A method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis

Abstract

The present invention provides a method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis, comprising: using Abaqus software to establish a three-dimensional finite element model of the asphalt pavement, simulating the dynamic response of the pavement structure under the action of moving load and temperature, and obtaining the maximum tensile strain value at the bottom of each layer of the asphalt surface layer; combining the temperature correction coefficient, the humidity correction coefficient and the thickness correction coefficient to correct the model to improve the prediction accuracy; using the extended finite element method to simulate the expansion process of reflected cracks under the action of load, and calculating the composite stress intensity factor and its influence on crack expansion; referring to the Paris formula, introducing the equivalent crack damage rate, and constructing a life prediction model that considers the damage of crack expansion to the pavement structure; comprehensively considering the influence of temperature, humidity, load, the overall strain accumulation of the asphalt layer, the thickness of the pavement structure layer and reflective cracks, and establishing an asphalt pavement life prediction model based on finite elements for accurately predicting the service life of the asphalt pavement.

Description

Technical Field

[0001] The present invention belongs to the field of road engineering, and in particular relates to a method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis. Background Art

[0002] With the development of road construction and the rapid growth of traffic in my country, the frequent passage of heavy and overloaded vehicles has led to the emergence of asphalt pavement defects such as rutting, cracking, and interlayer slippage. In particular, under extreme conditions such as high temperatures and heavy loads, asphalt pavements are prone to fatigue cracking. Therefore, accurately predicting the service life of asphalt pavements has become particularly important for road maintenance, upkeep, and replacement.

[0003] Traditional asphalt pavement life prediction methods are primarily based on empirical formulas and field test data. These methods often lack detailed mechanical analysis and fail to fully account for the nonlinear properties of the material, complex traffic loads, and environmental influences. The collection of field test data is often limited by high variability, high cost, and difficulty in obtaining it, resulting in limited reliability of the prediction results. In recent years, finite element analysis (FEA) and extended finite element analysis (XFEA) have been gradually applied to pavement design and performance analysis. These methods can accurately predict the mechanical behavior of pavements under complex loads and environmental conditions through numerical simulation. This method can more accurately assess the dynamic response of pavement structures and provide more valuable mechanical indicators for life prediction. Summary of the Invention

[0004] Technical Problem Solved: This invention provides a method for establishing an asphalt pavement life prediction model based on coupled environmental and load analysis. This method comprehensively considers the effects of traffic load, temperature, humidity, and pavement structural layer thickness, improving the accuracy and reliability of asphalt pavement life prediction. By combining finite element analysis (FEA) and extended finite element analysis (XFEA) with fracture mechanics theory, this method addresses complex environmental factors that are not fully considered in traditional methods, proposes new correction coefficients and crack propagation models, and thus overcomes the limitations of existing technologies.

[0005] Technical solution: A method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis, including the following steps:

[0006] Step S1, constructing a three-dimensional finite element model: A three-dimensional finite element model is constructed using Abaqus software to simulate the multi-physics coupling of moving loads, temperature, humidity, and pavement structure layers, and obtain the mechanical response parameters of the asphalt pavement structure layers, including the maximum layer bottom tensile strain value, stress distribution, and displacement field;

[0007] Step S2: Calculate the temperature correction coefficient, humidity correction coefficient, and thickness correction coefficient based on the mechanical response parameters obtained in step S1, taking into account the effects of temperature, humidity, and pavement structure layer thickness, and correct the three-dimensional finite element model constructed in step S1 to improve prediction accuracy;

[0008] Among them, the specific method for calculating the temperature correction coefficient is:

[0009]

[0010] Where, T is temperature, m is comprehensive coefficient, when T = 20℃, m = 1; k and i are constants related to the material properties of asphalt mixture;

[0011] The specific method for calculating the humidity correction coefficient is:

[0012]

[0013] Where M 沥青混合料 is the diffusion coefficient of asphalt mixture, that is, the diffusion rate of water in the material; M 集料 is the diffusion rate of water in the aggregate that is not wrapped by asphalt and is tightly packed; d is the adjustment coefficient related to rainfall; s is the air humidity; w is the moisture content of the granular base or soil base, that is, when there is a granular base, the moisture content of the granular base is taken, and generally the moisture content of the soil base surface is taken; w s For the best moisture content, the granular base is generally 3%, and the soil base is generally 8%;

[0014] The specific method for calculating the thickness correction factor is:

[0015]

[0016] Where, ε t is the tensile strain at the bottom of the asphalt layer; n is the regression coefficient determined by the experiment; h is the thickness of the asphalt layer;

[0017] Step S3, crack propagation simulation: using the extended finite element method (XFEA) to simulate the propagation process of the reflection crack under the action of moving load and multi-physics field coupling, calculate the stress intensity factor of each iterative step, and determine the crack propagation direction, length, and crack growth rate;

[0018] Step S4, establishing a composite stress intensity factor and crack growth model: Calculate the composite stress intensity factor according to the Paris formula; introduce the equivalent crack damage rate D, and calculate the total crack growth under a given number of load applications by integrating the crack growth rate; construct a life prediction model based on the composite stress intensity factor and crack growth rate to reflect the crack damage evolution law of asphalt pavement structures under the influence of multiple factors;

[0019] Step S5, modification of the life prediction model: modify the parameters of the life prediction model based on the composite stress intensity factor and crack growth rate constructed in step S4, including the temperature correction coefficient Humidity correction factor and thickness correction factor The final asphalt pavement life prediction model is obtained; then the relevant parameters are substituted into the revised model to calculate and output the predicted life of the asphalt pavement.

[0020] According to another aspect of the present application, when constructing a three-dimensional finite element model of an asphalt pavement using Abaqus software in step S1, a simplified rectangular load is used, and the single-wheel rectangular load B×L=184mm×192mm; in order to realize the movement of the load on the pavement structure, the DLOAD subroutine is written in Fortran to simulate the movement of the vertical load; the Prony series is used in Abaqus to characterize the viscoelastic properties of the asphalt mixture to analyze the dynamic mechanical behavior of the asphalt material under vehicle load.

[0021] According to another aspect of the present application, in step S2, the maximum tensile strain ε of each asphalt layer bottom is calculated based on the strain model. i By integrating the thickness of the asphalt layer, the calculation formula for the overall fatigue cracking life of the asphalt layer is obtained:

[0022]

[0023] Where N fh is the number of fatigue cracking loads that takes into account the strain accumulation of the asphalt layer thickness, h is the thickness of the asphalt layer, ε t is the strain at the bottom of the asphalt layer, and n is the regression coefficient determined by the experiment;

[0024] The strain model is:

[0025] N f =K(ε t ) -n ,

[0026] Where N f is the number of repeated loads the asphalt mixture endures when fatigue failure occurs, ε t is the tensile strain at the bottom of the asphalt layer, and n and K are the regression coefficients determined by the experiment.

[0027] According to another aspect of the present application, in step S3, the extended finite element method (XFEA) is used to simulate the crack propagation path. The Williams element type is selected to directly provide the stress intensity factor at the crack tip, namely the type I stress intensity factor and the type II stress intensity factor, and finally form a composite stress intensity factor to describe the complex stress field effect of crack propagation:

[0028] ΔK* =f(K Ⅰ ,K Ⅱ ),

[0029] Where K Ⅰ is the type I stress intensity factor, K Ⅱ is the type II stress intensity factor; ΔK * It is the driving force for crack propagation. The larger the stress intensity factor, the more obvious the crack propagation trend.

[0030] According to another aspect of the present application, step S4 is further:

[0031] Step S41: refer to the Paris formula to obtain the crack growth rate:

[0032]

[0033] Step S42: Integrate the crack growth rate formula obtained in step S41 to obtain the relationship between the crack growth length and the number of load actions:

[0034]

[0035] Step S43: Obtain the relationship between the crack extension length and the number of load actions through the integral formula:

[0036]

[0037] Where N is the number of times the cracking load acts, A and n1 are material parameters, ΔK is the stress intensity factor, and a is the crack length. The relationship between the crack extension length and life is calculated by integration.

[0038] According to another aspect of the present application, the formula for the equivalent crack damage rate D in step S4 is:

[0039]

[0040] Where D is the equivalent crack damage rate, ΔK * is the composite stress intensity factor, K max is the maximum value of the composite stress intensity factor, ε t is the tensile strain at the bottom of the asphalt layer, k is a constant related to the asphalt mixture, and n is the regression coefficient determined by the experiment.

[0041] According to another aspect of the present application, step S5 is based on the finite element simulation results, taking into account the influencing factors of temperature, humidity, moving load, overall strain accumulation of the asphalt layer, pavement structure layer thickness, and reflective cracks, and deforming and correcting the constructed life prediction model based on the composite stress intensity factor and crack growth rate. The final corrected asphalt pavement life prediction model is:

[0042]

[0043] Where N f The number of repeated loads that the asphalt mixture bears when fatigue failure occurs; is the temperature correction coefficient, is the humidity correction factor, is the thickness correction coefficient, f is a constant, when When 1 is taken, When T is temperature, m is comprehensive coefficient. When T=20℃, m=1. 沥青混合料 is the diffusion coefficient of asphalt mixture, M 集料 is the diffusion rate of water in the aggregate that is not wrapped by asphalt and is tightly packed. d is the adjustment coefficient related to rainfall. s is the air humidity. w is the moisture content of the granular base or soil base. That is, when there is a granular base, the moisture content of the granular base is taken. Generally, the moisture content of the soil base surface is taken. w s is the optimal moisture content, which is generally 3% for granular base and 8% for soil base; C, k and i are constants related to the material properties of asphalt mixture; H is the crack extension length; D is the equivalent crack damage rate; ε t is the tensile strain at the bottom of the asphalt layer, n is the regression coefficient determined by the experiment, h is the thickness of the asphalt layer; the composite stress intensity factor ΔK * =f(K Ⅰ ,K Ⅱ ).

[0044] Beneficial effects: The technical solution of this application significantly improves the accuracy and reliability of asphalt pavement life prediction through multi-step refined analysis and model correction, providing strong technical support for practical engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is an overall flow chart of the scheme of the present invention.

[0046] Figure 2 Schematic diagram of the asphalt pavement structure of Example 1.

[0047] Figure 3 Schematic diagram of the three-dimensional finite element model of the asphalt pavement in Example 1.

[0048] Figure 4 This is a diagram of viscoelastic parameters of the asphalt mixture of Example 1.

[0049] Figure 5 This is a graph showing the variation of the tensile strain at the bottom of the asphalt layer with the depth of the pavement structure in Example 1.

[0050] Figure 6 This is a schematic diagram of the initial crack locations of the asphalt pavement structure of Example 1.

[0051] Figure 7 is the composite stress intensity factor ΔK of Example 1 * Variation with crack length. DETAILED DESCRIPTION

[0052] like Figure 1 As shown, an embodiment of the present invention provides a method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis. This embodiment predicts the fatigue life of asphalt pavement through finite element modeling, correction coefficient calculation, crack propagation simulation, and life prediction model establishment.

[0053] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0054] Example 1

[0055] A method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis includes the following steps:

[0056] The first step is to build a three-dimensional finite element model. Using Abaqus software, a three-dimensional finite element model of the asphalt pavement is constructed to simulate the mechanical response of the pavement structure under moving loads, specifically the maximum bottom tensile strain values ​​of each asphalt surface layer.

[0057] In this embodiment, the schematic diagram of the asphalt pavement structure is shown in the attached Figure 1 As shown. Abaqus software was used to establish a three-dimensional finite element model of the asphalt pavement. The pavement structure size selected for modeling in this paper was 6m×3m×3.76m, and the calculated depth of the roadbed was determined to be 3.76m. The boundary conditions were a completely fixed constraint at 3.76m in the longitudinal direction of the pavement (Y-axis direction), and horizontal constraints for limiting displacement in the transverse direction of the pavement structure (X-axis direction) and the direction of vehicle travel (Z-axis direction). A simplified rectangular load was used to simulate the load, and the single-wheel rectangular load was B×L=184mm×192mm. The DLOAD subroutine written in Fortran was used to realize the movement of the load on the pavement, as shown in the attached figure. Figure 2 In this embodiment, the Prony series is used to describe the viscoelastic behavior of asphalt mixture. The setting of viscoelastic parameters is shown in the attached figure. Figure 3 As shown in the figure, a 3D finite element model is finally generated. The model is submitted to the job to obtain the simulation results and extract the tensile strain data of the bottom of the asphalt layer. The variation of the tensile strain of the bottom of the asphalt layer with the depth of the pavement structure is shown in the figure. Figure 4 shown.

[0058] The second step is to calculate the correction coefficient. According to the maximum tensile strain value of each layer of the asphalt surface layer obtained by simulation, the temperature correction coefficient is calculated respectively considering the influence of temperature and pavement structure layer thickness. Humidity correction factor Thickness correction factor

[0059] In this embodiment, the parameters in the literature are used, where n is -0.5, m is 0.8, the set temperature T is 40°C, k is -0.02, and i is 0.5. The specific calculation process is as follows:

[0060]

[0061] In this embodiment, the parameters in the literature are adopted, where d is 10, M 沥青混合料 =5.0×10 -4 , M 集料 =1.9×10 -2 , humidity s is taken as 0.9, w is taken as 0.1, w s Take 0.08, and the specific calculation process is as follows:

[0062]

[0063] The calculation process of thickness correction factor is as follows:

[0064]

[0065] The third step is crack propagation simulation. The extended finite element method (XFEM) is used to simulate the propagation process of the reflected crack under the action of load. The stress intensity factor of the current analysis step is calculated in each iteration, and the propagation direction and length of the crack are determined. In this embodiment, the mesh is refined in the expected crack area, and the location and length of the initial crack are defined in the base layer, as shown in the attached figure. Figure 5 As shown in the figure. Through finite element analysis, the stress and strain distribution of the asphalt pavement under load is calculated, and the stress intensity factor at the crack tip is extracted to analyze the results of crack expansion.

[0066] The fourth step is to develop a crack growth and life prediction model. Considering the damage caused by reflected cracks, a composite stress intensity factor model is established with reference to the Paris formula. Considering the contribution of type I and type II stress intensity factors to crack growth, the composite stress intensity factor is defined as:

[0067] ΔK * =f(K Ⅰ ,K Ⅱ )=|K Ⅰ |+K Ⅱ

[0068] In this embodiment, the composite stress intensity factor changes with the crack length as shown in Figure 6 Combining the stress intensity factor and the crack growth rate, the concept of equivalent crack damage rate D is proposed to describe the cumulative effect of crack growth.

[0069] Step 5: Correction of the life prediction model. Based on the calculated temperature correction coefficient and thickness correction factor The life prediction model is modified. The modified parameters are introduced into the life prediction model to obtain the estimated life of the asphalt pavement.

[0070] In this embodiment, based on the finite element simulation results and empirical formulas, the fatigue cracking life model of asphalt pavement proposed based on fracture mechanics theory is deformed and modified to obtain a finite element-based asphalt pavement life prediction model.

[0071]

[0072] In this example, the H value is taken as the asphalt surface layer thickness of 20 cm, and the calculation results are as follows:

[0073] The parameter C is taken from the literature and is 3.44×10 -4.68 , k is 2.32, n is -0.5, K max According to the simulation results, ε t The tensile strain at the bottom of the asphalt layer is taken as 3.93με.

[0074] Although the present invention has been described in detail in this embodiment, those skilled in the art will understand that any modification, improvement, or substitution of the present invention, so long as it does not deviate from its basic concept and creative contribution, shall be deemed to be within the scope of protection of the present invention. The scope of protection of the present invention shall include all equivalent technical solutions that achieve its objectives and functions, regardless of whether such solutions are explicitly mentioned in this invention.

Claims

1. A method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis, characterized in that: The following steps are involved: Step S1, constructing a three-dimensional finite element model: A three-dimensional finite element model is constructed using Abaqus software to simulate the multi-physics coupling of moving loads, temperature, humidity, and pavement structure layers, and obtain the mechanical response parameters of the asphalt pavement structure layers, including the maximum layer bottom tensile strain value, stress distribution, and displacement field; Step S2: Calculate the temperature correction coefficient, humidity correction coefficient, and thickness correction coefficient based on the mechanical response parameters obtained in step S1, taking into account the effects of temperature, humidity, and pavement structure layer thickness, and correct the three-dimensional finite element model constructed in step S1 to improve prediction accuracy; Among them, the specific method for calculating the temperature correction coefficient is: Where, T is temperature, m is comprehensive coefficient, when T = 20℃, m = 1; k and i are constants related to the material properties of asphalt mixture; The specific method for calculating the humidity correction coefficient is: Where M 沥青混合料 is the diffusion coefficient of asphalt mixture, that is, the diffusion rate of water in the material; M 集料 is the diffusion rate of water in the aggregate that is not wrapped by asphalt and is tightly packed; d is the adjustment coefficient related to rainfall; s is the air humidity; w is the moisture content of the granular base or soil base, that is, when there is a granular base, the moisture content of the granular base is taken, and generally the moisture content of the soil base surface is taken; w s For the best moisture content, the granular base is generally 3%, and the soil base is generally 8%; The specific method for calculating the thickness correction factor is: Where, ε t is the tensile strain at the bottom of the asphalt layer; n is the regression coefficient determined by the experiment; h is the thickness of the asphalt layer; Step S3, crack propagation simulation: using the extended finite element method (XFEA) to simulate the propagation process of the reflection crack under the action of moving load and multi-physics field coupling, calculate the stress intensity factor of each iterative step, and determine the crack propagation direction, length, and crack growth rate; Step S4, establishing a composite stress intensity factor and crack growth model: Calculate the composite stress intensity factor according to the Paris formula; introduce the equivalent crack damage rate D, and calculate the total crack growth under a given number of load applications by integrating the crack growth rate; construct a life prediction model based on the composite stress intensity factor and crack growth rate to reflect the crack damage evolution law of asphalt pavement structures under the influence of multiple factors; Step S5, modification of the life prediction model: modify the parameters of the life prediction model based on the composite stress intensity factor and crack growth rate constructed in step S4, including the temperature correction coefficient Humidity correction factor and thickness correction factor The final asphalt pavement life prediction model is obtained; then the relevant parameters are substituted into the revised model to calculate and output the predicted life of the asphalt pavement.

2. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized by: When constructing the three-dimensional finite element model of the asphalt pavement using Abaqus software in step S1, a simplified rectangular load is used; the single-wheel rectangular load B×L=184mm×192mm. To achieve the movement of the load on the pavement structure, the DLOAD subroutine is written in Fortran to simulate the movement of the vertical load. The Prony series is used in Abaqus to characterize the viscoelastic properties of the asphalt mixture to analyze the dynamic mechanical behavior of the asphalt material under vehicle load.

3. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized by: In step S2, the maximum tensile strain ε of each asphalt layer bottom is calculated based on the strain model. i By integrating the thickness of the asphalt layer, the calculation formula for the overall fatigue cracking life of the asphalt layer is obtained: Where N fh is the number of fatigue cracking loads that takes into account the strain accumulation of the asphalt layer thickness, h is the thickness of the asphalt layer, ε t is the strain at the bottom of the asphalt layer, and n is the regression coefficient determined by the experiment; The strain model is: N f =K(e t ) -n , Where N f is the number of repeated loads the asphalt mixture endures when fatigue failure occurs, ε t is the tensile strain at the bottom of the asphalt layer, and n and K are the regression coefficients determined by the experiment.

4. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized by: In step S3, the extended finite element method (XFEA) is used to simulate the crack propagation path. The Williams element type is selected to directly provide the stress intensity factor at the crack tip, namely the type I stress intensity factor and the type II stress intensity factor. Finally, a composite stress intensity factor is formed to describe the complex stress field effect of crack propagation: ΔK * =f(K Ⅰ ,K Ⅱ ), Where K Ⅰ is the type I stress intensity factor, K Ⅱ is the type II stress intensity factor; ΔK * It is the driving force for crack propagation. The larger the stress intensity factor, the more obvious the crack propagation trend.

5. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized in that: Step S4 is further as follows: Step S41: refer to the Paris formula to obtain the crack growth rate: Step S42: Integrate the crack growth rate formula obtained in step S41 to obtain the relationship between the crack growth length and the number of load actions: Step S43: Obtain the relationship between the crack extension length and the number of load actions through the integral formula: Where N is the number of times the cracking load acts, A and n1 are material parameters, ΔK is the stress intensity factor, and a is the crack length. The relationship between the crack extension length and life is calculated by integration.

6. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized by: The formula for the equivalent crack damage rate D in step S4 is: Where D is the equivalent crack damage rate, ΔK * is the composite stress intensity factor, K max is the maximum value of the composite stress intensity factor, ε t is the tensile strain at the bottom of the asphalt layer, k is a constant related to the asphalt mixture, and n is the regression coefficient determined by the experiment.

7. The method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis according to claim 1 is characterized by: In step S5, based on the finite element simulation results, the life prediction model constructed based on the composite stress intensity factor and crack growth rate is deformed and corrected by considering the influencing factors of temperature, humidity, moving load, overall strain accumulation of the asphalt layer, pavement structure layer thickness, and reflective cracks. The corrected asphalt pavement life prediction model is finally obtained as follows: Where N f The number of repeated loads that the asphalt mixture bears when fatigue failure occurs; is the temperature correction coefficient, is the humidity correction factor, is the thickness correction coefficient, f is a constant, when When 1 is taken, When T is temperature, m is comprehensive coefficient. When T=20℃, m=1. 沥青混合料 is the diffusion coefficient of asphalt mixture, M 集料 is the diffusion rate of water in the aggregate that is not wrapped by asphalt and is tightly packed. d is the adjustment coefficient related to rainfall. s is the air humidity. w is the moisture content of the granular base or soil base. That is, when there is a granular base, the moisture content of the granular base is taken. Generally, the moisture content of the soil base surface is taken. w s is the optimal moisture content, which is generally 3% for granular base and 8% for soil base; C, k and i are constants related to the material properties of asphalt mixture; H is the crack extension length; D is the equivalent crack damage rate; ε t is the tensile strain at the bottom of the asphalt layer, n is the regression coefficient determined by the experiment, h is the thickness of the asphalt layer; the composite stress intensity factor ΔK * =f(K Ⅰ ,K Ⅱ ).

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