A lsam-50 bending fatigue life prediction method considering temperature-load coupling effect and fatigue limit constraint

Abstract

This invention relates to a method for predicting the flexural fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints. Through a systematic innovation across the entire process from material forming, experimental design, data processing to model construction, it is the first to systematically introduce temperature variables and fatigue limit parameters into the flexural fatigue model. This enables an accurate description and quantitative prediction of the fatigue behavior of LSAM-50 under temperature-load coupling, effectively solving three major problems of existing models: failure to consider coupling effects, lack of fatigue limit characterization, and absence of a dedicated model for this ultra-large particle size material. This achievement can provide direct theoretical basis and key design parameters for the fatigue resistance design, life prediction, and integrated optimization of LSAM-50 and its pavement structures, thereby significantly improving the scientific rigor, reliability, and economy of long-life asphalt pavement design.

Description

Technical Field

[0001] This invention belongs to the field of road engineering technology, and specifically relates to a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints. Background Technology

[0002] In the field of road engineering, LSAM-50, a novel flexible base course material with a nominal maximum particle size of 53mm, has become a key material for constructing long-life asphalt pavements due to its superior structural load-bearing and stress diffusion capabilities. In actual service, it endures the combined effects of continuous traffic loads and complex environmental temperatures. This temperature-load coupling effect is the core factor inducing material fatigue damage and ultimately limiting the service life of pavement structures. For LSAM-50 flexible base courses, the service environment temperature range is wide. Temperature changes not only directly affect the material's mechanical modulus but also fundamentally alter its stress response mode and damage accumulation law under repeated traffic loads. Therefore, developing fatigue life prediction methods that can accurately reflect the temperature-load coupling effect is the theoretical cornerstone for achieving scientific design and reliable life prediction of this type of pavement structure.

[0003] Currently, research on the fatigue performance of LSAM-50 has significant limitations. Firstly, in terms of research perspective and methodology, existing studies largely focus on static tests to evaluate the material's basic strength or splitting fatigue tests emphasizing its tensile crack resistance. While splitting tests can reflect the uniform tensile characteristics within the material, their stress state differs fundamentally from the repeated bending stress state of pavement structures under actual wheel loads. Bending fatigue tests, by simulating the failure process of materials under bending moments, can more directly characterize the overall structural response and fatigue damage evolution of pavement structural layers, making them a more direct and relevant mechanical approach for pavement fatigue resistance design. However, systematic bending fatigue research specifically targeting ultra-large particle size mixtures like LSAM-50, especially considering wide-temperature-range coupling effects, remains a gap.

[0004] Secondly, in the theoretical development of fatigue models, most existing mainstream models are based on experimental data under a single, constant temperature, and adopt a simple power function relationship between stress level and fatigue life. These models have two major drawbacks: first, they fail to systematically embed temperature as an independent variable into the model framework, making it impossible to quantify the interaction mechanism between temperature fluctuations and load stress on fatigue life, resulting in severely insufficient extrapolation and prediction capabilities under actual variable temperature environments; second, the models generally lack the definition and characterization of material fatigue limits, ignoring the "durability limit" characteristics that materials may possess under low stress levels. This makes it impossible for the models to support optimization designs based on long-life or even infinite-life concepts, and hinders the full realization of the potential of LSAM-50.

[0005] In summary, the existing technological system suffers from a critical gap: on the one hand, there is a lack of systematic research on LSAM-50 using bending fatigue testing methods that more realistically reflect structural responses; on the other hand, it has failed to develop an advanced life prediction model that simultaneously considers temperature-load coupling effects and material fatigue limits. This gap means that the design of LSAM-50 pavements still relies on experience or indirect calculations, failing to achieve accurate connection and reliable prediction from material-level fatigue characteristics to structural-level service life. Therefore, there is an urgent need to establish a dedicated life prediction method centered on bending fatigue testing, capable of integrating multiple temperature conditions, characterizing coupling effects, and determining fatigue limit parameters. This would fill the technological gap in this field and provide key theoretical tools and technical support for the refined design of long-life LSAM-50 asphalt pavements. Summary of the Invention

[0006] The purpose of this invention is to provide a method for predicting the bending fatigue life of LSAM-50 that considers the temperature-load coupling effect and fatigue limit constraints, thereby solving the problems of existing fatigue models that do not systematically consider the temperature-load coupling effect, do not include the material fatigue limit, and lack applicability to LSAM-50 materials with ultra-large particle sizes.

[0007] To achieve the above objectives, the technical solution adopted by this invention is as follows: a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints, specifically implemented according to the following steps: Step 1: Prepare LSAM-50 thick rut plate specimens, and then divide them into LSAM-50 beam specimens; Step 2: Bend tests were conducted on the LSAM-50 beam specimens obtained in Step 1 under different temperature conditions to obtain their tensile bending strength at each test temperature. R B ; Step 3: Conduct bending fatigue tests on the LSAM-50 beam specimen obtained in Step 1 under temperature-load coupling, and record its bending fatigue life at different test temperatures and stress levels. N B The test temperature in step 3 is exactly the same as the temperature set for the LSAM-50 bending test in step 2. Step 4: Using the Weibull distribution test method, the bending fatigue test data of the LSAM-50 beam specimen obtained in Step 3 under temperature-load coupling are processed and analyzed to solve for different reliability levels. P Bending fatigue life N p ; Step 5: Construct the LSAM-50 three-parameter bending fatigue equation including the fatigue limit, its basic form being lg Np = A - B lg( σ-C ); In the formula, N p For bending fatigue life under different reliability levels, A , B, C For the fitting parameters, s For stress; Step 6: Determine the reliability based on the highway grade. P stress s Let x be the x-axis, lg N p Plot the results at different test temperatures on the ordinate. T The scatter plot below is based on the basic form lg of the LSAM-50 three-parameter bending fatigue equation including the fatigue limit described in step 5. N p = A - B lg( s-s th The parameters at different experimental temperatures were obtained by solving the nonlinear programming method. A , B With LSAM-50 bending fatigue limit s th The fitted value; Step 7, at the test temperature T The x-axis is represented by parameters. A , B and LSAM-50 bending fatigue limit s th Plot three scatter plots with the vertical axis as the ordinate; perform regression fitting on each scatter plot to obtain the parameters. A , B and bending fatigue limit s th The corresponding temperature-related regression equations; Step 8, take the result from step 7 A , B , s th With test temperature T Substituting the three sets of functional relationships into the basic form of the LSAM-50 three-parameter bending fatigue equation containing the fatigue limit described in step 5, lg N p = A - B lg( s-s th By doing so, we can obtain the LSAM-50 bending fatigue life prediction equation that takes into account temperature-load coupling and fatigue limit.

[0008] The technical solution of the present invention also has some features: As a preferred technical solution of the present invention, in step 1, the LSAM-50 thick rut plate specimen is formed using a large thickness rut ​​test method.

[0009] As a preferred technical solution of the present invention, in step 1, the working parameters of the thick rut test method are set as follows: the size of the LSAM-50 rut specimen is 42cm long × 42cm wide × 12cm thick, and the number of compaction passes is 30.

[0010] As a preferred technical solution of the present invention, in step 1: the LSAM-50 beam specimen should be formed by dividing the rut specimen using a high-precision cutting machine. The dimensions of the LSAM-50 beam specimen are 400mm long × 100mm wide × 100mm high, and the flatness of the cut end face should be guaranteed to be within ±0.1mm.

[0011] As a preferred technical solution of the present invention, in step 2: the test temperature needs to cover the actual service temperature range of the LSAM-50 flexible base layer, and the number of tests should be evenly distributed at intervals not exceeding 10°C.

[0012] As a preferred technical solution of the present invention, in step 3: Stress level S The value range is 0.3 to 0.9, and the interval between each stress level is 0.1 to 0.2. Stress level S The actual stress experienced by the specimen during a bending fatigue test. s With flexural tensile strength R B The ratio of [value], therefore, the actual stress experienced by the specimen during the bending fatigue test [is determined by the stress]. s stress level S × Bending tensile strength R B ,Right now σ=S × R B ; The experiment was set at a high stress level, i.e., stress level S The stress level is 0.7~0.9. Six to ten parallel tests are conducted under the same conditions, at low stress levels, i.e., stress level... S If the value is 0.3~0.6, then 10~15 sets of parallel tests should be conducted; at the same time, the test results should be discarded, and it should be ensured that there are no less than 5 valid parallel specimens in each set of tests after the discarding.

[0013] As a preferred embodiment of the present invention, step 4 is specifically implemented according to the following steps: Step 4.1: Sort by lifetime. The bending fatigue lives of LSAM-50 under the same temperature and stress level conditions were sorted in ascending order of numerical value, and then labeled as 1, 2, …, i , …, n .in, i This is the sequence number for the bending fatigue life of a single line. n This represents the total number of bending fatigue life data entries under the given temperature and stress level conditions. Step 4.2: Perform reliability calculations; According to the formula P =1- i / (1+ n Calculate the reliability corresponding to the bending fatigue life after each sorting. P ; Step 4.3: Perform linear fitting; Define the bending fatigue life random variable as a Weibull variable. N p ,by x =ln N p x-axis y =lnln(1 / P A scatter plot is drawn with the ordinate as the vertical axis, and the scatter points are fitted using a univariate linear function to obtain the result. x and y regression equation y = bx - β Record regression coefficients b , β ; Step 4.4: Solve for bending fatigue life; If the correlation coefficient of the regression equation is greater than 0.80, then the equivalent bending fatigue life under different reliability levels can be solved using this regression equation. N p .

[0014] As a preferred technical solution of the present invention, in step 5: when s Approaching C hour, N p Approaching infinity, at this point s Approaching C This is the bending fatigue limit of LSAM-50, denoted as . s th .

[0015] As a preferred embodiment of the present invention, in step 6: the reliability corresponding to the highway P =95%, the reliability corresponding to a Class I highway P=90%, the reliability corresponding to Class II and below highways P =85%.

[0016] As a preferred technical solution of the present invention, in step 6: when solving the splitting fatigue equation using nonlinear programming, the following solution conditions are set: allowable error 5%, convergence degree 0.0001, derivative calculation using forward difference method, estimation method using tangent function method, and iteration method using conjugate method.

[0017] The beneficial effects of this invention are: (1) The present invention provides a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints. For the first time, a complete set of testing and modeling methods for the bending fatigue performance of LSAM-50 flexible base material with a nominal maximum particle size of 53 mm has been systematically established, filling the technical gap in the study of structural fatigue response of this novel ultra-large particle size material. This method overcomes the limitations of existing fatigue studies, which are mostly focused on conventional particle size materials or other stress modes (such as splitting), and provides a direct and reliable theoretical basis for the life prediction and structural fatigue resistance design of LSAM-50 pavement based on the bending fatigue mechanism.

[0018] (2) The present invention provides a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints, which introduces temperature as a core variable system for the first time. By conducting bending fatigue tests under multiple temperature conditions, the functional relationship between the key parameters of the model and temperature was established, thereby constructing a fatigue equation that can quantify the temperature-load coupling effect. This solves the problem of inaccurate prediction by traditional models under variable temperature environments, making the life prediction more consistent with the actual wide temperature range service conditions of road surfaces, and significantly improving the engineering applicability and prediction accuracy of the model.

[0019] (3) The present invention provides a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints. It innovatively uses a three-parameter equation containing the fatigue limit to describe the bending fatigue behavior of LSAM-50, and successfully determines the temperature-related material fatigue limit through an adapted mathematical method. This overcomes the problem that traditional two-parameter models cannot characterize the "infinite life" characteristics under low stress levels, providing key parameter basis for pavement structure optimization based on the long-life design concept. Furthermore, it allows for optimization of stress level schemes in experimental design, improving research efficiency.

[0020] (4) The present invention provides a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints, forming a complete technical system from bending fatigue test design and data reliability processing to coupled model construction. This method is scientific and rigorous, and its results (i.e., fatigue equations directly related to temperature and reliability) can directly serve the differentiated fatigue resistance design and accurate life prediction of LSAM-50 pavement structures for different grades of highways, thereby providing key technical support for improving the long-term service performance of pavement and reducing the total life cycle cost, and has significant engineering application value. Attached Figure Description

[0021] Figure 1 The equivalent bending fatigue life under 90% reliability; Figure 2 lg at 90% reliability N p - s Scatter plot; Figure 3 lg at 90% reliability N p - s Regression curve; Figure 4 Equation parameters A , B , s th and T The fitted curve. Detailed Implementation

[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Example 1 The present invention provides a method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints, which is implemented according to the following steps: Step 1: Prepare LSAM-50 thick rut plate specimens, and then divide them into LSAM-50 beam specimens; Step 2: Bend tests were conducted on the LSAM-50 beam specimens obtained in Step 1 under different temperature conditions to obtain their tensile bending strength at each test temperature. R B ; Step 3: Conduct bending fatigue tests on the LSAM-50 beam specimen obtained in Step 1 under temperature-load coupling, and record its bending fatigue life at different test temperatures and stress levels. N B The test temperature in step 3 is exactly the same as the temperature set for the LSAM-50 bending test in step 2. Step 4: Using the Weibull distribution test method, the bending fatigue test data of the LSAM-50 beam specimen obtained in Step 3 under temperature-load coupling are processed and analyzed to solve for different reliability levels. P Bending fatigue life N p ; Step 5: Construct the LSAM-50 three-parameter bending fatigue equation including the fatigue limit, its basic form being lg N p = A - B lg( σ-C ); In the formula, N p For bending fatigue life under different reliability levels, A , B, C For the fitting parameters, s For stress; when s Approaching C hour, N p Approaching infinity, at this point s Approaching C This is the bending fatigue limit of LSAM-50, denoted as . s th ; Step 6: Determine the reliability based on the highway grade. P stress s Let x be the x-axis, lg N p Plot the results at different test temperatures on the ordinate. T The scatter plot below is based on the basic form lg of the LSAM-50 three-parameter bending fatigue equation including the fatigue limit described in step 5. N p = A - B lg( s-s th The parameters at different experimental temperatures were obtained by solving the nonlinear programming method. A , B With LSAM-50 bending fatigue limit s th The fitted value; Step 7, at the test temperature T The x-axis is represented by parameters. A , B and LSAM-50 bending fatigue limit s thPlot three scatter plots with the vertical axis as the ordinate; perform regression fitting on each scatter plot to obtain the parameters. A , B and bending fatigue limit s th The corresponding temperature-related regression equations; Step 8, take the result from step 7 A , B , s th With test temperature T Substituting the three sets of functional relationships into the basic form of the LSAM-50 three-parameter bending fatigue equation containing the fatigue limit described in step 5, lg N p = A - B lg( s-s th By doing so, we can obtain the LSAM-50 bending fatigue life prediction equation that takes into account temperature-load coupling and fatigue limit.

[0024] This invention addresses the shortcomings of existing fatigue models when describing LSAM-50, such as failing to systematically consider the temperature-load coupling effect, lacking fatigue limit parameters, and not being specifically adapted to its ultra-large particle size characteristics. It proposes a method for predicting the flexural fatigue life of LSAM-50 that considers both the temperature-load coupling effect and fatigue limit constraints. This method, through a systematic innovation across the entire process from material forming, experimental design, data processing to model construction, introduces temperature variables and fatigue limit parameters into the flexural fatigue model for the first time. This enables an accurate description and quantitative prediction of the fatigue behavior of LSAM-50 under temperature-load coupling, providing direct theoretical basis and key design parameters for the fatigue resistance design, life prediction, and integrated optimization of LSAM-50 and its pavement structures. This significantly improves the scientific rigor, reliability, and economy of long-life asphalt pavement design.

[0025] Example 2 Unlike Example 1, in step 1 of the LSAM-50 bending fatigue life prediction method of the present invention considering temperature-load coupling effect and fatigue limit constraint in Example 2: The LSAM-50 thick rutting plate specimen was formed using the thick rutting test method, and then divided into LSAM-50 beam specimens. The working parameters for the thick rut test method are set as follows: the LSAM-50 rut specimen size is 42cm long × 42cm wide × 12cm thick, and the number of compaction passes is 30. The median gradation value of LSMA-50 aggregate shown in Table 1 was selected, and the aggregate was gradually remixed and molded into LSAM-50 thick rut plate specimens with dimensions of 42cm in length × 42cm in width × 12cm in thickness.

[0026] Table 1. Dense Grading Range of LSAM-50 with Strong Interlocking Skeleton The rut specimens were cut using a high-precision cutting machine to form LSAM-50 beam specimens with a length of 400mm, a width of 100mm, and a height of 100mm. The flatness of the cut end face was ±0.03mm.

[0027] Example 3 Unlike Example 2, in step 2 of the LSAM-50 bending fatigue life prediction method considering temperature-load coupling effect and fatigue limit constraint in Example 3 of the present invention, the test temperature needs to cover the actual service temperature range of the LSAM-50 flexible base layer and be evenly distributed at intervals not exceeding 10℃. For example, according to the LSAM-50 pavement temperature field monitoring stations deployed in Daqing, Heilongjiang and Wuwei, Anhui, since 2020, the bottom of the LSAM-50 base layer has generally been in the temperature range of -5℃ to 35℃, with the lowest temperature reaching -15℃. Therefore, the test temperatures used are 35℃, 25℃, 15℃, 5℃, -5℃, and -15℃.

[0028] The test results of LSAM-50 bending test under different temperature conditions are shown in Table 2.

[0029] Table 2 Bending Test Results of LSAM-50

[0030] Example 4 Unlike Example 3, in step 3 of the LSAM-50 bending fatigue life prediction method of the present invention considering temperature-load coupling effect and fatigue limit constraint in Example 4: The test temperature should correspond exactly to the temperature set in the LSAM-50 bending test in step 2. Therefore, 35℃, 25℃, 15℃, 5℃, -5℃, and -15℃ are used.

[0031] Stress level S The selection of stress levels needs to take into account the test cycle and the actual heavy and overloaded vehicle loads on the road. The recommended stress level range is 0.3 to 0.9, with an interval of 0.1 to 0.2 between each stress level. Therefore, stress levels of 0.3, 0.5, 0.7, and 0.9 are adopted.

[0032] Stress level S The actual stress experienced by the specimen during a bending fatigue test. s With flexural tensile strength R B The ratio of [value], therefore, the actual stress experienced by the specimen during the bending fatigue test [is determined by the stress]. s stress level S × Bending tensile strengthR B ,Right now σ=S × R B Therefore, the actual stress experienced by the specimen during the bending fatigue test is... s See Table 3.

[0033] Table 3. Actual stresses experienced by LSAM-50 beam specimens during bending fatigue tests. Considering that lower stress levels result in longer bending fatigue life, longer testing cycles, and greater variability in results, the tests were conducted at high stress levels (0.7–0.9), with 6–10 parallel tests performed under the same conditions. At low stress levels (0.3–0.6), 10–15 parallel tests were performed. Furthermore, the test results were processed according to the relevant requirements for bending fatigue testing in JTG E20-2011, ensuring that each set of tests contained 5 valid parallel specimens after the discrepancies were corrected.

[0034] LSAM-50 bending fatigue life under different test temperatures and stress levels N B The test results are shown in Table 4. In the table, "-" indicates that no fatigue fracture occurred after more than 1.3 million loading cycles. Considering the test time and the condition of the loading equipment, the loading was manually stopped, and fatigue life data was not recorded.

[0035] Table 4. Results of LSAM-50 Bending Fatigue Test

[0036] Example 5 Unlike Example 4, step 4 of the LSAM-50 bending fatigue life prediction method of the present invention, which considers the temperature-load coupling effect and fatigue limit constraint, in Example 5 is specifically implemented according to the following steps: Step 4.1: Sort by lifetime. The bending fatigue lives of LSAM-50 under the same temperature and stress level conditions were sorted in ascending order of numerical value, and then labeled as 1, 2, …, i , …, n The results are the same as in Table 4. Among them, i If the rank is the sequence number of the single bending fatigue life, then i =1, 2, 3, 4, 5; n Let be the total number of bending fatigue life data points under this temperature and stress level condition. n =5; Step 4.2: Perform reliability calculations; According to the formula P =1- i / (1+ n Calculate the reliability corresponding to the bending fatigue life after each sorting. P Then when i When the sum is 1, 2, 3, 4, 5, P The values ​​calculated in sequence are 0.83, 0.67, 0.5, 0.33, and 0.17. Step 4.3: Perform linear fitting; Define the splitting fatigue life random variable as a Weibull variable. N p ,by x =ln N p x-axis y =lnln(1 / P A scatter plot is drawn with the ordinate as the vertical axis, and the scatter points are fitted using a univariate linear function to obtain the result. x and y regression equation y = bx - β Record regression coefficients b , β See Table 4.

[0037] Define the bending fatigue life random variable as a Weibull variable. N p ,by x =ln N p x-axis y =lnln(1 / P A scatter plot is drawn with the ordinate as the vertical axis, and the scatter points are fitted using a univariate linear function to obtain the result. x and y regression equation y = bx - β Record regression coefficients b , β See Table 5.

[0038] Table 5. Weibull distribution model coefficients for LSAM-50 bending fatigue life.

[0039] Step 4.4: Solve for the equivalent splitting fatigue life. If the correlation coefficient of the regression equation is greater than 0.80, then the equivalent bending fatigue life under different reliability levels can be solved using this regression equation. N p .

[0040] According to Table 5, the correlation coefficients of the regression equations R2 >0.85, meeting the preset requirements, then according to the regression equation y = bx - β and the regression coefficients shown in Table 5 b , β Solve for the equivalent bending fatigue life under 90% reliability. N p The results are shown Figure 1 .

[0041] Example 6 Unlike Example 5, in step 6 of Example 6, the reliability of the highway is... (The sentence is incomplete and requires further context to be fully translated.) P =95%, the reliability corresponding to a Class I highway P =90%, the reliability corresponding to Class II and below highways P =85%.

[0042] Taking a Class I highway as an example, the reliability of a Class I highway P =90%, with stress s The x-axis represents the logarithm at 90% reliability. N p Plot different test temperatures on the ordinate. T The following scatter plot is shown Figure 2 As shown.

[0043] Based on the basic form of the three-parameter bending fatigue equation including the fatigue limit described in step 5, lg N p = A - B lg( s - s th The parameters at different experimental temperatures were obtained by solving the nonlinear programming method. A , B With bending fatigue limit s th The fitted values ​​are shown in Figure 3 And Table 6. When solving the bending fatigue equation using nonlinear programming, the following solution conditions are set: allowable error 5%, convergence degree 0.0001, derivative calculation using the forward difference method, estimation using the tangent function method, and iterative method using the conjugate method.

[0044] Table 6 N p ~ s ~ s th Related parameters of the fitting equation

[0045] Based on the results of step 6, in step 7, the test temperature is... T The x-axis is represented by parameters. A , B and bending fatigue limit s th Plot three scatter plots with the vertical axis as the ordinate; perform regression fitting on each scatter plot to obtain the parameters. A , B and bending fatigue limit s th The corresponding temperature-related regression equations are shown in the figure. Figure 4 With formulas (1) to (3).

[0046] A =7.19-0.122 T (1) B =3.71-0.054 T (2) s th =0.059 e -0.024T (3) Step 8, take the result from step 7 A , B , s th With test temperature T Substituting the three sets of functional relationships into the basic form of the three-parameter bending fatigue equation containing the fatigue limit described in step 5, lg N p = A - B lg( s - s th By doing so, we can obtain the LSAM-50 bending fatigue life prediction equation that takes into account temperature-load coupling and fatigue limit.

[0047] Substituting formulas (1) to (3) into the basic form of the equation lg N p = A - B lg( s - s th Therefore, the LSAM-50 bending fatigue life prediction equation considering temperature-load coupling and fatigue limit at 90% reliability is as follows: (4).

[0048] In summary, it can be seen that this invention has successfully constructed a repeatable LSAM-50 bending fatigue life prediction method that covers the entire process from data acquisition to engineering application. N ~ s ~ s th ~ T This method, for the first time, systematically introduces temperature variables and fatigue limit parameters into a bending fatigue model, enabling accurate description and quantitative prediction of the fatigue behavior and life of LSAM-50 under temperature-load coupling. It effectively solves three major problems of existing models: failure to consider coupling effects, lack of fatigue limit characterization, and absence of a dedicated model for this ultra-large particle size material. This achievement can provide direct theoretical basis and key design parameters for the fatigue resistance design, life prediction, and integrated optimization of LSAM-50 and its pavement structures, thereby significantly improving the scientific rigor, reliability, and economy of long-life asphalt pavement design.

Claims

1. A method for predicting the bending fatigue life of LSAM-50 considering the temperature-load coupling effect and fatigue limit constraints, characterized in that, The specific steps are as follows: Step 1: Prepare LSAM-50 thick rut plate specimens, and then divide them into LSAM-50 beam specimens; Step 2: Bend tests were conducted on the LSAM-50 beam specimens obtained in Step 1 under different temperature conditions to obtain their tensile bending strength at each test temperature. R B ; Step 3: Conduct bending fatigue tests on the LSAM-50 beam specimen obtained in Step 1 under temperature-load coupling, and record its bending fatigue life at different test temperatures and stress levels. N B The test temperature in step 3 is exactly the same as the temperature set for the LSAM-50 bending test in step 2. Step 4: Using the Weibull distribution test method, the bending fatigue test data of the LSAM-50 beam specimen obtained in Step 3 under temperature-load coupling are processed and analyzed to solve for different reliability levels. P Bending fatigue life N p ; Step 5: Construct the LSAM-50 three-parameter bending fatigue equation including the fatigue limit, its basic form being lg N p = A - B lg( σ-C ); In the formula, N p For bending fatigue life under different reliability levels, A , B, C For the fitting parameters, σ For stress; Step 6: Determine the reliability based on the highway grade. P stress σ Let x be the x-axis, lg N p Plot the results at different test temperatures on the ordinate. T The scatter plot below is based on the basic form lg of the LSAM-50 three-parameter bending fatigue equation including the fatigue limit described in step 5. N p = A - B lg( σ-σ th The parameters at different experimental temperatures were obtained by solving the nonlinear programming method. A , B With LSAM-50 bending fatigue limit σ th The fitted value; Step 7, at the test temperature T The x-axis is represented by parameters. A , B and LSAM-50 bending fatigue limit σ th Plot three scatter plots with the vertical axis as the ordinate; perform regression fitting on each scatter plot to obtain the parameters. A , B and bending fatigue limit σ th The corresponding temperature-related regression equations; Step 8, take the result from step 7 A , B , σ th With test temperature T Substituting the three sets of functional relationships into the basic form of the LSAM-50 three-parameter bending fatigue equation containing the fatigue limit described in step 5, lg N p = A - B lg( σ-σ th By doing so, we can obtain the LSAM-50 bending fatigue life prediction equation that takes into account temperature-load coupling and fatigue limit.

2. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint as described in claim 1, characterized in that, In step 1, the LSAM-50 thick rutting plate specimen is formed using the thick rutting test method.

3. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 2, characterized in that, In step 1, the working parameters of the thick rut test method are set as follows: the LSAM-50 rut specimen size is 42cm long × 42cm wide × 12cm thick, and the number of compaction passes is 30.

4. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 3, characterized in that, In step 1: The LSAM-50 beam specimen should be formed by cutting the rut specimen using a high-precision cutting machine. The dimensions of the LSAM-50 beam specimen are 400mm long × 100mm wide × 100mm high. The flatness of the cut end face should be guaranteed to be within ±0.1mm.

5. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 4, characterized in that, In step 2: the test temperature must cover the actual service temperature range of the LSAM-50 flexible base layer, and the number of tests should be evenly distributed at intervals not exceeding 10°C.

6. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 5, characterized in that, In step 3: Stress level S The value range is 0.3 to 0.9, and the interval between each stress level is 0.1 to 0.

2. Stress level S The actual stress experienced by the specimen during a bending fatigue test. σ With flexural tensile strength R B The ratio of [value], therefore, the actual stress experienced by the specimen during the bending fatigue test [is determined by the stress]. σ stress level S × Bending tensile strength R B ,Right now σ=S × R B ; The experiment was set at a high stress level, i.e., stress level S The stress level is 0.7~0.

9. Six to ten parallel tests are conducted under the same conditions, at low stress levels, i.e., stress level... S If the value is 0.3~0.6, then 10~15 sets of parallel tests should be conducted; at the same time, the test results should be discarded, and it should be ensured that there are no less than 5 valid parallel specimens in each set of tests after the discarding.

7. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 6, characterized in that, Step 4 is implemented specifically according to the following steps: Step 4.1: Sort by lifetime. The bending fatigue lives of LSAM-50 under the same temperature and stress level conditions were sorted in ascending order of numerical value, and then labeled as 1, 2, …, i , …, n .in, i This is the sequence number for the bending fatigue life of a single line. n This represents the total number of bending fatigue life data entries under the given temperature and stress level conditions. Step 4.2: Perform reliability calculations; According to the formula P =1- i / (1+ n Calculate the reliability corresponding to the bending fatigue life after each sorting. P ; Step 4.3: Perform linear fitting; Define the bending fatigue life random variable as a Weibull variable. N p ,by x =ln N p x-axis y =lnln(1 / P A scatter plot is drawn with the ordinate as the vertical axis, and the scatter points are fitted using a univariate linear function to obtain the result. x and y regression equation y = bx - β Record regression coefficients b , β ; Step 4.4: Solve for bending fatigue life; If the correlation coefficient of the regression equation is greater than 0.80, then the equivalent bending fatigue life under different reliability levels can be solved using this regression equation. N p .

8. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 7, characterized in that, In step 5: when σ Approaching C hour, N p Approaching infinity, at this point σ Approaching C This is the bending fatigue limit of LSAM-50, denoted as . σ th .

9. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 8, characterized in that, In step 6: the reliability corresponding to the highway P =95%, the reliability corresponding to a Class I highway P =90%, the reliability corresponding to Class II and below highways P =85%.

10. The method for predicting the bending fatigue life of LSAM-50 considering temperature-load coupling effect and fatigue limit constraint according to claim 9, characterized in that, In step 6: When solving the splitting fatigue equation using nonlinear programming, the following solution conditions are set: allowable error 5%, convergence degree 0.0001, derivative calculation using forward difference method, estimation method using tangent function method, and iterative method using conjugate method.

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