A method for realizing cement pavement slab bottom void simulation based on a finite element model

Abstract

This invention relates to a method for simulating the void at the bottom of a cement pavement slab based on a finite element model. The method includes the following steps: establishing a structural layer model of the cement pavement to form at least two surface layer models and a base layer model; establishing a z-direction spring K1 between the surface layer models and x, y, and z-direction springs K1 between the surface layer models and the base layer models. x K y K z Based on simulation data, construct the relationship between joint deflection load transfer coefficient and K1 spring stiffness, and between base layer modulus and K... z Spring stiffness, coefficient of friction and K x K y Three relational models of spring stiffness are proposed. An ABAQUS GUI plugin tool developed using Python enables parametric modeling. Modifications to the spring stiffness at the nodes in the vacancy region of the INP file simulate vacancy under different shapes, sizes, and support conditions. These three relational models improve the accuracy and computational efficiency of the slab bottom vacancy simulation model, allowing for the study of the mechanical response of the track panel under different vacancy states.

Description

Technical Field

[0001] This invention relates to a method for simulating the void at the bottom of a cement pavement panel based on a finite element model. Background Technology

[0002] Cement concrete pavement is a typical multi-layered shell structure. Due to its long service life, high strength, and relatively mature design and construction methods, it is widely used in the construction of airport runways in large and medium-sized cities in my country.

[0003] The typical service life of cement concrete pavement is 30 years. However, during service, erosion, settlement, and other factors can cause localized material loss between the bottom layers of rigid pavement panels, creating voids. Due to the combined effects of environmental factors and repeated loads, these voids gradually develop into slab breakage. The presence of these breakages alters the pavement's support structure and reduces the mechanical properties of the slabs at the breakage points. Under repeated aircraft loads, the pavement is highly susceptible to severe pavement damage, such as slab breakage and panel fracture, which seriously affects the safety of aircraft operations.

[0004] Voids are located beneath the pavement panel and cannot be directly observed from the surface, making it easy to miss the optimal curing period. Therefore, there is an increasing amount of research using finite element numerical simulation methods to study the stress-strain evolution of voided pavement panels. The bottom support of rigid pavement panels mainly manifests as the base layer's support to the pavement panel. Holding power Functions. Currently, in numerical modeling, methods such as reducing the foundation resilient modulus, directly constructing voids, and removing interlayer contacts are often used to express the void morphology. However, the foundation modulus reduction method is mainly applicable to single-layer plate models on elastic foundations, and it is insufficient in describing the support state of the surface layer and the base layer; directly constructing voids requires high local finite element meshes, which can easily lead to non-convergence; removing interlayer contacts requires the introduction of the Coulomb friction model, which significantly increases the computational cost and is not accurate enough for simulating actual voids.

[0005] To address the shortcomings of current research, it is necessary to establish a pavement model that accurately simulates the voiding condition based on inter-slab joint springs and inter-layer contact springs. This would improve the efficiency of numerical simulation while ensuring accuracy, and further explore the mechanical response laws of pavement panels under different load types, joint load transfer capacity, and voiding conditions. This would lay the foundation for evaluating the evolution of pavement panel voiding dimensions and positional status. Summary of the Invention

[0006] The purpose of this invention is to provide a method for simulating the void at the bottom of a cement pavement slab based on a finite element model, based on the relationship between surface layer models. Springs and the relationship between the surface model and the base model A simulation model of the void at the bottom of a cement concrete pavement slab was established using springs, and the joint deflection load transfer coefficient was constructed. Spring stiffness, base modulus and Spring stiffness and coefficient of friction Three relationship models between spring stiffness are used to accurately characterize the shear force transmission between surface layer models and the contact between surface layer models and base layer models, which improves the accuracy and computational efficiency of numerical simulation models, so as to study the mechanical response of the bottom of the plate under different void states.

[0007] To achieve this objective, the present invention adopts the following technical solution:

[0008] A method for simulating the void at the bottom of a cement pavement slab based on a finite element model includes the following steps:

[0009] Step 1: Obtain the structural and material parameters of the cement pavement;

[0010] Step 2: Establish an XYZ coordinate system and create a cement pavement structure layer model to form at least two surface layer models and a base layer model. Simulate the material parameters of the actual cement pavement in Step 1 and assign material properties to the surface layer model and the base layer model.

[0011] Step 3: Create a flexible foundation at the bottom of the base model to simulate the Winkler foundation;

[0012] Step 4: Run a Python script to capture all mesh node pairs between surface models one by one, and batch-create z-direction springs between surface models. To simulate the load transfer effect at the joints between surface layer models; a Python script is run to capture all mesh node pairs between the surface layer model and the base layer model one by one, and to batch create springs in the x, y, and z directions between the surface layer model and the base layer model. To simulate the normal and tangential contact between the surface layer model and the base layer model;

[0013] Step 5: Apply HWD load to the middle of the edge of the intermediate surface layer model and extract the sensor deflection value of HWD at the edge of the loaded plate. And the sensor deflection value at the edge of the unloaded plate. Calculate different Joint deflection load transfer coefficient under spring stiffness ;

[0014] Step six, based on the results obtained in step five, under different HWD loads... The joint deflection load transfer coefficient value corresponding to the spring stiffness is used to construct... Joint deflection load transfer coefficient and The relationship model between spring stiffness and spring stiffness is expressed as follows:

[0015]

[0016] In the formula, This is the joint deflection load transfer coefficient; For spring stiffness; Factors to eliminate the influence of pavement structural parameters; These are model parameters;

[0017] Step 7: Apply HWD load to the middle of the edge of the intermediate surface layer model, calculate and extract different loads. The maximum tensile stress and surface deflection along the plate edge path under spring stiffness; the maximum tensile stress and surface deflection along the plate edge path under different base moduli and different friction coefficients when the surface layer model and the base layer model are set as a Coulomb friction model.

[0018] Step 8, Establish The relationship model between spring stiffness and base modulus:

[0019]

[0020] In the formula, For spring stiffness; For the basic modulus; These are model parameters; This represents the number of grid nodes per unit area.

[0021] Step 9, Establish Model of the relationship between spring stiffness and coefficient of friction:

[0022]

[0023] In the formula, For spring stiffness; The coefficient of friction; This represents the number of grid nodes per unit area. These are the model parameters.

[0024] Step 10: Modify the Python code and define functions based on the abaqus.jnl file generated in Steps 1, 2, and 3; develop the ABAQUS GUI plugin tool; use the RSG dialog box builder to create dialog boxes; and achieve efficient parametric modeling and batch creation of springs.

[0025] Step 11: Use Windows batch commands to modify the grid node numbers corresponding to the empty regions in the INP file. Spring stiffness is used to simulate the actual voiding conditions of different shapes, sizes, and support states, and to calculate the stress-strain response of the voiding channel panel under load.

[0026] 2. Preferably, in step one, the structural and material parameters of the cement pavement are obtained by referring to the cement pavement design data and the results of on-site core drilling.

[0027] 3. Preferably, in step one, the number of surface models is 9, arranged in a 3×3 array.

[0028] 4. Preferably, the HWD load application method in step five is the same as that in step seven.

[0029] 5. Preferably, in step six, according to the formula

[0030]

[0031]

[0032] get Value, where, The elastic modulus of the concrete surface layer; The thickness of the concrete surface layer; Poisson's ratio for the concrete surface layer; It is the foundation reaction modulus; The number of grid nodes per unit joint length.

[0033] 6. Preferably, in step six, the regression calculation model parameters are performed based on the large amount of simulation data extracted in step five. value.

[0034] 7. Preferably, in step six, the modeling parameters are determined based on the joint deflection load transfer coefficient calculated from the actual HWD test results. Spring stiffness.

[0035] 8. Preferably, in step seven, remove The spring model was set to a Coulomb friction model between the surface layer model and the base layer model to verify the accuracy of the spring model.

[0036] 9. Preferably, in steps eight and nine, the model parameters are calculated by regression based on the large amount of simulation data extracted in step seven. and value.

[0037] 10. Preferably, the model is parametrically processed and automatically modeled using ABAQUS software.

[0038] The beneficial effect of the method for simulating the void at the bottom of cement pavement slabs based on the finite element model of the present invention is that: based on the joint deflection load transfer coefficient and Spring stiffness, base modulus and Spring stiffness and coefficient of friction Three relationship models between spring stiffness can be used to improve the accuracy and efficiency of numerical simulation results. A simulation model of voids at the bottom of cement concrete pavement slabs, established based on the spring model, can be used to explore the mechanical response of pavement slabs under different load types, joint load transfer capacity, and void conditions. This allows for the study of the evolution of void conditions at the bottom of cement concrete pavement slabs and clarification of their fatigue damage process under repeated traffic loads. Attached Figure Description

[0039] Figure 1 This is a schematic diagram of a cement pavement model according to an embodiment of the present invention;

[0040] Figure 2 The spring in the z-direction between the surface models in this embodiment of the invention. Schematic diagram;

[0041] Figure 3 Springs in the x, y, and z directions between the surface layer model and the base layer model in an embodiment of the present invention. Schematic diagram;

[0042] Figure 4 This is a schematic diagram illustrating the application of HWD load in an embodiment of the present invention;

[0043] Figure 5 The joint deflection load transfer coefficient in this embodiment of the invention is related to... Regression curve of spring stiffness;

[0044] Figure 6a and Figure 6b This is an embodiment of the present invention. Comparison results between the spring model and the Coulomb friction model;

[0045] Figure 7 This is a schematic diagram of the dialog box interface and the input model parameters in an embodiment of the present invention;

[0046] Figure 8 This is a schematic diagram of the grid node numbering in the corner void area of ​​an embodiment of the present invention;

[0047] Figure 9 This is a cloud diagram showing the maximum tensile stress of the loaded surface plate in an embodiment of the present invention. Detailed Implementation

[0048] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0049] This embodiment discloses a method for simulating the underside void of a cement pavement slab based on a finite element model. This method for simulating the underside void of a cement pavement slab based on a finite element model includes the following steps:

[0050] Step 1: Obtain the structural and material parameters of the cement pavement. Specifically, referring to the cement pavement design data and the results of on-site core sampling, the structural and material parameters of the cement pavement are obtained, as shown in Table 1.

[0051] Table 1 Parameters of Cement Pedestrian Street Panel Structure

[0052]

[0053] Step 2: Use ABAQUS software to create models of each structural layer of the cement pavement. Specifically, establish an XYZ coordinate system, where XY represents the horizontal plane and Z represents the depth direction. Create components "concrete-1" to "concrete-9" to simulate nine surface layer models. Preferably, the nine surface layer models are arranged in a 3×3 array on the "XY" plane, with a preferred planar size of 5.0m×5.0m and a specified extrusion depth of 0.30m. Preferably, an 8mm joint distance is set between the surface layer models. Create component "base-1" to simulate the base layer, with a planar size of 15.016m×15.016m and a specified extrusion depth of 0.30m. Assign material properties to the nine surface layer models and the base layer model according to the material parameters in Step 1. Assemble the nine surface layer models and the base layer model to simulate the actual cement pavement panel. The overall model is as follows: Figure 1 As shown.

[0054] As a preferred option, in order to balance the calculation speed and accuracy of the model, the mesh size of the finite element division of the 9 surface layer models and the base layer model is preferably 10cm.

[0055] Step 3: Create a static general analysis step "Step-1", setting the time duration to 0.05, the initial increment step to 0.01, the maximum increment step to 0.03, and the minimum increment step to 1e-6. Select stress S, strain E, and displacement U for the field output. Next, create an elastic foundation at the bottom of the base model to simulate the Winkler foundation, with a foundation stiffness of 40,000,000 per unit area. Set boundary conditions to constrain the vertical displacement of the model on the sides of the surface and base models. Apply a uniformly distributed load to the top surface of the surface model and select user-defined. Finally, set the global mesh size to 0.1m and the mesh element type to a reduced integral element of C3D8R.

[0056] Step 4: Use Python to batch set z-direction springs at all mesh nodes between surface models. To simulate the load transfer effect at the joints between the surface layers of a cement pavement slab, a spring in the z-direction... Schematic diagram as follows Figure 2 As shown; springs in the x, y, and z directions are set in batches at all mesh nodes between the surface model and the base model. To simulate the normal and tangential contact between the surface layer and the base layer of a cement pavement, springs in the x, y, and z directions are used between the surface layer model and the base layer model. Schematic diagram as follows Figure 3 As shown. Based on a large amount of simulation data regression, the joint deflection load transfer coefficient and... A model relating spring stiffness; constructing a model of the relationship between base modulus and spring stiffness. A model relating spring stiffness; constructing a model of the relationship between friction coefficient and... A model relating spring stiffness; accurately characterizing the contact between cement concrete surface layers and between surface layers and base layers.

[0057] Specifically, a Python script is run to capture mesh node pairs where the distance between surface models is less than 0.01m, and then two-point springs in the z-direction are created in batches for these mesh node pairs. The axis is selected in a fixed direction, and the degrees of freedom of both points are selected as 3 (in the z direction). The spring stiffness is selected sequentially as 0.001, 0.005, 0.01, 0.03, 0.05, 0.06, 0.08, 0.1, 0.2, 0.3, 0.4, 0.5, 0.7, 1, 2, 3, 4, 5, 6, 8, 10, 30, 50, 100MN / m.

[0058] Step 5, apply HWD load to the center of the plate edge of the intermediate surface layer model, such as... Figure 4 As shown, the load is 140kN, the diameter of the bearing plate is 30cm, and the equivalent pressure is 1.98MPa; the sensor deflection value of HWD at the edge of the loaded plate is extracted in the model. And the sensor deflection value at the edge of the unloaded plate. Calculate the joint deflection load transfer coefficient under different spring stiffnesses. As shown in Table 2.

[0059] Table 2 Different Spring Stiffnesses Lower joint deflection load transfer coefficient value

[0060]

[0061] Step 6, based on the different spring stiffnesses obtained in Step 5 under HWD load The corresponding joint deflection load transfer coefficient value is used to construct... Joint deflection load transfer coefficient and A model relating spring stiffness. Regression model parameters based on simulation data. It is used to accurately characterize the shear force transfer between loaded and unloaded slabs of cement pavement under different conditions. The regression curve is as follows: Figure 5 As shown, its R 2 It is 0.99.

[0062] For the Winkler foundation model, relative stiffness radius It is related to the elastic modulus of the surface layer, the thickness of the surface layer, Poisson's ratio, and the soil reaction modulus, and the expression is as follows:

[0063]

[0064] In the formula, The elastic modulus of the concrete surface layer is expressed in MPa. The thickness of the concrete surface layer is in meters (m). Poisson's ratio for the concrete surface layer; The ground reaction modulus is MN / m. 3 .

[0065] Specifically, in the formula, The elastic modulus of the concrete surface layer is 36,000 MPa. The thickness of the concrete surface layer is 0.3m. The Poisson's ratio for the concrete surface layer is 0.15. The ground reaction modulus is 40 MN / m. 3 ; The relative stiffness radius is 1.20m; .

[0066]

[0067]

[0068] In the formula, The number of grid nodes per unit joint length is 40.8 / m; Factors that eliminate the influence of pavement structural parameters are related to the number of grid nodes per unit area, the foundation reaction modulus, and the relative stiffness radius; Let MN be the spring stiffness, in meters (m). This is the joint deflection load transfer coefficient; Here are the model parameters, where , , .

[0069] This embodiment It can be obtained from HWD simulation experiments or field tests, and the expression is as follows:

[0070]

[0071] In the formula, This represents the sensor deflection value of a falling weight deflectometer at the edge of the loaded plate. ; This represents the sensor deflection value of a falling weight deflectometer at the edge of an unloaded plate. .

[0072] Step 7, as a preferred embodiment, in this example, the joint deflection load transfer coefficient calculated based on the actual HWD test results is used to determine the modeling parameters. For spring stiffness, this example selects the joint deflection load transfer coefficient. The joint spring stiffness at 72% It is 2.0MN.

[0073] Step 8: Run a Python script to capture mesh node pairs where the distance between the surface model and the base model is 0, and then create two-point springs in the x, y, and z directions for these mesh node pairs in batches. The axis is selected in a fixed direction, and the degrees of freedom of the two points are selected as 1 (x-direction), 2 (y-direction), and 3 (z-direction), respectively, where the spring stiffness in the z-direction is... Select values ​​of 10, 20, 30, 40, 50, 60, 70, 80, 90, and 100 MN / m in sequence.

[0074] Step 9: Apply an HWD load to the center of the edge of the intermediate surface layer model, using the same loading method as in Step 5. Specifically, the load is 140 kN, the bearing plate diameter is 30 cm, and the equivalent pressure is 1.98 MPa. Calculate and extract different... The maximum bending tensile stress along the edge path of the plate under spring stiffness is shown in Table 3.

[0075] Table 3 Different Spring Stiffnesses Maximum bending tensile stress results along the lower edge of the plate

[0076]

[0077] Step 10: Remove the springs in the x, y, and z directions between the surface model and the base model. The surface model and the base model were set as a Coulomb friction model to verify the accuracy of the spring model. The maximum flexural tensile stress and surface deflection under HWD load were calculated for both methods. The calculation results are shown in Figure 6. It can be seen that the distribution patterns of the maximum flexural tensile stress and deflection obtained by the two methods are almost the same, and the numerical difference is within 1%.

[0078] These two methods differ significantly in computational efficiency. For the same pavement model, the calculation time using the Coulomb friction model is approximately 10 to 20 times that using the spring model. Furthermore, the Coulomb friction model has high requirements for mesh generation and is prone to non-convergence when simulating complex and irregular void support states. In contrast, this embodiment uses the spring model, which can simulate the bottom support effect of the slab by changing the stiffness of spring elements at different locations, thus constructing void regions of varying degrees and ranges.

[0079] This embodiment ensures the connection between the surface layer model and the base layer model. The spring serves to simulate tangential and normal contact. Unlike the "hard contact" between the surface layer and the base layer in the Coulomb friction model, where the surface layer and the base layer have a certain coefficient of friction, a certain gap needs to be set between the surface layer and the base layer during model assembly. The preferred gap distance is 0.1m.

[0080] Step 11: Calculate the regression model parameters based on the large amount of simulation data extracted in steps 8-10. Value, Establish A linear regression model for spring stiffness decreasing with the modulus of the base layer is used to accurately characterize the normal contact between the cement concrete surface layer and the base layer. The regression expression is as follows:

[0081]

[0082] In the formula, Let MN be the spring stiffness, in meters (m). The base modulus is 1000 MPa; The model parameters are derived from regression analysis of numerous simulation results. ; The number of grid nodes per unit area, 101 / m 2 .

[0083] Step 12: Based on a large amount of simulation data, regression calculations are performed to establish... A regression model for spring stiffness as a function of the friction coefficient between the surface layer and the base layer is used to accurately characterize the tangential contact between the cement concrete surface layer and the base layer. The regression expression is as follows:

[0084]

[0085] In the formula, Let MN be the spring stiffness, in meters (m). The coefficient of friction; The number of grid nodes per unit area, 101 / m 2 ; The model parameters are derived from regression analysis of numerous simulation results. .

[0086] Step 13: The abaqus.jnl file is the ABAQUS log file, containing ABAQUS / CAE commands used to copy the stored model database. Rename the abaqus.jnl file generated in the previous step to a .py file, define the function main, and set the corresponding model dimensions, materials, spring stiffness, and other parameters. Replace the previously defined model parameters with the specific values ​​of model dimensions, materials, spring stiffness, etc., to perform parameterization of the model.

[0087] Specifically, the function contains 10 parameters: H1 (surface layer model thickness), H2 (base layer model thickness), E1 (surface layer modulus), E2 (base layer modulus), K (foundation reaction modulus), Size (finite element mesh size), cjspringsx ( Spring stiffness coefficient), cjspringsy Spring stiffness coefficient), cjspringsz ( Spring stiffness coefficient), jfsprings ( (Spring stiffness coefficient). Replace the specific values ​​for dimensions, materials, spring stiffness, etc. in the previous .py file with the parameters defined above to achieve parameterization of the model.

[0088] Step 14: The ABAQUS GUI plug-in tool can be implemented using the RSG dialog builder built into the ABAQUS software. Specifically, after starting ABAQUS / CAE, click

Plug-ins menu

Abaqus

RSG DialogBuilder…

Module:

Function:

Plug-in menu

[0089] Step 15: After completing the automated modeling, create and submit the job. This will automatically generate the Abaqus input file (INP). Assuming there is a 1.0m side-length triangular void at the corner of the pavement panel, query the mesh node number of this void in the Abaqus / CAE interface. Figure 8 As shown. Using Windows batch commands, modify the x, y, and z direction springs corresponding to the mesh node numbers within the empty region of the INP file. The stiffness coefficient is used to simulate the reduction of local base modulus and friction coefficient caused by the void at the bottom of the slab. In this example, the base modulus and friction coefficient at the void are reduced to 0. A triangular void with a side length of 1.0m × 1.0m is set at the corner of the void at the bottom of the slab for simulation.

[0090] Step 16: Apply the J-10 aircraft load to the surface plate using the Abaqus user subroutine Dload. The load location is at the corner of the takeoff plate. The load parameters are shown in Table 4. Finally, calculate the stress response of the takeoff plate panel under load at the corner of the J-10 plate. The maximum tensile stress contour diagram of the loaded surface plate is shown in Table 4. Figure 9 As shown.

[0091] Table 4. Load parameters of J-10 aircraft

[0092]

[0093] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the implementation of the present invention. Those skilled in the art will be able to make various obvious changes, readjustments, and substitutions without departing from the scope of protection of the present invention. It is neither necessary nor possible to exhaustively describe all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for simulating the void at the bottom of a cement pavement slab based on a finite element model, characterized in that, Including the following steps: Step 1: Obtain the structural and material parameters of the cement pavement; Step 2: Establish an XYZ coordinate system and create a cement pavement structure layer model to form at least two surface layer models and a base layer model. Simulate the material parameters of the actual cement pavement in Step 1 and assign material properties to the surface layer model and the base layer model. Step 3: Create a flexible foundation at the bottom of the base model to simulate the Winkler foundation; Step 4: Run a Python script to capture all mesh node pairs between surface models one by one, and batch-create z-direction springs between surface models. To simulate the load transfer effect at the joints between surface layer models; a Python script is run to capture all mesh node pairs between the surface layer model and the base layer model one by one, and to batch create springs in the x, y, and z directions between the surface layer model and the base layer model. To simulate the normal and tangential contact between the surface layer model and the base layer model; Step 5: Apply HWD load to the middle of the edge of the intermediate surface layer model and extract the sensor deflection value of HWD at the edge of the loaded plate. And the sensor deflection value at the edge of the unloaded plate. Calculate different Joint deflection load transfer coefficient under spring stiffness ; Step six, based on the results obtained in step five, under different HWD loads... The joint deflection load transfer coefficient value corresponding to the spring stiffness is used to construct... Joint deflection load transfer coefficient and The relationship model between spring stiffness and spring stiffness is expressed as follows: In the formula, This is the joint deflection load transfer coefficient; For spring stiffness; Factors to eliminate the influence of pavement structural parameters; These are model parameters; Step 7: Apply HWD load to the middle of the edge of the intermediate surface layer model, calculate and extract different loads. Maximum bending tensile stress and surface deflection along the plate edge path under spring stiffness; Calculate and extract the maximum tensile stress along the plate edge path and the surface deflection when the surface model and the base model are set to a Coulomb friction model with different base moduli and different friction coefficients; Step 8, Establish The relationship model between spring stiffness and base modulus: In the formula, For spring stiffness; For the basic modulus; These are model parameters; This represents the number of grid nodes per unit area. Step 9, Establish Model of the relationship between spring stiffness and coefficient of friction: In the formula, For spring stiffness; The coefficient of friction; This represents the number of grid nodes per unit area. These are model parameters; Step 10: Modify the Python code and define functions based on the abaqus.jnl file generated in Steps 1, 2, and 3; develop the ABAQUS GUI plugin tool; use the RSG dialog box builder to create dialog boxes; and achieve efficient parametric modeling and batch creation of springs. Step 11: Use Windows batch commands to modify the grid node numbers corresponding to the empty regions in the INP file. Spring stiffness is used to simulate the actual voiding conditions of different shapes, sizes, and support states, and to calculate the stress-strain response of the voiding channel panel under load.

2. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step one, the structural and material parameters of the cement pavement are obtained by referring to the cement pavement design data and the results of on-site core drilling.

3. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step one, there are 9 surface models, arranged in a 3×3 array.

4. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: The HWD load is applied in the same way as in step five and step seven.

5. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step six, according to the formula get Value, where, The elastic modulus of the concrete surface layer; The thickness of the concrete surface layer; Poisson's ratio for the concrete surface layer; It is the foundation reaction modulus; The number of grid nodes per unit joint length.

6. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step six, the model parameters are calculated by regression based on the large amount of simulation data extracted in step five. value.

7. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step six, the joint deflection load transfer coefficient calculated based on the actual HWD test results is used to determine the modeling parameters. Spring stiffness.

8. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In step seven, remove The spring model was set to a Coulomb friction model between the surface layer model and the base layer model to verify the accuracy of the spring model.

9. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: In steps eight and nine, the model parameters are calculated by regression based on the large amount of simulation data extracted in step seven. and value.

10. The method for simulating the void at the bottom of a cement pavement slab based on a finite element model according to claim 1, characterized in that: The model is parametrically processed and automated using ABAQUS software.

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