the soil. Currently, research methods on the microstructure of saline-alkali soils are mostly limited to a single scale: at the mesoscale, techniques such as X-ray computed tomography (CT) are primarily used to characterize micron-sized pores and fractures; at the microscale, methods such as nuclear magnetic resonance (NMR) are often employed to analyze the distribution of nanoscale pores. However, existing technologies lack a comprehensive analytical method that can effectively connect and integrate the mesoscale and microscale, making it difficult to systematically and accurately reveal the structural characteristics, distribution patterns, and interaction mechanisms of pores from the nanoscale to the microscale. This limitation of a single scale restricts a deeper understanding of the multi-scale structural evolution mechanisms behind the macroscopic mechanical behavior of saline-alkali soils and also limits the comprehensive assessment of the structural response of soils under engineering disturbances (such as freeze-thaw cycles and load changes).

[0004] Therefore, the existing technology has the following main drawbacks: First, existing analytical methods are mostly isolated at a single mesoscale or microscale, failing to achieve a coherent characterization of pore structures across scales and thus unable to provide complete information on the full-scale pore size distribution.

[0005] Second, due to the lack of full-scale structural data, it is difficult to accurately reveal the interaction between pore structures at different scales and their synergistic influence mechanism on the macroscopic mechanical properties of soil.

[0006] Third, the respective advantages of CT and NMR technologies were not fully combined to effectively correct and fuse complementary pore information, which limited the comprehensiveness and accuracy of structural parameter acquisition.

[0007] To address the aforementioned shortcomings, there is an urgent need to develop a method that can cover the nano to micro scale and achieve integrated quantitative analysis of microstructures, so as to more completely reveal the mechanical property mechanism of saline soil and provide a more reliable theoretical basis for related engineering problems. Summary of the Invention

[0008] Therefore, this invention aims to address the problem that existing analyses of the mechanical properties of marine saline soils are limited to a single micro or mesoscopic scale and lack full-scale integration of nanometer to micrometer-level pores, making it difficult to accurately reveal the interaction mechanisms of structural changes at different scales. Simultaneously, it provides mechanistic support for the soil mechanical changes induced by artificial freezing during the construction of submarine tunnels in coastal areas. Thus, it provides a method and system for quantitative analysis of the full-scale microstructure of chloride-containing silty clay. The method for quantitative analysis of the full-scale microstructure of chloride-containing silty clay includes the following steps: Step S1: Prepare chloride silty clay samples for microstructure analysis; Step S2: The chloride silty clay sample is subjected to X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests, respectively. The CT test yields a two-dimensional sequence image, and the NMR test yields the transverse relaxation time distribution. Step S3: Based on the two-dimensional sequence images, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale; based on the transverse relaxation time distribution, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale. Step S4: Compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping area to generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

[0009] In one embodiment of the present invention, the method for preparing chloride silty clay samples for microstructure analysis in step S1 is as follows: Chloride silty clay from the target area was selected and prepared into saturated cylindrical undisturbed or remolded specimens according to geotechnical testing standards. Then, a standard specimen with a diameter of φ19mm and a height of 25mm was cut from the cylindrical specimen using a ring cutter.

[0010] In one embodiment of the present invention, in step S3, based on the two-dimensional sequence images, the pore size distribution and structural parameters of the microporous structure are analyzed to obtain the pore characteristic parameters at the microscale, as follows: The two-dimensional sequence image is filtered to obtain the filtered image; The filtered image is subjected to threshold segmentation processing. The segmentation threshold is determined by gray value statistics. The image is binarized into porous phase and solid particle phase to obtain a binarized image sequence. The binarized image sequence is reconstructed in three dimensions to establish a three-dimensional spatial model of the pore structure. Quantitative analysis of the three-dimensional spatial model yields mesoscale pore characteristic parameters, including porosity and pore size distribution parameters; wherein, the porosity... The calculation formula is: , The pore volume extracted from the three-dimensional spatial model. This refers to the total volume of the sample. The method for obtaining the aperture distribution parameters is as follows: by calculating the equivalent diameter of each connected pore. The calculation formula is as follows: , where V is the volume of a single pore; the number or volume ratio of pores in different equivalent diameter ranges are statistically analyzed to form a micrometer-scale pore size distribution histogram or cumulative curve.

[0011] In one embodiment of the present invention, in step S3, based on the transverse relaxation time distribution, the pore size distribution and structural parameters of the micro-pore structure are analyzed to obtain the pore characteristic parameters at the microscale, as follows: For clay samples, the rate of surface relaxation is much greater than that of free relaxation and diffusion relaxation. Therefore, in actual calculations, the effects of free relaxation and diffusion relaxation are ignored, and only the surface relaxation mechanism is considered, using a conversion formula. Lateral relaxation time Equivalent radius converted to target pore size The pore radius distribution was obtained, where The surface relaxation rate, Pore ​​shape factor; Regarding the lateral relaxation time The distribution curve is integrated to obtain the total signal peak area; by testing standard soil samples with known porosity, a calibration relationship between the total signal peak area and porosity is established; based on the calibration relationship, the total peak area is converted into total porosity at the microscale. Based on the converted pore radius distribution, the pores are classified and statistically analyzed according to the preset pore diameter range, and the percentage of the volume of each type of pore in the total pore volume is calculated. Thus, we obtain the result based on the lateral relaxation time. The microscale pore characteristic parameters consist of the converted pore radius distribution, the total micro porosity obtained through calibration, and the proportion of pore volume of each size after classification.

[0012] In one embodiment of the present invention, the method for comparing and fusing the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale in step S4 is as follows: Obtain the pore size distribution range corresponding to the pore characteristic parameters at the mesoscale and the pore size distribution range corresponding to the pore characteristic parameters at the microscale, plot them on the same coordinate system, and identify and determine the overlapping interval of the two distribution curves. A threshold for the cumulative pore volume ratio is set. If, within the overlapping region, the cumulative pore volume ratio of the pore characteristic parameters at the microscale is lower than the threshold, then data fusion is performed according to the following rules: For the pore size range before the overlapping region, pore size distribution data at the microscale is used; starting from the starting point of the overlapping region, including the entire overlapping region and the larger pore size range thereafter, pore size distribution data at the mesoscale is used to obtain calibrated microscale pore radius distribution data.

[0013] In one embodiment of the present invention, the specific steps for generating the full-scale aperture distribution curve are as follows: The calibrated microscale pore radius distribution data and the pore radius distribution data obtained by equivalent diameter inversion at the mesoscale are sorted in ascending order of pore radius; A nonlinear fitting method is used to fit the sorted discrete pore radius distribution data to generate a smooth and continuous full-scale pore size cumulative volume distribution curve covering both micro and mesoscale. The curve shape of the small pore size segment is determined by the microscale pore radius distribution data, while the curve shape of the large pore size segment is determined by the mesoscale pore radius distribution data.

[0014] In one embodiment of the present invention, the method for quantitative analysis of full-scale microstructure based on the full-scale aperture distribution curve includes fractal dimension calculation, specifically: Take the logarithm of the full-scale aperture distribution curve and plot it. Relationship diagram, in which For the cumulative volume fraction, Where is the pore radius; According to the above The relationship diagram determines the inflection point of the curve and divides it into two linear characteristic segments: small pore size and large pore size, which correspond to two different pore structure systems: intragranular pores and intergranular pores, respectively. Based on fractal theory formulas Fittings are performed on the two linear regions respectively, and the slopes are used to determine the approximation. Calculate the corresponding fractal dimension Thus, the fractal dimension of the small aperture segment is obtained. and fractal dimension of large aperture segment ;in, The maximum pore radius; The fractal dimension of the small aperture segment and the fractal dimension of the large aperture segment It serves as a quantitative indicator to characterize the complexity and heterogeneity of pore structures across different scale ranges.

[0015] Based on the same inventive concept, the present invention also provides a quantitative analysis system for the full-scale microstructure of chloride silty clay, comprising: a sample preparation module, a data measurement module, a data processing module, and a result analysis module; The sample preparation module is used to prepare chloride silty clay samples for microstructure analysis. The data measurement module is used to perform X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests on the chloride silty clay sample, respectively. The CT test yields a two-dimensional sequence image, and the NMR test yields the transverse relaxation time distribution. The data processing module is used to analyze the pore size distribution and structural parameters of the micro-pore structure based on the two-dimensional sequence images to obtain pore characteristic parameters at the micro-scale; and to analyze the pore size distribution and structural parameters of the micro-pore structure based on the transverse relaxation time distribution to obtain pore characteristic parameters at the micro-scale. The result analysis module is used to compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping intervals, generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

[0016] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for quantitative analysis of the full-scale microstructure of chloride silty clay.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for quantitative analysis of the full-scale microstructure of chloride silty clay.

[0018] Compared with the prior art, the above-described technical solution of the present invention has the following advantages: The core advantage of this technical solution lies in its innovative integration of the complementary advantages of CT and NMR technologies. CT precisely captures micron-level micropores, while NMR efficiently inverts nano-level micropores. After data correction and stitching, a full-scale pore size distribution curve covering the nano to micron scale is formed, overcoming the limitations of traditional single-scale analysis. The sample preparation process strictly follows standards while taking into account soil structure. The experimental parameters are set scientifically and precisely, and professional processing methods such as median filtering and threshold segmentation, along with fractal dimension quantification analysis, ensure the accuracy and comprehensiveness of pore structure parameters. The method rationally reuses existing mature equipment and software, eliminating the need for additional specialized instruments. While reducing the difficulty of parameter acquisition and experimental costs, it can reveal the interaction mechanism of pores at different scales in marine saline soils more deeply, providing reliable mechanistic support for soil mechanical changes caused by the application of artificial freezing methods in coastal infrastructure construction. It combines practicality and scientific rigor. Attached Figure Description

[0019] To make the content of this invention easier to understand, the invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0020] Figure 1 This is a flowchart illustrating a method for quantitative analysis of the full-scale microstructure of chloride silty clay provided in an embodiment of the present invention. Figure 2 It is the particle size distribution curve of the soil used in the experiment; Figure 3 This refers to the CT image processing workflow; Figure 4 The porosity and its relative growth rate of samples under different freeze-thaw conditions (no freeze-thaw, -10℃, -20℃, -30℃) are curves under the conditions of 2% salt content and 0.6 MPa consolidation pressure. Figure 5 The curves show the trend of total porosity and its relative growth rate of samples with different salt contents under the conditions of freezing temperature -10℃ and consolidation pressure of 0.6 MPa. Figure 6 The curves show the trend of total porosity and its relative growth rate of samples under different consolidation pressures at a freezing temperature of -10℃ and a salt content of 2%. Figure 7 The cumulative volume distribution curves of pore size for samples in different freeze-thaw states are obtained under the conditions of 2% salt content and 0.6 MPa consolidation pressure. Figure 8 The cumulative volume distribution curves of pore size for samples with different salt contents are obtained under the condition of -10℃ freeze-thaw and 0.6 MPa consolidation pressure. Figure 9The cumulative volume distribution curves of pore size of the samples under different consolidation pressures under conditions of no freeze-thaw and 2% salt content are shown. Figure 10 The total porosity of the samples was measured at different freezing temperatures under the conditions of 2% salt content and 0.6 MPa consolidation pressure. Figure 11 The changes in total porosity and growth rate of samples with different salt contents before and after freeze-thaw are investigated under the conditions of freezing temperature -10℃ and consolidation pressure of 0.6 MPa. Figure 12 The changes in the volume content of large, medium and small pores under different salt contents are determined under the conditions of freezing temperature -10℃ and consolidation pressure of 0.6 MPa. Figure 13 The changes in pore size distribution and total porosity of the samples under different consolidation pressures at a freezing temperature of -10℃ and a salt content of 2% are shown. Figure 14 The cumulative pore size distribution of CT and NMR test data under different freeze-thaw temperatures is compared under the conditions of 2% salt content and 0.6 MPa consolidation pressure. Figure 15 The cumulative pore size distribution of CT and NMR test data under different salt contents is compared after freezing and thawing at -10℃ and consolidation pressure of 0.6 MPa. Figure 16 The cumulative pore size distribution of CT and NMR test data under different consolidation pressures under conditions of no freeze-thaw and 2% salt content is compared. Figure 17 This is a schematic diagram of the full-scale pore size distribution correction method, taking a sample with a consolidation pressure of 0.6 MPa, a salt content of 2%, and no freeze-thaw conditions as an example. Figure 18 It is the total volumetric pore size distribution of all samples after correction. Figure 19 This is a schematic diagram of the double logarithmic relationship between the cumulative volume fraction of pores and the pore radius based on the full-scale pore size distribution; Figure 20 This is a schematic diagram of a full-scale microstructure quantitative analysis system for chloride silty clay provided in an embodiment of the present invention.

[0021] Explanation of reference numerals in the accompanying drawings: 100, Sample preparation module; 200, Data measurement module; 300, Data processing module; 400, Result analysis module. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0023] Example 1: Reference Figure 1 As shown, this invention provides a method for quantitative analysis of the full-scale microstructure of chloride silty clay, specifically including the following steps: Step S1: Prepare chloride silty clay samples for microstructure analysis; Step S2: The chloride silty clay sample is subjected to X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests, respectively. The CT test yields a two-dimensional sequence image, and the NMR test yields the transverse relaxation time distribution. Step S3: Based on the two-dimensional sequence images, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale; based on the transverse relaxation time distribution, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale. Step S4: Compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping area to generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

[0024] Further, in step S1, the method for preparing chloride silty clay samples for microstructure analysis is as follows: Typical chloride-rich silty clay from the Yangtze River Delta region was selected as the test soil. Particle size distribution was analyzed using a Microtrac S3500 laser particle size analyzer, and the particle size distribution curves are shown below. Figure 2 The basic physical properties of the soil sample are shown in Table 1, and the contents of the main ions (Na⁺, K⁺, Ca²⁺, Cl⁻, HCO3⁻, SO4²⁻) are shown in Table 2. The contents of each ion are all less than 0.015%, and the total salt content is only 0.03%. The influence of the initial salt content was ignored during sample preparation, and no additional salt washing was required.

[0025] Table 1 Basic physical properties of the soil used in the experiment

[0026]

[0027] Table 2. Main ion content of the soil used in the experiment

[0028]

[0029] NaCl was selected as the salt content representative, and the reshaped sample was prepared by the compaction method. The specific process was as follows: (1) The soil sample was dried, crushed and passed through a 2mm sieve; (2) NaCl was mixed with water to prepare salt solutions with different target salt contents; (3) The salt solution was mixed with soil particles to make the soil moisture content reach the optimal moisture content of 21%; (4) The mixed soil particles were placed in a sealed bag and left to stand for 24 hours to ensure that the salt solution was evenly distributed; (5) The samples were compacted in layers according to the maximum dry density of 1.65g / cm³ to make cylindrical samples with a diameter of 50mm×100mm; (6) The samples were immersed in water and vacuum saturated for 24 hours; (7) The consolidation treatment was carried out by simulating the actual burial depth of the strata using a triaxial test device; (8) After the consolidation was completed, a standard sample with a diameter of φ19mm and a height of 25mm was cut from the center of the sample with a ring cutter for subsequent CT and NMR tests.

[0030] For scenarios requiring simulation of artificial freezing construction environments, some consolidated standard samples were subjected to freeze-thaw cycles: the samples were sealed with plastic wrap, and petroleum jelly was applied to the joints to prevent moisture loss. They were then placed in a low-temperature environment chamber and frozen at a preset temperature for 12 hours to ensure that the samples were completely frozen and the temperature was uniform. Subsequently, they were thawed at room temperature of 20°C for 12 hours to obtain samples that had undergone one freeze-thaw cycle, which were used to compare the changes in the microstructure of the soil before and after the freeze-thaw cycle.

[0031] Further, in step S2, the chloride silty clay sample is subjected to X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests, respectively. The X-ray computed tomography test yields a two-dimensional sequence image, and the nuclear magnetic resonance test yields the transverse relaxation time distribution. The specific method steps are as follows: The CT test used a 125kV scanning voltage and a 100μA scanning current to perform 1000×1000×1000 slice scanning on the sample, with a scanning resolution of 15μm. Two-dimensional sequence images of the sample were obtained through the test. The NMR experiment was conducted in a permanent magnet environment at 32℃. The transverse relaxation time (T2) distribution was measured using a CPMG sequence. The experimental parameters were set as follows: repeat sampling wait time (TW) of 1000 ms, echo time (TE) of 0.1 ms, and number of echoes (NECH) of 1500. The transverse relaxation time (T2) distribution data of the samples were obtained through the experiment. The specific CT and NMR experimental plans are shown in Table 3.

[0032] Table 3 CT and NMR Trial Plans

[0033]

[0034] Furthermore, in step S3, based on the two-dimensional sequence images, Avizo software is used to perform pore size distribution and structural parameter quantification analysis on the microscopic pore structure to obtain pore characteristic parameters at the microscopic scale. The specific method is as follows: To address the noise interference present in the original CT images, a median filter algorithm is used to denoise the two-dimensional image sequence. Each pixel value is replaced with the median of its adjacent pixel values. While suppressing image noise and eliminating noise points, the edge contours, geometric shapes, and topological features of the pores are preserved, resulting in a filtered image. The filtered image is subjected to threshold segmentation: based on the mathematical and statistical characteristics of the image grayscale histogram, the optimal segmentation threshold is determined, wherein pixels with grayscale values ​​below the threshold are identified as porous phases, and pixels with grayscale values ​​above the threshold are classified as soil particle solid skeleton phases, thereby accurately separating the porous network from the complex background and obtaining a binarized image sequence. After extracting the pores, pore characteristic parameters, including porosity, pore length-to-minor axis ratio, orientation angle, shape factor, and fractal dimension, are calculated using functional modules such as Label Analysis, Volume Fraction, and Fractal Dimension. Specifically, pore types are distinguished based on the shape factor parameter; this method defines pores with a shape factor greater than 5 as fractures, and fractures are filtered using an Analysis Filter. Three-dimensional volume rendering technology is then used to perform 3D visualization reconstruction of both pores and fractures, visually displaying their spatial distribution. The core workflow of the entire image processing is as follows: Figure 3 As shown. Wherein: Porosity It is calculated using the following formula (1): (1); where, The pore volume extracted from the three-dimensional spatial model is expressed in μm³. The total volume of the sample is expressed in μm³.

[0035] Based on the calculation results of the total porosity of the samples under different test conditions (freeze-thaw temperature, salt content, consolidation pressure) Figures 4 to 6 By combining this with the relative growth rate calculated using the first data point of each group as the baseline, the following pattern can be derived: Effect of freeze-thaw temperature: Freeze-thaw action significantly increased the total porosity of the samples. Among them, the porosity increase was most significant after freezing and thawing at -10℃, with a relative growth rate of 120%. As the freezing temperature decreased, the porosity growth rate showed an exponential decreasing trend; after freezing and thawing at -30℃, the total porosity of the samples was basically the same as that of the unfrozen samples, with a growth rate of only 2%.

[0036] Effect of salt content: Regardless of whether it was before or after freeze-thaw, the total porosity of the samples showed a trend of first increasing and then decreasing with increasing salt content, and there was a critical salt content that caused the total porosity to reach its maximum value. Before freeze-thaw, this critical salt content was 3%; after freeze-thaw, the critical salt content shifted to 2%. The comparison showed that the change in porosity caused by salt content after freeze-thaw was smaller than before freeze-thaw, indicating that freeze-thaw action inhibited the effect of salt content to a certain extent. In addition, under low salt content conditions (0%-2%), the total porosity after freeze-thaw was significantly higher than before freeze-thaw; while under high salt content conditions (3% and 4%), the difference in total porosity before and after freeze-thaw was not significant.

[0037] The effect of consolidation pressure: The effect of freeze-thaw cycles is modulated by consolidation pressure. Before freeze-thaw, the total porosity decreases approximately linearly with increasing consolidation pressure, with all growth rates being negative, indicating that the pores are compressed under pressure. For example, when the consolidation pressure increases from 0.2 MPa to 0.4 MPa, the total porosity decreases by about 76%. After freeze-thaw, the linear relationship between total porosity and consolidation pressure is broken, and its value distribution tends to be concentrated (about 2.5%~3%). Although it is slightly higher at a consolidation pressure of 0.6 MPa, the overall effect of consolidation pressure changes is significantly weakened.

[0038] To quantify pore size, the volume of each individual pore is equivalent to that of a sphere, with its equivalent diameter being... (Unit: μm) It is calculated using the following formula (2): (2); Where V is the volume of a single pore, in μm³. By statistically analyzing the equivalent diameters of all pores, the pore size distribution of the sample at the micrometer scale (e.g., 15 μm to 1000 μm) can be obtained.

[0039] Based on the cumulative volume distribution curve of pore size (e.g.) Figures 7 to 9 The analysis yields the following main conclusions: Freeze-thaw cycles lead to pore size expansion: The freeze-thaw process causes a significant shift in the overall pore size distribution curve towards larger pores, indicating a general increase in pore size. Specifically, the minimum pore size increases from approximately 15 μm before freeze-thaw to around 28 μm; the increase in maximum pore size is particularly significant, increasing from 286 μm before freeze-thaw to 957 μm (-10°C), 732 μm (-20°C), and 546 μm (-30°C), respectively. The increase in maximum pore size is negatively correlated with the freezing temperature; that is, the higher the freezing temperature, the more significant the increase in maximum pore size after freeze-thaw.

[0040] Salt content expands the pore size distribution range: The minimum pore size of samples with different salt contents is similar. However, after freeze-thaw, the sample with a salt content of 2% has the widest pore size distribution curve, indicating that the pore size range is the widest under this condition, i.e., there are more large pores. This shows that the incorporation of salt, especially at a specific content, makes the pore size distribution more dispersed after freeze-thaw.

[0041] Consolidation confining pressure dominates pore size compression effect: Based on pore size distribution characteristics, samples under different confining pressures can be divided into two groups: low confining pressure group (0.2 MPa and 0.4 MPa) and high confining pressure group (0.6 MPa and 0.8 MPa). With increasing consolidation confining pressure, the pore size distribution curve shifts significantly to the left (towards smaller pore sizes), indicating an overall refinement of the pore structure. Specifically, the minimum pore size decreases from approximately 26 μm under low confining pressure to approximately 15 μm under high confining pressure; simultaneously, the maximum pore size decreases significantly from approximately 667 μm to approximately 228 μm. This demonstrates that consolidation pressure has a strong compressive and reshaping effect on the pore structure.

[0042] Furthermore, in step S3, based on the transverse relaxation time distribution, the pore size distribution and structural parameters of the micro-pore structure are analyzed to obtain the pore characteristic parameters at the microscale, as follows: The transverse relaxation time (T2) of the sample was obtained using a nuclear magnetic resonance (NMR) core analysis system, taking advantage of the spin characteristics of the hydrogen nucleus (¹H). The relaxation time is influenced by multiple mechanisms, primarily including free relaxation, surface relaxation, and diffusion relaxation. Free relaxation originates from the fluid's inherent properties and is related to fluid composition, viscosity, and environmental factors such as temperature and pressure. Surface relaxation occurs at the interface between the porous fluid and solid particles, and its rate is determined by the surface relaxation rate (ρ2), pore surface area (S), and pore volume (V). Diffusion relaxation is related to the magnetic field gradient and echo interval; a longer echo interval was used in this experiment to highlight its effect.

[0043] Therefore, the transverse relaxation time T2 can be expressed by the following formula: (3); In the formula: T2 is the transverse relaxation time (ms); T2B, T2S, and T2D are the transverse relaxation times (ms) corresponding to free relaxation, surface relaxation, and diffusion relaxation, respectively; ρ2 is the surface relaxation rate (μm / ms); S is the pore surface area (μm²); and V is the pore volume (μm³).

[0044] For the clay samples studied, surface relaxation is the dominant relaxation mechanism, and its rate is much greater than that of free relaxation and diffusion relaxation. Therefore, in practical analysis, the influence of the latter two can be ignored, and equation (3) can be simplified to: (4); In the formula: This is the pore shape factor (assuming the pores are columnar, the value is 2); Let T2 be the equivalent radius (μm) of the target pore. This formula establishes the relationship between the relaxation time T2 and the equivalent radius of the target pore. The inverse relationship between them forms the theoretical basis for inverting aperture distribution using NMR T2 spectra.

[0045] The peak area of ​​the T2 spectrum can be obtained by integrating the measured T2 distribution curve. Prior to the experiment, a quantitative relationship between the NMR peak area and porosity of different soil samples was established through calibration tests. Based on this calibration result, the measured T2 peak area can be converted into the total porosity of the sample, thereby achieving a quantitative characterization of its microporous structure.

[0046] Based on the nuclear magnetic resonance (NMR) test results, the parameter analysis of the microporous structure of the sample is as follows, and the influence of various conditions is summarized as follows: Depend on Figure 10 The influence of freeze-thaw temperature is as follows: freeze-thaw action increases the total porosity of the sample, and the increase is negatively correlated with the freezing temperature. The total porosity of the unfrozen sample was 20.5%; after freeze-thaw at -10℃, it increased to 23.6%, a relative increase of approximately 15.1%; after freeze-thaw at -30℃, it increased slightly to 20.6%, a relative increase of only about 0.5%. Based on pore size classification (macropores: >50 nm; mesopores: 2~50 nm; micropores: <2 nm), the composition ratio of pore volume under different freeze-thaw conditions was basically consistent: mesopores accounted for the highest proportion (approximately 88%), followed by micropores (approximately 11%), and macropores accounted for the lowest proportion (approximately 1%). This indicates that freeze-thaw temperature mainly affects the absolute value of porosity, but does not significantly change the overall distribution pattern of pore types.

[0047] Depend on Figures 11-12 The influence of salt content can be observed as follows: at a freezing temperature of -10℃, the total porosity first increases and then decreases with increasing salt content. Figure 11After freeze-thaw cycles, the porosity of samples with different salt contents was higher than that in the unfrozen state, but the growth rate decreased in stages with increasing salt content: when the salt content was ≤2%, the growth rate was approximately linearly correlated with the salt content; when the salt content increased from 2% to 3%, the growth rate decreased sharply. Among them, the porosity of the 0% salt content sample increased from 21.1% to 25.1% after freeze-thaw, with the highest growth rate (approximately 19.0%); while the porosity of the 4% salt content sample increased from 18.5% to 19.0%, with the lowest growth rate (approximately 2.7%).

[0048] From the perspective of pore composition ( Figure 12 Both before and after freeze-thaw cycles, the pore volume was predominantly mesopores. After freeze-thaw, the pore structure of the 0% salt content sample showed the most significant changes: the proportion of mesopores decreased from 93.1% to 78.4%, the proportion of macropores increased significantly from 0.7% to 13.2%, and the proportion of micropores increased from 6.2% to 8.4%. This change reveals two main mechanisms during the freeze-thaw process: some mesopores expand and merge into macropores, while the expansion of macropores may compress surrounding structures to form new micropores. A similar transformation also occurred in the low salt content (1%) sample, but to a weaker degree, with a pore reduction rate of only 4.2%.

[0049] Depend on Figure 13 The influence of consolidation pressure can be observed: for samples with a salt content of 2% and a freezing temperature of -10℃, the total porosity before and after freeze-thaw shows a linear decreasing trend with increasing consolidation pressure, but the rate of decrease differs. Figure 13 Before the freeze-thaw cycle, as the confining pressure increased from 0.2 MPa to 0.8 MPa, the porosity decreased from 24.3% to 18.9%, a reduction of approximately 22.2%. After the freeze-thaw cycle, under the same change in confining pressure, the porosity only decreased from 24.6% to 23.2%, a reduction of approximately 5.7%. This indicates that the freeze-thaw cycle significantly weakens the compressive effect of the consolidation confining pressure on the porosity.

[0050] Meanwhile, the consolidation pressure also significantly modulates the effect of freeze-thaw cycles: under a low consolidation pressure of 0.2 MPa, the porosity increase caused by freeze-thaw is only 1.5% (24.3%→24.6%); while under a high consolidation pressure of 0.8 MPa, the increase reaches 23.2% (18.9%→23.2%), a difference of approximately 15 times. This phenomenon indicates a significant coupled interaction between freeze-thaw cycles and consolidation pressure. Under these specific salinity and temperature conditions, the volume ratio of large, medium, and small pores did not change significantly before and after freeze-thaw, with medium pores still maintaining a dominant proportion of approximately 88%.

[0051] Nuclear magnetic resonance (NMR) test results show that the microstructure of the sample is jointly regulated by freeze-thaw temperature, salt content, and consolidation pressure: freeze-thaw action increases porosity, but its effect is inhibited by temperature and salt content; salt content affects the porosity change trend and pore transformation during freeze-thaw process; consolidation pressure not only compresses pores but also has a coupling effect with freeze-thaw action, jointly shaping the final pore structure characteristics.

[0052] In step S4, based on the pore characteristic parameters obtained from CT and NMR experiments, this section performs a comprehensive analysis of the full-scale (micrometer–nanometer) micro-pore structure of the sample. The specific method is as follows: like Figures 14-16 As shown, there are significant differences in the pore size distribution range revealed by CT and NMR experiments: CT experiments mainly characterize micron-sized pores (distribution range of approximately 10). 2 -10 3 While NMR experiments primarily reflect nanoscale pores (distribution range approximately 10 μm), NMR experiments mainly reflect nanoscale pores (distribution range approximately 10 μm). −1 -10 2 Although there is some overlap between the two, the pore volume measured by NMR in the overlapping region is extremely low (e.g., <0.01%), so the two types of experiments can be regarded as complementary: CT is mainly used to capture micron-sized large pores and cracks, while NMR focuses on characterizing nano-sized small pores.

[0053] To obtain a continuous pore size distribution from nanometer to micrometer scale, CT and NMR data need to be stitched and corrected. An example is taken of an unfrozen sample with a consolidation pressure of 0.6 MPa and a salt content of 2%. Figure 17 (This section describes the splicing method.) Plot the aperture distribution curves of the two sets of experiments on the same coordinate system to determine their overlapping aperture range.

[0054] According to the established splicing rules: before the overlap zone (i.e., the small pore end), the NMR results shall prevail; in the overlap zone and after (i.e., extending towards the large pore size), because NMR is easily affected by factors such as surface moisture at larger pore sizes and its contribution to pore volume in this range is minimal, the CT test results shall prevail.

[0055] By stitching the curves according to the above rules, the corrected full-scale cumulative volume distribution of apertures is obtained.

[0056] The corrected full-scale cumulative pore volume distribution of all samples is as follows: Figure 18 As shown. The results indicate that: In the small aperture range ( The curve shape is similar to that of NMR results, but the volume fraction is generally reduced after correction, and it is less affected by different experimental conditions. In the large pore size range ( The curves are mainly controlled by CT results. The curve shapes and volume ratios under different experimental conditions vary significantly, reflecting the obvious influence of various factors on the macroporous structure.

[0057] In summary, by complementing and stitching CT and NMR data, continuous characterization of pore structure from the nanometer to the micrometer scale was achieved, providing a reliable method for a comprehensive understanding of the full-scale evolution of soil pore systems under the influence of multiple factors.

[0058] Based on the aforementioned full-scale pore size distribution, fractal theory is further employed to quantify the differences in pore structure. The fractal characteristics of pore structure can be analyzed through the fractal dimension of pore size. The characterization, and its derivation process, are as follows: In fractal structures, pore radius Its quantity The relationship between them satisfies: (5); In the formula, C is a proportionality constant.

[0059] Assuming the pores are composed of capillary bundles of equal diameter, then the number of pores... It can also be expressed as the ratio of volume to the volume of a single tube: (6); In the formula, For the corresponding pore volume, Let be the length of the capillary. To simplify the model, assume the capillary length is proportional to the radius, and let be... Substituting into equation (6), we obtain the pore volume: (7).

[0060] Substituting equation (5) into equation (7), we obtain the relationship between volume and aperture: (8); right Differentiating, we obtain the volume density function for the pore size distribution: (9); Integrating equation (9), we can obtain that the aperture is less than cumulative volume : (10); In the formula, This represents the minimum pore radius. Similarly, the total pore volume... for: (11); In the formula, This is the maximum pore radius. Therefore, the pore diameter is smaller than... Pore ​​cumulative volume fraction for: (12).

[0061] when Then, equation (12) can be simplified to: (13); Taking the common logarithm of both sides of equation (13), we can obtain a linear relationship: (14); Equation (14) shows that, and The relationship is linear, and its slope is... With fractal dimension satisfy Therefore, the slope can be calculated by fitting. .

[0062] according to Figure 19 shown The relationship curve was found to be non-linear, indicating that the pore structure exhibits multifractal characteristics. Therefore, a piecewise fitting method was adopted: the pores were divided into small-pore segments (usually corresponding to intragranular pores) and large-pore segments (usually corresponding to intergranular pores) using the inflection points of the curve as boundaries. The slopes of the two segments were calculated separately to obtain the corresponding fractal dimensions. (Small aperture section) and (Large pore size segment). Analysis shows that the double logarithmic curves of all samples exhibit a highly consistent trend, and can be characterized using the same set of shape dimensions, i.e. , .

[0063] The fractal dimension of the small aperture segment and the fractal dimension of the large aperture segment As quantitative indicators, they characterize the complexity, irregularity, and heterogeneity of pore structures at the micro and mesoscale, respectively, to achieve a complete description of the fractal properties of soil pore systems across all scales.

[0064] Through the above process, this invention systematically integrates complementary micro- and nano-scale experimental information, overcomes the scale limitations of single technologies, establishes a continuous full-scale pore distribution characterization method, and provides a powerful quantitative analysis tool for the evolution mechanism of pore structures.

[0065] Example 2: like Figure 20 As shown, based on the same inventive concept as in Embodiment 1, the present invention also provides a full-scale microstructure quantitative analysis system for chloride silty clay, including: a sample preparation module 100, a data measurement module 200, a data processing module 300, and a result analysis module 400. The sample preparation module 100 is used to prepare chloride silty clay samples for microstructure analysis. The data measurement module 200 is used to perform X-ray computed tomography and nuclear magnetic resonance tests on the chloride silty clay sample, respectively. The X-ray computed tomography test yields a two-dimensional sequence image, and the nuclear magnetic resonance test yields a transverse relaxation time distribution. The data processing module 300 is used to perform pore size distribution and structural parameter analysis on the micro-pore structure based on the two-dimensional sequence image to obtain pore characteristic parameters at the micro-scale; and to perform pore size distribution and structural parameter analysis on the micro-pore structure based on the transverse relaxation time distribution to obtain pore characteristic parameters at the micro-scale. The result analysis module 400 is used to compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping intervals, generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

[0066] This embodiment proposes a full-scale microstructure quantitative analysis system for chloride silty clay, which is used to implement the aforementioned full-scale microstructure quantitative analysis method for chloride silty clay. Therefore, the specific implementation of the full-scale microstructure quantitative analysis system for chloride silty clay can be found in the embodiment section of the aforementioned full-scale microstructure quantitative analysis method for chloride silty clay. For example, the sample preparation module 100, data measurement module 200, data processing module 300, and result analysis module 400 are respectively used to implement steps S1 to S4 in the method described in Embodiment 1. Therefore, the specific implementation can be referred to the description of the corresponding embodiments. To avoid redundancy, it will not be repeated here.

[0067] Example 3: The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the full-scale microstructure quantitative analysis method for chloride silty clay described in Embodiment 1.

[0068] Example 4: The present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the full-scale microstructure quantitative analysis method for chloride silty clay described in Embodiment 1.

[0069] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0070] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0071] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0072] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0073] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for quantitative analysis of the full-scale microstructure of chloride-containing silty clay, characterized in that, include: Step S1: Prepare chloride silty clay samples for microstructure analysis; Step S2: The chloride silty clay sample is subjected to X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests, respectively. The CT test yields a two-dimensional sequence image, and the NMR test yields the transverse relaxation time distribution. Step S3: Based on the two-dimensional sequence images, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale; based on the transverse relaxation time distribution, perform pore size distribution and structural parameter analysis on the micro-pore structure to obtain pore characteristic parameters at the micro-scale. Step S4: Compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping area to generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

2. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 1, characterized in that: In step S1, the method for preparing chloride silty clay samples for microstructure analysis is as follows: Chloride silty clay from the target area was selected and prepared into saturated cylindrical undisturbed or remolded specimens according to geotechnical testing standards. Then, a standard specimen with a diameter of φ19mm and a height of 25mm was cut from the cylindrical specimen using a ring cutter.

3. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 1, characterized in that: In step S3, based on the two-dimensional sequence images, the pore size distribution and structural parameters of the microporous structure are analyzed to obtain the pore characteristic parameters at the microscale. The method is as follows: The two-dimensional sequence image is filtered to obtain the filtered image; The filtered image is subjected to threshold segmentation processing. The segmentation threshold is determined by gray value statistics. The image is binarized into porous phase and solid particle phase to obtain a binarized image sequence. The binarized image sequence is reconstructed in three dimensions to establish a three-dimensional spatial model of the pore structure. Quantitative analysis of the three-dimensional spatial model yields mesoscale pore characteristic parameters, including porosity and pore size distribution parameters; wherein, the porosity... The calculation formula is: , The pore volume extracted from the three-dimensional spatial model. This refers to the total volume of the sample. The method for obtaining the aperture distribution parameters is as follows: by calculating the equivalent diameter of each connected pore. The calculation formula is as follows: V represents the volume of a single pore; the number or volume ratio of pores in different equivalent diameter ranges are statistically analyzed to form a micrometer-scale pore size distribution histogram or cumulative curve.

4. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 1, characterized in that: In step S3, based on the transverse relaxation time distribution, the pore size distribution and structural parameters of the micro-pore structure are analyzed to obtain the pore characteristic parameters at the microscale. The method is as follows: For clay samples, the rate of surface relaxation is much greater than that of free relaxation and diffusion relaxation. Therefore, in actual calculations, the effects of free relaxation and diffusion relaxation are ignored, and only the surface relaxation mechanism is considered, using a conversion formula. Lateral relaxation time Equivalent radius converted to target pore size The pore radius distribution was obtained, where The surface relaxation rate, Pore ​​shape factor; Regarding the lateral relaxation time The total signal peak area is obtained by integrating the distribution curve; by testing standard soil samples with known porosity, a calibration relationship between the total signal peak area and porosity is established; based on the calibration relationship, the total peak area is converted into total porosity at the microscale.

5. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 1, characterized in that: In step S4, the method for comparing and fusing the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale is as follows: Obtain the pore size distribution range corresponding to the pore characteristic parameters at the mesoscale and the pore size distribution range corresponding to the pore characteristic parameters at the microscale, plot them on the same coordinate system, and identify and determine the overlapping interval of the two distribution curves. A threshold for the cumulative pore volume ratio is set. If, within the overlapping region, the cumulative pore volume ratio of the pore characteristic parameters at the microscale is lower than the threshold, then data fusion is performed according to the following rules: For the pore size range before the overlapping region, pore size distribution data at the microscale is used; starting from the starting point of the overlapping region, including the entire overlapping region and the larger pore size range thereafter, pore size distribution data at the mesoscale is used to obtain calibrated microscale pore radius distribution data.

6. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 5, characterized in that: The specific steps for generating the full-scale pore size distribution curve are as follows: The calibrated microscale pore radius distribution data and the pore radius distribution data obtained by equivalent diameter inversion at the mesoscale are sorted in ascending order of pore radius; A nonlinear fitting method is used to fit the sorted discrete pore radius distribution data to generate a smooth and continuous full-scale pore size cumulative volume distribution curve covering both micro and mesoscale. The curve shape of the small pore size segment is determined by the microscale pore radius distribution data, while the curve shape of the large pore size segment is determined by the mesoscale pore radius distribution data.

7. The method for quantitative analysis of the full-scale microstructure of chloride silty clay according to claim 6, characterized in that: The method for quantitative analysis of full-scale microstructure based on the full-scale aperture distribution curve includes fractal dimension calculation, specifically: Take the logarithm of the full-scale aperture distribution curve and plot it. Relationship diagram, in which For the cumulative volume fraction, Where is the pore radius; According to the above The relationship diagram determines the inflection point of the curve and divides it into two linear characteristic segments: small pore size and large pore size, which correspond to two different pore structure systems: intragranular pores and intergranular pores, respectively. Based on fractal theory formulas Fittings are performed on the two linear regions respectively, and the slopes are used to determine the approximation. Calculate the corresponding fractal dimension Thus, the fractal dimension of the small aperture segment is obtained. and fractal dimension of large aperture segment ;in, The maximum pore radius; The fractal dimension of the small aperture segment and the fractal dimension of the large aperture segment It serves as a quantitative indicator to characterize the complexity and heterogeneity of pore structures across different scale ranges.

8. A quantitative analysis system for the full-scale microstructure of chloride-containing silty clay, characterized in that, include: The sample preparation module is used to prepare chloride silty clay samples for microstructure analysis. The data measurement module is used to perform X-ray computed tomography (CT) and nuclear magnetic resonance (NMR) tests on the chloride silty clay sample, respectively. The CT test yields a two-dimensional sequence image, and the NMR test yields the transverse relaxation time distribution. The data processing module is used to analyze the pore size distribution and structural parameters of the micro-pore structure based on the two-dimensional sequence images to obtain pore characteristic parameters at the micro-scale; and to analyze the pore size distribution and structural parameters of the micro-pore structure based on the transverse relaxation time distribution to obtain pore characteristic parameters at the micro-scale. The results analysis module is used to compare and fuse the pore characteristic parameters at the mesoscale and the pore characteristic parameters at the microscale, correct and stitch the data in the overlapping intervals, generate a full-scale pore size distribution curve covering the nanoscale to the microscale, and perform full-scale microstructure quantitative analysis based on the full-scale pore size distribution curve.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the full-scale microstructure quantitative analysis method for chloride silty clay as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the full-scale microstructure quantitative analysis method for chloride silty clay as described in any one of claims 1 to 7.

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