Pavement fatigue damage prediction system and method considering semi-rigid base modulus attenuation

Abstract

The application discloses a kind of road surface fatigue damage prediction systems and methods considering semi-rigid base modulus attenuation, it is related to road engineering technical field.The method of the present application obtains the traffic volume and axle load spectrum of road structure in real time based on the road surface fatigue damage prediction system considering semi-rigid base modulus attenuation, according to the test of preparing test piece according to road structure material parameter, determine fatigue life prediction model, modulus attenuation model and dynamic modulus master curve, after obtaining the dynamic modulus of asphalt layer by combining measurement temperature, the cumulative number of times of semi-rigid base fatigue life and the cumulative equivalent axle load number of times of each analysis period are calculated, based on the elastic layered theory system, the asphalt layer bottom tensile strain of asphalt layer in each axle type is calculated in each axle load interval, and the asphalt layer fatigue damage of road structure in total analysis period is determined using asphalt fatigue damage model.The application fully considers the influence of semi-rigid base modulus attenuation on road surface fatigue damage, which is beneficial to the scheme design and scientific maintenance of road structure.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of road engineering, in particular to a pavement fatigue damage prediction system and method considering modulus attenuation of semi-rigid base. BACKGROUND

[0002] Asphalt pavement has been widely used in highway, tunnel, airport and bridge pavement engineering due to its driving comfort and durability. During the service process of asphalt pavement, repeated traffic load and external environment cause various forms of diseases in pavement structure, among which pavement structure fatigue damage is one of the main reasons for pavement structure damage. Precise calculation and prediction of asphalt pavement fatigue damage have important guiding significance for the formulation of pavement structure design scheme and pavement structure maintenance and repair decision.

[0003] As the most commonly used asphalt pavement structure in domestic highway engineering at present, the fatigue damage calculation of semi-rigid base asphalt pavement structure generally adopts Miner linear damage accumulation rule, but this rule does not consider the modulus attenuation of semi-rigid base material with the increase of service life, that is, it ignores the weakening of the mechanical properties of the material itself with the increase of service time, so that the overall fatigue damage of pavement structure is greater than the damage obtained by conventional calculation. In addition, the current fatigue damage calculation method still uses the equivalent equivalent axle load to process the cumulative traffic volume, which leads to the problem of inaccurate calculation of asphalt pavement structure fatigue damage, which is not conducive to the accurate formulation of asphalt pavement structure control design and maintenance and repair decision, and affects the service quality of asphalt pavement. SUMMARY

[0004] The present application aims to solve the above problems and provides a pavement fatigue damage prediction system and method considering modulus attenuation of semi-rigid base, which fully considers the influence of modulus attenuation of semi-rigid base on pavement fatigue damage by real-time acquisition of traffic volume and axle load spectrum of pavement structure, realizes accurate prediction of pavement fatigue damage, and provides basis for the formulation of pavement structure design scheme and maintenance and repair decision.

[0005] To achieve the above purpose, the present application adopts the following technical solutions:

[0006] A pavement fatigue damage prediction system considering modulus attenuation of semi-rigid base, comprising a traffic dynamic weighing device, a pavement structure temperature field measuring device and a pavement data processing device;

[0007] The traffic dynamic weighing device is embedded at the top of the asphalt layer of the pavement structure, and is used to collect the vehicle type, speed and axle load data of the vehicle driving on the pavement structure;

[0008] The pavement structure temperature field measuring device is embedded at different depths of the pavement structure, and is used to measure the internal temperature of each structural layer of the pavement structure;

[0009] The pavement data processing device is connected with the traffic dynamic weighing device and the pavement structure temperature field measuring device respectively, and is used for receiving and processing the measurement data of the traffic axle load measuring device and the pavement structure temperature field measuring device, calculating and outputting the pavement fatigue damage considering the modulus attenuation of the semi-rigid base.

[0010] A pavement fatigue damage prediction method considering the modulus attenuation of the semi-rigid base, adopts the pavement fatigue damage prediction system considering the modulus attenuation of the semi-rigid base as described above, and comprises the following steps:

[0011] Step 1, setting the total length of the pavement fatigue damage prediction, and dividing it into multiple analysis periods according to months;

[0012] Step 2, obtaining the vehicle type, speed and axle load data of the road driving vehicle by using the traffic dynamic weighing device, and calculating the joint axle load spectrum of each analysis period;

[0013] Step 3, preparing semi-rigid base material specimens according to the material parameters of the pavement structure, and performing bending tensile strength test and repeated fatigue loading test by using the semi-rigid base material specimens, to determine the fatigue life prediction model and the modulus attenuation model;

[0014] Step 4, preparing asphalt mixture specimens of each structural layer according to the material parameters of the pavement structure, and performing uniaxial dynamic compression modulus test by using the asphalt mixture specimens, to determine the dynamic modulus master curve of each structural layer;

[0015] Step 5, measuring the average temperature of the asphalt layer of each analysis period by using the pavement structure temperature field measuring device, and substituting it into the dynamic modulus master curve to obtain the dynamic modulus of the asphalt layer of each analysis period;

[0016] Step 6, calculating the layer bottom tensile stress of the semi-rigid base under the action of the standard axle load based on the elastic layered theory system, combining the fatigue life prediction model to obtain the cumulative action frequency of the fatigue life of the semi-rigid base, and converting the axle load data obtained by the traffic dynamic weighing device to obtain the cumulative equivalent axle load action frequency of the semi-rigid base at the end of each analysis period;

[0017] Step 7, determining the modulus value of the semi-rigid base of each analysis period;

[0018] Step 8, for each analysis period, according to the dynamic modulus of the asphalt layer of the semi-rigid base material and the modulus value of the semi-rigid base, combining the pavement structure parameters, based on the elastic layered theory system, calculating the asphalt layer bottom tensile strain of each axle type acting on each axle load interval;

[0019] Step 9, the asphalt layer bottom tensile strain of each axle type in each axle load interval in each analysis period is substituted into the asphalt fatigue damage model to calculate the asphalt layer damage caused by single traffic load of each axle type in each axle load interval, and the asphalt layer fatigue damage of the pavement structure in the whole total analysis period is obtained.

[0020] Preferably, the pavement structure of the asphalt pavement is arranged from top to bottom as an asphalt layer, a semi-rigid base and a soil base, wherein a plurality of structural layers are arranged in the asphalt layer, and the plurality of structural layers are arranged from top to bottom as an upper surface layer, a middle surface layer and a lower surface layer, and the semi-rigid base is arranged as a single-layer structure or a double-layer structure.

[0021] Preferably, the combined axle load spectrum calculation formula is as follows:

[0022]

[0023] In the formula, i is the axle type serial number, 1≤i≤4 and i is a positive integer, wherein i=1 is a single axle single tire, i=2 is a single axle double tire, i=3 is a double axle, and i=4 is a triple axle; j is the axle load interval serial number, j=1, 2, …, N, N is the total number of axle load intervals; m is the vehicle type serial number, 1≤m≤M and m is a positive integer, M is the total number of vehicle types; JALDF ij is a combined axle load spectrum, which is used to represent the percentage of different axle types in different axle load intervals; NAPT mi is the average number of axles of the axle type i in the mth vehicle type; ALDF mij is the axle load distribution coefficient of the axle type i in the mth vehicle type in the jth axle load interval; VTDC m is the wheel type distribution coefficient of the mth vehicle type.

[0024] Preferably, in step 7, the modulus value of the semi-rigid base in the first analysis period is obtained through the repeated fatigue loading test in step 3;

[0025] The modulus value determination process of the semi-rigid base in the remaining analysis period is as follows:

[0026] If the cumulative equivalent axle load action frequency of the semi-rigid base at the end of the current analysis period is less than the cumulative action frequency of the semi-rigid base fatigue life calculated in step 6, the modulus value of the semi-rigid base in the next analysis period is calculated by using the modulus attenuation model;

[0027] If the cumulative equivalent axle load action frequency of the semi-rigid base at the end of the current analysis period is not less than the cumulative action frequency of the semi-rigid base fatigue life calculated in step 6, the modulus value of the semi-rigid base is set as a fixed value, and the value range is 500-2000 MPa.

[0028] Preferably, when the semi-rigid base layer is a double-layer structure, the calculation position of the modulus attenuation model is set at the bottom of the semi-rigid base layer when calculating the modulus value of the semi-rigid base layer by using the modulus attenuation model.

[0029] Preferably, in step 9, the asphalt fatigue damage model is:

[0030]

[0031] Wherein,

[0032]

[0033]

[0034] In the formula, D is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. ij is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. fij is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. a is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. b is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. T1 is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. a is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. a is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient. aij is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient.

[0035] Preferably, the asphalt layer fatigue damage of the pavement structure in the total analysis period is:

[0036]

[0037] In the formula, D is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the two-way initial annual average daily traffic of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is a direction coefficient; and LDF is a lane coefficient.

[0038] The present application has the following beneficial technical effects:

[0039] The present application provides a pavement fatigue damage prediction system considering modulus attenuation of semi-rigid base layer, which accurately obtains specific values of pavement structure material parameters after reduction with the increase of pavement structure traffic by real-time measurement of traffic volume, axle load spectrum and temperature field data of pavement structure, and provides important process data for accurate prediction of pavement fatigue damage.

[0040] This invention also proposes a method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base layers. This method fully considers the impact of the modulus decay of semi-rigid base layers on pavement fatigue damage. Combined with a method for determining the modulus of semi-rigid base layer materials that considers modulus decay, the method observes the operation of the pavement structure during its service life and uses the elastic layered theory system to obtain the mechanical response of the bottom layer of the asphalt pavement structure in different analysis periods. This enables accurate prediction of pavement fatigue damage, which is beneficial for the formulation of structural design schemes and maintenance decisions for asphalt pavements, and lays the foundation for the safe operation of pavement structures. Attached Figure Description

[0041] Figure 1 This is a schematic diagram of the pavement structure of the experimental section.

[0042] Figure 2 This is a single-axle, single-tire axle load spectrum.

[0043] Figure 3 This is the axle load spectrum for single-axle dual-tire systems.

[0044] Figure 4 This is a biaxial axis loading spectrum.

[0045] Figure 5 This is the three-axis axial load spectrum.

[0046] Figure 6 The dynamic modulus master curves are shown below, where SMA13 is the dynamic modulus master curve for the upper layer, AC-20 is the dynamic modulus master curve for the middle layer, and AC-25 is the dynamic modulus master curve for the lower layer.

[0047] Figure 7 This is a graph showing the cumulative fatigue development trend of the pavement structure.

[0048] In the diagram, 1 is the top layer, 2 is the middle layer, 3 is the bottom layer, 4 is the semi-rigid base layer, 5 is the semi-rigid subbase layer, and 6 is the subgrade. Detailed Implementation

[0049] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0050] Example 1

[0051] This embodiment takes a highway in a certain region as an example, selecting an asphalt pavement as the experimental section on the highway, such as... Figure 1 As shown, the experimental road section consists of an asphalt layer, a semi-rigid base course, a semi-rigid subbase course, and a subgrade 6 from top to bottom. The asphalt layer contains multiple structural layers, which are, from top to bottom, the top layer 1, the middle layer 2, and the bottom layer 3, respectively designated as SMA-13, AC-20, and AC-25 layers. The semi-rigid base course 4 and the semi-rigid subbase course 5 are both cement-stabilized crushed stone layers, paved with cement-stabilized crushed stone.

[0052] The pavement fatigue damage prediction system considering the modulus attenuation of semi-rigid base is installed on the experimental section. The pavement fatigue damage prediction system considering the modulus attenuation of semi-rigid base in the embodiment comprises a traffic dynamic weighing device, a pavement structure temperature field measuring device and a pavement data processing device. The traffic dynamic weighing device is embedded on the top of the asphalt layer of the pavement structure to collect the vehicle type, speed and axle load data of the vehicle driving on the pavement structure. The pavement structure temperature field measuring device is embedded at different depths of the pavement structure to measure the internal temperature of each structural layer of the pavement structure. The pavement data processing device is connected with the traffic dynamic weighing device and the pavement structure temperature field measuring device to receive and process the measurement data of the traffic axle load measuring device and the pavement structure temperature field measuring device, calculate and output the pavement fatigue damage considering the modulus attenuation of semi-rigid base.

[0053] The real-time axle load spectrum and temperature field of the experimental section are obtained in real time by using the pavement fatigue damage prediction system considering the modulus attenuation of semi-rigid base, and the pavement fatigue damage of the experimental section is predicted by using a pavement fatigue damage prediction method considering the modulus attenuation of semi-rigid base provided by the present application. The method specifically comprises the following steps:

[0054] Step 1, the total fatigue damage prediction time is set to 15 years, and the total fatigue damage prediction time is divided into 180 analysis periods in units of months.

[0055] Step 2, the traffic dynamic weighing device is used to obtain the vehicle type, speed and axle load data of the vehicle driving on the pavement, and the combined axle load spectrum of each analysis period is calculated.

[0056] In the embodiment, the traffic dynamic weighing device is used to obtain the axle load spectrum of 11 types of axle vehicles, the two-way initial annual average daily traffic volume AADTT of the vehicle with six or more wheels in each analysis period, the direction coefficient DDF, the lane coefficient LDF and the wheel type distribution coefficient, and the combined axle load spectrum of various axle types is calculated, as shown in formula (1):

[0057]

[0058] In the formula, i is the axle type serial number, 1≤i≤4 and i is a positive integer, wherein i=1 is single axle single tire, i=2 is single axle double tire, i=3 is double axle and i=4 is triple axle; j is the axle load interval serial number, j=1, 2, …, N, N is the total number of axle load intervals; m is the vehicle type serial number, 1≤m≤M and m is a positive integer, M is the total number of vehicle types, and the total number of vehicle types M is 11 in the embodiment; JALDF ij is the combined axle load spectrum, which is used to represent the percentage of axle type i in the jth axle load interval, i.e. the percentage of different axle types in different axle load intervals; NAPT miis the average number of axles of the i-th axle type in the m-th vehicle class; ALDF mij is the axle load distribution factor of the i-th axle type in the m-th vehicle class in the j-th axle load interval; VTDC m is the wheel type distribution factor of the m-th vehicle class.

[0059] In this embodiment, the two-way initial annual average daily traffic volume AADTT of the two-axle six-wheel or more vehicle and the wheel type distribution factor in the first to twelfth analysis periods are shown in Table 1, and the wheel type distribution factor in the first to twelfth analysis periods is shown in Table 2, the direction factor DDF is 0.5, and the lane factor LDF is 0.5. Figures 2-5 is the combined axle load spectrum of various axle types, wherein, Figure 2 is the single-axle single-tire axle load spectrum, Figure 3 is the single-axle double-tire axle load spectrum, Figure 4 is the double-axle axle load spectrum, Figure 5 is the triple-axle axle load spectrum.

[0060] Table 1 AADTT in the first to twelfth analysis periods

[0061] Analysis period 1 2 3 4 5 6 7 8 9 10 11 12 AADTT 1996 1607 2205 2849 2994 3231 2838 2603 3372 2850 2342 1876

[0062] Table 2 Wheel type distribution factor in the first to twelfth analysis periods

[0063]

[0064] Step 3, prepare a semi-rigid base layer material test piece according to the material parameters of the pavement structure, and perform a bending tensile strength test and a repeated fatigue loading test on the semi-rigid base layer material test piece, in this embodiment, the bending tensile strength of the bending tensile strength test is set to 1.9 MPa, the repeated fatigue loading test is performed using different stress ratios, the fatigue life data and modulus attenuation data of the semi-rigid base layer material test piece are collected, and the fatigue life prediction model and the modulus attenuation model are determined by regression analysis on the fatigue life data and modulus attenuation data of the semi-rigid base layer material test piece:

[0065]

[0066] In the formula, N is the number of fatigue loading actions; is the stress ratio; σ is the stress, the unit is MPa; S is the bending tensile strength, the unit is MPa; E N is the bending modulus of the semi-rigid base layer material when the fatigue loading number is N, the unit is MPa; E0 is the initial bending modulus of the semi-rigid base layer material, the unit is MPa; e is the natural constant.

[0067] Step 4, asphalt mixture test pieces of each structural layer are prepared according to the material parameters of the pavement structure, uniaxial dynamic compression modulus tests are carried out on the asphalt mixture test pieces at different temperatures and different frequencies, fitting analysis is carried out on the test results of the uniaxial dynamic compression modulus tests, and the dynamic modulus master curve of each structural layer in the asphalt layer is determined, as shown in FIG. 1. Figure 6

[0068] Step 5, the average temperature of the asphalt layer in each analysis period is measured by using the pavement structure temperature field measuring device and substituted into the dynamic modulus master curve, and the dynamic modulus of the asphalt layer in each analysis period is obtained.

[0069] In this embodiment, the dynamic modulus of each structural layer in the asphalt layer in the first to twelfth analysis periods is shown in Table 3.

[0070] Table 3 Dynamic modulus of each structural layer in the asphalt layer in the first to twelfth analysis periods

[0071]

[0072] Step 6, according to the initial parameters of the pavement structure, as shown in Table 4. Based on the elastic layered theory system, the bottom tensile stress of the semi-rigid base under the action of the standard axle load is calculated to be 0.174, and combined with the fatigue life prediction model in step 3, the cumulative action frequency of the semi-rigid base is calculated to be 5.1 x 10 9 .

[0073] Table 4 Initial parameters of pavement structure

[0074]

[0075] According to the axle load data obtained by the traffic dynamic weighing device, the cumulative equivalent axle load action frequency of the semi-rigid base at the end of each analysis period is obtained, as shown in Table 5.

[0076] Table 5 Cumulative equivalent axle load action frequency of semi-rigid base at the end of each analysis period

[0077]

[0078]

[0079] Step 7, the modulus value of the semi-rigid base in each analysis period is determined, wherein the modulus value of the semi-rigid base in the first analysis period is obtained by the repeated fatigue loading test in step 3; the modulus value of the semi-rigid base in the remaining analysis periods is determined as follows:

[0080] ​If the accumulated equivalent axle load action times of the semi-rigid base at the end of the current analysis period is less than the accumulated action times of the semi-rigid base fatigue life calculated in step 6, the modulus decay model is used to calculate the semi-rigid base modulus value of the next analysis period.

[0081] If the accumulated equivalent axle load action times of the semi-rigid base at the end of the current analysis period is not less than the accumulated action times of the semi-rigid base fatigue life calculated in step 6, the semi-rigid base modulus value is set to a fixed value, and the value range is 500-2000MPa.

[0082] In this embodiment, the semi-rigid base modulus value of each analysis period is attenuated according to the modulus decay model and the equivalent accumulated axle load action times at the end of each analysis period, and the stress ratio of the pavement structure in the last analysis period, and the semi-rigid base modulus value starts to take a fixed value at the 147th analysis period, as shown in Table 6.

[0083] Table 6 Semi-rigid base modulus value of each analysis period

[0084]

[0085] Step 8, according to the asphalt layer dynamic modulus of the semi-rigid base material in each analysis period and the semi-rigid base modulus value, combined with the pavement structure parameters (including pavement structure thickness and Poisson's ratio), based on the elastic layer theory system, the asphalt layer bottom tensile strain of each axle type acting on each axle load interval in each analysis period is calculated, and in this embodiment, the middle value of each axle load interval is taken as the asphalt layer bottom tensile strain of the axle load calculation, and part of the axle load interval is shown in Table 7.

[0086] Table 7 Strain of single axle dual tire in axle load interval [108kN, 112.5KN] in the first-12th analysis period

[0087]

[0088] Step 9, according to the asphalt layer bottom tensile strain of each axle type acting on each axle load interval in each analysis period, the asphalt layer damage caused by single traffic load of each axle type in each axle load interval is calculated by using the asphalt fatigue damage model, and the asphalt layer fatigue damage of the pavement structure in the whole total analysis period is obtained.

[0089] In this embodiment, the asphalt fatigue damage model is:

[0090]

[0091] Wherein,

[0092]

[0093]

[0094] In the formula, D ij is the asphalt layer fatigue damage generated by the axle type i in the jth axle load interval when passing through the pavement structure in the analysis period; N fij is the pavement structure fatigue life of the axle type i in the jth axle load interval when passing through the pavement structure in the analysis period; β is the target reliability; k a is the seasonal frozen soil area adjustment coefficient; k b is the fatigue loading mode coefficient; k T1 is the temperature adjustment coefficient; E a is the dynamic modulus of asphalt mixture; VFA is the asphalt saturation of asphalt mixture; h a is the thickness of the asphalt mixture layer, in mm; ε aij is the asphalt layer bottom tensile strain generated by the axle type i in the jth axle load interval when passing through the pavement structure.

[0095] In this embodiment, the median value in the axle load interval is taken as the calculation axle load when calculating the asphalt layer bottom tensile strain, and the mechanical response calculation module in the existing technology “Dao Keyi” system platform (i.e. an online design system for asphalt pavement structure of highway-related research institutes and design institutes nationwide) is used to calculate based on the elastic layered system theory. During the calculation process, the calculation section position refers to the related pavement structure parameters set in the asphalt pavement mechanics-experience design method (MEPDG) and “JTG D50-2017 Highway Asphalt Pavement Design Specification”.

[0096] Based on the asphalt layer fatigue damage generated by each axle type in different axle load intervals when passing through the pavement structure in each analysis period, combined with the bidirectional initial annual average daily traffic volume, direction coefficient and lane coefficient of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device, the asphalt layer fatigue damage of the pavement structure in the total analysis period is obtained, as shown in formula (5):

[0097]

[0098] In the formula, D is the asphalt layer fatigue damage of the pavement structure in the total analysis period; AADTT is the bidirectional initial annual average daily traffic volume of the double-axle six-wheel or more vehicles measured by the traffic dynamic weighing device; DDF is the direction coefficient; and LDF is the lane coefficient.

[0099] In this embodiment, the asphalt layer fatigue damage of the pavement structure in the entire total analysis period is calculated to be 0.56, and the cumulative fatigue development trend of the pavement structure is further obtained, as shown in formula (6): Figure 7 As shown in formula (6), it can be obtained that Figure 7 After the modulus of the semi-rigid base layer decays to a fixed value, the asphalt pavement fatigue damage appears rapid growth.

[0100] Therefore, the method fully considers the influence of the modulus attenuation of the semi-rigid base on the fatigue damage of the pavement, realizes the accurate prediction of the fatigue damage condition of the pavement structure according to the axle load spectrum and the temperature field collected by the system in real time, and provides a basis for the controlled design of the asphalt pavement structure and the maintenance and repair decision.

[0101] Of course, the above description is not a limitation of the present application, and the present application is not limited to the above examples. Changes, modifications, additions or replacements made by the skilled in the art within the essential scope of the present application should also belong to the protection scope of the present application.

Claims

1. A method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses, characterized in that, A pavement fatigue damage prediction system considering the modulus decay of a semi-rigid base course is adopted. This system includes a traffic dynamic weighing device, a pavement structure temperature field measurement device, and a pavement data processing device. The traffic dynamic weighing device is embedded in the top of the asphalt layer of the pavement structure to collect data on vehicle type, speed, and axle load. The pavement structure temperature field measurement device is embedded at different depths within the pavement structure to measure the internal temperature of each structural layer. The pavement data processing device is connected to both the traffic dynamic weighing device and the pavement structure temperature field measurement device to receive, store, process, calculate, and output pavement fatigue damage considering the modulus decay of the semi-rigid base course. Includes the following steps: Step 1: Set the total duration for predicting road fatigue damage, and divide it into multiple analysis periods by month; Step 2: Use a traffic dynamic weighing device to obtain vehicle type, speed and axle load data of vehicles traveling on the road, and calculate the joint axle load spectrum for each analysis period; Step 3: Prepare semi-rigid base material specimens based on the material parameters of the pavement structure, and conduct flexural tensile strength tests and repeated fatigue loading tests using the semi-rigid base material specimens to determine the fatigue life prediction model and modulus decay model; Step 4: Prepare asphalt mixture specimens for each structural layer according to the material parameters of the pavement structure, and conduct uniaxial dynamic compression modulus tests using the asphalt mixture specimens to determine the master curve of the dynamic modulus of each structural layer. Step 5: Measure the average temperature of the asphalt layer in each analysis period using the pavement structure temperature field measuring device and substitute it into the dynamic modulus master curve to obtain the dynamic modulus of the asphalt layer in each analysis period. Step 6: Calculate the tensile stress at the bottom of the semi-rigid base layer under standard axle load based on the elastic layer theory system. Combined with the fatigue life prediction model, obtain the cumulative number of fatigue life cycles of the semi-rigid base layer. Convert the axle load data obtained by the traffic dynamic weighing device to obtain the cumulative equivalent axle load cycles of the semi-rigid base layer at the end of each analysis period. Step 7: Determine the semi-rigid base modulus value for each analysis period; Step 8: For each analysis period, based on the dynamic modulus of the asphalt layer and the modulus of the semi-rigid base material, combined with the pavement structure parameters, and based on the elastic layered theory system, calculate the tensile strain at the bottom of the asphalt layer for each axle type acting on each axle load interval. Step 9: Substitute the tensile strain at the bottom of the asphalt layer of each axle type acting on each axle load interval in each analysis period into the asphalt fatigue damage model, calculate the asphalt layer damage caused by a single traffic load for each axle type in each axle load interval, and obtain the asphalt layer fatigue damage of the pavement structure in the entire analysis period. In step 7, the semi-rigid base modulus value for the first analysis period is obtained through the repeated fatigue loading test in step 3. The process for determining the semi-rigid base modulus value for the remaining analysis periods is as follows: If the cumulative equivalent axial load application times of the semi-rigid base layer are less than the cumulative fatigue life application times of the semi-rigid base layer calculated in step 6 at the end of the current analysis period, the modulus value of the semi-rigid base layer for the next analysis period is calculated using the modulus decay model. If, at the end of the current analysis period, the cumulative equivalent axial load application times of the semi-rigid base layer are not less than the cumulative fatigue life application times of the semi-rigid base layer calculated in step 6, then the modulus value of the semi-rigid base layer will be set to a fixed value, with a range of 500 to 2000 MPa.

2. The method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses according to claim 1, characterized in that, The pavement structure of asphalt pavement consists of an asphalt layer, a semi-rigid base course, and a subgrade from top to bottom. The asphalt layer contains multiple structural layers, which are the top layer, the middle layer, and the bottom layer from top to bottom. The semi-rigid base course is configured as a single-layer or double-layer structure.

3. The method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses according to claim 1, characterized in that, The formula for calculating the combined axial load spectrum is: In the formula, i is the axle type number, 1≤i≤4 and i is a positive integer, where i=1 is single axle single tire; i=2 is single axle dual tire; i=3 is dual axle; and i=4 is triple axle; j is the axle load interval number, j=1,2,…,N, where N is the total number of axle load intervals; m is the vehicle type number, 1≤m≤M and m is a positive integer, and M is the total number of vehicle types; JALDF ij This is a combined axle load spectrum, used to represent the percentage of different axle types in different axle load ranges; NAPT mi Let be the average number of axles of axle type i in vehicle class m; LADF mij VTDC is the axle load distribution coefficient of axle type i in vehicle class m within the axle load range of level j. m Let be the wheel type distribution coefficient for vehicle class m.

4. The method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses according to claim 1, characterized in that, When the semi-rigid base layer is a double-layer structure, the calculation position of the modulus attenuation model is set at the bottom of the semi-rigid base layer when calculating the modulus value of the semi-rigid base layer using the modulus attenuation model.

5. The method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses according to claim 1, characterized in that, In step 9, the asphalt fatigue damage model is as follows: in, In the formula, D ij N represents the asphalt layer fatigue damage caused by axle type i passing through the pavement structure once within the j-th axle load range during the analysis period; fij β represents the fatigue life of the pavement structure when axle type i passes through the pavement structure once within the j-th axle load range during the analysis period; β represents the target reliability; k a k is the adjustment factor for seasonally frozen soil regions. b k represents the fatigue loading mode coefficient. T1 E is the temperature adjustment factor. a VFA is the dynamic modulus of asphalt mixture; h is the asphalt saturation of asphalt mixture. a ε represents the thickness of the asphalt mixture layer. aij The tensile strain at the bottom of the asphalt layer is generated when axle type i passes through the pavement structure in the j-th axle load range.

6. The method for predicting pavement fatigue damage considering the modulus decay of semi-rigid base courses according to claim 5, characterized in that, The fatigue damage of the asphalt layer of the pavement structure during the total analysis period is as follows: In the formula, D represents the fatigue damage of the asphalt layer of the pavement structure during the total analysis period; AADTT represents the initial annual average daily traffic volume of two-axle vehicles with six or more wheels measured by the traffic dynamic weighing device; DDF represents the directional coefficient; and LDF represents the lane coefficient.

Images