CN110907296A - Method for identifying flow times of dynamic creep test of asphalt mixture - Google Patents
Method for identifying flow times of dynamic creep test of asphalt mixture Download PDFInfo
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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Abstract
The invention discloses a method for identifying the flow times of a dynamic creep test of an asphalt mixture. The MATLAB program based on the three-stage model algorithm is developed, the damage stages can be automatically divided, the dividing points and the flowing times can be identified, and the method is simple and convenient. The recognition algorithm developed by the invention can control the calculation precision within 3 percent aiming at the first stage and the calculation precision within 1 percent aiming at the second stage, namely the error of the flowing times does not exceed 1 percent, the calculation result has high accuracy, and the requirements of construction quality control and scientific research work can be met.
Description
Technical Field
The invention belongs to the technical field of road engineering, and particularly relates to a method for identifying the flowing times of a dynamic creep test of an asphalt mixture.
Background
Under the condition of high temperature in summer, the response deformation of the asphalt pavement under the action of traffic load increases along with the time, the response deformation is gradually recovered along with the time after the vehicle load disappears, and partial deformation can be permanently maintained, namely the permanent deformation of the asphalt pavement. Permanent deformation gradually accumulates to form ruts, which is a direct reflection of the viscoelastic properties of asphalt pavement. Based on the viscoelastic property of the asphalt mixture, in Simple Performance Tests (SPT) proposed by the American national road cooperative research project research Report (NCHRP Report 465), a repeated loading permanent deformation Test is recommended to be one of tests for evaluating the high-temperature rutting resistance of the asphalt mixture, and the dynamic response of a road surface under different load and environmental conditions is simulated, namely a dynamic creep Test. In the dynamic creep test, the sensor collects axial accumulated permanent strain data and draws a relation graph of accumulated permanent strain and repeated load action times. The permanent strain curve of an asphalt mixture under the action of repeated loads generally consists of three stages:
initial stage (migration phase): the cumulative permanent strain increases rapidly, but the strain rate decreases gradually;
second stage (stationary phase): the accumulated permanent strain is stably increased, and the strain rate is basically kept unchanged;
third stage (failure stage): the accumulated permanent strain and the strain rate are both increased sharply, and shear flow occurs until the test piece is damaged.
The NCHRP report indicates that the cumulative permanent set is not appropriate as an index for evaluating the high temperature performance of the asphalt mixture, and the number of rheologies (Fn) is recommended as an important index for this test. The physical meaning of the method is the starting point of the asphalt mixture entering the shearing flow deformation stage. And expressing the load acting times corresponding to the dividing point of the second stage and the third stage in the permanent strain curve of the asphalt mixture. The larger the rheological frequency of the asphalt mixture is, the smaller the probability of creep damage of the asphalt pavement is, so that the method can be used for evaluating the high-temperature performance of the asphalt pavement. Aiming at the calculation of the rheological times, the permanent strain curve (permanent strain epsilon) of the asphalt mixture is mostly calculated by various mathematical modelspThe number of times of load action N) is fitted and then the equation derivative is calculated to calculate the permanent responseBecome epsilonpRate of change (epsilon) of number of times N of load applicationpslope) which is kept constant for a certain period of time after the permanent strain rate is reduced to the minimum, and the load action times N and the change rate epsilon corresponding to the point where the permanent strain rate begins to increasepslope is the number of flows Fn and the creep rate. However, these model models appear to adequately characterize the primary stage only and do not effectively describe the secondary and tertiary stages.
The default of an asphalt mixture comprehensive test system (UTM) adopted by the dynamic creep test is to calculate the rheological times by using a Francken model, but the accuracy of the model is still to be tested. The patent of chinese utility model with the publication number of grant CN105891013A discloses a method for determining rheological times of high-temperature creep instability points of asphalt mixtures, which obtains shear strength parameters through unconfined compressive strength tests and uniaxial injection tests, and fits a fatigue equation by combining uniaxial dynamic creep, so as to predict the rheological times of the creep curve instability points under any load level. The patent of the utility model with the publication number of CN107966548A discloses a method for predicting the occurrence time of a track on an asphalt pavement, which utilizes an unconfined compressive strength test and a triaxial compression test to determine the shear strength parameters of an asphalt mixture, and combines a triaxial dynamic creep test and finite element software to predict the occurrence time of the instability of the pavement material. However, the dynamic creep test of the above two methods does not preferably check the flow number calculation model, and the calculation result of the flow number directly influences the establishment of the subsequent fatigue equation and the prediction model. The chinese utility model patent with the publication number of CN107807055A discloses a method for processing and analyzing data of a multi-sequence dynamic creep test of an asphalt mixture, which calculates the average permanent strain rate of each loading sequence and obtains three indexes for evaluating the creep characteristics of the asphalt mixture: strain rate sensitivity index SRSI, composite average permanent strain rate CAPSR, composite creep stiffness modulus CCSM. However, the calculation for each loading sequence causes the calculation process to be too heavy, the three constructed evaluation indexes are not widely verified, and the index of the flow times recommended by the abandon specification lacks confidence.
At present, a perfect model for calculating the flowing times of the dynamic creep test of the asphalt mixture does not exist.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide the method for identifying the flow times of the dynamic creep test of the asphalt mixture, which can accurately describe each creep stage and is simple in calculation.
The method for identifying the flow times of the asphalt mixture dynamic creep test comprises the following steps:
s1, acquiring permanent deformation curve data of a dynamic creep test of an asphalt mixture test piece according to the test;
s2, defining a first-stage description model;
s3, in the step of selecting S1, in the range of 100 to the total loading times NmaxK sets of permanent deformation data are adopted, namely, an array (100, K) is selectedth)，KthRepresenting the Kth permanent deformation data, then adopting the selected array to fit the first-stage model in the step S2, and determining regression coefficients a and b in the model to obtain a first-stage model equation; then, calculating the accumulated permanent strain corresponding to the Kth loading time according to a first-stage model equation;
s4, according to the accumulated permanent strain difference D of the Kth time actually measured in the step S1 and the accumulated permanent strain difference D corresponding to the Kth time loading times calculated in the step S3eJudging whether iterative calculation is needed, if so, deleting the selected K groups of data and setting K to K-1, and carrying out iterative calculation according to the step S3 until judging the initial point N of the second stagePS(also the end of the first stage), the next step is entered; if the iterative computation is not needed, directly entering the next step;
s5, defining a model of a second stage;
s6, in the step of selecting S1, in the range of 100 to the total loading times NmaxM is equal to K-NPS+1 sets of permanent deformation data, i.e. selecting the array (N)PS，Kth) Setting the initial point of the second stage as the new origin of the coordinate axis; performing second-stage model fitting by using the M groups of data after adjusting the origin to ensureDetermining regression coefficients c and d to obtain a second-stage model equation; the Mth permanent deformation data in this step is Mth，Mth＝Kth-NPS；
S7, calculating an intercept d and a current strain epsilon 'on a longitudinal axis of a second-stage model equation'pAbsolute value of maximum ratio RdJudging whether iterative calculation is needed, if so, deleting selected M groups of data and setting M to be M-1, and carrying out iterative calculation according to the step S6 until judging the initial point N of the third stageST(also end of the second stage), NSTNamely the flowing times; if no iterative calculations need to be performed, the identification procedure terminates.
In step S1, the permanent deformation curve data loading factor is the number of times that the axial cumulative strain reaches 5% or the number of times that the load acts reaches 10000.
In step S2, the first-order model is:
εp＝aNbN＜NPS
wherein epsilonpFor accumulating the permanent strain, N is the number of repeated loading times, a and b are regression coefficients, and NPSThe loading times corresponding to the initial point of the second stage (i.e. the terminal point of the first stage).
In the step S4, the cumulative permanent strain difference D between the K-th cumulative permanent strain actually measured in the step S1 and the K-th loading frequency calculated in the step S3eThe calculation formula of (2) is as follows:
wherein: epsilonpMeasuredRepresenting the cumulative permanent strain, epsilon, of the actual measurementpPredictedAnd representing the predicted accumulated permanent strain of the corresponding loading times of the current K.
In step S4, the method for determining whether iterative calculation is required is as follows:
A. if D iseIs less than 3 percent, and the loading times corresponding to the current K are equal to NmaxDescription of the permanent deformationThe curve has no second stage, the identification is stopped, and the test curve has no flowing times;
B. if D iseIs less than 3 percent, and the loading times corresponding to the current K are less than NmaxThen current KthThe corresponding loading times are the initial points of the second stage;
C. if not, iterative calculation is performed.
In step S5, the second stage model is:
εp＝εPs+c(N-NPS)，NPS≤N＜NST
εp′＝cN′+d；
in the formula: epsilonPSRepresenting the corresponding permanent strain of the initial point in the second stage, c and d representing regression coefficients, NSTRepresenting the loading times corresponding to the initial point of the third stage; epsilon'pFor the adjusted permanent set, N' is the adjusted number of loads.
In the step S6, the method of selecting data and setting the initial point of the second stage as the new origin of the coordinate axis includes:
the first stage comprises NPSGroup data, therefore, M ═ K-N remainsPS+1 data remains including the end point N of the first stagePSAnd epsilonPSI.e. selecting the remaining array (N)PS，Kth)；
Setting the initial point of the second stage (x ═ N)PS，y＝εPS) Is a new origin of the coordinate axis; from the remaining array (N)PS，Kth) N is subtracted from the cumulative permanent setPSValue and epsilonPSValues of the number of times of loading and permanent set after adjustment were designated as ε'pAnd N'.
In the step S7, the absolute value R of the ratiodThe calculation formula of (2) is as follows:
in the formula: d represents the fitting intercept, ε'pRepresenting the current strain value.
In the step S7, the method for determining whether iterative computation is required is as follows:
A. if R isd< 1% (or d > 0), and the number of loads corresponding to the current M is equal to (N)max-NPS) Indicating that the permanent deformation curve has no third stage, stopping identification, and the test curve has no flowing times;
B. if R isd< 1% (or d > 0), and the number of loads corresponding to the current M is less than (N)max-NPS) If the current M corresponding loading times is the initial point of the third stage, add back NPSObtaining the original loading times;
C. if not, iterative calculation is performed.
The algorithm of the present invention is written as MATLAB program code, the code of which is as follows:
clear% delete all variables of workspace
name [ 'D: \ user-defined data file · xls' ]; % read user-defined Excel file in D disk directory
fori-the maximum number of user-input loads Nmax1: 1% first stage
A＝xlsread(name,'A1:ANmax') to a host; % read files A2 to ANmaxData of line and assign to A1
C＝xlsread(name,'C1:CNmax') to a host; % read files C2 to CNmaxData of line and assign value to C1
x1＝A(1:i)；
y1＝C(1:i)；
fun @ (x, x1) x (1) × 1 ^ x (2); % definition function y ═ ax ^ b; x (1) and x (2) respectively as a and b
t ═ 10.2; % given a b initial value
x ═ lsqcurvefit (fun, t, x1, y 1); % solution a b
y2＝x(1)*A(i).^x(2)；
y3＝abs(y2-C(i))；
De＝y3/C(i)；
if De<0.03&&i＝＝Nmax
disp ([ 'the permanent deformation curve does not have the second stage' ])
break
elseif De<0.03&&i<Nmax
disp ([ 'this permanent deformation curve exists in the second stage, starting at' num2str (i) ])
a＝i；
x(1)
x(2)
A(i)
C(i)
break
else
continue
end
end
for j＝Nmax1: a% second stage
x6＝A(a)*ones(j+1-a,1)；
y6＝y2*ones(j+1-a,1)；
x5＝A(a:j)-x6；
y5＝C(a:j)-y6；
fun1＝@(z,x5)z(1)*x5+z(2)；
m ═ 11; % given c d initial value
z ═ lsqcurvefit (fun1, m, x5, y 5); % solution c d
Rd＝abs(z(2)/C(j))；
if(Rd<0.01|z(2)>0)&&j＝＝Nmax
disp ([ 'the permanent deformation curve does not exist the third stage' ])
break
elseif(Rd<0.01|z(2)>0)&&j<626
disp ([ 'this permanent deformation curve exists in the third stage, and the end point of the second stage is' num2str (j) ])
b＝j；
A(j)
C(j)
break
else
continue
end
end
for i 1% third stage
x10＝A(b:517)；
y10＝C(b:517)；
fun2＝@(u,x10)u(1)*exp(u(2)*x10)+u(3)*exp(u(4)*x10)；
p＝[239000-0.0002322 0 0.003729]；
u-lsqcurvefit (fun2, p, x10, y 10); % solution f
end
for i 1% drawing
x8＝A(1:a)；
y8＝C(1:a)；
plot the% first stage of plot (x8, y8, x8, x (1) × 8 ^ x (2), 'r')%
hold on
plot of plot (x5+ x6, y5+ y6, x5+ x6, z (1) × 5+ y6, 'r')% of the second phase
plot the plot of plot (x10, y10, x10, u (1) × exp (u (2) × 10) + u (3) × exp (u (4) × 10), 'r')% of the third stage
end
The invention provides an algorithm for representing a permanent deformation curve in an asphalt mixture dynamic creep test by using a multi-stage model, and a method for automatically identifying and dividing multi-stage calculation flow times. When a dynamic creep test is carried out to analyze the high-temperature rutting resistance of the asphalt mixture, the identification algorithm and the calculation method can simply and conveniently divide a dynamic creep permanent deformation curve and accurately calculate the flowing times. Therefore, scientific research work can be effectively assisted, production and construction can be effectively guided, the accuracy of the calculation result of the dynamic creep test can be ensured, and the quality of construction and production can be controlled.
Compared with the prior art, the invention has the beneficial technical effects that:
(1) the multi-stage model can fully represent the characteristics of the permanent deformation curve of the dynamic creep test of the asphalt mixture, and the characterization model is independently established for each stage by combining the constitutive characteristics of the asphalt mixture in different stages, so that the multi-stage model is more in line with the actual situation.
(2) The MATLAB program based on the multi-stage model algorithm is developed, the damage stages can be automatically divided, the dividing points and the flowing times can be identified, and the method is simple and convenient.
(3) The recognition algorithm developed by the invention can control the calculation precision within 3 percent aiming at the first stage and the calculation precision within 1 percent aiming at the second stage, namely the error of the flowing times does not exceed 1 percent, the calculation result has high accuracy, and the requirements of construction quality control and scientific research work can be met.
(4) The identification algorithm developed by the invention not only can calculate the flowing times, but also can provide detailed information such as loading times, accumulated deformation total amount, curve slope, curve intercept and the like when different stages are finished, and provides information for further analyzing the creep characteristic of the asphalt mixture.
Drawings
FIG. 1 is a schematic diagram of a dynamic creep test load loading waveform.
FIG. 2 is a graph showing the permanent set curve of the dynamic creep test.
FIG. 3 is a diagram illustrating the three-stage division and the calculation of the number of flow times after the identification.
Fig. 4 is a schematic diagram of the permanent deformation curve identification result of the embodiment.
Fig. 5 is a graph showing the permanent deformation curve recognition result of the comparative example.
Detailed Description
The measuring device in the embodiment of the present invention will be clearly and completely described below, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments, and all other embodiments obtained by those skilled in the art without any inventive work based on the embodiment of the present invention belong to the protection scope of the present invention.
The invention will be further elucidated with reference to the drawings and examples.
Examples
The method for identifying the flow times of the dynamic creep test of the asphalt mixture of the three-stage model, provided by the invention, comprises the following steps of:
and step S1, designing the mix proportion of the asphalt mixture by adopting a Marshall test method, selecting the asphalt mixture SMA-13 as a sample, selecting the asphalt with No. 70 matrix asphalt, selecting diabase as aggregate, and selecting limestone mineral powder as filler. According to the relevant regulations of the highway engineering construction technical specification, the design range of the mix proportion is determined, and the design range is shown in the table 1.
TABLE 1 SMA-13 design mix proportions
In step S2, a Marshall stability test is performed using four oilstone ratios. The SMA-13 Marshall test piece is prepared as follows: firstly, mineral materials mixed according to target gradation are added and dry-mixed for 60 seconds, the target mixing proportion is added to design the asphalt dosage, the mixture is mixed for 60 seconds, mineral powder (9.5 percent of the mass of the mineral materials) is added, the mixture is mixed for 60 seconds, fiber (0.3 percent of the mass of the asphalt mixture) is added, the mixture is mixed for 60 seconds, and compaction molding is carried out. The results of the Marshall stability test are shown in Table 2.
TABLE 2 SMA-13 design mix proportion Marshall stability test results
And step S3, determining the optimal asphalt dosage. According to the results of Marshall stability test, the four oilstone ratios corresponding to the maximum density, the maximum stability, the target void ratio and the median value of the saturation range are respectively 6.20, 6.00, 6.38 and 6.30, and the average value of the four is 6.22%, which is the initial value OAC of the optimal oilstone ratio1. Meanwhile, the relationship graph of each index and the oilstone ratio can obtain the oilstone ratio which meets the requirements of each index and is 6.0-6.4, wherein the value is 6.2 percent, namely the OAC2，OAC1And OAC2The average value of (A) was 6.21%, and the optimum oilstone ratio was empirically determined to be 6.2%. The results of the finally determined mixing ratio of the SMA-13-ore powder type mixture are shown in Table 3.
TABLE 3 SMA-13 optimum oilstone ratio design results
| Mix type | Oil-to-stone ratio (%) | Bulk relative density | Void ratio (%) | Actual measured theoretical relative density |
| SMA-13 | 6.2 | 2.388 | 4.02 | 2.488 |
Step S4, a test piece for the dynamic creep test is produced. The test adopts a cylindrical test piece with the diameter of 100mm and the height of 150mm, the cylindrical test piece with the diameter of 100mm and the height of 180mm is formed by cutting through a rotary compaction instrument, the porosity is measured, and the deviation of the porosity is ensured to be not more than +/-0.5%. Each set of experiments used 3 parallel test pieces. Before the test, the test piece is placed in a temperature control box and is kept at the constant temperature for 4 hours.
And step S5, carrying out a dynamic creep test to obtain a permanent deformation curve of the asphalt mixture. The test adopts half-sine pressure load to carry out uniaxial dynamic repeated loading, the loading time is 0.1s, the intermittence time is 0.9s, and the period is 1s, as shown in figure 1. The axial pressure was set at 100KPa, with no lateral confining pressure. The test temperature is set to be 60 ℃, the termination condition is that the axial accumulated strain reaches 5 percent or the frequency of load action reaches 10000 times, and a tetrafluoroethylene film is respectively padded at the two ends of the test piece so as to eliminate the influence of the end part constraint effect of the test piece on the test result and the precision.
In step S6, the obtained load number-cumulative creep deformation sequence is plotted as a permanent deformation curve, as shown in fig. 2. The curve was imported into MATLAB, the M main program was run, three damage stages were divided and the number of flows was calculated as shown in fig. 3. The identification of the permanent set curve and creep rate after reconstruction for the first and second phases is shown in fig. 4. Specifically, the following steps are adopted for repetition:
(1) in the range of 100 to NmaxAdopting K groups of permanent deformation data between the total loading times, namely selecting the array (100, K)th) Performing a power function model (ε)p＝aNb，N＜NPS) Fitting, and determining a regression coefficient a-2881.9 and b-0.2468;
(2) using the power function equation (epsilon) determined in (1)p＝2881.9N0.2468，N＜NPS) Calculating and current KthCumulative permanent strain epsilon corresponding to number of loadsPS(με)＝20160；
(3) Calculating the difference between the actual measured and predicted cumulative permanent strain: de< 3%, and currently Kth2545 corresponds to a number of loads less than NmaxThen current KthThe corresponding loading times are the initial points N of the second stagePS(cycle)。
(4) The first stage determined according to (1) to (3) includes 2545 sets of data. Therefore, there is still M-K-2045 +1 data remaining, including the end point N of the first stagePS2545(cycle) and εPS20160(μ ∈), i.e. select the remaining array (2545, K)th)；
(5) The initial point of the second stage (x 2545, y 20160) is set as the new origin of the coordinate axis. From the remaining array (2045, K)th) N is subtracted from the cumulative permanent setPS2545(cycle) value and εPS20160(μ ∈) values, and the number of times of loading and permanent strain after adjustment were designated N ' and ∈ ', respectively 'p；
(6) Linear function model (. epsilon. ') was prepared using M sets of data after adjusting the origin'pcN' + d) to determine the regression coefficients c 2.7518 and d;
(7) calculating d and current epsilon'pAbsolute value of maximum ratio, up to Rd< 1% (or d > 0),and currently Mth3456 corresponds to a load count of less than (N)max2545), then M is presentthThe corresponding loading times are the initial points of the third stage, and N is added backPS2545 get the original number of loads NST(cycle) 6001. That is, the number of flows in the dynamic creep test of the specimen was 6001, at which time ε corresponds to the permanent set curveST(με)＝29880。
The invention also provides a three-stage model-based dynamic creep test flow frequency identification method, in order to verify the calculation accuracy of the identification method, the dynamic creep test curve is fitted by using a traditional Francken model, the flow frequency is calculated, and the accuracy comparison is carried out according to the correlation of the fitting curve.
Comparative example
The test piece manufacturing and test process and the example are completely the same, the division of the permanent deformation curve and the calculation of the flow times are identified by using a Francken model, and the identification result is shown in FIG. 5 and Table 5.
TABLE 5 summary of three stage identification parameters for examples and comparative examples
| Parameter(s) | Examples | Comparative example |
| First stage fitting error | 0.74 | 1.47％ |
| Second stage fitting error | 0.86％ | 1.05％ |
| Third stage fitting error | / | 8.77％ |
| Number of flows | 6001 | 5438 |
| Correlation coefficient of test curve | 0.996 | 0.986 |
| Maximum fitting error | 0.86％ | 8.77％ |
As can be seen from Table 5, the number of flow times calculated in the examples was 6001, the correlation coefficient was 0.996, the relative error of the calculation results of the test samples was controlled to be within 0.86%, and the accuracy of the identification results was high. The number of flows calculated in the comparative example was 5438, the correlation coefficient was 0.986, the maximum relative error of the calculation results of the test samples reached 8.77%, and the accuracy of the recognition results was relatively low. This is because the Francken model used in the comparative example fits the curve in the failure stage comprehensively, which will affect the fitting results in the first and second stages. In fact, it is expected that the asphalt pavement does not enter the shear failure stage all the time during service, and the development state of the failure stage is not concerned. Therefore, the influence of the third stage is eliminated, the fitting range is reduced, and the identification precision can be improved. The method can be widely applied to the calculation of the flow times of other asphalt mixture dynamic creep tests, scientifically evaluate the high-temperature anti-rutting performance of the asphalt mixture, and guide the control of construction and production quality and the research of scientific research work.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A method for identifying the flow times of a dynamic creep test of an asphalt mixture comprises the following steps:
s1, acquiring permanent deformation curve data of a dynamic creep test of an asphalt mixture test piece according to the test;
s2, defining a first-stage description model;
s3, in the step of selecting S1, in the range of 100 to the total loading times NmaxK sets of permanent deformation data are adopted, namely, an array (100, K) is selectedth)，KthRepresenting the Kth permanent deformation data, then adopting the selected array to fit the first-stage model in the step S2, and determining regression coefficients a and b in the model to obtain a first-stage model equation; then, calculating the accumulated permanent strain corresponding to the Kth loading time according to a first-stage model equation;
s4, according to the accumulated permanent strain difference D of the Kth time actually measured in the step S1 and the accumulated permanent strain difference D corresponding to the Kth time loading times calculated in the step S3eJudging whether iterative calculation is needed, if so, deleting the selected K groups of data and setting K to K-1, and carrying out iterative calculation according to the step S3 until judging the initial point N of the second stagePSThen the next step is entered; if the iterative computation is not needed, directly entering the next step;
s5, defining a model of a second stage;
s6, in the step of selecting S1, in the range of 100 to the total loading times NmaxM is equal to K-NPS+1 sets of permanent deformation data, i.e. selecting the array (N)PS，Kth) Setting the initial point of the second stage as the new origin of the coordinate axis; performing second-stage model fitting by using the M groups of data after the origin point is adjusted, determining regression coefficients c and d, and obtaining a second-stage model equation;
s7, calculating an intercept d and a current strain epsilon 'on a longitudinal axis of a second-stage model equation'pAbsolute value of maximum ratio RdJudging whether iterative calculation is needed, if so, deleting selected M groups of data and setting M to be M-1, and carrying out iterative calculation according to the step S6 until judging the initial point N of the third stageST，NSTNamely the flowing times; if no iterative calculations need to be performed, the identification procedure terminates.
2. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step 1), the permanent deformation curve data loading times are the times when the axial accumulated strain reaches 5% or the loading acting times reach 10000.
3. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step 2), the first-order model is as follows:
εp＝aNbN＜NPS
wherein epsilonpFor accumulating the permanent strain, N is the number of repeated loading times, a and b are regression coefficients, and NPSAnd the loading times corresponding to the initial point of the second stage are obtained.
4. The method for identifying the number of times of flow in the asphalt mixture dynamic creep test according to claim 1 or 3, wherein in the step S4, the cumulative permanent strain difference D between the K-th cumulative permanent strain actually measured in the step S1 and the K-th loading number calculated in the step S3 is determinedeThe calculation formula of (2) is as follows:
wherein: epsilonpMeasuredRepresenting the cumulative permanent strain, epsilon, of the actual measurementpPredictedForecasting and accumulating permanent response for representing current K corresponding loading timesAnd (6) changing.
5. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 4, wherein in the step S4, the method for determining whether iterative calculation is required is as follows:
A. if D iseIs less than 3 percent, and the loading times corresponding to the current K are equal to NmaxIf the permanent deformation curve has no second stage, stopping identification, and if the test curve has no flowing times;
B. if D iseIs less than 3 percent, and the loading times corresponding to the current K are less than NmaxThen current KthThe corresponding loading times are the initial points of the second stage;
C. if not, iterative calculation is performed.
6. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step S5, the model of the second stage is:
εp＝εPS+c(N-NPS)，NPS≤N＜NST
ε′p＝cN′+d；
in the formula: epsilonPSRepresenting the corresponding permanent strain of the initial point in the second stage, c and d representing regression coefficients, NSTRepresenting the loading times corresponding to the initial point of the third stage; epsilon'pFor the adjusted permanent set, N' is the adjusted number of loads.
7. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step S6, the method for selecting data and setting the initial point of the second stage as the new origin of the coordinate axis comprises: the first stage includes x sets of data, so M-K-N remainsPS+1 data remains including the end point N of the first stagePSAnd epsilonPSI.e. selecting the remaining array (N)PS，Kth)；
Is provided with a secondInitial point of stage (x ═ N)PS，y＝εPS) Is a new origin of the coordinate axis; from the remaining array (N)PS，Kth) N is subtracted from the cumulative permanent setPSValue and epsilonPSValues for the number of times of loading and permanent set after adjustment were designated as N 'and ε'p。
8. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step S7, the absolute value R of the ratiodThe calculation formula of (2) is as follows:
in the formula: d represents the fitting intercept, ε'pRepresenting the current strain value.
9. The method for identifying the flow times of the asphalt mixture dynamic creep test according to claim 1, wherein in the step S7, the method for judging whether iterative computation is required is as follows:
A. if R isd< 1% or d > 0, and the number of loads corresponding to the current M is equal to (N)max-NPS) Indicating that the permanent deformation curve has no third stage, stopping identification, and the test curve has no flowing times;
B. if R isd< 1% or d > 0, and the number of loads corresponding to the current M is less than (N)max-NPS) If the current M corresponding loading times is the initial point of the third stage, add back NPSObtaining the original loading times;
C. if not, iterative calculation is performed.
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