A method for simulating and preventing latent erosion of sand with discontinuous gradation based on CFD-DEM coupling

Abstract

The present application belongs to the technical field of geotechnical engineering seepage failure prevention and control, and particularly relates to a discontinuous graded sand soil latent erosion simulation and prevention and control method based on CFD-DEM coupling. The method breaks through the limitation of traditional models, adopts a micro calcium carbonate particle filling method, gives linear contact models and parallel bonding models to the three types of contacts of sand particle-sand particle, sand particle-calcium carbonate and calcium carbonate-calcium carbonate, and truly reproduces the double reinforcement mechanism of MICP "filling + cementation". A multi-dimensional dynamic evaluation system covering fine particle erosion rate, average coordination number, porosity and force chain network is constructed, and macroscopic and microscopic collaborative analysis is realized. Through systematic comparison, the three major prevention and control mechanisms of MICP filling, cementation and structure strengthening are quantitatively revealed. Further simulation of the latent erosion process under different fine particle contents, discontinuous ratios and calcium carbonate deposition amounts summarizes clear prevention and control rules, provides reliable numerical basis for differentiated and economically efficient MICP reinforcement schemes, and has important engineering application value.

Description

Technical Field

[0001] This invention belongs to the field of seepage damage prevention and control technology in geotechnical engineering, specifically involving a method for simulation and prevention of intermittent graded sand erosion based on CFD-DEM coupling. Background Technology

[0002] Seepage-induced erosion refers to the phenomenon where fine particles migrate and even erode in discontinuous graded sand under the action of seepage water, migrating along the pore channels formed by coarse particles. It is a significant contributing factor to geotechnical engineering disasters such as seepage instability of dams, landslide dam failure, and rainfall-induced slope instability. Traditional physical model tests are insufficient for effectively observing and quantitatively characterizing the particle migration characteristics and microstructural evolution processes within MICP-reinforced soils. Computational fluid dynamics-discrete element coupling (CFD-DEM) methods can achieve refined simulations of the interaction between the seepage field and the particle system at the particle scale. However, existing CFD-DEM-based erosion simulation studies mainly focus on the influence of soil gradation, fine particle content, and hydraulic conditions, and have not yet established a complete fluid-structure interaction analysis framework that couples the cementation effect of microbially induced calcium carbonate (MICP). This makes it difficult to systematically compare and analyze the microscopic response of soil before and after MICP treatment under seepage, and also lacks mature methods for quantitatively evaluating the erosion-inhibiting effect of MICP using multi-dimensional microscopic indicators such as coordination number and force chain network.

[0003] Therefore, it is urgent to construct a CFD-DEM undercut simulation system that couples the cementing effect of MIP to fill the existing research gap and provide scientific microscopic simulation support and quantitative evaluation method for the prevention and control of seepage undercut disasters using MIP technology. Summary of the Invention

[0004] The purpose of this invention is to address existing problems by providing a method for simulating and controlling the erosion of discontinuous graded sand based on CFD-DEM coupling.

[0005] This invention is achieved through the following technical solution: A method for simulating and controlling the erosion of discontinuous graded sand based on CFD-DEM coupling includes the following steps: Step 1: Establish a solid phase numerical model. A DEM model characterizing the microstructure of MICP mineralized sand is constructed using the microparticle filling method. The model includes three contact types: sand particle-sand particle, sand particle-calcium carbonate particle, and calcium carbonate particle-calcium carbonate particle. A linear contact model is used for sand particle-sand particle, while a parallel bonding model is used for sand particle-calcium carbonate particle and calcium carbonate particle-calcium carbonate particle contacts. Different calcium carbonate deposition amounts are simulated by adjusting the number of calcium carbonate particles. Step 2: Constructing the fluid domain and realizing CFD-DEM bidirectional coupling. A fluid computational domain is established around the DEM particle model and meshed. The CFD-DEM bidirectional coupling solver is used to realize the interaction between the fluid and the particles, thereby updating the porosity. Step 3: Design the erosion simulation conditions, systematically vary the fine particle content, discontinuity ratio, and calcium carbonate deposition after MIP treatment of the sand, and use the discontinuous graded sand without MIP treatment as the control sample to conduct seepage erosion simulation under the same hydraulic boundary conditions. Step 4: Real-time monitoring and data acquisition of multiple indicators, real-time monitoring and recording of fine particle loss and erosion rate, average coordination number, porosity, and force chain network; Step 5: Based on the monitoring data from Step 4, divide the stages of the erosion process of discontinuous graded sand, quantify the control effect of MIP treatment, reveal the microscopic mechanism of control, and summarize the control rules.

[0006] Furthermore, the DEM model mentioned in step one is a cylinder with a diameter of 39.1 mm and a height of 80 mm, or a cube with a side length of 25 mm. The particle size distribution is set according to discontinuously graded sand, the calcium carbonate particle size range is 0.03~0.1 mm, and the sand particle density is 2630 kg / m³. 3 The density of calcium carbonate particles is 3150 kg / m³. 3 .

[0007] Furthermore, the number of calcium carbonate particles mentioned in step one is calculated using the following formula: ; Where: m Calcium Carbonate For the mass of calcium carbonate crystals; C c R represents the mass fraction of calcium carbonate crystals. v The volume correction factor is set to 0.74. ρ Calcium Carbonate The density of calcium carbonate crystals is taken as 3150 kg / m³. 3 ; r Calcium Carbonate The radius of the calcium carbonate crystal is taken as 0.065 mm.

[0008] Furthermore, the microscopic contact parameters of the DEM model described in step one are determined by comparing and calibrating the stress-strain curves of geotechnical triaxial tests and numerical simulations. The specific parameters are assigned values ​​according to the contact types of intermediate graded sand and MICP mineralized sand as shown in Tables 4.2 to 4.6.

[0009] Furthermore, in step two, the fluid computation domain is a 25mm×25mm×25mm cube with a grid number of 125. The fluid used is incompressible water with a density set to 1000 kg / m³. 3The viscosity was set to 0.001 Pa·s, the time step was 5e-5s for CFD and 1e-5s for DEM, a fixed flow rate of 0.1 m / s was applied to the top of the fluid domain, and the bottom flowed out freely.

[0010] Further, the fine particle content in step three is 15%, 25%, and 35%, corresponding to Gap-A1, Gap-A2, and Gap-A3 samples, respectively; the discontinuity ratios are 3.33, 4.0, and 4.44, corresponding to Gap-A1, Gap-B1, and Gap-C1 samples, respectively; and the calcium carbonate deposition amount is set to four levels: 0g, 2.97g, 8.58g, and 13.36g, corresponding to Quantity-1 to Quantity-4 samples, respectively.

[0011] Furthermore, the optimal MIP treatment protocol described in step three is as follows: ambient temperature 20-30°C, bacterial culture medium of Bacillus pasteurellii (strain number ATCC11859), and bacterial concentration OD... 600 The value was 1.0, the cementing solution concentration was 0.5 mol / L (prepared by mixing urea and calcium chloride at a volume ratio of 1:1), and the mineralization cycle consisted of two rounds; each round of mineralization included one bacterial solution soak (2 h) and three cementing solution soaks (8 h each), with an 8 h interval between bacterial solution soaks and cementing solution soaks and between the three cementing solution soaks, and an 8 h interval between the two rounds of mineralization.

[0012] Furthermore, the erosion rate mentioned in step four R er uses the number of fine particles lost through erosion Δ N Compared with the initial total amount of fine particles N The ratio of 0 is represented by the following formula:

[0013] The average coordination number N Ave is calculated using the following formula:

[0014] In the formula, N c N represents the total number of contacts. p This represents the total number of particles.

[0015] Furthermore, the porosity described in step four is monitored and cross-checked simultaneously in two ways. The check method is to ensure that the relative deviation between the two monitoring results is <3% to guarantee the reliability of the porosity data: ① Layout measurement spheres in PFC3D and calculate the local porosity evolution based on the particle volume fraction in the spheres; ② Calculate the overall porosity distribution based on the particle volume fraction in the CFD grid cells. The force chain network uses color spectrum and line thickness to represent the magnitude of contact force, with blue to red indicating that the contact force increases sequentially. The force chain shape is, for example, but not limited to, “I-shaped”, “Y-shaped”, “U-shaped”, “dumbbell-shaped” and “umbrella-shaped”.

[0016] Furthermore, the criteria for dividing the stages of the latent erosion process described in step five are as follows: the initiation stage refers to the erosion rate... R er > 0.1% and the growth rate remains positive; development stage refers to the erosion rate. R The permeability increased from 0.1% to 90% of the maximum permeability, and the coordination number decreased at a rate >0.05 / s; the failure stage refers to the permeability... R After reaching its maximum value, er tends to stabilize (change <5% within 5 consecutive seconds), and the porosity no longer increases significantly (change <1% within 5 consecutive seconds). The quantitative aspects of the control effect include: the percentage reduction in average permeability, the increase in initial coordination number, the delay in the occurrence of each stage of latent corrosion, and the reduction in final porosity. The control principles include: the higher the fine particle content, the more significant the relative improvement effect after MIP treatment; the larger the discontinuity ratio, the more sensitive the effect of MIP on improving the soil's erosion resistance; and the amount of calcium carbonate deposited needs to reach the Quantity-4 level (13.36g) to maintain the stability of the skeleton under high hydraulic action.

[0017] The present invention has the following advantages over the prior art: 1. High model accuracy and close alignment with engineering practice: This invention breaks through the limitations of traditional CFD-DEM undercut simulation which simply uses linear contact models or regular cemented units. It adopts a micro-calcium carbonate particle filling method, and assigns linear contact models and parallel bonding models to the different mechanical properties of three types of contacts: sand particle-sand particle, sand particle-calcium carbonate, and calcium carbonate-calcium carbonate. This realistically reproduces the dual reinforcement mechanism of "filling + cementation" in MICP mineralized sand, effectively solving the technical defect of existing models that cannot accurately characterize the microstructure of microbial cementation. It provides an accurate and engineering-aligned solid phase numerical model for seepage undercut simulation, laying a solid foundation for subsequent microscopic simulation analysis. 2. Comprehensive evaluation system with synergistic macro-microscopic assessment: This invention constructs a multi-dimensional, multi-scale dynamic evaluation system that includes fine particle permeability, average coordination number, porosity, and force chain network. It can not only accurately quantify the macroscopic loss of fine particles, but also reveal the evolution law of the soil's internal structure at the particle scale. This breaks through the technical bottleneck of traditional detection methods that can only observe macroscopic deformation and fine particle loss, and realizes the synergistic analysis, dynamic monitoring, and comprehensive evaluation of macro- and microscopic indicators, thereby improving the scientificity and comprehensiveness of the evaluation of MIP's anti-submarine erosion effect. 3. Clarifying the microscopic mechanism of MIP's anti-underflow corrosion and filling research gaps: This invention, through a systematic comparison of multi-index simulation results of samples before and after MIP treatment, quantitatively reveals the three core prevention and control mechanisms of MIP technology at the microscopic level: the filling effect, the cementing effect, and the structural strengthening effect. It clearly explains the intrinsic core reasons why MIP technology inhibits seepage underflow corrosion, effectively filling the technical gap in existing research where it is difficult to quantitatively explain the mechanism of MIP's anti-underflow corrosion action, and providing theoretical support for the application of MIP technology in the field of underflow corrosion prevention and control. 4. Provides practical engineering parameters and has significant practical value: This invention systematically simulates the seepage erosion process under typical working conditions such as different fine particle contents, different discontinuity ratios, and different calcium carbonate deposition amounts. It summarizes the clear laws of MIP reinforcement for preventing seepage erosion and quantifies the key control parameters under various soil conditions. It provides reliable numerical basis and forward-looking analysis tools for developing differentiated, economical, and efficient MIP reinforcement schemes for specific soil conditions in actual engineering (such as determining the optimal grouting rounds and concentrations). It has important engineering application value and practical guiding significance. Attached Figure Description

[0018] Figure 1 For technology roadmap; Figure 2 This is a bacterial growth curve; Figure 3 Particle size distribution diagram for the test sand; Figure 4 SEM images of MICP mineralized sand at different magnifications, including (a) SEM image at 130x magnification; (b) SEM image at 250x magnification; (c) SEM image at 500x magnification; and (d) SEM image at 1000x magnification. Figure 5 The particle size distribution of calcium carbonate crystals under SEM; Figure 6 Numerical model of MICP mineralized discontinuous graded sand; where (a) numerical sample of MICP mineralized sand; (b) contact type of MICP mineralized sand model. Figure 7 Measure the circle for the model; Figure 8 The changes in the permeation rate of samples with different fine particle contents over time are shown in the following figures: (a) the curves of the permeation rate of samples with different fine particle contents over time; (b) the curves of the permeation rate of samples with different fine particle contents over time after MIP treatment; (c) the comparison curves of the permeation rate over time; and (d) the trends of the permeation rate at 0s and 20s. Figure 9The changes in coordination number over time for samples with different fine particle contents are shown in the following figures: (a) Curves showing the changes in coordination number over time for samples with different fine particle contents; (b) Curves showing the changes in coordination number over time for samples with different fine particle contents after MICP treatment; and (c) Comparison curves showing the changes in coordination number over time. Figure 10 The porosity of samples with different fine particle contents changes over time, including (a) the porosity of samples with different fine particle contents changes over time; (b) the porosity of samples with different fine particle contents changes over time after MICP treatment; and (d) the porosity change trends at 0s and 20s. Figure 11 The diagram shows the force chain changes at different stages of the model with different fine particle contents, where (a) is the initial stage; (b) is the initiation stage; (c) is the development stage; and (d) is the failure stage. Figure 12 The diagram shows the force chain morphology, where (a) represents the loss of fine particles and (b) represents the movement of skeletal particles. Figure 13 The following are the changes in the corrosion rate of samples with different discontinuity ratios over time: (a) the corrosion rate of samples with different discontinuity ratios over time; (b) the corrosion rate of samples with different discontinuity ratios over time after MICP treatment; (c) the comparison curve of corrosion rate over time; and (d) the trend of corrosion rate at 0s and 20s. Figure 14 The changes in coordination number of samples with different discontinuity ratios over time are shown in (a) curves of coordination number of samples with different discontinuity ratios over time; (b) curves of coordination number of samples with different discontinuity ratios over time after MICP mineralization; and (c) comparative curves of coordination number changes over time. Figure 15 The porosity of samples with different discontinuity ratios changes over time, including (a) porosity curves of samples with different discontinuity ratios over time; (b) porosity curves of samples with different discontinuity ratios over time after MICP treatment; (c) comparative curves of porosity changes over time; and (d) porosity trends at 0s and 20s. Figure 16 The diagram shows the force chain change process of the model at each stage with different discontinuity ratios, where (a) is the initial stage; (b) is the initiation stage; (c) is the development stage; and (d) is the failure stage. Figure 17 The changes in the corrosion rate of samples with different calcium carbonate deposition amounts over time are shown in (a) the curves of the corrosion rate of samples with different calcium carbonate deposition amounts over time; and (b) the trend of the average corrosion rate of samples with different calcium carbonate deposition amounts during the undercutting process. Figure 18 The change of coordination number over time for samples with different calcium carbonate deposition amounts; Figure 19The porosity of samples with different calcium carbonate deposition amounts varies with time. Figure 20 The diagram shows the force chain changes at different stages of the model with different amounts of calcium carbonate deposition, where (a) is the initial stage; (b) is the initiation stage; (c) is the development stage; and (d) is the destruction stage. Detailed Implementation

[0019] To further explain the present invention, the following specific embodiments are described.

[0020] Discontinuously graded soils, due to the lack of intermediate particle size distribution, typically exhibit an intermediate "plateau" in their particle size distribution curve, with two discontinuities.

[0021] The overall technical approach of this invention is as follows: Figure 1 As shown.

[0022] A method for simulating and controlling the erosion of discontinuous graded sand based on CFD-DEM coupling includes the following steps: Step 1: Suggested numerical model for solid phase - three-phase coupled discrete element model A DEM model capable of characterizing the microstructure of MICP mineralized sand was constructed using the microparticle filling method, with the following specific requirements: 1. Basic Model Parameters Size specifications: consistent with actual test results, two sizes are available: a cylinder with a diameter of 39.1mm and a height of 8mm or a cube with a side length of 25mm; Particle size distribution: Strictly set according to the particle size distribution of discontinuously graded sand, the specific gradation curve is as follows: Figure 3 As shown, ensure that the particle composition of the model is consistent with that of the actual sand.

[0023] 2. Contact type and model selection: Contact type classification: The model includes three types of particle contact relationships: sand particle-sand particle, sand particle-calcium carbonate particle, and calcium carbonate particle-calcium carbonate particle. Contact model matching: A linear contact model was used for sand particle-sand particle contact, while a parallel bonding model was used for sand particle-calcium carbonate particle and calcium carbonate particle-calcium carbonate particle contact to truly reflect the cementation effect and mechanical transfer characteristics between particles after MICP mineralization.

[0024] 3. Particle physical parameters: Calcium carbonate particles: particle size ranges from 0.03 to 0.1 mm. The statistical results of the actual particle size distribution of calcium carbonate crystals are as follows: Figure 5 As shown, the density of calcium carbonate particles is 3150 kg / m³. 3 ; Sand particles: The density of sand particles is 2630 kg / m³3 The particle size shall be in accordance with the specifications in Table 1 (coarse particles 5~2mm, fine particles 0.25~0.60mm).

[0025] Table 1 Classification of Sandy Soils at Various Levels ; 4. Adjustment of calcium carbonate deposition: Adjustment method: By changing the number of calcium carbonate particles filled in the model, different levels of calcium carbonate deposition are simulated; Quantity Calculation: The number of calcium carbonate particles is calculated using the following formula: ; In the formula: mCalcium Carbonate is the mass of calcium carbonate crystals (unit: g), determined by actual mineralization test; Cc is the mass fraction of calcium carbonate crystals (unit: %) (Table 2); Rv is the volume correction factor, taken as 0.74, used to consider the difference in solid fraction at the densest particle arrangement; ρCalcium Carbonate is the density of calcium carbonate crystals, taken as 3150 kg / m3; rCalciumCarbonate is the radius of calcium carbonate crystals, taken as 0.065 mm.

[0026] Table 2. Calcium carbonate content after mineralization tests of sandy soils with different discontinuous gradations ; 5. Detailed parameter calibration: Calibration method: The micro-contact hyperparameters of the DEM model were determined by comparing the stress-strain curves of the geotechnical triaxial test with those of the numerical simulation to ensure that the mechanical response of the numerical model is consistent with that of the actual soil. Parameter assignment: Specific parameters are assigned according to Tables 3 to 7, as shown in the following example: Between sand particles: Effective modulus 1.0 × 10⁻⁶ 8 Pa, stiffness ratio 1.0, friction coefficient 1.2; Calcium carbonate: Effective modulus 5.0 × 10⁻⁶ 9 Pa, bonding tensile strength 22.0 MPa, cohesion 22.0 MPa; Between sand particles and calcium carbonate: effective modulus 5.0 × 10⁻⁶ 9 Pa, bonding tensile strength 94.0 MPa, cohesion 94.0 MPa.

[0027] Table 3. Microscopic contact parameters of MICP-mineralized Gap-A1 ; Table 4. Microscopic contact parameters of MICP mineralized Gap-A2 ; Table 5. Microscopic contact parameters of MICP-mineralized Gap-A3 ; Table 6. Microscopic contact parameters of MICP-mineralized Gap-B1 ; Table 7. Microscopic contact parameters of MICP-mineralized Gap-C1 ; Step 2: Constructing the fluid domain and realizing bidirectional coupling of CFD-DEM 1. Construction of the fluid computational domain: Domain size: Construct a cubic fluid domain with dimensions of 25mm×25mm×25mm around the established DEM particle model; Mesh generation: The fluid domain is meshed with a grid number of 125 to ensure a balance between flow field calculation accuracy and computational efficiency.

[0028] 2. Fluid physical parameter setting Fluid type: Incompressible water; Density: set at 1000 kg / m³ 3 ; Viscosity: set to 0.001 Pa·s.

[0029] 3. Implementation via bidirectional coupling: Coupling Platform: The PFC3D and OpenFOAM coupling platform is used to realize bidirectional data interaction of CFD domain DEM; Coupling mechanism: CFD module: Solve the Navier-Stokes equations to calculate fluid forces such as drag force and pressure gradient force on particles; DEM module: Based on the fluid interaction force and the contact force between particles, it solves the particle motion equation, updates the particle position and velocity in real time, and thus changes the porosity of the flow field region; Momentum exchange: The momentum exchange between the mobile phase and the solid phase is achieved through a drag force model; Time step: The CFD time step is 5e-5s and the DEM time step is 1e-5s to ensure the stability of the coupled calculation.

[0030] 4. Boundary condition settings: Velocity boundary: A fixed velocity of 0.1 m / s is applied at the top of the fluid domain; Outflow boundary: The bottom of the fluid domain is set as a free outflow boundary; Particle interception: The upper and lower boundary walls of the model are removed and replaced with a filter device to intercept particles while allowing fluid to pass through.

[0031] Step 3: Design simulation conditions for erosion. A series of systematic simulation scenarios were designed to comprehensively explore the impact of key factors on the undercutting process and the effectiveness of MIP control. The specific settings are as follows: 1. Operating condition variables and levels: Variable 1: Fine particle content of sandy soil, with three levels set at 15%, 25%, and 35%, corresponding to sample numbers Gap-A1, Gap-A2, and Gap-A3; Variable 2: Discontinuity ratio of sand, with three levels set at 3.33, 4.0 and 4.44, corresponding to sample numbers Gap-A1, Gap-B1 and Gap-C1; Variable 3: The amount of calcium carbonate deposited after MICP treatment, determined by varying the cementitious solution concentration at four levels, specifically: Quantity-1: Cementing solution concentration 0 mol / L, calcium carbonate deposition amount 0 g; Quantity-2: Cementing solution concentration 0.25 mol / L, calcium carbonate deposition amount 2.97 g; Quantity-3: Cementing solution concentration 0.5 mol / L, calcium carbonate deposition amount 8.58 g; Quantity-4: Cementing solution concentration 1.0 mol / L, calcium carbonate deposition amount 13.36 g; After MICP treatment, irregular calcium carbonate crystal clusters formed on the surface of sand particles, with crystal particle sizes ranging from 0.03 to 0.1 mm. Their microstructure is as follows: Figure 4 As shown.

[0032] 2. Controlled Design: Control group: Discontinuous graded sand without MIP treatment, used to compare and evaluate the control effect of MIP treatment; Experimental group: discontinuously graded sandy soil treated with different levels of MICP (corresponding to different amounts of calcium carbonate deposition).

[0033] 3. Standardize test conditions: Hydraulic boundary conditions: The same hydraulic boundary conditions are used for all operating conditions (fixed flow velocity at the top of 0.1 m / s, free flow at the bottom); Simulation duration: The simulation duration for each working condition is set to 20 seconds; Ambient temperature: The ambient temperature during the MIP treatment process simulation is controlled at 20~30℃.

[0034] 4. MICP processing procedure: Optimal parameter: bacterial concentration OD 600 The value was 1.0, indicating that the strain entered the stationary phase after 24 hours of culture.600 The value is approximately 2.3, and its growth curve is as follows: Figure 2 As shown, the cementing solution concentration was 0.5 mol / L (prepared by mixing urea and calcium chloride at a volume ratio of 1:1), and the mineralization process consisted of two rounds. Immersion process: Each round of mineralization includes one bacterial solution immersion (lasting 2 hours) and three cementing solution immersions (lasting 8 hours each); there is an 8-hour interval between the bacterial solution immersion and the first cementing solution immersion, and an 8-hour interval between each of the three cementing solution immersions; there is an 8-hour interval between two rounds of mineralization.

[0035] Step 4: Real-time monitoring and data collection of multiple indicators Throughout the simulation, based on the PFC3D built-in History command and measurement sphere, the following four key macro- and micro-indicators are monitored and recorded in real time to ensure comprehensive and accurate data: 1. Fine particle loss and corrosion rate: Data Acquisition: Real-time statistics of the number of fine particles flowing out of the computation domain (Δ N Record the initial total amount of fine particles ( N 0); Calculation method: Calculate according to the following formula:

[0036] 2. Average coordination number (Nave) of the particulate system: Data acquisition: Real-time recording of the total number of contacts (Nc) and the total number of particles (Np) in the particulate system; Calculation method: Calculate according to the following formula

[0037] Significance of the indicator: It reflects the degree of contact between particles. The higher the coordination number, the more reliable the data.

[0038] 3. Internal porosity of the sample: Monitoring method: Two methods are used for simultaneous monitoring and cross-verification to ensure data reliability. ① Local porosity: Measurement spheres are uniformly distributed in PFC3D, and the dynamic evolution of local porosity is calculated based on the particle volume fraction within the spheres (the spatial distribution of the measurement spheres in the model is as follows). Figure 7 (as shown) ② Overall porosity: Based on the particle volume fraction within the CFD mesh cells, the porosity distribution across the entire fluid domain is calculated; Definition of index: Porosity is the ratio of the internal pore volume of a sample to the total volume of the sample (unit: %).

[0039] 4. Interparticle contact force chain network: Monitoring content: Real-time recording of the spatial distribution, contact strength, and evolution process of the force chain; Strength characterization: The strength of the force chain is represented by a combination of color spectrum and line thickness, with the contact force increasing sequentially in the order of blue → green → yellow → orange → red; Morphological classification: Records typical force chain morphologies, including "one-line," "Y-shaped," "U-shaped," "dumbbell-shaped," and "umbrella-shaped." Typical force chain morphologies appearing during the erosion process are as follows: Figure 12 As shown.

[0040] Step 5: Comparative Analysis and Mechanism Demonstration of MICP Prevention and Control Effects Based on the macroscopic and microscopic data collected from monitoring, the system analyzes the effectiveness, underlying mechanism, and patterns of MIP treatment in preventing and controlling latent corrosion, as detailed below: 1. Quantifying the effectiveness of prevention and control: Data processing: Plot the curves of permeation rate, average coordination number, porosity, and force chain network strength of the control group and each experimental group under different working conditions over time; Quantitative indicators: The control effect of MIP treatment is calculated and characterized through curve comparison, specifically including: ① Percentage reduction in average corrosion rate: (average corrosion rate of control group - average corrosion rate of test group) / average corrosion rate of control group × 100%; ② Increase in initial coordination number: (Initial coordination number in experimental group - Initial coordination number in control group) / Initial coordination number in control group × 100%; ③ Delay in the occurrence time of each stage of erosion: the difference between the start time of each stage in the experimental group and the control group; ④ Reduction in final porosity: Final porosity of control group - Final porosity of experimental group.

[0041] 2. Quantitative criteria for determining the latent erosion stage: Start-up phase: Permeability R er>0.1%, and the rate of erosion continues to be positive (i.e., fine particles begin to continuously erode). Development stage: Erosion rate R The er increased from 0.1% to 90% of the maximum erosion rate under this working condition, and the coordination number decrease rate was >0.05 / s (i.e., particle contact decreased rapidly and the structure began to loosen). The coordination number decrease rate was the amount of decrease in the average coordination number per unit time (second). Destruction stage: Permeability R After er reaches its maximum value, it tends to stabilize (the change in permeability rate is <5% within 5 consecutive seconds), and the porosity no longer increases significantly (the change in porosity is <1% within 5 consecutive seconds) (i.e., the loss of fine particles stops and the soil structure is stable).

[0042] 3. Explanation of the prevention and control mechanism Filling effect: MICP generates calcium carbonate crystals that fill the pores inside the sand, reducing the size of the seepage channels, prolonging the time required for fine particles to start up, and reducing the migration efficiency of fine particles. Cementing effect: Calcium carbonate forms a cementing effect between sand particles and fine particles, and between sand particles themselves, which enhances the bonding strength between particles and increases the hydraulic threshold for fine particle loss (i.e., a greater water flow force is required for fine particles to detach from the skeleton). Structural strengthening effect: Calcium carbonate cementation forms a continuous network structure, which enhances the integrity of the particle system and the stability of the force chain network, delays the destruction and reconstruction process of the soil skeleton structure, and thus inhibits the development of burrowing.

[0043] 4. Summary of prevention and control patterns: The effect of fine particle content: The higher the fine particle content, the more severe the primary erosion of the untreated sand. After MIP treatment, the reduction in erosion rate and the increase in coordination number of sand with high fine particle content are more significant, that is, the relative improvement effect is more prominent. The effect of discontinuity ratio: The larger the discontinuity ratio, the larger the pore size inside the sand, the worse the structural stability, and the higher the risk of primary erosion. MIP treatment is more sensitive to the improvement of the erosion resistance of sand with high discontinuity ratio (such as Gap-C1, discontinuity ratio 4.44), showing a greater increase in coordination number and a more obvious decrease in porosity. The effect of calcium carbonate deposition: The amount of calcium carbonate deposition is positively correlated with the control effect. Low deposition (such as Quantity-2) samples still have the risk of skeleton reconstruction. Only when the deposition reaches the Quantity-4 level can the soil skeleton be stabilized under high hydraulic action by constructing a strong contact network, thus achieving the best control effect.

[0044] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0045] Example 1: Simulation and control effect evaluation of microporous erosion in MIP mineralized sand under different fine particle contents Model construction: DEM models of three discontinuous graded sands, namely Gap-A1 (15% fine particle content), Gap-A2 (25%), and Gap-A3 (35%), were established according to step one, and the micro-contact parameters were assigned according to Tables 3 to 5. For each sample, control sample without MICP treatment and test group model with MICP optimal treatment scheme were established respectively. Coupling and Simulation: Construct the CFD mesh and set up two-way coupling as in step two, and apply a seepage velocity of 0.1 m / s as in step three. The simulation duration is 20 s. Monitoring and Analysis: Follow step four to monitor the permeability, coordination number, porosity, and force chain network in real time. Results are as follows: Figure 8 , Figure 9 , Figure 10 , Figure 11 As shown; The results showed that after MIP treatment, the maximum fine particle penetration rates of samples with fine particle contents of 15%, 25%, and 35% decreased from 2.04%, 3.09%, and 5.04% to 1.85%, 2.85%, and 4.75%, respectively, with average reductions of 13%, 20%, and 19%. Figure 8 The initial coordination number increased by 18%, 13%, and 10%, respectively. Figure 9 The initial porosity decreased by 3.34%, 3.46%, and 3.03%, respectively. Figure 10 Force chain network analysis shows that MICP treatment significantly increases weak contacts (blue) and makes the framework structure more stable. Figure 11 ).

[0046] Example 2: Simulation and Evaluation of the Control Effect of MIP Mineralized Sand Pitting Erosion under Different Discontinuity Ratios Model construction: DEM models of three discontinuous graded sands, namely Gap-A1 (discontinuity ratio 3.33), Gap-B1 (discontinuity ratio 4.0), and Gap-C1 (discontinuity ratio 4.44), were established according to step one, and the microscopic contact parameters were assigned according to Tables 3, 6, and 7; control sample and MIP mineralization test group models were set up. Coupling and Simulation: Conduct CFD-DEM erosion simulation according to steps two and three; Monitoring and Analysis: Results are as follows Figure 13 , Figure 14 , Figure 15 , Figure 16 As shown; The results showed that after MIP treatment, the maximum fine-particle erosion rate of Gap-A1, Gap-B1, and Gap-C1 samples decreased from 2.04%, 3.40%, and 4.98% to 1.85%, 3.21%, and 4.74%, respectively, with an average reduction of 13%. Figure 13 The initial coordination number was increased by 10%, 50%, and 30% respectively. Figure 14 The initial porosity decreased by 3.34%, 3.93%, and 2.92%, respectively. Figure 15 For samples with a larger discontinuity ratio, the increase in weak contacts after MIP treatment is more significant, and strong contacts remain more intact during the failure stage. Figure 16 ).

[0047] Example 3: Simulation and Evaluation of the Control Effect of Microchip Petroleum Embedding in Mineralized Sand under Different Calcium Carbonate Deposition Conditions Model construction: Following step one, using Gap-A1 as the base soil, four types of calcium carbonate deposition samples (Quantity-1 to Quantity-4) were constructed by changing the cementing solution concentration, and the micro-contact parameters in Table 3 were assigned values. Coupling and Simulation: Conduct CFD-DEM erosion simulation according to steps two and three; Monitoring and Analysis: Results are as follows Figure 17 , Figure 18 , Figure 19 , Figure 20 As shown; The results showed that with the increase of calcium carbonate deposition, the maximum permeability of fine particles decreased successively from 2.04% (Quantity-1) to 1.86%, 1.85%, and 1.20% (Quantity-1). Figure 17 The initial coordination number was increased from 2.08 to 2.12, 2.50, and 3.15 respectively. Figure 18 The initial porosity decreased by 1.73%, 3.34%, and 4.46% relative to the blank group, respectively, and the final porosity decreased by 2.95%, 9.45%, and 15.45%, respectively. Figure 19 Force chain network analysis shows that the high deposition amount (Quantity-4) still maintains a relatively intact strong contact framework during the failure phase. Figure 20 ).

[0048] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for simulating and controlling the erosion of discontinuous graded sandy soil based on CFD-DEM coupling, characterized in that, Includes the following steps: Step 1: Establish a solid phase numerical model. A DEM model characterizing the microstructure of MICP mineralized sand is constructed using the microparticle filling method. The model includes three contact types: sand particle-sand particle, sand particle-calcium carbonate particle, and calcium carbonate particle-calcium carbonate particle. A linear contact model is used for sand particle-sand particle, while a parallel bonding model is used for sand particle-calcium carbonate particle and calcium carbonate particle-calcium carbonate particle contacts. Different calcium carbonate deposition amounts are simulated by adjusting the number of calcium carbonate particles. Step 2: Constructing the fluid domain and realizing bidirectional coupling of CFD-DEM. A fluid computational domain is established around the DEM particle model and meshed. The interaction between the fluid and particles is realized using the CFD-DEM bidirectional coupling solver to update the porosity. Step 3: Design the erosion simulation conditions, systematically vary the fine particle content, discontinuity ratio, and calcium carbonate deposition after MIP treatment of the sand, and use the discontinuous graded sand without MIP treatment as the control sample to conduct seepage erosion simulation under the same hydraulic boundary conditions. Step 4: Real-time monitoring and data acquisition of multiple indicators, real-time monitoring and recording of fine particle loss and erosion rate, average coordination number, porosity, and force chain network; Step 5: Based on the monitoring data from Step 4, divide the stages of the erosion process of discontinuous graded sand, quantify the control effect of MIP treatment, reveal the microscopic mechanism of control, and summarize the control rules.

2. The method according to claim 1, characterized in that, The DEM model mentioned in step one is a cylinder with a diameter of 39.1 mm and a height of 80 mm, or a cube with a side length of 25 mm. The particle size distribution is set according to the discontinuous gradation of sand, with calcium carbonate particle size ranging from 0.03 to 0.1 mm and sand particle density of 2630 kg / m³. 3 The density of calcium carbonate particles is 3150 kg / m³. 3 .

3. The method according to claim 1, characterized in that, The number of calcium carbonate particles mentioned in step one is calculated using the following formula: ； Where: m Calcium Carbonate For the mass of calcium carbonate crystals; C c R represents the mass fraction of calcium carbonate crystals. v The volume correction factor is set to 0.

74. ρ Calcium Carbonate The density of calcium carbonate crystals is taken as 3150 kg / m³. 3 ; r Calcium Carbonate The radius of the calcium carbonate crystal is taken as 0.065 mm.

4. The method according to claim 1, characterized in that, The microscopic contact parameters of the DEM model described in step one were determined by comparing and calibrating the stress-strain curves of geotechnical triaxial tests and numerical simulations. The specific parameters were assigned values ​​according to the contact type of discontinuous graded sand and MICP mineralized sand.

5. The method according to claim 1, characterized in that, The fluid computation domain described in step two is a 25mm×25mm×25mm cube with a grid number of 125. The fluid used is incompressible water with a density set to 1000 kg / m³. 3 The viscosity was set to 0.001 Pa·s, the time step was 5e-5s for CFD and 1e-5s for DEM, a fixed flow rate of 0.1 m / s was applied to the top of the fluid domain, and the bottom flowed out freely.

6. The method according to claim 1, characterized in that, The fine particle content in step three is 15%, 25%, and 35%, corresponding to Gap-A1, Gap-A2, and Gap-A3 samples, respectively; the discontinuity ratios are 3.33, 4.0, and 4.44, corresponding to Gap-A1, Gap-B1, and Gap-C1 samples, respectively; and the calcium carbonate deposition amount is set to four levels: 0g, 2.97g, 8.58g, and 13.36g, corresponding to Quantity-1 to Quantity-4 samples, respectively.

7. The method according to claim 1, characterized in that, The optimal MIP treatment protocol described in step three is as follows: ambient temperature 20-30℃, bacterial culture medium of Bacillus pasteurellii, and bacterial concentration OD... 600 The value was 1.0, the cementing solution concentration was 0.5 mol / L, and the mineralization cycle consisted of two cycles. Each mineralization cycle included one bacterial solution soak and three cementing solution soaks. There was an 8-hour interval between the bacterial solution soak and the cementing solution soak, as well as between the three cementing solution soaks, and an 8-hour interval between the two mineralization cycles.

8. The method according to claim 1, characterized in that, The corrosion rate mentioned in step four R er uses the number of fine particles lost through erosion Δ N Compared with the initial total amount of fine particles N The ratio of 0 is represented by the following formula: ； The average coordination number N Ave is calculated using the following formula: ； In the formula, N c N represents the total number of contacts. p This represents the total number of particles.

9. The method according to claim 1, characterized in that, The porosity described in step four is monitored and cross-checked simultaneously in two ways: ① Measurement spheres are placed in PFC3D, and the local porosity evolution is calculated based on the particle volume fraction within the spheres; ② The overall porosity distribution is calculated based on the particle volume fraction within the CFD grid cells. The force chain network uses a color spectrum and line thickness to represent the magnitude of the contact force, with blue to red indicating that the contact force increases sequentially. The force chain shapes include "I-shaped", "Y-shaped", "U-shaped", "dumbbell-shaped" and "umbrella-shaped".

10. The method according to claim 1, characterized in that, The criteria for dividing the stages of the latent corrosion process described in step five are as follows: the initiation stage refers to the corrosion rate. R er > 0.1% and the growth rate remains positive; development stage refers to the erosion rate. R The permeability increased from 0.1% to 90% of the maximum permeability, and the coordination number decreased at a rate >0.05 / s; the failure stage refers to the permeability... R After reaching its maximum value, er tends to stabilize, and the porosity no longer increases significantly; The quantitative aspects of the control effect include: the percentage reduction in average permeability, the increase in initial coordination number, the delay in the occurrence of each stage of latent corrosion, and the reduction in final porosity. The control principles include: the higher the fine particle content, the more significant the relative improvement effect after MIP treatment; the larger the discontinuity ratio, the more sensitive the effect of MIP on improving the soil's erosion resistance; and the amount of calcium carbonate deposited needs to reach the Quantity-4 level (13.36g) to maintain the stability of the skeleton under high hydraulic action.

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