Asphalt pavement life prediction model establishment method based on environment and load coupling analysis

Abstract

The invention provides an asphalt pavement life prediction model establishment method based on environment and load coupling analysis, which comprises the following steps: establishing a three-dimensional finite element model of an asphalt pavement by using Abaqus software, simulating dynamic response of a pavement structure under the action of moving load and temperature, and obtaining the maximum tensile strain value of the bottom of each layer of an asphalt surface layer; in combination with a temperature correction coefficient, a humidity correction coefficient and a thickness correction coefficient, the model is corrected to improve the prediction precision; simulating the expansion process of the reflection crack under the load action by adopting an expansion finite element method, and calculating a composite stress intensity factor and the influence of the composite stress intensity factor on crack expansion; referring to a Paris formula, introducing an equivalent crack damage rate, and constructing a service life prediction model considering the damage of crack propagation to the pavement structure; influences of temperature, humidity, load, asphalt layer overall strain accumulation, pavement structure layer thickness and reflection cracks are comprehensively considered, and an asphalt pavement life prediction model based on finite elements is established and used for accurately predicting the service life of an asphalt pavement.

Description

Technical Field

[0001] The 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 volume in my country, the frequent passage of heavy and overloaded vehicles has caused asphalt pavements to be prone to rutting, cracking, interlayer slippage and other diseases. In particular, under extreme conditions such as high temperature and heavy load, asphalt pavements are prone to fatigue cracking. Therefore, in view of the maintenance, upkeep and replacement needs of roads, it is particularly important to accurately predict the service life of asphalt pavements.

[0003] Traditional asphalt pavement life prediction methods are mainly based on empirical formulas and field test data, which usually lack detailed mechanical analysis and cannot fully consider the nonlinear characteristics of materials and complex traffic loads and environmental impacts. The collection of field test data is also often limited due to large variability, high cost, and difficulty in obtaining, resulting in limited reliability of prediction results. In recent years, finite element analysis (FEA) and extended finite element analysis (XFEA) have gradually been applied to pavement design and performance analysis, and can accurately predict the mechanical behavior of pavements under complex loads and environmental conditions through numerical simulation methods. This method can more accurately evaluate the dynamic response of pavement structures and provide more valuable mechanical indicators for life prediction. Summary of the invention

[0004] Technical problem solved: The present invention provides a method for establishing an asphalt pavement life prediction model based on environment and load coupling analysis, which can comprehensively consider the influence of traffic load, temperature, humidity and pavement structure layer thickness, and improve the accuracy and reliability of asphalt pavement life prediction. This method combines finite element analysis (FEA) and extended finite element analysis (XFEA) with fracture mechanics theory, and proposes a new correction coefficient and crack propagation model for complex environmental factors that are not fully considered in traditional methods, thereby overcoming 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, comprising 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-physical field coupling of moving load, temperature, humidity and pavement structure layer, and obtain various mechanical response parameters of the asphalt pavement structure layer, including the maximum layer bottom tensile strain value, stress distribution and displacement field;

[0007] Step S2, according to the mechanical response parameters obtained in step S1, considering the influence of temperature, humidity and the thickness of the pavement structure layer, calculating the temperature correction coefficient, the humidity correction coefficient and the thickness correction coefficient, and correcting the three-dimensional finite element model constructed in step S1 to improve the 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 ° C, m = 1; k and i are constants related to the material properties of asphalt mixture;

[0011] The specific method for calculating the humidity correction factor 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] In the formula, 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 extension simulation: simulate the extension process of the reflection crack under the action of moving load and multi-physical field coupling by using the extended finite element method XFEA, calculate the stress intensity factor of each iterative step, and determine the crack extension direction, length and crack growth rate;

[0018] Step S4, establishing a composite stress intensity factor and crack extension model: according to the Paris formula, the composite stress intensity factor is calculated; the equivalent crack damage rate D is introduced, and the total extension of the crack under a given number of load actions is calculated by integrating the crack extension rate; a life prediction model based on the composite stress intensity factor and the crack extension rate is constructed to reflect the crack damage evolution law of the asphalt pavement structure under the influence of multiple factors;

[0019] Step S5, modification of the life prediction model: modifying 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 at the bottom of each asphalt layer is calculated according to 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 accumulated strain of the asphalt layer thickness, h is the thickness of the asphalt layer, ε t is the bottom strain of the asphalt layer, 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 that the asphalt mixture is subjected to when fatigue failure occurs, ε t is the tensile strain at the bottom of the asphalt layer, 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, and the Williams unit type is selected to directly provide the stress intensity factor at the crack tip, that is, 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] In the formula, 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 extension. The larger the stress intensity factor, the more obvious the crack extension 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 extension rate formula obtained in step S41 to obtain the relationship between the crack extension 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 n 1 is the material parameter, ΔK is the stress intensity factor, a is the crack length, and 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 influence of temperature, humidity, moving load, overall strain accumulation of the asphalt layer, thickness of the pavement structure layer, and reflective cracks, and deforming and correcting the constructed life prediction model based on the composite stress intensity factor and crack growth rate, and finally obtaining the corrected asphalt pavement life prediction model as follows:

[0042]

[0043] Where N f It is the number of repeated loads that the asphalt mixture is subjected to 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 optimum 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 It is a schematic diagram of the asphalt pavement structure of Example 1.

[0047] Figure 3 It is a schematic diagram of the three-dimensional finite element model of the asphalt pavement of Example 1.

[0048] Figure 4 It is the viscoelastic parameter diagram 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 6It is a schematic diagram of the initial crack positions of the asphalt pavement structure of Example 1.

[0051] Figure 7 is the composite stress intensity factor ΔK of Example 1 * Variation of 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 the asphalt pavement through finite element modeling, correction coefficient calculation, crack propagation simulation and establishment of a life prediction model.

[0053] To make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the embodiments of the present invention will be described clearly and completely 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 them.

[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 establish a three-dimensional finite element model. A three-dimensional finite element model of the asphalt pavement is established using Abaqus software to simulate the mechanical response of the pavement structure layer under the action of moving loads, especially the maximum bottom tensile strain value of each layer of the 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 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 to limit 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 three-dimensional 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 change of the tensile strain of the bottom of the asphalt layer with the depth of the pavement structure is shown in the figure below. 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 the thickness of the pavement structure layer. 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 used, 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 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. 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 extension.

[0066] The fourth step is the crack extension and life prediction model. Considering the reflected crack damage, the 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 extension, 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 varies 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 embodiment, the H value is taken as the asphalt surface layer thickness of 20cm, 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 is described in detail in this embodiment, it should be understood by those skilled in the art that any modification, improvement or replacement of the present invention, as long as it does not deviate from its basic concept and creative contribution, should be regarded as the protection scope of the present invention. The protection scope of the present invention should include all equivalent technical solutions that achieve its purpose and function, regardless of whether these solutions are explicitly mentioned in the present 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-physical field coupling of moving load, temperature, humidity and pavement structure layer, and obtain various mechanical response parameters of the asphalt pavement structure layer, including the maximum layer bottom tensile strain value, stress distribution and displacement field; Step S2, according to the mechanical response parameters obtained in step S1, considering the influence of temperature, humidity and the thickness of the pavement structure layer, calculating the temperature correction coefficient, the humidity correction coefficient and the thickness correction coefficient, and correcting the three-dimensional finite element model constructed in step S1 to improve the 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 ° C, 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: In the formula, 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 extension simulation: simulate the extension process of the reflection crack under the action of moving load and multi-physical field coupling by using the extended finite element method XFEA, calculate the stress intensity factor of each iterative step, and determine the crack extension direction, length and crack growth rate; Step S4, establishing a composite stress intensity factor and crack extension model: according to the Paris formula, the composite stress intensity factor is calculated; the equivalent crack damage rate D is introduced, and the total extension of the crack under a given number of load actions is calculated by integrating the crack extension rate; a life prediction model based on the composite stress intensity factor and the crack extension rate is constructed to reflect the crack damage evolution law of the asphalt pavement structure under the influence of multiple factors; Step S5, modification of the life prediction model: modifying 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, 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 the 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 in that: In step S2, according to the strain model, the maximum tensile strain ε of each asphalt layer bottom is calculated. 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 accumulated strain of the asphalt layer thickness, h is the thickness of the asphalt layer, ε t is the bottom strain of the asphalt layer, 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 that the asphalt mixture is subjected to when fatigue failure occurs, ε t is the tensile strain at the bottom of the asphalt layer, 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 in that: In step S3, the extended finite element method XFEA is used to simulate the crack propagation path. The Williams unit 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: ΔK * =f(K Ⅰ ,K Ⅱ ), In the formula, 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 extension. The larger the stress intensity factor, the more obvious the crack extension 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 extension rate formula obtained in step S41 to obtain the relationship between the crack extension 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 failure 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: Step S5 is based on the finite element simulation results, taking into account the influence of temperature, humidity, moving load, overall strain accumulation of the asphalt layer, pavement structure layer thickness, and reflective cracks, and deforms and modifies the life prediction model based on the composite stress intensity factor and crack growth rate. Finally, the modified asphalt pavement life prediction model is obtained as follows: Where N f It is the number of repeated loads that the asphalt mixture is subjected to 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 optimum 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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