System calibration and verification method for discontinuous graded cohesive soil DEM model

Abstract

The invention provides a system calibration and verification method for a discontinuous graded cohesive soil DEM model. The system calibration and verification method comprises the following steps: (1) preliminarily determining microscopic parameter values of the DEM model; (2) sensitivity analysis of microscopic parameters of each DEM model; (3) gradually optimizing and iteratively analyzing each factor in combination with a sensitivity analysis result to obtain a microscopic parameter optimization value range of the DEM; (4) further optimizing the microscopic parameters of the DEM model based on Box-Behnken test design to obtain multiple groups of optimization parameter combinations; and (5) parameter verification. The method is reasonable in conception, integrates parameter calibration, precision verification and actual experiments, enables the purpose of parameter calibration to be clearer, can provide a more efficient and directional parameter calibration thought for cohesive soil with complex parameter calibration and fewer references, especially fine-grained soil or granular materials with extremely uneven grain size distribution, and is suitable for popularization and application. And meso-scale parameter calibration under quasi-static stress can be converted into parameter calibration and verification under dynamic load stress simulation.

Description

Technical Field

[0001] The invention relates to the technical field of mechanical manufacturing, and in particular to a system calibration and verification method of a discontinuously graded clay soil DEM model. Background Art

[0002] As an important tool for mechanical analysis of non-continuous media, the discrete element method (DEM) has made significant progress in the field of geomechanics and geotechnical engineering in recent years, especially in the study of complex problems such as soil-structure interaction and large deformation failure mechanism. Unlike numerical methods based on the assumption of continuous media (such as the finite element method FEM), DEM can reveal the dynamic response characteristics of granular materials at the microscopic scale by tracking the motion trajectory of particles and the evolution of force chains.

[0003] Building a high-precision soil DEM simulation model is the key to obtaining reliable results. It requires comprehensive consideration of multiple factors, including issues such as particle size distribution, particle scaling, and particle shape involved in the generation of the particle model, as well as the determination of the contact model and the calibration of the microscopic parameters of the contact model. Among them, selecting a suitable contact model and accurately calibrating the model parameters are the primary tasks to accurately reflect the macroscopic mechanical behavior of the soil. Parameter calibration is also the most difficult part of discrete element simulation.

[0004] Although there are many calibration studies on sandy soil, clay soil and soil with high water content, there are few reports on the calibration of clay soil with discontinuous gradation and extremely uneven particle distribution. On the one hand, the cohesive contact model (such as JKR and EEPA models) is highly sensitive to parameters and needs to balance the multiple coupling effects of adhesion, elastic-plastic deformation and energy dissipation; on the other hand, clay soil belongs to fine-grained soil with a small average particle size and a large particle size span. When calibrating parameters, the particle size needs to be scaled to generate a total number of particles that can meet the computing power. At the same time, the influence of particle size effect and boundary effect needs to be considered. Since the particle characteristics directly affect the accuracy of model generation and simulation results, the above factors undoubtedly increase the difficulty of calibration of such soils.

[0005] Current DEM calibration methods mainly rely on time-consuming trial and error methods, that is, through the continuous iteration of parameter combinations, to achieve the match between simulation results and experimental results, or calibration experiments based on a single physical property (such as angle of repose, direct shear test, triaxial or cone penetration test), and use other software to achieve the optimization design of the calibration test. There are two major problems: first, the singleness of the calibration target. Static mechanical parameters cannot accurately map the behavior of particle migration and contact failure under dynamic impact, resulting in limited extrapolation ability of the model. The parameters calibrated under quasi-static stress may not be suitable for characterizing the mechanical behavior of soil when disturbed, such as impact penetration or penetration stress; second, the non-uniqueness of parameter combinations, that is, the lack of a unique solution for volumetric properties, and different mesoscopic parameters may produce equivalent macroscopic responses. Therefore, further research is needed to develop a calibration process to obtain accurate and highly applicable parameters. Summary of the invention

[0006] In view of the technical problems existing in the above-mentioned background technology, the present invention proposes a discrete element simulation parameter system calibration and verification method based on actual operation results. The method has a reasonable conception and integrates parameter calibration, accuracy verification and actual experiments, making the purpose of parameter calibration clearer. It can provide a more efficient and directional parameter calibration idea for clay soils with relatively complex parameter calibration and fewer references, especially fine-grained soils or granular materials with extremely uneven particle grading, and can realize the calibration and verification of parameters from microscopic parameter calibration under quasi-static stress to parameter calibration and verification under dynamic load stress simulation.

[0007] In order to solve the above technical problems, the present invention provides a method for system calibration and verification of a discontinuously graded clay soil DEM model, which comprises the following steps: (1) Preliminary determination of the microscopic parameters of the DEM model; (2) Sensitivity analysis of the mesoscopic parameters of each DEM model; (3) Combined with the results of sensitivity analysis, each factor is gradually optimized and iteratively analyzed to obtain the optimal value range of the mesoscopic parameters of the DEM model; (4) Based on the Box-Behnken experimental design, the mesoscopic parameters of the DEM model are further optimized to obtain multiple sets of optimized parameter combinations; (5) Parameter verification.

[0008] The method for systematic calibration and verification of the DEM model of discontinuously graded clay soil, wherein the specific process of step (1) is as follows: based on existing literature and repose angle test, and through the discrete element particle model database built into the EDEM software, the initial reference value range of the DEM model microscopic contact parameters is determined as a reference for constructing the discrete element model.

[0009] The method for systematically calibrating and verifying the DEM model of discontinuous graded clay soil, wherein: the microscopic contact parameters of the DEM model in the step (1) include shear modulus, restitution coefficient COR, static friction coefficient CSF, rolling friction coefficient CRF and free surface energy JKR; the initial reference value range of the shear modulus is 2e +7 ~3e +7 The initial reference value range of the coefficient of restitution COR is 0.60~0.90, the initial reference value range of the coefficient of rolling friction CRF is 0.3~0.6, the initial reference value range of the coefficient of static friction CSF is 1.00~1.40, and the initial reference value range of the free surface energy JKR is 2.5~6.5.

[0010] The method for systematic calibration and verification of the DEM model of discontinuously graded clay is as follows: the specific process of step (2) is as follows: taking the shear strength σ and the elastic modulus E as evaluation indicators, calculating different values ​​of the microscopic contact parameters of the DEM model, and comparing and analyzing the unit increments of σ and E; then, obtaining the average value of the unit increment under different values ​​as the basis for judging the sensitivity, and the calculation formulas are as follows (1) and (2): ; ; In the above formulas (1)-(2), x and y are the values ​​of the microscopic contact parameters of each DEM model; Through comprehensive analysis of the above formulas (1) and (2), the sensitivity of the micro-contact parameters of each DEM model can be obtained.

[0011] The method for systematic calibration and verification of the DEM model of discontinuously graded clay soil, wherein the specific process of the stepwise optimization iterative analysis of each factor in step (3) is as follows: according to the sensitivity analysis result of step (2), the values ​​of the mesoscopic contact parameters of the DEM model are adjusted in sequence; based on the stress-strain curve comparison result of the direct shear simulation test and the direct shear indoor test, the value range of the mesoscopic contact parameters of each DEM model is further narrowed and the value interval of the mesoscopic contact parameters of each DEM model is optimized.

[0012] The method for systematic calibration and verification of the DEM model of discontinuous graded clay soil, wherein the parameter optimization range obtained in step (3) is: elastic modulus is 3.5e+07 Pa, rolling friction coefficient CRF is 0.4-0.6, restitution coefficient COR is 0.70-0.85, static friction coefficient CSF is 1.0-1.5, and free surface energy JKR is 3.0-6.5.

[0013] The method for system calibration and verification of the discontinuous graded clay soil DEM model, wherein the step (4) specifically comprises the following steps: (4.1) Orthogonal rotation experimental design and regression model According to the optimization range of discrete element model parameters obtained in step (3), a calibration test is designed based on the Box-Behnken method: that is, the rolling friction coefficient CRF, the restitution coefficient COR, the static friction coefficient CSF and the free surface energy JKR in the DEM model micro-contact parameters are used as test factors, the elastic modulus and the shear strength are used as optimization targets, and the test factors and level data are designed; Based on the orthogonal rotation test designed by Design-Expert software, a multivariate regression fitting analysis was performed on the test factor combination and the corresponding result data, and the polynomial regression model of the direct shear calibration test was obtained as follows: ; (4.2) Parameter optimization and determination of optimal parameter combinations Based on the polynomial regression model in the above step (4.1), the optimization function in the Design-expert software is used to optimize the micro-contact parameters of the DEM model; the optimization criterion is set according to the result range of the elastic modulus and shear strength; the obtained optimization solution is not unique, but a combination of multiple parameters. The result can be used as the basis for calibration and verification of model parameters under dynamic load conditions.

[0014] The method for system calibration and verification of the discontinuous graded clay soil DEM model, wherein the step (5) specifically comprises the following steps: (5.1) Based on the optimized parameter combination obtained in step (4), the impact penetration simulation test is used as a verification method. Based on the impact penetration test, a discontinuous graded clay impact penetration DEM model is first constructed; (5.2) Quantitatively analyze the time history curve of the resistance of the cone tip of the impact penetration probe in the impact penetration test, and compare it with the impact penetration indoor test results to obtain the test and simulation results under different working conditions. Take the shear strength as the reference index. When the relative error is less than 5%, the calibration of discontinuously graded silty clay is realized, and the calibration and verification of the parameters under dynamic load simulation are realized from the calibration of the micro-parameters under quasi-static stress. When the relative error is not less than 5%, return to the step (4) to further optimize the micro-parameters of the DEM model.

[0015] The method for systematically calibrating and verifying the DEM model of discontinuously graded clay soil includes: in the impact penetration test, the setting of the contact relationship between soil particles and the impact penetration probe geometry can be initially kept consistent with the parameters between particles, and after the parameter combination closest to the test result is determined, a small range adjustment is performed, and micro-adjustments are successively achieved to make the calibration parameters more accurate.

[0016] By adopting the above technical solution, the present invention has the following beneficial effects: The system calibration and verification method of the discontinuous graded clay soil DEM model of the present invention is well conceived. The multi-step system calibration and verification method based on the angle of repose test, direct shear or triaxial test makes the purpose of parameter calibration clearer and the verification more comprehensive. The present invention can improve the parameter calibration accuracy of discontinuously graded clay soil and fine-grained soil with extremely uneven particle distribution; the present invention can provide a more efficient and more directional parameter calibration idea for clay soil whose parameter calibration is relatively complex and has few references, especially fine-grained soil or granular material with extremely uneven particle gradation; The present invention provides a new method for realizing the applicability from the calibration of microscopic parameters under quasi-static stress to the simulation under dynamic load stress.

[0017] The present invention is different from the previous single-form calibration method based on a single physical property of soil (such as the natural angle of repose or shear characteristics). It is a multi-step, continuously iteratively optimized system calibration method that can overcome the problems of poor calibration accuracy and lack of a unique solution caused by the large discreteness of geotechnical tests in a single method. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a multi-step calibration and verification method involved in the system calibration and verification method of the discontinuous graded clay soil DEM model of the present invention; Figure 2 A discontinuously graded clay particle gradation curve diagram involved in the system calibration and verification method of the discontinuously graded clay DEM model of the present invention; Figure 3 The system calibration and verification method of the discontinuous graded clay soil DEM model of the present invention is based on existing literature and repose angle test diagrams ((a) repose angle measuring instrument; (b) repose angle virtual test; (c) angle measurement schematic diagram); Figure 4 The direct shear test diagram involved in the system calibration and verification method of the discontinuous graded clay DEM model of the present invention ((a) direct shear tester (b) direct shear simulation test model); Figure 5It is a stress-strain curve diagram under different mesoscopic parameters involved in the system calibration and verification method of the discontinuous graded clay DEM model of the present invention; Figure 6 It is a single factor sensitivity analysis diagram involved in the system calibration and verification method of the discontinuous graded clay soil DEM model of the present invention; Figure 7 It is a step-by-step optimization analysis diagram of the microscopic parameters involved in the system calibration and verification method of the discontinuous graded clay DEM model of the present invention; Figure 8 It is an impact penetration indoor test and simulation diagram involved in the system calibration and verification method of the discontinuous graded clay DEM model of the present invention; Fig. 9 1. A comparison diagram of the test and simulation results involved in the system calibration and verification method of the discontinuous graded clay DEM model of the present invention ((a) in dry state and (b) at 20% moisture content). DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] The present invention is further explained below in conjunction with specific implementation modes.

[0022] like Figure 1 As shown, the present embodiment provides a method for calibrating and verifying the DEM model of discontinuously graded clay soil. The method takes the calibration of the microscopic parameters of discontinuously graded silty clay soil as an example. The soil sample was taken from Yangbajing, Tibet, with a depth of 0-60 cm. The basic physical parameters and particle gradation of the soil sample are shown in Tables 1 and Figure 2 As shown; Table 1: Basic physical properties of silty clay

[0023] The Hertz-Mindlin model with JKR is used as the contact model of soil. The Hertz-Mindlin with JKR contact model not only considers the elastic deformation between particles, but also considers the influence of the adhesion between particles on the movement law of particles. It is suitable for simulating the particle adhesion and agglomeration caused by factors such as electrostatic force and moisture, and is widely used in the simulation of materials such as powder, crops, and soil. The mesoscopic parameters that need to be calibrated in the JKR contact model mainly include the rolling friction coefficient (CRF) between particles and between particles and geometric bodies, the static friction coefficient (CSF), the restitution coefficient (COR), and the surface energy (JKR). The purpose of the calibration test is mainly to determine the mesoscopic parameters that can characterize the properties of the soil itself. Therefore, the present invention mainly takes the CRF, CSF, COR, and JKR parameters between particles as the main analysis objects.

[0024] The system calibration and verification method of the discontinuous graded clay soil DEM model of the present invention specifically comprises the following steps: Preliminary determination of microscopic parameter values ​​of S100 and DEM models Based on existing literature and angle of repose tests (e.g. Figure 3 The initial reference value range of the DEM model microscopic contact parameters (including shear modulus, restitution coefficient COR, static friction coefficient CSF, rolling friction coefficient CRF and free surface energy JKR) is determined by the discrete element particle model database built into the EDEM software (shear modulus: 2e +7 ~3e +7 ; COR: 0.60~0.90; CRF: 0.3~0.6; CSF: 1.00~1.40; JKR: 2.5~6.5) as a reference for constructing the discrete element model.

[0025] S200, sensitivity analysis of each microscopic parameter In the contact model, different meso parameters have different degrees of influence on the macroscopic mechanical behavior. In order to avoid blindness in the calibration process and improve the calibration efficiency, it is first necessary to adjust each parameter and conduct a single factor sensitivity analysis. According to the reference, the meso shear modulus has the greatest influence on the macroscopic mechanical behavior. Therefore, based on the initial meso parameter value range determined in step S100, the meso shear modulus is initially set to 2.5e+7. Direct shear test and triaxial test are commonly used methods for measuring soil mechanical properties. In order to calibrate the parameters of the DEM model, it is necessary to perform direct shear or triaxial virtual calibration experiments on the model samples. The present invention is illustrated by taking a direct shear test as an example. Figure 4 shown.

[0026] Taking shear strength σ and elastic modulus E as evaluation indicators, the unit increments of σ and E are compared and analyzed by calculating different values ​​of the microscopic contact parameters of the DEM model, such as Figure 5 As shown; then, the average value of the unit increment under different values ​​is obtained as the basis for judging the sensitivity. The calculation formulas are as follows (1) and (2): ; ; In the above formula, x and y are the values ​​of each microscopic parameter. Through comprehensive analysis of formulas (1)-(2), the sensitivity of the microscopic contact parameters of each DEM model can be obtained. like Figure 6 As shown in the figure, the results of single factor analysis show that CRF has the greatest impact on shear strength σ, with a unit increment of 197.31, while COR has the most significant impact on elastic modulus E, with a unit increment of 56.55, and JKR has the smallest impact on both evaluation indicators. Comprehensive analysis shows that the single factor sensitivity is CRF> COR> CSF> JKR.

[0027] S300, each factor is gradually optimized and iterated to obtain the parameter optimization value range According to the sensitivity analysis results of step S200, the values ​​of each mesoscopic parameter are adjusted in sequence (shearmodulus>CRF>COR>CSF>JKR); based on the stress-strain curve comparison results of the direct shear simulation test and the direct shear indoor test, a multi-factor stepwise optimization analysis is carried out to further narrow the value range of each DEM model mesoscopic contact parameter and optimize the value range of each DEM model mesoscopic contact parameter; Figure 7 As shown; the optimization analysis results are as follows: the elastic modulus is 3.5e+07Pa, CRF is 0.4~0.6, COR is 0.70~0.85, CSF is 1.0~1.5, and JKR is 3.0~6.5.

[0028] S400, further optimize the parameters based on Box-Behnken experimental design to obtain multiple groups of optimized parameter combinations; S410, Orthogonal Rotation Experimental Design and Regression Model According to the optimization range of discrete element model parameters obtained in step S300, a calibration test is designed based on the Box-Behnken method to reduce the workload of parameter calibration and avoid blindness in parameter adjustment during the calibration process; the rolling friction coefficient CRF, restitution coefficient COR, static friction coefficient CSF and free surface energy JKR in the DEM model micro-contact parameters are used as test factors, and the elastic modulus and shear strength are used as optimization targets. The designed test factors and level data are shown in Table 2.

[0029] Table 2. Simulation test factors and levels

[0030] Based on Design-Expert software, an orthogonal rotation test was designed (the core is to balance the test efficiency and model accuracy; the specific steps are: select "Central Composite Design" in Design-Expert; check the "Rotatable" or "Orthogonal" option (according to needs); enter the factor range, generate the test matrix and execute the test; establish a quadratic regression model and optimize the parameters.) to conduct multi-factor simulation analysis. This experiment involves 4 factors and 3 levels, and a total of 29 test points are designed for response surface analysis. The test points are divided into two categories: one is the factorial point, a total of 24; the other is the center point of the zero point area. The experiment was repeated 5 times to estimate the test error. The experimental factor combination and corresponding results are shown in Table 3.

[0031] Table 3. Experimental factor combinations and corresponding results

[0032] The test data in Table 3 were subjected to multivariate regression fitting analysis, and the polynomial regression model of the direct shear calibration test was obtained as follows: ; The coefficient of determination R of the regression equation 2 =0.9922, corrected determination coefficient adj-R 2 The value is 0.963, indicating that the model has excellent fitting effect and can replace the real test data for analysis. The results of variance analysis (see Table 4) show that the F value of the model is >1, and P=0.0001<0.05, indicating that the model difference is significant and the model design is reasonable. The direct shear calibration test can be predicted based on the model.

[0033] Table 4. Y E ANOVA for Polynomial Regression Models

[0034]

[0035] S420: Parameter optimization and determination of optimized parameter combination Based on the polynomial regression model in step S410 above, the optimization function in the Design-expert software is used to optimize the micro-contact parameters of the DEM model. The optimization criteria are set according to the result range of the elastic modulus and shear strength in Table 3. The obtained optimization solution is not unique, but a combination of multiple parameters, as shown in Table 5. The result can be used as a basis for calibration and verification of model parameters under dynamic load conditions.

[0036] Table 5. Different combinations of optimal parameters

[0037] S500, calibration results and verification In order to verify the accuracy and applicability of the system calibration method of the present invention, the impact penetration simulation test is used as a verification method according to the optimal parameter combination determined in step S400. Based on the impact penetration test, a discontinuous graded clay impact penetration DEM model is first constructed, such as Figure 8 shown.

[0038] The time history curve of the resistance of the cone tip of the impact penetration probe in the impact penetration test (i.e., the cone tip resistance time history curve) is quantitatively analyzed and compared with the results of the impact penetration indoor test. Fig. 9 As shown in the figure, with shear strength as the control index, the relative error is less than 5%, which verifies the effectiveness of the calibration method of the system and also shows that the method has good practicality in the dynamic load simulation of soil-tool interaction. In the impact penetration test here, the setting of the contact relationship between the particles and the geometric body can be initially consistent with the parameters between the particles. After determining the parameter combination closest to the test results, a small range adjustment is made to achieve the purpose of fine-tuning to make the calibration parameters more accurate.

[0039] According to the parameter calibration process of steps S100 to S400 and the parameter verification process of step S500, the microscopic contact parameters of the discontinuously graded silty clay under impact load are determined, as shown in Table 6.

[0040] Table 6: Microscopic contact parameters of silty clay particles at different moisture contents

[0041] The present invention can provide a more efficient and directional parameter calibration method for clay soils with relatively complex parameter calibration and few references, especially fine-grained soils or granular materials with extremely uneven particle grading, and can realize the calibration of microscopic parameters under quasi-static stress and parameter calibration and verification under dynamic load stress simulation.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A systematic calibration and verification method for DEM model of discontinuous graded clay soil, characterized by , including the following steps: Step 1: Preliminary determination of the values ​​of the mesoscopic parameters of the DEM model; Step 2: Sensitivity analysis of each DEM model’s microscopic parameters; Step 3: Combined with the results of sensitivity analysis, each factor is gradually optimized and iteratively analyzed to obtain the optimal value range of the mesoscopic parameters of the DEM model; Step 4: Further optimize the mesoscopic parameters of the DEM model based on the Box-Behnken experimental design to obtain multiple sets of optimized parameter combinations; Step 5: Parameter verification.

2. The method for system calibration and verification of the discontinuous graded clay DEM model according to claim 1, characterized in that: The specific process of step 1 is: based on existing literature and repose angle tests, and through the discrete element particle model database built into the EDEM software, the initial reference value range of the DEM model micro-contact parameters is determined as a reference for constructing the discrete element model.

3. The method for system calibration and verification of the discontinuous graded clay soil DEM model as claimed in claim 2, characterized in that: The microscopic contact parameters of the DEM model in step 1 include shear modulus, restitution coefficient COR, static friction coefficient CSF, rolling friction coefficient CRF and free surface energy JKR; the initial reference value range of the shear modulus is 2e +7 ~3e +7 The initial reference value range of the coefficient of restitution COR is 0.60~0.90, the initial reference value range of the coefficient of rolling friction CRF is 0.3~0.6, the initial reference value range of the coefficient of static friction CSF is 1.00~1.40, and the initial reference value range of the free surface energy JKR is 2.5~6.

5.

4. The method for system calibration and verification of the discontinuous graded clay soil DEM model as claimed in claim 2, characterized in that: The specific process of step 2 is as follows: taking shear strength σ and elastic modulus E as evaluation indicators, calculating different values ​​of the microscopic contact parameters of the DEM model, and comparing and analyzing the unit increments of σ and E; then, obtaining the average value of the unit increment under different values ​​as the basis for judging the sensitivity, and the calculation formulas are as follows (1) and (2): ； ； In the above formulas (1)-(2), x and y are the values ​​of the microscopic contact parameters of each DEM model; Through comprehensive analysis of the above formulas (1) and (2), the sensitivity of the micro-contact parameters of each DEM model can be obtained.

5. The method for system calibration and verification of the discontinuous graded clay DEM model according to claim 1, characterized in that: The specific process of the stepwise optimization and iterative analysis of each factor in step 3 is as follows: according to the sensitivity analysis results of step 2, the values ​​of the mesoscopic contact parameters of the DEM model are adjusted in sequence; based on the stress-strain curve comparison results of the direct shear simulation test and the direct shear indoor test, the value range of the mesoscopic contact parameters of each DEM model is further narrowed and the value range of the mesoscopic contact parameters of each DEM model is optimized.

6. The method for system calibration and verification of the discontinuous graded clay soil DEM model as claimed in claim 5, characterized in that: The parameter optimization ranges obtained in step 3 are: elastic modulus is 3.5e+07 Pa, rolling friction coefficient CRF is 0.4-0.6, restitution coefficient COR is 0.70-0.85, static friction coefficient CSF is 1.0-1.5, and free surface energy JKR is 3.0-6.

5.

7. The method for system calibration and verification of a discontinuously graded clay soil DEM model as claimed in claim 1, characterized in that: The step 4 specifically comprises the following steps: Step 4.1: Orthogonal rotation experimental design and regression model According to the optimization range of discrete element model parameters obtained in step 3, a calibration test is designed based on the Box-Behnken method: that is, the rolling friction coefficient CRF, the restitution coefficient COR, the static friction coefficient CSF and the free surface energy JKR in the DEM model micro-contact parameters are used as test factors, the elastic modulus and the shear strength are used as optimization targets, and the test factors and level data are designed; Based on the orthogonal rotation test designed by Design-Expert software, a multivariate regression fitting analysis was performed on the test factor combination and the corresponding result data, and the polynomial regression model of the direct shear calibration test was obtained as follows: ； Step 4.2: Parameter optimization and determination of optimal parameter combinations Based on the polynomial regression model in step 4.1 above, the optimization function in the Design-expert software is used to optimize the micro-contact parameters of the DEM model; the optimization criterion is set according to the result range of the elastic modulus and shear strength; the obtained optimization solution is not unique, but a combination of multiple parameters. The result can be used as the basis for calibration and verification of model parameters under dynamic load conditions.

8. The method for system calibration and verification of a discontinuously graded clay soil DEM model as claimed in claim 1, characterized in that: The step 5 specifically comprises the following steps: Step 5.1: Based on the optimized parameter combination obtained in step 4, the impact penetration simulation test is used as a verification method. Based on the impact penetration test, a discontinuous graded clay impact penetration DEM model is first constructed; Step 5.2: Quantitatively analyze the time history curve of the resistance of the cone tip of the impact penetration probe in the impact penetration test, and compare it with the indoor test results of the impact penetration test to obtain the test and simulation results under different working conditions. Taking the shear strength as the control index, when the relative error is less than 5%, the calibration of the discontinuous graded silty clay is realized, and the calibration and verification of the parameters under dynamic load simulation are realized from the calibration of the mesoscopic parameters under quasi-static stress; when the relative error is not less than 5%, return to the step 4 to further optimize the mesoscopic parameters of the DEM model.

9. The method for system calibration and verification of a discontinuously graded clay soil DEM model as claimed in claim 8, characterized in that: In the impact penetration test, the setting of the contact relationship between soil particles and the impact penetration probe geometry can be initially kept consistent with the parameters between particles. After the parameter combination closest to the test results is determined, small-range adjustments are made, and fine adjustments are made in turn to make the calibration parameters more accurate.

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