Evaluation method for low-temperature crack resistance of asphalt mixture based on equivalent fracture temperature

Abstract

The invention discloses an asphalt mixture low-temperature crack resistance evaluation method based on equivalent fracture temperature, which comprises the following steps: S1, preparing a standardized test piece by combining microwave pretreatment with a rotary compaction method, eliminating aggregate segregation and simulating a field compaction process; s2, setting a multi-gradient test temperature to carry out a bending test, and synchronously collecting load and mid-span deflection data; s3, calculating fracture energy, flexural modulus and an energy loss coefficient, and constructing a multi-dimensional evaluation system; s4, establishing a coupling correlation model of the test temperature and the three variables; s5, the equivalent fracture temperature is determined through double-feature correlation value calibration and interpolation calculation; and S6, evaluating the low-temperature crack resistance of the material based on the equivalent fracture temperature. According to the method, the representativeness of the test piece is improved by innovatively introducing a microwave pretreatment and rotary compaction process, multi-dimensional quantitative analysis of the low-temperature performance is realized by combining a multi-gradient test and a three-variable coupling model, and the stability and repeatability of equivalent fracture temperature calculation are ensured through a double-feature calibration mechanism.

Description

Technical Field

[0001] This invention relates to the field of performance testing of road engineering materials, and in particular to a method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature. Background Technology

[0002] In the field of road engineering material performance testing, asphalt mixtures, as the core material of pavement structure, directly affect the durability and safety of the pavement due to their low-temperature crack resistance. With increasing traffic loads and the frequent occurrence of extreme weather events, accurately evaluating the crack resistance of asphalt mixtures in low-temperature environments has become a key issue in material research and development and engineering quality control. Existing evaluation methods mostly simulate low-temperature conditions through laboratory tests, combining mechanical indicators (such as fracture energy and flexural modulus) to determine performance, aiming to provide a basis for material design, construction, and maintenance.

[0003] Common methods for evaluating the low-temperature crack resistance of asphalt mixtures often neglect aggregate segregation in specimen preparation, leading to significant differences between the internal structure of the specimens and actual pavement materials, thus affecting the engineering applicability of the test results. Some methods only use a single temperature point or a simple temperature gradient for testing, failing to comprehensively reflect the mechanical response of materials under different low-temperature conditions. Furthermore, existing evaluation models often rely on single indicators such as fracture energy or flexural modulus, failing to comprehensively consider the strength characteristics, deformation capacity, and energy dissipation characteristics of materials, resulting in strong subjectivity and limited coverage. Simultaneously, the lack of dynamic adjustment mechanisms for model parameters makes it difficult to adapt to the material characteristics of different asphalt mixtures, leading to insufficient stability and repeatability of calculation results, failing to meet the needs of accurate evaluation, and not satisfying the requirements of road engineering material performance testing. Therefore, this paper proposes a method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature. Summary of the Invention

[0004] This invention provides the following technical solution: a method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature, comprising: S1 Preparation of Standardized Asphalt Mixture Specimens: First, asphalt and aggregate are mixed according to the preset gradation and asphalt-aggregate ratio. Then, a microwave pretreatment mechanism is introduced and a rotary compaction method is used to form cylindrical specimens, which are then cut into small beam specimens. By combining microwave pretreatment with rotary compaction, rapid and uniform heating of the mixture is achieved, eliminating aggregate segregation and ensuring that the internal structure of the specimen is highly consistent with the actual road surface material. The rotary compaction process simulates the on-site construction compaction process, making the density distribution of the specimen closer to the real road surface condition and significantly improving the engineering applicability of the test results. S2 undergoes a bending test: At least five gradient test temperatures are set, and then a bending test is performed on the small beam specimen at each test temperature. Load and mid-span deflection data are recorded until the specimen breaks, thereby obtaining the load and mid-span deflection curves at each temperature. Multi-gradient test temperature settings combined with synchronous data acquisition can comprehensively reflect the mechanical response of materials under different low-temperature conditions, avoid the limitations of evaluation at a single temperature point, and provide a more complete data foundation for low-temperature performance analysis. S3 calculates fracture energy and flexural modulus: Based on the load and mid-span deflection curves obtained in step S2, the fracture energy and flexural modulus of the asphalt mixture at each test temperature are calculated. At the same time, an energy loss coefficient is introduced. The larger the energy loss coefficient, the more significant the low-temperature brittleness of the material. By introducing the energy loss coefficient as a brittleness evaluation index, the energy dissipation capacity of materials during fracture is quantified. Together with fracture energy and flexural modulus, it forms a multi-dimensional evaluation system that more accurately characterizes low-temperature performance. S4 establishes a relational model: Subsequently, a three-variable coupled correlation model was established between the test temperature and the fracture energy, flexural modulus, and energy loss coefficient. The three-variable coupled correlation model breaks through the traditional single-index evaluation mode. Through the dynamic correlation between temperature and mechanical properties, it realizes multi-dimensional quantitative analysis of the low-temperature performance of asphalt mixtures, and improves the comprehensiveness and scientificity of the evaluation results. S5 determines the equivalent fracture temperature: The equivalent fracture temperature is determined based on the three-variable coupled correlation model established in step S4. Then, the temperature corresponding to the ratio of the fracture energy to the flexural modulus of the asphalt mixture is obtained by the dual-feature correlation value calibration mechanism and interpolation calculation, which is the equivalent fracture temperature. The dual-feature correlation value calibration mechanism, combined with interpolation calculation, considers both the material strength characteristics (fracture energy) and the deformation capacity and energy dissipation characteristics (flexural modulus, energy loss coefficient). By dynamically adjusting the model parameters to adapt to different material properties, it ensures the stability and repeatability of the equivalent fracture temperature calculation. S6 crack resistance performance evaluation: Finally, the low-temperature crack resistance of asphalt mixtures is evaluated by the equivalent fracture temperature obtained in step S5. That is, the higher the equivalent fracture temperature, the better the crack resistance of asphalt mixtures in low-temperature environments. Using equivalent fracture temperature as the core evaluation index, complex multi-dimensional data is transformed into a single quantitative parameter, simplifying the evaluation process while retaining key performance information, providing an intuitive and reliable basis for decision-making in material design, construction and maintenance.

[0005] Preferably, in step S1, the application of the microwave pretreatment mechanism is adjusted in conjunction with the characteristics of the old material in the recycled asphalt mixture. For old material containing a large amount of aged asphalt, a segmented heating method is adopted in the pretreatment process. That is, the old material is preheated with low power first to slowly increase the overall temperature of the old material, and then the power is gradually increased. At the same time, when the pretreated old material is mixed with new asphalt and new aggregate, a multi-stage mixing process is adopted. That is, the old material and new aggregate are first dry-mixed to ensure that the particles are in full contact, and then new asphalt is added for wet mixing. The segmented heating method for old material containing a large amount of aged asphalt can avoid local overheating affecting the asphalt performance. The multi-stage mixing process can fully combine the new and old materials, improve the uniformity of the specimen structure, and provide a guarantee for the stability of the test results.

[0006] Preferably, in step S1, the cylindrical specimen is formed by rotary compaction in a constant temperature and humidity environment. After compaction, the cut part is simultaneously cooled during the cutting of the small beam specimen. Compaction in a constant temperature and humidity environment can reduce the influence of temperature fluctuations on asphalt viscosity. Simultaneous cooling during cutting can prevent frictional heat from changing the asphalt properties and ensure that the specimen can truly reflect the low-temperature crack resistance characteristics of the material.

[0007] Preferably, in step S2, the setting of the gradient test temperature is synchronized with the climate characteristics of the actual application area of ​​the evaluation object. That is, for the high-latitude region of the seasonally frozen zone, the temperature gradient should cover the historical lowest temperature of the region and the surrounding temperature range. For the region with a mild climate, the lower limit of the temperature gradient is adjusted synchronously. At the same time, before the bending test at each test temperature, the temperature of the specimen is monitored 2-4 times. Setting the temperature gradient with reference to the climate characteristics of the actual application area can make the test more in line with the actual environment. Multiple temperature monitoring can avoid data deviation caused by uneven temperature of the specimen and improve the pertinence and accuracy of the evaluation.

[0008] Preferably, in step S2, during the bending test, an elastic pad is used at the contact point between the specimen and the support device of the testing machine. At the same time, the load is continuously applied during the loading process, and a continuous sampling method is used when recording the load and mid-span deflection data. The use of an elastic pad at the contact point between the specimen and the support device can reduce local stress concentration, and the continuous sampling and recording of data can completely capture the entire process from the specimen being stressed to fracture, thereby improving the integrity and reliability of the test data.

[0009] Preferably, in step S3, when calculating the fracture energy and flexural modulus, the analysis of the load and mid-span deflection curve is segmented. The initial stage of the curve is the elastic deformation segment, in which the linear response characteristics of the material are analyzed. The middle stage of the curve is the plastic deformation segment, in which the nonlinear relationship between load and deflection is analyzed. The later stage of the curve is the fracture stage, capturing the critical state before the load drops sharply. The energy loss coefficient is calculated in conjunction with the change characteristics of the entire curve. By comparing the energy change patterns at different stages, the energy dissipation capacity of the material during low-temperature stress is reflected. The segmented analysis of the load and mid-span deflection curve can accurately grasp the characteristics of the material at different stress stages. The energy loss coefficient is calculated in conjunction with the overall characteristics of the curve, which can more scientifically reflect the low-temperature energy dissipation capacity of the material.

[0010] Preferably, in step S4, when establishing the three-variable coupled correlation model, the collected experimental data is first preprocessed, i.e., outlier data that deviates from the overall trend is removed. Then, the data is standardized so that the fracture energy, bending modulus, and energy loss coefficient are on the same order of magnitude. In the process of model construction, multiple analysis methods are used for cross-validation. By comparing different methods, the correlation relationship is obtained. Preprocessing the experimental data and using multiple methods for cross-validation can remove outlier interference, ensure data consistency, and make the established three-variable coupled correlation model more closely fit the intrinsic relationship between temperature and material properties.

[0011] Preferably, in step S5, the implementation of the dual-feature correlation value calibration mechanism is combined with the performance benchmark values ​​of different types of asphalt mixtures. When using this mechanism for calibration, the compatibility between the benchmark value and the mixture to be evaluated is first verified. If the material to be evaluated differs significantly from conventional materials, the range of the feature correlation value is adjusted simultaneously. The dual-feature correlation value calibration is implemented in combination with the performance benchmark values ​​of different types of mixtures. By verifying the compatibility and adjusting the range of values, the equivalent fracture temperature can more accurately reflect the low-temperature crack resistance of the material and reduce misjudgments.

[0012] Preferably, in step S5, the interpolation calculation adopts the principle of data distribution continuity. When the performance change within the test temperature interval exhibits nonlinear characteristics, a nonlinear interpolation method is used. When test data for some temperature points is missing, it is supplemented by trend analysis of adjacent valid data. At the same time, the error range of the interpolation is recorded in real time during the calculation process and compared with the actual test data for verification.

[0013] Preferably, in step S6, when evaluating crack resistance using equivalent fracture temperature, a differentiated evaluation standard is simultaneously formulated based on the actual application scenario of the asphalt mixture. For mixtures used on main roads, a higher equivalent fracture temperature threshold is set, while for mixtures used on secondary roads or sidewalks, the threshold standard is lowered. Formulating a differentiated evaluation standard based on the actual application scenario and setting different thresholds for different road types can make the evaluation results more in line with engineering needs and provide more accurate guidance for mixture selection.

[0014] In summary, compared with the prior art, the present invention provides a method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature, which has the following beneficial effects: 1. This invention introduces a specimen preparation process that combines microwave pretreatment with rotary compaction, which can rapidly and uniformly heat the mixture, eliminate aggregate segregation, and ensure that the internal structure of the specimen is consistent with the actual pavement material. The rotary compaction process simulates the compaction process during on-site construction, making the density distribution of the specimen closer to the actual pavement condition and enhancing the engineering applicability of the test results. In addition, the multi-gradient test temperature and simultaneous acquisition of load and mid-span deflection data can comprehensively reflect the mechanical response law of the material under different low-temperature conditions, avoiding the limitations of evaluation at a single temperature point. At the same time, by establishing a three-variable coupled correlation model between test temperature and fracture energy, flexural modulus and energy loss coefficient, a multi-dimensional quantitative analysis of the low-temperature performance of asphalt mixtures is realized. 2. This invention improves the scientific rigor and accuracy of low-temperature crack resistance evaluation by establishing a dual-feature correlation value calibration mechanism and an equivalent fracture temperature determination method. Furthermore, by using the ratio of fracture energy to flexural modulus as a feature correlation value and combining it with an energy loss coefficient for dynamic calibration, it considers both the material's strength characteristics and its deformation capacity and energy dissipation characteristics, avoiding the subjectivity and one-sidedness of single-index evaluation. Simultaneously, through interpolation calculations, it can automatically adjust model parameters to adapt to different material properties, ensuring the stability and repeatability of the calculation results. Attached Figure Description

[0015] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0016] Please see Figure 1 This invention provides a technical solution: a method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature, comprising the following steps: S1 Preparation of Standardized Asphalt Mixture Specimens: First, asphalt and aggregate are mixed according to the preset gradation and asphalt-aggregate ratio. Then, a microwave pretreatment mechanism is introduced and a rotary compaction method is used to form cylindrical specimens, which are then cut into small beam specimens. The application of microwave pretreatment mechanism is combined with the characteristics of old material in recycled asphalt mixture. For old material containing more aged asphalt, a segmented heating method is adopted in the pretreatment process. That is, the old material is preheated with low power first to make the overall temperature of the old material rise slowly, and then the power is gradually increased. At the same time, when the pretreated old material is mixed with new asphalt and new aggregate, a multi-stage mixing process is adopted. That is, the old material and new aggregate are dry mixed first to make the particles fully contact, and then new asphalt is added for wet mixing. When the cylindrical specimens were formed by the rotary compaction method, the process was carried out in a constant temperature and humidity environment. After compaction, the cut parts were simultaneously cooled during the cutting of the small beam specimens. S2 undergoes a bending test: At least five gradient test temperatures are set, and then a bending test is performed on the small beam specimen at each test temperature. Load and mid-span deflection data are recorded until the specimen breaks, thereby obtaining the load and mid-span deflection curves at each temperature. The temperature gradient test should be set in accordance with the actual application area climate characteristics of the evaluation object. For high-latitude areas in the frozen zone, the temperature gradient should cover the historical lowest temperature and the surrounding temperature range. For areas with mild climate, the lower limit of the temperature gradient should be adjusted accordingly. At the same time, the temperature of the specimen should be monitored 2-4 times before the bending test at each test temperature. During the bending test, an elastic pad was used at the contact point between the specimen and the support device of the testing machine. At the same time, the load was continuously applied during the loading process, and a continuous sampling method was used when recording the load and mid-span deflection data. The specific implementation process of the above method is as follows: Before conducting bending tests, a temperature gradient must be set based on the climatic characteristics of the actual application area of ​​the evaluated object. For seasonally frozen regions or high-latitude areas, the temperature gradient should cover the historical lowest temperature and surrounding temperature range, typically divided in 5°C increments, with the lowest temperature not exceeding 3°C below the local historical lowest temperature. For regions with mild climates or no severe cold season, the lower limit of the temperature gradient should be adjusted accordingly to avoid setting excessively low temperatures that could reduce test efficiency. Each test temperature point must be tested independently to ensure that the data do not interfere with each other. Before the experiment, the prepared beam specimens were removed from the constant temperature and humidity environment and immediately placed in an environmental chamber at the target temperature for pretreatment. During the pretreatment, the surface and internal temperature of the specimens were monitored at regular intervals (e.g., every 15 minutes). A non-contact infrared thermometer and an insertion temperature sensor were used in conjunction to ensure that the overall temperature of the specimens was uniform and reached the target value. The pretreatment time was adjusted according to the size of the specimens, but was usually no less than 2 hours, to eliminate the influence of temperature gradients on the test results. The pretreated specimen is placed on the support device of the bending testing machine, and the position of the specimen is adjusted so that its axis is aligned with the loading axis of the testing machine. To reduce stress concentration during loading, an elastic pad is laid at the contact area between the specimen and the support device. The pad material should have an elastic modulus similar to that of the asphalt mixture to avoid sudden changes in local stress due to stiffness differences. The testing machine was started, and a concentrated load was applied simultaneously to the middle section of the top surface of the specimen. The load must be continuously applied during the loading process to avoid intermittent loading interfering with the crack propagation pattern inside the specimen. Simultaneously, a high-precision displacement sensor was used to record the mid-span deflection changes in real time, with a data acquisition frequency of no less than 100Hz, to ensure that subtle changes in the load-deflection curve were captured. When the specimen shows obvious fracture (e.g., a sudden load drop exceeding 30% of the maximum load) or the mid-span deflection reaches 80% of the specimen height, loading should be stopped and the test data saved. At least three parallel tests must be performed at each test temperature point, and the average of the valid data should be taken as the final result. If any test data deviates from the average by more than 15%, the cause must be analyzed and the test repeated. During the test, operators must closely observe the fracture mode of the specimens and record the crack propagation path and fracture surface characteristics. For recycled asphalt mixture specimens, attention should also be paid to the interface bonding between the old and new aggregates, and the influence of the old aggregate distribution on low-temperature crack resistance should be analyzed. All test data must be labeled with information such as the test date, ambient temperature and humidity, and specimen number to ensure data traceability. S3 calculates fracture energy and flexural modulus: Based on the load and mid-span deflection curves obtained in step S2, the fracture energy and flexural modulus of the asphalt mixture at each test temperature are calculated. At the same time, an energy loss coefficient is introduced. The larger the energy loss coefficient, the more significant the low-temperature brittleness of the material. When calculating fracture energy and flexural modulus, the analysis of load and mid-span deflection curves is performed in segments. The initial stage of the curve is the elastic deformation segment, in which the linear response characteristics of the material are analyzed. The middle stage of the curve is the plastic deformation segment, in which the nonlinear relationship between load and deflection is analyzed. The later stage of the curve is the fracture stage, capturing the critical state before the load drops sharply. The energy loss coefficient is calculated in conjunction with the change characteristics of the entire curve. By comparing the energy change patterns in different stages, the energy dissipation capacity of the material during low-temperature stress is reflected. The specific implementation process of the above method is as follows: Before calculating the fracture energy and flexural modulus, the load and mid-span deflection curve data recorded in step S2 must be obtained. The curve data at each test temperature must be preliminarily verified to remove invalid data segments caused by test anomalies (such as specimen slippage or loading interruption) to ensure that the curve fully reflects the entire process of the material from loading to fracture. A segmented approach was used to analyze the load-deflection curve. First, the initial stage of the curve was identified, representing the elastic deformation segment where the load and deflection exhibited an approximately linear relationship. By observing the change in the curve's slope, the start and end points of the elastic stage were determined: the start point was the small deflection region in the initial loading stage (typically less than 5% of the specimen height), and the end point was the turning point where the load increase rate first showed a significant slowdown. During this stage, the focus was on analyzing the material's linear response characteristics, recording the maximum elastic load and corresponding deflection to provide fundamental data for subsequent calculations of the flexural modulus. The middle section of the curve represents the plastic deformation phase, where the load and deflection exhibit a nonlinear relationship, characterized by a gradually decreasing curve slope until it approaches zero. During this stage, it is crucial to capture the energy accumulation characteristics of the material during plastic deformation. By marking the load peak point (i.e., the highest point of the curve) and key inflection points before the peak, the start and end ranges of the plastic deformation phase can be defined. In this phase, it is necessary to record the deflection value when the load reaches its peak and analyze the load-deflection trend before and after the peak, providing crucial data support for the calculation of fracture energy. The later part of the curve represents the fracture stage, characterized by a sudden drop in load, typically defined as the load decreasing to below 30% of the peak load or complete specimen fracture. During this stage, it is crucial to capture the critical state before the sudden load drop. By observing the steep drop at the end of the curve, the specific location of the fracture point can be determined. Simultaneously, the mid-span deflection value at the time of fracture should be recorded, and combined with the specimen's geometric dimensions (such as height and width), a complete data chain should be provided for the final calculation of the fracture energy. The calculation of fracture energy is based on the area under the load-deflection curve, which is the region enclosed by the curve from the start of loading to the end of fracture. In practice, the curve is divided into several small segments, and the total area under the curve is approximated by accumulating the product of the load increment and the corresponding deflection increment of each segment. This process must ensure that the integration interval covers the elastic deformation segment, the plastic deformation segment, and the fracture stage to avoid missing the energy contribution of any stage. The calculation of flexural modulus is based on load and deflection data during the elastic deformation phase. Multiple data points within the elastic stage are selected, the load-to-deflection ratio is calculated, and the average value is taken as the material's flexural modulus. If the data in the elastic stage fluctuates significantly, a linear regression method can be used to fit the load-deflection relationship, and the slope of the fitted line is taken as the basis for calculating the flexural modulus. The introduction of the energy loss coefficient needs to be considered in conjunction with the overall curve's variation characteristics. By comparing the energy variation patterns in the elastic, plastic, and fracture stages, the energy proportion of each stage is calculated: the energy in the elastic stage is the integral area of ​​the initial segment of the curve; the energy in the plastic stage is the integral area before the peak minus the energy in the elastic stage; and the energy in the fracture stage is the integral area after the peak. The energy loss coefficient is defined as the ratio of the energy in the fracture stage to the total input energy. The larger this value, the weaker the material's energy dissipation capacity during fracture, and the more pronounced its low-temperature brittleness characteristics. All calculations must be performed using dedicated software or custom algorithms to ensure automated and standardized data processing. After calculation, the results must be cross-validated: comparing the fracture energy, flexural modulus, and energy loss coefficient of different specimens at the same test temperature. If the coefficient of variation exceeds 15%, the original data must be re-checked or additional tests conducted. Finally, the calculation results for each temperature point are summarized to form a complete low-temperature performance dataset, providing reliable input for the subsequent establishment of correlation models. S4 establishes a relational model: Subsequently, a three-variable coupled correlation model was established between the test temperature and the fracture energy, flexural modulus, and energy loss coefficient. When establishing a three-variable coupled correlation model, the collected experimental data are first preprocessed, i.e., outlier data that deviates from the overall trend is removed. Then, the data is standardized to make the fracture energy, bending modulus and energy loss coefficient of the same order of magnitude. In the process of model construction, multiple analysis methods are used for cross-validation, and the correlation is obtained by comparing different methods. The specific implementation process of the above method is as follows: Before establishing a three-variable coupled correlation model between test temperature and fracture energy, flexural modulus, and energy loss coefficient, the collected test data needs to be systematically processed and analyzed. First, data preprocessing is performed, using visualization techniques (such as scatter plots and trend lines) to observe the overall pattern of each variable's variation with temperature, identifying and eliminating outlier data points that deviate from the mainstream trend. For example, if the fracture energy at a certain temperature is significantly higher or lower than that at adjacent temperature points, and cannot be explained by the material property variation pattern, it is identified as an outlier and excluded. After data cleaning, standardization was performed to eliminate dimensional differences. A minimum-maximum normalization method was used to linearly map the values ​​of fracture energy, flexural modulus, and energy loss coefficient to the [0,1] interval, ensuring that different indicators have equal weight in the model. Specifically, the minimum and maximum values ​​of each variable were calculated over the entire temperature range. A multi-method cross-validation strategy was employed during the model building phase. First, an initial correlation model between temperature and various variables was established based on linear regression analysis, and the linear fit was observed. If the linear model could not accurately describe the complex relationships between variables (e.g., fracture energy exhibits nonlinear decay with decreasing temperature), multinomial regression or nonlinear regression methods were introduced. The model fit was improved by adjusting the polynomial order or selecting a nonlinear function form (e.g., exponential or logarithmic functions). To verify the model's stability and generalization ability, the entire dataset was divided into a training set (70%) and a test set (30%). After fitting the model parameters using the training set data, the test set data was substituted into the model to calculate predicted values. The model's prediction accuracy was evaluated by comparing the error range between the predicted and actual values. If the test error of a certain model is consistently lower than that of other methods, it is selected as the final association model. During model optimization, the focus is on the coupling effect among the three variables. By analyzing the interaction mechanism of fracture energy, flexural modulus, and energy loss coefficient in low-temperature environments (e.g., high flexural modulus may be accompanied by low fracture energy, or high energy loss coefficient may be correlated with low flexural modulus), interaction terms are introduced into the model or multidimensional surfaces are constructed to quantify the synergistic effect between variables. For example, a product term of temperature and fracture energy is added to the polynomial regression model to capture the moderating effect of temperature on changes in fracture energy. Ultimately, the optimal model, after cross-validation and error assessment, was determined to be a three-variable coupled correlation model. This model can systematically describe the dynamic relationship between test temperature and fracture energy, flexural modulus, and energy loss coefficient, providing core theoretical support for the subsequent determination of equivalent fracture temperature and evaluation of crack resistance. Through the above process, the scientific validity, accuracy, and engineering applicability of the correlation model can be ensured, meeting the needs of low-temperature performance evaluation of asphalt mixtures. S5 determines the equivalent fracture temperature: The equivalent fracture temperature is determined based on the three-variable coupled correlation model established in step S4. Then, the temperature corresponding to the ratio of the fracture energy to the flexural modulus of the asphalt mixture is obtained by the dual-feature correlation value calibration mechanism and interpolation calculation, which is the equivalent fracture temperature. The implementation of the dual-feature correlation value calibration mechanism is combined with the performance benchmark values ​​of different types of asphalt mixtures. When using this mechanism for calibration, the compatibility between the benchmark value and the mixture to be evaluated is first verified. If the material to be evaluated differs greatly from conventional materials, the range of the feature correlation value is adjusted simultaneously. The application of interpolation calculation adopts the principle of continuous data distribution. When the performance change within the test temperature interval exhibits nonlinear characteristics, a nonlinear interpolation method is used. When test data for some temperature points is missing, it is supplemented by trend analysis of adjacent valid data. At the same time, the error range of interpolation is recorded in real time during the calculation process and compared with the actual test data for verification. The specific implementation process of the above method is as follows: First, dynamic relationship data between experimental temperature and fracture energy, flexural modulus, and energy loss coefficient were extracted from the three-variable coupled correlation model. By analyzing the temperature-performance curves output by the model, the sensitive ranges of each variable with temperature variation were identified. For example, fracture energy may exhibit a rapid decay characteristic at low temperatures, while flexural modulus may gradually increase with decreasing temperature, and the trend of energy loss coefficient reflects the brittle evolution law of the material. When initiating the dual-feature correlation value calibration mechanism, the performance benchmark values ​​of different types of asphalt mixtures must be considered simultaneously. For conventional asphalt mixtures (such as base asphalt mixtures), historical test data or benchmark values ​​recommended by specifications are used as initial references; for modified asphalt mixtures or recycled asphalt mixtures, their performance benchmark values ​​need to be determined through pre-tests. During the calibration process, the ratio of fracture energy to flexural modulus of the mixture to be evaluated is first compared with the benchmark value. If the deviation exceeds a preset threshold (such as 20%), it is determined that there is a significant difference in material properties, and the range of the feature correlation value needs to be adjusted simultaneously. For example, for highly elastic modified asphalt mixtures, the range of the ratio of fracture energy to flexural modulus can be appropriately widened to accommodate its unique deformation characteristics. After calibration, the interpolation calculation stage begins. Based on the data distribution characteristics within the test temperature interval, a suitable interpolation method is selected: if the temperature-performance curve exhibits an approximately linear change, linear interpolation is used; if the curve shows significant nonlinear characteristics (such as an exponential decrease in fracture energy with decreasing temperature), nonlinear interpolation methods (such as quadratic or cubic spline interpolation) are used. For missing data at certain temperature points due to test limitations, a temporary prediction model is constructed to fill in the missing data by analyzing the data trends of adjacent effective temperature points. For example, if the -15℃ test data is missing, an approximate value for -15℃ can be estimated by combining the data change rates of -10℃ and -20℃. During the interpolation calculation, the interpolation error range needs to be recorded in real time. The reliability of the interpolation method is evaluated by comparing the interpolation results with actual experimental data (if available) or historical experience values. If the interpolation error at a certain temperature point exceeds the allowable range (e.g., 15%), the interpolation method should be adjusted or a correction factor should be introduced to ensure the accuracy of the final equivalent fracture temperature calculation. Finally, by iteratively adjusting the characteristic correlation values ​​and interpolation parameters, the ratio of fracture energy to flexural modulus is brought to the calibrated target range. The temperature corresponding to this is the equivalent fracture temperature. This temperature comprehensively reflects the material's strength, deformation capacity, and energy dissipation characteristics in low-temperature environments, and can objectively evaluate its crack resistance. For example, a mixture with an equivalent fracture temperature of -18℃ has better low-temperature crack resistance than a mixture with an equivalent fracture temperature of -22℃, because the former can still maintain better toughness at lower temperatures. The above process allows for the systematic determination of the equivalent fracture temperature of asphalt mixtures, providing a key quantitative indicator for subsequent crack resistance evaluation. This process combines the advantages of calibration mechanisms and interpolation calculations, ensuring both the engineering applicability of the calculation results and enhancing the generalization ability of the method across different material types. S6 crack resistance performance evaluation: Finally, the low-temperature crack resistance of asphalt mixtures is evaluated by the equivalent fracture temperature obtained in step S5. That is, the higher the equivalent fracture temperature, the better the crack resistance of asphalt mixtures in low-temperature environments. When evaluating crack resistance using equivalent fracture temperature, differentiated evaluation standards should be developed in conjunction with the actual application scenarios of asphalt mixtures. For mixtures used on main roads, a higher equivalent fracture temperature threshold should be set, while for mixtures used on secondary roads or sidewalks, the threshold standard should be lowered.

[0017] This scheme introduces a specimen preparation process that combines microwave pretreatment with rotary compaction, enabling rapid and uniform heating of the mixture, eliminating aggregate segregation, and ensuring that the internal structure of the specimen is consistent with the actual pavement material. The rotary compaction process simulates the compaction process during on-site construction, making the density distribution of the specimen closer to the actual pavement condition and enhancing the engineering applicability of the test results. In addition, the multi-gradient test temperature setting and simultaneous acquisition of load and mid-span deflection data can comprehensively reflect the mechanical response law of the material under different low-temperature conditions, avoiding the limitations of evaluation at a single temperature point. Furthermore, by establishing a three-variable coupled correlation model between test temperature and fracture energy, flexural modulus, and energy loss coefficient, a multi-dimensional quantitative analysis of the low-temperature performance of asphalt mixtures is achieved.

[0018] This scheme improves the scientific rigor and accuracy of low-temperature crack resistance evaluation by establishing a dual-feature correlation value calibration mechanism and an equivalent fracture temperature determination method. Furthermore, by using the ratio of fracture energy to flexural modulus as a feature correlation value and combining it with an energy loss coefficient for dynamic calibration, it considers both the material's strength characteristics and its deformation capacity and energy dissipation characteristics, avoiding the subjectivity and one-sidedness of single-index evaluation. Simultaneously, through interpolation calculations, it can automatically adjust model parameters to adapt to different material properties, ensuring the stability and repeatability of the calculation results.

Claims

1. A method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature, characterized in that, Includes the following steps: S1 Preparation of standardized asphalt mixture specimens: First, asphalt and aggregate are mixed according to the preset gradation and asphalt-aggregate ratio. Then, a microwave pretreatment mechanism is introduced and a rotary compaction method is used to form cylindrical specimens, which are then cut into small beam specimens. S2 undergoes a bending test: At least five gradient test temperatures are set, and then a bending test is performed on the small beam specimen at each test temperature. Load and mid-span deflection data are recorded until the specimen breaks, thereby obtaining the load and mid-span deflection curves at each temperature. S3 calculates fracture energy and flexural modulus: Based on the load and mid-span deflection curves obtained in step S2, the fracture energy and flexural modulus of the asphalt mixture at each test temperature are calculated. At the same time, an energy loss coefficient is introduced. The larger the energy loss coefficient, the more significant the low-temperature brittleness of the material. S4 establishes a relational model: Subsequently, a three-variable coupled correlation model was established between the test temperature and the fracture energy, flexural modulus, and energy loss coefficient. S5 determines the equivalent fracture temperature: The equivalent fracture temperature is determined based on the three-variable coupled correlation model established in step S4. Then, the temperature corresponding to the ratio of the fracture energy to the flexural modulus of the asphalt mixture is obtained by the dual-feature correlation value calibration mechanism and interpolation calculation, which is the equivalent fracture temperature. S6 crack resistance performance evaluation: Finally, the low-temperature crack resistance of asphalt mixtures is evaluated by the equivalent fracture temperature obtained in step S5. That is, the higher the equivalent fracture temperature, the better the crack resistance of asphalt mixtures in low-temperature environments.

2. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S1, the application of the microwave pretreatment mechanism is adjusted in conjunction with the characteristics of the old material in the recycled asphalt mixture. For the old material containing a lot of aged asphalt, a segmented heating method is adopted in the pretreatment process. That is, the old material is preheated with low power first to make the overall temperature of the old material rise slowly, and then the power is gradually increased. At the same time, when the pretreated old material is mixed with new asphalt and new aggregate, a multi-stage mixing process is adopted. That is, the old material and new aggregate are dry mixed first to make the particles fully contact, and then new asphalt is added for wet mixing.

3. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S1, the cylindrical specimen is formed by rotary compaction in a constant temperature and humidity environment, and the cut part is simultaneously cooled during the cutting of the small beam specimen after compaction.

4. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S2, the gradient test temperature is set in sync with the climate characteristics of the actual application area of ​​the evaluation object. That is, for high-latitude areas of the seasonally frozen zone, the temperature gradient should cover the historical lowest temperature and the surrounding temperature range of the area. For areas with mild climate, the lower limit of the temperature gradient is adjusted in sync. At the same time, the temperature of the specimen is monitored 2-4 times before the bending test at each test temperature.

5. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S2, during the bending test, an elastic pad is used at the contact point between the specimen and the support device of the testing machine. At the same time, the load is continuously applied during the loading process, and a continuous sampling method is used when recording the load and mid-span deflection data.

6. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S3, when calculating the fracture energy and flexural modulus, the analysis of the load and mid-span deflection curve is performed in segments. The initial stage of the curve is the elastic deformation segment, in which the linear response characteristics of the material are analyzed. The middle stage of the curve is the plastic deformation segment, in which the nonlinear relationship between load and deflection is analyzed. The later stage of the curve is the fracture stage, capturing the critical state before the load drops sharply. The energy loss coefficient is calculated in sync with the change characteristics of the entire curve. By comparing the energy change patterns in different stages, the energy dissipation capacity of the material during low-temperature stress is reflected.

7. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S4, when establishing the three-variable coupled correlation model, the collected experimental data is first preprocessed, that is, abnormal data that deviates from the overall trend is removed. Then, the data is standardized so that the fracture energy, bending modulus and energy loss coefficient are on the same order of magnitude. In the process of model construction, multiple analysis methods are used for cross-validation, and the correlation is obtained by comparing different methods.

8. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S5, the implementation of the dual-feature correlation value calibration mechanism is combined with the performance benchmark values ​​of different types of asphalt mixtures. When using the mechanism for calibration, the compatibility between the benchmark value and the mixture to be evaluated is first verified. If the material to be evaluated differs greatly from conventional materials, the range of the feature correlation value is adjusted simultaneously.

9. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S5, the interpolation calculation adopts the principle of data distribution continuity. When the performance change within the test temperature interval exhibits nonlinear characteristics, a nonlinear interpolation method is used. When test data for some temperature points is missing, it is supplemented by trend analysis of adjacent valid data. At the same time, the error range of the interpolation is recorded in real time during the calculation process and compared with the actual test data for verification.

10. The method for evaluating the low-temperature crack resistance of asphalt mixtures based on equivalent fracture temperature according to claim 1, characterized in that: In step S6, when evaluating crack resistance using equivalent fracture temperature, differentiated evaluation standards are simultaneously formulated based on the actual application scenarios of asphalt mixtures. For mixtures used on main roads, a higher equivalent fracture temperature threshold is set, while for mixtures used on secondary roads or sidewalks, the threshold standard is lowered.

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