Soil body reinforcement visualized tracer method and simulation device

Abstract

The application relates to the technical field of soil body reinforcement visualization construction, and discloses a soil body reinforcement visualization tracing method and a simulation device. The application aims to solve the technical problems that the traditional soil body reinforcement detection method is destructive, high in cost, cannot realize continuous tracing detection, and cannot intuitively understand the diffusion range, flow distribution and reinforcement effect identification of the reinforcement material in the soil body. The soil body reinforcement visualization tracing method comprises the following steps: (1) exciting electrode array arrangement; (2) exciting electrode discharge measurement; (3) potential difference measurement; (4) calculating resistivity; and (5) geologic body response judgment. The technical application can judge the quality of the soil body reinforcement engineering, and improve the safety of engineering implementation through the means of exciting current real-time monitoring, accurate positioning of defect positions, dynamic optimization of reinforcement parameters and three-dimensional visualization tracing.

Description

Technical Field

[0001] This invention relates to the field of soil reinforcement visualization construction technology, and in particular to a soil reinforcement visualization tracing method and simulation device. Background Technology

[0002] In engineering construction, such as foundation construction, slope stabilization, and underground engineering excavation, soil stability is a key factor in ensuring project safety and quality. Many natural soils, due to insufficient strength and other characteristics, cannot meet technical requirements and therefore require reinforcement. For example, unreinforced soil in high-rise buildings may lead to settlement and cracking; unreinforced soil in slopes is prone to landslides and collapses, endangering safety. During soil reinforcement, real-time and intuitive monitoring of the diffusion range, uniformity of distribution, and soil reinforcement effect is crucial for optimizing construction parameters and improving reinforcement quality. If the grout diffusion status cannot be monitored in real time, localized insufficient or excessive grouting can easily occur, weakening the reinforcement effect and potentially inducing secondary engineering problems. Traditional soil reinforcement testing methods are highly destructive and costly, cannot achieve continuous tracer detection, and lack the technical expertise to intuitively understand the diffusion range, flow distribution, and reinforcement effect assessment of the reinforcement material in the soil.

[0003] Chinese patent document 202411584612.X discloses an automated method and apparatus for proportioning conductive grouting tracer materials. This aims to address the technical problem in existing technologies where the design of conductive tracer material proportions during foundation pit grouting reinforcement lacks automated means, resulting in poor resistivity tomography (ERT) results. The invention includes the following steps: data acquisition and collection; parameter setting and construction plan formulation; controlling the grouting proportion and determining construction measures; automated proportion generation and output; and automated real-time feedback and correction.

[0004] However, the above-mentioned solutions suffer from at least the following technical problems during implementation: Traditional soil reinforcement methods lack effective real-time monitoring during construction, making it impossible to intuitively understand the diffusion range, distribution uniformity, and reinforcement effect of the reinforcement material in the soil. This easily leads to uneven reinforcement effects, and in complex geological conditions, it is difficult to accurately locate abnormal areas, resulting in reinforcement measures that cannot effectively target problem areas, and making it difficult to optimize construction parameters. Therefore, there is an urgent need to propose a visual implementation tracking method and device for soil reinforcement. This method can accurately reflect the distribution of reinforcement materials in the soil and the reinforcement effect in real time, which is of significant practical importance for improving the quality and efficiency of soil reinforcement projects. It can not only provide intuitive construction guidance for construction personnel, helping them adjust construction parameters in a timely manner to ensure uniform distribution and effective diffusion of reinforcement materials, but also provide reliable technical support for project supervision and quality inspection, reducing project risks and ensuring the safety and reliability of project construction. Summary of the Invention

[0005] In view of the above technical problems, this disclosure provides a method and device for visual implementation tracking of soil reinforcement, which solves the technical problem that traditional soil reinforcement methods in the prior art lack effective real-time monitoring means during construction, and cannot intuitively understand the diffusion range, distribution uniformity and reinforcement effect of reinforcement materials in the soil.

[0006] According to one aspect of this disclosure, a method for visualizing and tracing soil reinforcement is provided, comprising the following steps:

[0007] S1: Deployment of excitation electrode array: Deploy electrode arrays in surface and underground boreholes within the soil area enclosed by the survey area.

[0008] S2: Excitation electrode discharge measurement: Using the prepared conductive tracer material, an artificial electric field is formed in the underground medium by injecting a current of I into the ground through the excitation electrode during the grouting process.

[0009] S3: Potential difference measurement: During the grouting process, while injecting current into the excitation electrodes, the potential difference at any point in the electrode array is measured. ;

[0010] S4: Calculate resistivity: Resistivity at any point in the electrode array: In the formula: Adjust the coefficients for the testing device; To measure the potential difference between the electrodes; I is the supply current;

[0011] S5: Geological body response judgment: The geological body response is judged by the difference in resistivity. When the geological body is dry cavity or unfilled fissure, it hinders the passage of current and is manifested as high resistance; when it is water-filled cavity or water-rich area, it forms a channel to collect current and is manifested as low resistance anomaly.

[0012] In the S5 geological body response, the soil moisture content and the measured relative resistivity of the soil both satisfy the following functional relationship:

[0013] ;

[0014] In the formula, R is the measured relative resistance of the soil, a0, b0, and c0 are all fitting parameters, and ω is the soil moisture content.

[0015] In some embodiments of this disclosure, the conductive tracer material described in step S2 is used to detect the flow of soil slurry during grouting, to understand the diffusion range, flow distribution, and reinforcement effect of the reinforcing material in the soil, and the preparation method of the conductive tracer material includes the following steps:

[0016] S1: Dry mix: Cement and fly ash are dry mixed;

[0017] S2: Dispersion preparation: After mixing graphite powder with dispersant and water, tributyl phosphate is added to the dispersion and thoroughly mixed by high-speed stirring to form a dispersion;

[0018] S3: Tracer material: The dry-mixed cement and fly ash are wet-mixed with the above-prepared dispersion in a cement sand mixer to obtain a conductive tracer material.

[0019] S4: Testing: The prepared conductive tracer material is subjected to flowability testing, water separation rate testing, and viscosity testing.

[0020] In some embodiments of this disclosure, the fluidity test of the conductive tracer material is performed using an extended conical flow test plate and a rheometer. The fluidity of the material is evaluated by measuring its diffusion diameter after the grouting material is poured into the fluid mold material and flows out naturally.

[0021] In some embodiments of this disclosure, the water separation rate test of the conductive tracer material is performed using a glass plate and a standard container; the water separation rate is calculated by comparing the height difference between the initial and final states of the conductive tracer material after it has been left to stand.

[0022] In some embodiments of this disclosure, the viscosity of the conductive tracer material is tested using a Marshall funnel and a standard cup, and its viscosity is evaluated based on the time it takes for the material to flow into the standard cup.

[0023] In some embodiments of this disclosure, the resistivity of the conductive tracer material is dynamically monitored during the curing period. The time-varying dynamic monitoring results of resistivity are fitted to obtain the following functional relationship between resistivity and curing age:

[0024] ;

[0025] In the formula, N is the test resistivity of the grout, in Ω·cm, t is the curing age, t0, ρ1, and ρ2 are all fitting parameters, where ρ1 and ρ2 can indirectly reflect the magnitude of the material's impedance in the initial monitoring stage and the final state of the material, respectively, t0 reflects the time point when the resistivity of the conductive tracer material increases the fastest, and p is a control parameter related to the time-varying characteristics of the material.

[0026] According to another aspect of this disclosure, a soil reinforcement visualization and tracing simulation device is provided, applicable to soil reinforcement visualization and tracing methods. It includes a spring electrode assembly surrounding a sample, wherein the spring electrode assembly is arranged in a multi-layered structure along the longitudinal direction to obtain the cross-sectional resistivity at different heights of the sample, forming a three-dimensional measurement network. The spring electrode assembly is connected to a data acquisition and control unit, which is used to acquire the excitation and response voltages of the multi-layered electrodes. The data acquisition and control unit is connected to a data processing unit, which fuses the multi-layered resistivity data based on an interpolation algorithm to reconstruct a complete three-dimensional resistivity distribution image inside the sample.

[0027] The beneficial effects of this invention are as follows:

[0028] By deploying electrode arrays and measuring potential, combined with resistivity calculations, the diffusion and distribution of tracer materials in the soil can be monitored in real time, forming an intuitive three-dimensional resistivity distribution image. This visualization technology allows construction personnel to observe the injection effect of the reinforcement material in real time during the reinforcement process, promptly identifying problems such as uneven grouting and insufficient diffusion, thereby optimizing construction parameters and ensuring uniform distribution of the reinforcement material. Based on the geological response, abnormal areas in the soil, such as cavities, fissures, and water-rich areas, can be accurately located, providing accurate target locations for subsequent reinforcement treatment, avoiding blind construction, and improving the targeting and effectiveness of reinforcement. During construction, through real-time monitoring and visualization feedback, construction personnel can adjust construction parameters such as grouting pressure, grouting speed, and grouting volume in a timely manner based on the diffusion of the tracer material and changes in soil resistivity, ensuring that the reinforcement material can fully fill the soil pores and achieve the expected reinforcement effect. This effectively avoids the problems of uneven reinforcement and poor reinforcement effect caused by fixed construction parameters in traditional reinforcement methods. Through precise reinforcement and optimized construction techniques, the strength and stability of soil can be significantly improved, reducing the probability of engineering accidents such as soil deformation and landslides, thereby extending the service life of the project and reducing later maintenance costs and risks. In traditional reinforcement methods, due to the lack of effective monitoring tools, construction personnel often need to conduct multiple trials and adjustments to achieve the desired reinforcement effect. This not only increases construction time and costs but may also lead to project delays. This technology, through real-time monitoring and visual feedback, can quickly determine the optimal construction parameters, reducing trial-and-error steps in the construction process, thus shortening the construction cycle and reducing labor and material costs. In the grouting reinforcement process, precise control of the grouting range and volume avoids the material waste caused by uneven or excessive grouting in traditional grouting methods. This not only saves on the amount of reinforcement materials used and reduces material costs but also reduces environmental impact, aligning with the concept of green construction. In some complex geological conditions or underground engineering construction, such as underground caverns and tunnels, traditional reinforcement methods may pose certain construction risks, such as excessive grouting pressure leading to soil rupture and groundwater outbursts. This application effectively avoids these construction risks and ensures the safety of the construction process by real-time monitoring and precise control of the grouting process, protecting the safety of construction personnel and the surrounding environment. It employs a micron-sized graphite-fly ash composite cement-based grouting tracer material, which not only possesses excellent mechanical properties and flowability but is also environmentally friendly. Fly ash, as an industrial waste residue, reduces the exploitation of natural resources through its reuse, aligning with the requirements of sustainable development. Simultaneously, precise grouting and material dosage control reduce pollution of groundwater resources and damage to the surrounding ecological environment. Through dynamic monitoring and fitting analysis of resistivity throughout the entire curing cycle, the relationship between the tracer material's resistivity and curing age can be derived, providing a scientific basis for engineering design.Designers can rationally determine the curing time and strength development patterns of reinforcement materials, optimize engineering design schemes, and ensure that the reinforcement effect meets engineering requirements. During construction, real-time monitoring and visual feedback can promptly identify construction quality problems, such as uneven grouting or unsatisfactory reinforcement effects, and allow for corresponding remedial measures. This real-time quality control method effectively guarantees the quality of reinforcement projects, reduces engineering accidents and economic losses caused by quality problems, and provides reliable technical support for project quality acceptance. Attached Figure Description

[0029] Figure 1 Schematic diagram of a visual tracing device for soil reinforcement;

[0030] Figure 2 Another perspective structural schematic diagram of a soil reinforcement visualization tracer device;

[0031] Figure 3 This is a structural diagram of the flexural strength testing device;

[0032] Figure 4 This is a schematic diagram of the flexural strength testing device from another perspective.

[0033] Figure 5 Comparison of high-precision algorithm imaging effects;

[0034] Figure 5 It is divided into four parts: top left, top right, bottom left, and bottom right. Each part has a model with a different shape. The top line is the model name, including GN_one_step, PDIPM, TSVD, and CG. The left side is the geometry input to the model, and the right side is the reconstruction and recognition results of each model for these shapes.

[0035] Figure 6 A comparison chart of prediction times for different algorithms;

[0036] Figure 6 In this context, "prediction time" refers to the prediction time.

[0037] Figure 7 This is a three-dimensional imaging result image;

[0038] Figure 7 The left side of the image shows the resistivity of multiple two-dimensional cross sections, while the right side shows the three-dimensional resistivity distribution image.

[0039] Figure 8 This is a stability test diagram for the outdoor system.

[0040] Outdoor multi-scale tests of 0.4×0.4m, 0.5×0.5m, 1×1m, and 3×3m were conducted to check the stability and feasibility of the high-power tomographic imaging equipment. In the large-scale test, the inverted images could clearly show the distribution of voids and showed obvious and stable differences from the background field, which helped to determine the leakage and grouting situation.

[0041] Figure 9 These are stability test graphs for the same scenario;

[0042] For a 1m×1m square site, a stability analysis was conducted. The excitation electrode sequence signal was measured multiple times in the same scene to obtain the potential difference change curve. Image inversion was performed based on the potential difference distribution. After comparative analysis, it was found that the potential difference signal automatically collected by the device was basically consistent with the image reconstructed by the inversion algorithm in the same scene, indicating that it has stability.

[0043] Figure 10 This is a graph showing the migration of fluid solutes.

[0044] Figure 10 The left column shows the experimental model, which displays the seepage process in four different states (2nd, 15th, 24th, 33rd). The right column shows the results of processing the experimental model using five different methods (1D-CNN (tanh), GN_one_step, PDIPM, TSVD, CG).

[0045] Figure 11 The graph shows the results of the analysis of the poor flowability of the tracer material.

[0046] Figure 11 The vertical axes of the three sub-graphs represent the trends in concrete fluidity, water separation rate, and grout viscosity, respectively. The horizontal axes of the three sub-graphs are the same, representing different material ratios. From left to right, black, red, blue, and purple represent the percentages of W / S (water-cement ratio), fly ash, graphite, and superplasticizer, respectively.

[0047] Figure 12 The results of the flexural strength test and range analysis are shown in the figure.

[0048] Figure 12The vertical axis represents flexural strength in MPa, and the horizontal axis on the left represents the sample number. The horizontal axis on the right represents W / C (water-cement ratio), FA% (fly ash percentage), MG% (mineral admixture percentage), and SP% (additive percentage). Blue indicates the test results after 3 days (3d), black indicates the test results after 7 days (7d), and red indicates the test results after 28 days (28d).

[0049] Figure 13 The results of the compressive strength test and range analysis are shown in the figure.

[0050] Figure 13 The left-hand chart shows the sample number on the horizontal axis and the compression test results on the vertical axis. Red represents Results by 3 days; black represents Results by 7 days; and blue represents Results by 28 days. The right-hand chart is divided into four sections, each showing the relationship between compressive strength and different parameters: W / C (water-cement ratio), FA (%) (fly ash), MG (slag powder), and SP (admixture).

[0051] Figure 14 The resistivity of the grout during the 28-day curing period is shown in the time-varying characteristics diagram.

[0052] Figure 14 The horizontal axis represents time, and the vertical axis represents resistivity. Experimental data points are marked with red squares, and the blue solid line is the fitted curve of the experimental data points. R 2 For goodness of fit;

[0053] Figure 15 Reference values ​​for the background and interference fields of the newly fabricated tracer material and an imaging effect diagram;

[0054] Figure 15 (a) The X-axis represents the Electrode testing sequence, and the Y-axis represents the Background field test value. Blue circles represent Background field values, and red circles represent Interference field values. (b) The title is Nominal conductivity.

[0055] Figure 16The graph shows the test results of impedance and sensitive field eigenvalues ​​of soil at different moisture contents.

[0056] Figure 16 The X-axis represents soil moisture content. The left side of the Y-axis represents relative resistance, and the right side represents the imaging field average. Blue dots (Relative resistance): represent the actual measured value of relative resistance; blue dashed line (Fit of relative resistance): represents the fitted curve of relative resistance; red dots (Imaging field average): represent the actual measured value of the imaging field average; red dashed line (Fit of imaging field average): represents the fitted curve of the imaging field average.

[0057] Figure 17 Inversion imaging of foreign object embedding under different soil moisture contents;

[0058] Figure 17 The X-axis represents the average imagining field value; the Y-axis represents the relative resistance. Data points are represented by blue squares (labeled "R-Φ") indicating the relationship between the actual measured relative resistance value and the average imagining field value. The fit curve is represented by a red dashed line. The inset is located in the lower right corner of the main graph, magnified to show details of a segment of data in the main graph.

[0059] Figure 18 Voltage distribution and imaging effects were collected at different excavation depths;

[0060] Figure 18 The left-hand chart shows the horizontal axis for Acquisition sequences and the vertical axis for Voltage reference value. Legend: Background: Black dots represent the voltage reference value without holes; Hole-2.5cm, Hole-5cm, Hole-7.5cm, Hole-10cm, and Hole-15cm: Red, orange, green, blue, and purple dots represent the voltage reference values ​​with holes at different depths (2.5cm, 5cm, 7.5cm, 10cm, and 15cm), respectively. The right-hand chart shows the x-axis (x / cm) for horizontal position, the y-axis (y / cm) for vertical position, and the z-axis (Depth / cm) for depth. The color bars indicate the range of voltage values.

[0061] Figure 19 The distribution results of sensitive field eigenvalues ​​at different excavation depths are shown in the figure.

[0062] Figure 19 The horizontal axis represents cavity depth, and the vertical axis represents the imaging field average value. The blue triangle data points illustrate the relationship between Φ and D. p This represents the relationship between the actual measured average image field value and the cavity depth. The red line represents fitted curves, which are obtained by fitting the data points in blue.

[0063] Figure 20 Response results of sensitive fields with different excavation extents;

[0064] Figure 20 It consists of five small images, each representing a different excavation depth (D2.5, D5, D7.5, D12.5, D15). The title is "Nominal conductivity".

[0065] Figure 21 The distribution results of sensitive field eigenvalues ​​for different excavation extents are shown in the figure.

[0066] Figure 21 The horizontal axis represents the aperture diameter, and the vertical axis represents the imaging field average value. Data points are marked with red circles. Φ is related to D_ h : Represents the relationship between the average value of the imaging field and the aperture diameter. The fitted curve is represented by a solid black line. Fitted curves: Represents the fitted curves obtained based on the data points. Left and right regions are divided as follows: Non-imaging section: marked with a light yellow background; Imaging section: marked with a light blue background.

[0067] Figure 22 This is a comparison chart of the grouting performance of tracer materials and ordinary materials.

[0068] Figure 22Each heatmap at the bottom contains four sub-plots: (a) 0d, (b) 1d, (c) 2d, and (d) 3d, showing the distribution of the slurry in the medium at different time points (day 0, day 1, day 2, and day 3). The colors of the heatmaps, from blue to red, represent changes in conductivity, with red areas indicating higher conductivity and blue areas indicating lower conductivity. The four heatmaps on the left (for ordinary slurry): as time increases (from day 0 to day 3), the red areas gradually expand, indicating the diffusion of ordinary slurry in the medium. The four heatmaps on the right (for tracer slurry): compared to ordinary slurry, the diffusion range and speed of tracer slurry differ.

[0069] Figure 23 A schematic diagram illustrating the process of constructing a 3D image model from 2D image slices;

[0070] Figure 23 The sub-image below shows multiple two-dimensional image slices along the depth direction, which are then used to construct a three-dimensional image model;

[0071] The components in the diagram are named as follows: 1. Spring electrode assembly; 2. Spring electrode; 3. Upper loading plate; 4. Lower loading plate; 5. Hydraulic rod; 6. Level; 7. Force transmission rod; 8. Upper clamp back plate; 9. Lower clamp back plate; 10. Bending test loading rod; 11. Slurry sample. Detailed Implementation

[0072] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0073] A method for visualizing and tracing soil reinforcement is provided, including the following steps:

[0074] S1: Deployment of excitation electrode array: Deploy electrode arrays in surface and underground boreholes within the soil area enclosed by the survey area.

[0075] S2: Excitation electrode discharge measurement: Using the prepared conductive tracer material, an artificial electric field is formed in the underground medium by injecting a current of I into the ground through the excitation electrode during the grouting process.

[0076] S3: Potential difference measurement: During the grouting process, while injecting current into the excitation electrodes, the potential difference at any point in the electrode array is measured. ;

[0077] S4: Calculate resistivity: Resistivity at any point in the electrode array: In the formula: Adjust the coefficients for the testing device; To measure the potential difference between the electrodes; I is the supply current;

[0078] S5: Geological body response judgment: The geological body response is judged by the difference in resistivity. When the geological body is dry cavity or unfilled fissure, it hinders the passage of current and is manifested as high resistance; when it is water-filled cavity or water-rich area, it forms a channel to collect current and is manifested as low resistance anomaly.

[0079] In the S5 geological body response, the soil moisture content and the measured relative resistivity of the soil both satisfy the following functional relationship:

[0080] ;

[0081] In the formula, R is the measured relative resistance of the soil, a0, b0, and c0 are all fitting parameters, and ω is the soil moisture content.

[0082] In some embodiments of this disclosure, the conductive tracer material described in step S2 is used to detect the flow of soil slurry during grouting, to understand the diffusion range, flow distribution, and reinforcement effect of the reinforcing material in the soil, and the preparation method of the conductive tracer material includes the following steps:

[0083] S1: Dry mix: Cement and fly ash are dry mixed;

[0084] S2: Dispersion preparation: After mixing graphite powder with dispersant and water, tributyl phosphate is added to the dispersion and thoroughly mixed by high-speed stirring to form a dispersion;

[0085] S3: Tracer material: The dry-mixed cement and fly ash are wet-mixed with the above-prepared dispersion in a cement sand mixer to obtain a conductive tracer material.

[0086] S4: Testing: The prepared conductive tracer material is subjected to flowability testing, water separation rate testing, and viscosity testing.

[0087] The fluidity test of conductive tracer material preparation is carried out using an extended conical flow test plate and a rheometer. After the grouting material is poured into the fluid mold and the material flows out naturally, its diffusion diameter is measured to evaluate the material's fluidity.

[0088] The water separation rate test for conductive tracer materials is conducted using a glass plate and a standard container; the water separation rate is calculated by comparing the height difference between the initial and final states of the conductive tracer material after it has been left to stand.

[0089] Viscosity testing of conductive tracer materials is performed using a Marshall funnel and a standard cup, and the viscosity is evaluated based on the time it takes for the material to flow into the standard cup.

[0090] Dynamic monitoring of resistivity of conductive tracer materials during the curing period was conducted. The time-varying dynamic monitoring results of resistivity were fitted, and the relationship between resistivity and curing age was found to satisfy the following functional relationship:

[0091] ;

[0092] In the formula, N is the test resistivity of the grout, in Ω·cm, t is the curing age, t0, ρ1, and ρ2 are all fitting parameters, where ρ1 and ρ2 can indirectly reflect the magnitude of the material's impedance in the initial monitoring stage and the final state of the material, respectively, t0 reflects the time point when the resistivity of the conductive tracer material increases the fastest, and p is a control parameter related to the time-varying characteristics of the material.

[0093] A soil reinforcement visualization and tracing simulation device, applicable to soil reinforcement visualization and tracing methods, includes a spring electrode assembly surrounding a sample. The spring electrode assembly is arranged in a multi-layer structure along the longitudinal direction to obtain the cross-sectional resistivity at different heights of the sample, forming a three-dimensional measurement network. The spring electrode assembly is connected to a data acquisition and control unit, which is used to acquire the excitation and response voltages of the multi-layer electrodes. The data acquisition and control unit is connected to a data processing unit, which fuses the multi-layer resistivity data based on an interpolation algorithm to reconstruct a complete three-dimensional resistivity distribution image inside the sample.

[0094] Each layer of the spring electrode assembly 1 includes 16 circumferentially spaced spring electrodes 2, and the spring electrode assembly is arranged in 6 layers along the longitudinal direction.

[0095] Furthermore, to investigate the tracer effect of graphite fly ash grouting material in the high-pressure jet grouting reinforcement process of deep foundation pits, this study designed an indoor experimental platform. The platform used a 30cm cubic acrylic box as the experimental container and strip electrodes as the measuring electrodes. The platform was filled with 80-mesh homogeneous glass sand to simulate the electrical properties of homogeneous sand at a proportional scale. Imaging tests were performed using a 16-electrode imaging system.

[0096] In practical engineering projects involving grouting reinforcement, the excavation scale of the foundation pit is a crucial factor affecting the grouting effect. As the depth of the foundation pit increases, the distribution and permeation behavior of the grouting material may change. In particular, the electrical properties of the soil in deep foundation pits may be affected by more complex factors. To accurately evaluate the application effect of resistivity tomography in deep foundation pit grouting reinforcement, it is necessary to simulate the electrical properties and imaging effects under different excavation scales.

[0097] The excavation depth and the characteristic value of the imaging field show a strong linear correlation, indicating that the existing acquisition conditions of the current indoor test platform can effectively reflect the changes in voltage field value caused by the excavation depth. At the same time, the test accuracy for hole size increases as the excavation depth approaches the plane where the electrode is located. This shows that during the excitation process of the strip electrode, the acquired field value mainly depends on the plane where the electrode is located, while the voltage field reflects the conductivity distribution of the test field. This experiment proves that the test site can realize imaging test, and also proves that the distance between the electrode plane and the excavation depth can be further predicted by the average value of the imaging field. This has certain guiding significance for engineering to determine the three-dimensional spatial distance between the electrode and the hole and for borehole adjustment.

[0098] Similarly, correlation studies were conducted around different excavation extents. A strong linear correlation was also found between the excavation scale and the imaging field characteristic values. This also verifies that the existing acquisition conditions of the current indoor test platform can effectively reflect the changes in voltage field values ​​caused by the excavation extent. As the excavation extent increases, when the excavation diameter is 2.5 and 5 cm, the changes in sensitive field voltage caused by the excavation cannot be detected by differential imaging. However, when the excavation diameter is about 7.5 cm, imaging of position and geometric dimensions can be achieved, and this accuracy increases with subsequent excavation scales. The changes caused by the excavation extent can be reflected through imaging. This indicates that during the excitation process of the strip electrode, with the electrode position fixed, when the excavation depth is close to the electrode plane, the acquired field values ​​can reflect the impact of the excavation extent. From an imaging perspective, the testing accuracy of the current indoor scale equipment can meet the imaging requirements of a 7.5 cm diameter.

[0099] In summary, the excavation scale test established the basic grouting imaging scale for subsequent grouting tests, namely, the determination of the excavation diameter and grouting range of the test site. While verifying that the test site can achieve imaging testing, it also proved that the distance between the electrode plane and the excavation depth can be further predicted by the average value of the imaging field. This has certain guiding significance for engineering to determine the three-dimensional spatial distance between the electrode and the hole, as well as the adjustment of the borehole and the spatial distance adjustment of the electrode and hole scale range.

[0100] Indoor tracer material grouting simulation

[0101] Through the aforementioned indoor testing platform, indoor tomographic imaging grouting reinforcement simulation experiments were conducted, verifying the significant advantages of the tracer material compared to ordinary cement-based grouting materials. The tracer grout exhibits tracer stability, enabling full-cycle monitoring of the grouting reinforcement process. After solidification, its superior electrical properties, compared to ordinary grouts, still meet imaging requirements. This provides an economical, environmentally friendly, safe, and stable tracer material option for determining the grouting reinforcement range and evaluating grouting effects in grouting reinforcement projects. Finally, the significant advantages of the tracer material compared to ordinary materials are listed below:

[0102] Table 1 Comparison of tracer materials and ordinary grouting materials

[0103] characteristic tracer slurry ordinary slurry resistivity difference Graphite forms a continuously conductive network, enabling the resistivity of the jet grouting pile to be as low as 10² Ω·cm during the monitoring period, which is 1-2 orders of magnitude lower than the surrounding strata. The column-soil interface is highly sensitive to ERT detection, and the diameter and diffusion plume can be distinguished in real time. Resistivity increases rapidly with age, reaching levels close to those of the soil within the tested age period, resulting in insufficient contrast and blurred boundaries. Signal-to-noise ratio / resolution Inversion stability, reduced ghosting, and real-time resolution of diameter diffusion Poor electrical properties, non-unique solution inversion, and high noise levels. Multimodal compatibility It is both electrically and thermally conductive, and is compatible with various technologies such as ERT, thermal imaging, and microwave / ultrasound CT. — Force-electric coupling Intensity can be obtained through the resistivity-age relationship, allowing for non-destructive strength prediction. Destructive sampling is required; it is harmful. Liquidity Synergistic effect of fly ash "ball bearing effect" + micron-sized graphite sheet lubrication — stability Fly ash-graphite composite filler reduces pores, decreases bleeding, and densifies the slurry. Numerous pores and bubble / slurry segregation affect imaging. Pumpability of jet The introduction of micron-sized conductive dopants reduces viscosity, prevents pipe blockage, and stabilizes grouting. It has a higher viscosity and a smaller penetration radius than water-based adhesives. Health detection performance Micron-sized graphite exhibits piezoresistive effect, enabling the detection of pile health. Lack of self-awareness Corrosion resistance Micron-sized graphite exhibits exceptional stability and corrosion resistance, while fly ash enhances its resistance to chloride corrosion. Susceptible to corrosion Economic Fly ash can replace cement, and graphite can be obtained from graphite tailings processing, making it economical. All-cement system, high cost Environmental protection Grouting materials utilize solid waste, resulting in low carbon emissions. —

[0104] Although some preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0105] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this application and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for visualizing and tracing soil reinforcement, characterized in that, Includes the following steps: S1: Deployment of excitation electrode array: Deploy electrode arrays in surface and underground boreholes within the soil area enclosed by the survey area. S2: Excitation electrode discharge measurement: Using the prepared conductive tracer material, an artificial electric field is formed in the underground medium by injecting a current of I into the ground through the excitation electrode during the grouting process. S3: Potential difference measurement: During the grouting process, while injecting current into the excitation electrodes, the potential difference at any point in the electrode array is measured. ; S4: Calculate resistivity: Resistivity at any point in the electrode array: In the formula: Adjust the coefficients for the testing device; To measure the potential difference between the electrodes; I is the supply current; S5: Geological body response judgment: The geological body response is judged by the difference in resistivity. When the geological body is dry cavity or unfilled fissure, it hinders the passage of current and is manifested as high resistance; when it is water-filled cavity or water-rich area, it forms a channel to collect current and is manifested as low resistance anomaly. In the S5 geological body response, the soil moisture content and the measured relative resistivity of the soil both satisfy the following functional relationship: ; In the formula, R is the measured relative resistance of the soil, a0, b0, and c0 are all fitting parameters, and ω is the soil moisture content.

2. The soil reinforcement visualization and tracing method as described in claim 1, characterized in that: The conductive tracer material mentioned in step S2 is used to detect the flow of soil slurry during grouting, to understand the diffusion range, flow distribution, and reinforcement effect of the reinforcing material in the soil. The preparation method of the conductive tracer material includes the following steps: S1: Dry mix: Cement and fly ash are dry mixed; S2: Dispersion preparation: After mixing graphite powder with dispersant and water, tributyl phosphate is added to the dispersion and thoroughly mixed by high-speed stirring to form a dispersion; S3: Tracer material: The dry-mixed cement and fly ash are wet-mixed with the above-prepared dispersion in a cement sand mixer to obtain a conductive tracer material. S4: Testing: The prepared conductive tracer material is subjected to flowability testing, water separation rate testing, and viscosity testing.

3. The soil reinforcement visualization and tracing method as described in claim 2, characterized in that: The fluidity test of conductive tracer material preparation is carried out using an extended conical flow test plate and a rheometer. After the grouting material is poured into the fluid mold and the material flows out naturally, its diffusion diameter is measured to evaluate the material's fluidity.

4. The soil reinforcement visualization and tracing method as described in claim 2, characterized in that: The water separation rate test for conductive tracer materials is conducted using a glass plate and a standard container; the water separation rate is calculated by comparing the height difference between the initial and final states of the conductive tracer material after it has been left to stand.

5. The soil reinforcement visualization and tracing method as described in claim 2, characterized in that: Viscosity testing of conductive tracer materials is performed using a Marshall funnel and a standard cup, and the viscosity is evaluated based on the time it takes for the material to flow into the standard cup.

6. The soil reinforcement visualization and tracing method as described in claim 2, characterized in that: Dynamic monitoring of resistivity of conductive tracer materials during the curing period was conducted. The time-varying dynamic monitoring results of resistivity were fitted, and the relationship between resistivity and curing age was found to satisfy the following functional relationship: ; In the formula, N is the test resistivity of the grout, in Ω·cm, t is the curing age, t0, ρ1, and ρ2 are all fitting parameters, where ρ1 and ρ2 can indirectly reflect the magnitude of the material's impedance in the initial monitoring stage and the final state of the material, respectively, t0 reflects the time point when the resistivity of the conductive tracer material increases the fastest, and p is a control parameter related to the time-varying characteristics of the material.

7. A soil reinforcement visualization and tracing simulation device, applicable to the soil reinforcement visualization and tracing method as described in claim 1, characterized in that: The device includes a spring electrode assembly surrounding the sample, which is arranged in a multi-layered structure along the longitudinal direction to obtain the cross-sectional resistivity at different heights of the sample, forming a three-dimensional measurement network. The spring electrode assembly is connected to a data acquisition and control unit, which is used to acquire the excitation and response voltages of the multi-layered electrodes. The data acquisition and control unit is connected to a data processing unit, which fuses the multi-layered resistivity data based on an interpolation algorithm to reconstruct a complete three-dimensional resistivity distribution image inside the sample.

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