Asphalt anti-aging performance simulation analysis method and system

Abstract

The invention provides an asphalt anti-aging performance simulation analysis method and system, and relates to the technical field of asphalt detection, and the method comprises the following steps: obtaining application environment historical data; determining a core parameter weight according to the historical data of the application environment; determining an experimental aging data threshold according to the historical data of the application environment; performing an aging simulation experiment on the material asphalt according to the experiment aging data threshold value; obtaining experiment aging data of a plurality of experiment periods; acquiring initial physical performance data and end physical performance data of the material asphalt; according to the initial physical performance data, the ending physical performance data and the core parameter weight, determining the anti-aging coefficient of the material asphalt in the plurality of experimental periods; processing the historical data of the application environment according to the trained asphalt aging time prediction model, and determining predicted aging time; and generating an analysis report according to the predicted aging time. According to the invention, the accuracy of asphalt anti-aging performance simulation analysis can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of asphalt detection, and in particular to a simulation analysis method and system for asphalt anti-aging performance. Background Art

[0002] In related technologies, the anti-aging performance of asphalt is mainly simulated and analyzed by accelerating thermal oxidative aging. Therefore, related technologies may find it difficult to consider the impact of other factors such as ultraviolet rays and load on the anti-aging performance of asphalt.

[0003] The information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or any form of suggestion that the information constitutes the prior art already known to those skilled in the art. Summary of the Invention

[0004] The present invention provides a method and system for simulating and analyzing the anti-aging performance of asphalt, which can solve the technical problem that related technologies find it difficult to consider the effects of other factors such as ultraviolet rays and load on the anti-aging performance of asphalt.

[0005] According to a first aspect of the present invention, a method for simulating and analyzing the anti-aging performance of asphalt is provided, comprising: obtaining historical data of an application environment; determining core parameter weights based on the historical data of the application environment, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; determining an experimental aging data threshold based on the historical data of the application environment; performing an aging simulation experiment on the material asphalt in multiple experimental cycles based on the experimental aging data threshold; obtaining experimental aging data of multiple experimental cycles, wherein the experimental aging data include: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; obtaining initial physical property data and ending physical property data of the material asphalt at the start and end times of multiple experimental cycles; determining the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the initial physical property data, the ending physical property data and the core parameter weights; processing the application environment historical data based on a trained asphalt aging time prediction model to determine a predicted aging time; and generating an analysis report based on the predicted aging time.

[0006] According to the present invention, the core parameter weights are determined based on the historical data of the application environment, including: determining the historical environment ultraviolet intensity, historical environment temperature, historical application environment traffic flow and historical application environment scenarios based on the historical data of the application environment; determining the application environment requirement coefficient based on the historical application environment scenarios; and determining the core parameter weights based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature and the historical application environment traffic flow.

[0007] According to the present invention, the core parameter weights are determined based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature and the historical application environment vehicle flow, including: determining the high temperature area identification result and the low temperature area identification result based on the historical environment temperature; determining the historical environment temperature difference based on the historical environment temperature; determining the large temperature difference area identification result based on the historical environment temperature difference; determining the strong ultraviolet area identification result based on the historical application environment vehicle flow; determining the needle penetration weight based on the low temperature area identification result, the large temperature difference area identification result and the strong ultraviolet area identification result; determining the elongation weight based on the low temperature area identification result and the large temperature difference area identification result; determining the softening point weight based on the high traffic area identification result, the high temperature area identification result and the application environment requirement coefficient; and determining the viscosity weight based on the high traffic area identification result and the high temperature area identification result.

[0008] According to the present invention, the experimental aging data threshold is determined based on the historical application environment data, including: determining the experimental aging temperature threshold based on the historical environment temperature; determining the experimental aging temperature difference threshold based on the historical environment temperature difference; determining the experimental ultraviolet intensity threshold based on the historical environment ultraviolet intensity; determining the application road type based on the historical application environment scenario; and determining the experimental load intensity threshold based on the application road type.

[0009] According to the present invention, the anti-aging coefficient of the material asphalt for multiple experimental cycles is determined based on the initial physical property data, the ending physical property data and the core parameter weights, including: determining the initial penetration, initial softening point, initial ductility and initial viscosity based on the initial physical property data; determining the ending penetration, ending softening point, ending ductility and ending viscosity based on the ending physical property data; determining the penetration decrease ratio based on the initial penetration and the ending penetration; determining the softening point increase ratio based on the initial softening point and the ending softening point; determining the ductility decrease ratio based on the initial ductility and the ending ductility; determining the viscosity increase ratio based on the initial viscosity and the ending viscosity; determining the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the penetration decrease ratio, the softening point increase ratio, the ductility decrease ratio, the viscosity increase ratio and the core parameter weights.

[0010] According to the present invention, the anti-aging coefficient of the asphalt material of multiple experimental cycles is determined according to the needle penetration decrease ratio, the softening point increase ratio, the ductility decrease ratio, the viscosity increase ratio and the core parameter weight, including: according to the formula Determine the anti-aging coefficient of the material asphalt in the kth experimental cycle ,in, is the penetration reduction ratio of the asphalt material in the kth experimental cycle, is the penetration weight, is the softening point increase ratio of the asphalt material in the kth experimental cycle, is the softening point weight, is the ductility reduction ratio of the asphalt material in the kth experimental cycle, is the extension weight, is the viscosity increase ratio of the asphalt material in the kth experimental cycle, is the viscosity weight.

[0011] According to the present invention, the training steps of the asphalt aging time prediction model include: processing the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient according to the asphalt aging time prediction model to determine the sample predicted aging time; determining the training loss function of the asphalt aging time prediction model according to the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient; training the asphalt aging time prediction model according to the training loss function to obtain a trained asphalt aging time prediction model.

[0012] According to the present invention, the training loss function of the asphalt aging time prediction model is determined based on the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient, including: according to the formula Determining the training loss function for the asphalt aging time prediction model ,in, is the experimental aging time of the kth experimental cycle, Predict the aging time for the samples of the kth experimental cycle, is the experimental aging temperature of the kth experimental cycle, is the preset experimental temperature threshold, is the experimental aging temperature difference of the kth experimental cycle, To preset the experimental temperature difference threshold, is the experimental ultraviolet intensity of the kth experimental cycle, To preset the experimental ultraviolet intensity threshold, is the experimental load intensity of the kth experimental cycle, is the preset experimental load intensity threshold, is the anti-aging coefficient of the asphalt material in the kth experimental cycle, is the needle penetration weight, is the softening point weight, is the extension weight, is the viscosity weight, K is the number of experimental cycles, k≤K, and both k and K are positive integers.

[0013] According to a second aspect of the present invention, a simulation and analysis system for asphalt anti-aging performance is provided, comprising: a historical data module for acquiring application environment historical data; a parameter weight module for determining core parameter weights based on the application environment historical data, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; an experimental threshold module for determining an experimental aging data threshold based on the application environment historical data; a simulation experiment module for performing aging simulation experiments on the material asphalt in multiple experimental cycles based on the experimental aging data threshold; an aging data module for acquiring experimental aging data of multiple experimental cycles, wherein the experimental aging The data include: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; a physical data module, used to obtain the initial physical property data and the final physical property data of the material asphalt at the start and end times of multiple experimental cycles; an anti-aging coefficient module, used to determine the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the initial physical property data, the final physical property data and the core parameter weights; a prediction time module, used to process the application environment historical data according to the trained asphalt aging time prediction model to determine the predicted aging time; an analysis report module, used to generate an analysis report based on the predicted aging time.

[0014] Technical effect: According to the present invention, the requirements of the application environment of asphalt for the physical properties of asphalt can be accurately analyzed based on the historical data of the application environment of asphalt, the core parameter weights can be determined, and the anti-aging performance of the material asphalt in the simulated aging during the experimental period can be evaluated based on the core parameter weights to determine the anti-aging coefficient. Furthermore, the application environment historical data can be used to predict the predicted aging time of asphalt to reach a certain aging degree in the application environment through the trained asphalt aging time prediction model, and an analysis report can be generated based on the predicted aging time, thereby improving the accuracy of the simulation analysis of the asphalt anti-aging performance. When determining the anti-aging coefficient, the anti-aging coefficient can be determined based on the needle penetration decrease ratio, the softening point increase ratio, the ductility decrease ratio, the viscosity increase ratio and the core parameter weights. During the calculation process, the anti-aging performance of the material asphalt in the application environment can be evaluated in four aspects: needle penetration anti-aging, softening point anti-aging, ductility anti-aging and viscosity anti-aging, thereby improving the comprehensiveness and accuracy of the anti-aging coefficient. When determining the training loss function, the training loss function of the asphalt aging time prediction model can be determined based on the sample predicted aging time, experimental aging time, experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient. During the calculation process, the influence of the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient on the aging time can be used to determine the influence of the above data on the error of the sample predicted aging time, and based on this influence and the relative error of the sample predicted aging time, the training loss function is set to reduce the training loss function of the asphalt aging time prediction model during the training process, and to improve the accuracy of the asphalt aging time prediction model in a more targeted manner.

[0015] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and not limiting of the present invention. Other features and aspects of the present invention will become more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can derive other embodiments based on these drawings without inventive efforts. Figure 1 A schematic diagram exemplarily illustrates a flow chart of a method for simulating and analyzing the anti-aging performance of asphalt according to an embodiment of the present invention; Figure 2 A schematic diagram illustrating, by way of example, determining core parameter weights according to an embodiment of the present invention; Figure 3A schematic diagram exemplarily illustrates a method for determining an experimental aging data threshold according to an embodiment of the present invention; Figure 4 A schematic diagram illustrating, by way of example, determining an anti-aging coefficient according to an embodiment of the present invention; Figure 5 A block diagram of a simulation and analysis system for asphalt anti-aging performance according to an embodiment of the present invention is exemplarily shown. DETAILED DESCRIPTION

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0018] The following specific embodiments are used to describe the technical solution of the present invention in detail. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0019] Figure 1 A flow chart of a method for simulating and analyzing the anti-aging performance of asphalt according to an embodiment of the present invention is exemplarily shown, the method comprising: step S1, obtaining historical data of an application environment; step S2, determining core parameter weights according to the historical data of the application environment, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; step S3, determining an experimental aging data threshold according to the historical data of the application environment; step S4, performing an aging simulation experiment on the material asphalt in multiple experimental cycles according to the experimental aging data threshold; step S5, obtaining experimental aging data of multiple experimental cycles, wherein the experimental aging data The test aging data includes: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; step S6, obtaining the initial physical property data and the ending physical property data of the material asphalt at the start and end times of multiple experimental cycles; step S7, determining the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the initial physical property data, the ending physical property data and the core parameter weights; step S8, processing the application environment historical data according to the trained asphalt aging time prediction model to determine the predicted aging time; step S9, generating an analysis report based on the predicted aging time.

[0020] According to the asphalt anti-aging performance simulation and analysis method of an embodiment of the present invention, the requirements of the application environment of asphalt for the physical properties of asphalt can be accurately analyzed based on the historical data of the application environment of asphalt, the core parameter weights can be determined, and the anti-aging performance of the material asphalt under simulated aging in the experimental cycle can be evaluated based on the core parameter weights to determine the anti-aging coefficient. Furthermore, the application environment historical data can be used to predict the predicted aging time of asphalt to reach a certain aging degree in the application environment, and an analysis report can be generated based on the predicted aging time, thereby improving the accuracy of the simulation analysis of the asphalt anti-aging performance.

[0021] According to one embodiment of the present invention, in step S1, application environment historical data is obtained.

[0022] For example, based on the actual application scenario of asphalt, the application environment historical data is determined. For example, when the actual application scenario of asphalt is the strong ultraviolet area in Hexi, the historical environmental data of the area (such as ultraviolet intensity, temperature, real-life images and traffic data) is obtained, that is, the application environment historical data.

[0023] According to one embodiment of the present invention, in step S2, core parameter weights are determined based on the application environment historical data, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight.

[0024] Figure 2 A schematic diagram of determining core parameter weights according to an embodiment of the present invention is exemplarily shown.

[0025] According to one embodiment of the present invention, step S2 includes: step S21, determining the historical environment ultraviolet intensity, historical environment temperature, historical application environment traffic flow and historical application environment scenario based on the application environment historical data; step S22, determining the application environment requirement coefficient based on the historical application environment scenario; step S23, determining the core parameter weight based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature and the historical application environment traffic flow.

[0026] For example, based on the historical data of the application environment, the average daily UV intensity and temperature of the real application scenario of asphalt in the past year, that is, the historical environment UV intensity and historical environment temperature, are determined. Through the anonymous user location data of the navigation platform and the GPS trajectory of the fleet (such as logistics vehicles, taxis) management system, the average daily traffic volume of the real application scenario of asphalt in the past year, that is, the historical application environment traffic volume, is determined. The on-site images of the real application scenario of asphalt are collected by the camera, and the historical application environment scenarios are determined based on the on-site images, such as highway scenes, large slope scenes, intersection scenes, bus station scenes and general scenes. Access road scenario; determine the application environment requirement coefficient based on the historical application environment scenario. For example, when the historical application environment scenario is a highway scenario, a steep slope scenario, an intersection scenario, or a bus station scenario, the above scenarios have higher requirements for asphalt, and the application environment requirement coefficient is 2. When the historical application environment scenario is an ordinary road scenario, the above scenarios have relatively low requirements for asphalt, and the application environment requirement coefficient is 1. Based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature, and the historical application environment traffic volume, evaluate the requirements of the application scenario for the penetration, softening point, ductility, and viscosity of asphalt, and determine the core parameter weights.

[0027] According to one embodiment of the present invention, step S23 includes: step S231, determining the high temperature area identification result and the low temperature area identification result according to the historical ambient temperature; step S232, determining the historical ambient temperature difference according to the historical ambient temperature; step S233, determining the large temperature difference area identification result according to the historical ambient temperature difference; step S234, determining the strong ultraviolet area identification result according to the historical ambient ultraviolet intensity; step S235, determining the high traffic area identification result according to the historical application environment vehicle volume; step S236, determining the needle penetration weight according to the low temperature area identification result, the large temperature difference area identification result and the strong ultraviolet area identification result; step S237, determining the elongation weight according to the low temperature area identification result and the large temperature difference area identification result; step S238, determining the softening point weight according to the high traffic area identification result, the high temperature area identification result and the application environment requirement coefficient; step S239, determining the viscosity weight according to the high traffic area identification result and the high temperature area identification result.

[0028] For example, if the historical ambient temperature is less than 5 degrees Celsius, the area is determined to be a low temperature area, and the low temperature area identification result is 1, otherwise the low temperature area identification result is 0. If the historical ambient temperature is greater than 20 degrees Celsius, the area is determined to be a high temperature area, and the high temperature area identification result is 1, otherwise the high temperature area identification result is 0; according to the historical ambient temperature, the daily average temperature difference is determined, that is, the historical ambient temperature difference; if the historical ambient temperature difference is greater than or equal to 20 degrees Celsius, it means that the temperature difference in the area is large, and the large temperature difference area identification result is 1, otherwise, the large temperature difference area identification result is 0; if the historical ambient ultraviolet intensity is greater than or equal to 8, it means that the ultraviolet intensity in the area is high, and the strong ultraviolet area identification result is 1, otherwise, the strong ultraviolet area identification result is The identification result is 0; if the historical application environment traffic volume is greater than 20,000 vehicles / day, it means that there is a lot of traffic passing through the location, and the vehicle load has a greater impact on asphalt aging. The identification result of the high traffic area is 1, otherwise, the identification result of the high traffic area is 0; the main disease of the road surface in low temperature areas is low temperature cracking. The sharp drop in penetration after aging (hardening) will greatly weaken the low temperature plasticity of the asphalt, causing the road surface to be more prone to cracking under low temperature shrinkage stress. Therefore, the low temperature area has higher requirements for the penetration of asphalt. In areas with large temperature differences, the fatigue resistance of asphalt is required to be greater. Therefore, areas with large temperature differences have higher requirements for the penetration of asphalt. In strong ultraviolet radiation areas, the ultraviolet radiation is strong and the photo-oxidation aging rate is fast, requiring higher anti-aging ability to maintain the penetration. , reduce embrittlement, therefore, the strong ultraviolet region has higher requirements for the penetration of asphalt. The penetration weight is determined by adding 1 to the sum of the identification results of the low temperature region, the identification results of the large temperature difference region and the identification results of the strong ultraviolet region. The larger the penetration weight, the higher the requirements for the penetration anti-aging performance of the region; in the large temperature difference region, the thermal shrinkage stress is obvious, and good ductility is required to absorb the stress. Therefore, in the large temperature difference region, the requirements for the ductility of asphalt are higher. In the low temperature region, the ductility of asphalt after aging must be high enough. Therefore, in the low temperature region, the requirements for the ductility of asphalt are higher. The ductility weight is determined by adding 1 to the sum of the identification results of the low temperature region and the identification results of the large temperature difference region. The larger the ductility weight, the higher the requirements for the ductility anti-aging performance of the region. High; In high temperature areas, rutting is the main disease of asphalt pavement. Therefore, in high temperature areas, the softening point requirement for asphalt is higher. In high traffic areas, too many vehicles passing by will cause too many rutting on the asphalt pavement, and the anti-rutting requirement is high. Therefore, in high traffic areas, the softening point requirement for asphalt is higher. In scenarios with a large application environment requirement coefficient, such as traffic roads, highways, large slope scenarios, intersections and bus stops, vehicles frequently accelerate and decelerate, brake and start, the shear stress is large, the temperature is high, and the anti-rutting requirement is higher. Therefore, in scenarios with a large application environment requirement coefficient, the softening point requirement for asphalt is higher. The softening point weight is determined based on the sum of the high traffic area identification result, the high temperature area identification result and the application environment requirement coefficient plus 1;In high-traffic areas, excessive vehicle traffic can cause excessive rutting on asphalt pavement, necessitating high fatigue and rutting resistance. Therefore, higher viscosity requirements are imposed on asphalt in high-traffic areas. Similarly, high-temperature areas require high-temperature stability and rutting resistance. Therefore, higher viscosity requirements are imposed on asphalt in high-temperature areas. The viscosity weight is determined by adding 1 to the sum of the high-traffic and high-temperature area identification results.

[0029] According to an embodiment of the present invention, in step S3, an experimental aging data threshold is determined based on the application environment historical data.

[0030] Figure 3 A schematic diagram of determining a threshold value of experimental aging data according to an embodiment of the present invention is exemplarily shown.

[0031] According to one embodiment of the present invention, step S3 includes: step S31, determining an experimental aging temperature threshold based on the historical ambient temperature; step S32, determining an experimental aging temperature difference threshold based on the historical ambient temperature difference; step S33, determining an experimental ultraviolet intensity threshold based on the historical ambient ultraviolet intensity; step S34, determining an application road type based on the historical application environment scenario; step S35, determining an experimental load intensity threshold based on the application road type.

[0032] For example, when the historical ambient temperature is 20 degrees Celsius, the experimental aging temperature threshold is 20 degrees Celsius; when the historical ambient temperature difference is 15 degrees Celsius, the experimental aging temperature difference threshold is 15 degrees Celsius; if the historical ambient ultraviolet intensity is 6, the experimental ultraviolet intensity threshold is 6; according to the historical application environment scenario, determine the road type for the material asphalt simulation application, that is, the application road type, such as expressways, ordinary national highways and urban roads; when the application road type is expressway, the experimental load intensity threshold is 0.7MPa, when the application road type is ordinary national highway, the experimental load intensity threshold is 0.5MPa, when the application road type is urban road, the experimental load intensity threshold is 0.3MPa.

[0033] According to one embodiment of the present invention, in step S4, an aging simulation experiment is performed on the asphalt material in multiple experimental cycles according to the experimental aging data threshold.

[0034] For example, in multiple experimental cycles, by controlling temperature, temperature difference, ultraviolet intensity and load, the aging conditions of the asphalt material under different conditions are simulated. When the high temperature area identification result is 1, in the experimental cycle, the experimental aging temperature is greater than or equal to the experimental aging temperature threshold. When the low temperature area identification result is 1, in the experimental cycle, the experimental aging temperature is less than or equal to the experimental aging temperature threshold. In the experimental cycle, the experimental ultraviolet intensity is greater than or equal to the experimental ultraviolet intensity threshold. In the experimental cycle, the experimental load intensity is greater than or equal to the experimental load intensity threshold. When the experimental aging temperature threshold is 30 degrees Celsius, the experimental aging temperature difference threshold is 15 degrees Celsius, the experimental ultraviolet intensity threshold is 6, and the experimental load intensity threshold is 0.7 MPa, in the experimental cycle, a load of 0.7 MPa and ultraviolet light with an ultraviolet intensity of 6 are continuously applied to the asphalt material, and temperature cycles from 30 degrees Celsius to 15 degrees Celsius and from 15 degrees Celsius to 30 degrees Celsius are performed.

[0035] According to one embodiment of the present invention, in step S5, experimental aging data of multiple experimental cycles are obtained, wherein the experimental aging data include: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time.

[0036] For example, the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity, and the duration of the experimental cycle, that is, the experimental aging time, of multiple experimental cycles are determined.

[0037] According to one embodiment of the present invention, in step S6, initial physical property data and ending physical property data of the asphalt material are acquired at the start and end times of multiple experimental cycles.

[0038] For example, at the beginning and end of multiple experimental cycles, the penetration, softening point, ductility and viscosity of the asphalt material are tested by testing instruments to obtain the initial and ending physical property data of the asphalt material.

[0039] According to one embodiment of the present invention, in step S7, the anti-aging coefficient of the material asphalt of multiple experimental cycles is determined based on the initial physical property data, the end physical property data and the core parameter weights.

[0040] Figure 4 A schematic diagram of determining an anti-aging coefficient according to an embodiment of the present invention is exemplarily shown.

[0041] According to one embodiment of the present invention, step S7 includes: step S71, determining the initial penetration, initial softening point, initial elongation and initial viscosity based on the initial physical property data; step S72, determining the ending penetration, ending softening point, ending elongation and ending viscosity based on the ending physical property data; step S73, determining the penetration decrease ratio based on the initial penetration and the ending penetration; step S74, determining the softening point increase ratio based on the initial softening point and the ending softening point; step S75, determining the elongation decrease ratio based on the initial elongation and the ending elongation; step S76, determining the viscosity increase ratio based on the initial viscosity and the ending viscosity; step S77, determining the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the penetration decrease ratio, the softening point increase ratio, the elongation decrease ratio, the viscosity increase ratio and the core parameter weights.

[0042] For example, at the beginning and end of multiple experimental cycles, the penetration, softening point, elongation and viscosity of the asphalt material are tested by a penetration meter, a softening point meter, an elongation meter and a rotational viscometer respectively to determine the initial penetration, the end penetration, the initial softening point, the end softening point, the initial elongation, the end elongation, the initial viscosity and the end viscosity; the aging of asphalt causes the penetration to decrease, and the penetration decrease ratio is determined based on the ratio of the difference between the initial penetration and the end penetration to the initial penetration. The larger the penetration decrease ratio, the deeper the aging; the aging of asphalt causes the softening point to increase, and the difference between the end softening point and the initial softening point is determined based on the ratio of the initial softening point and the end softening point. The softening point increase ratio is determined. The larger the softening point increase ratio is, the deeper the aging degree is. The aging of asphalt causes the ductility to decrease. The ductility decrease ratio is determined according to the ratio of the difference between the initial ductility and the final ductility to the initial ductility. The larger the ductility decrease ratio is, the deeper the aging degree is. The aging of asphalt causes the viscosity to increase. The viscosity increase ratio is determined according to the ratio of the difference between the final viscosity and the initial viscosity to the initial viscosity. The larger the viscosity increase ratio is, the deeper the aging degree is. According to the needle penetration decrease ratio, softening point increase ratio, ductility decrease ratio, viscosity increase ratio and core parameter weights, the anti-aging performance of the material asphalt in multiple experimental cycles is evaluated to determine the anti-aging coefficient of the material asphalt.

[0043] According to one embodiment of the present invention, step S77 includes: determining the anti-aging coefficient of the asphalt material in the kth experimental cycle according to formula (1): , (1) in, is the penetration reduction ratio of the asphalt material in the kth experimental cycle, is the penetration weight, is the softening point increase ratio of the asphalt material in the kth experimental cycle, is the softening point weight, is the ductility reduction ratio of the asphalt material in the kth experimental cycle, is the extension weight, is the viscosity increase ratio of the asphalt material in the kth experimental cycle, is the viscosity weight.

[0044] According to one embodiment of the present invention, is the penetration reduction ratio of the asphalt material in the kth experimental cycle, The larger it is, the smaller the aging degree reflected by the change of needle penetration of the asphalt material is, and the stronger the anti-aging performance of the asphalt material in terms of needle penetration change is. is the penetration weight, which indicates the importance of the penetration anti-aging performance in actual application scenarios. It indicates the performance of weighted material asphalt in terms of needle penetration and anti-aging; is the softening point increase ratio of the asphalt material in the kth experimental cycle, The larger it is, the smaller the aging degree reflected by the change of the softening point of the asphalt material is, and the stronger the anti-aging performance of the asphalt material in terms of the change of the softening point is. is the softening point weight, which indicates the importance of the softening point anti-aging performance in actual application scenarios. Indicates the performance of weighted material asphalt in terms of softening point anti-aging; is the ductility reduction ratio of the asphalt material in the kth experimental cycle, The larger it is, the smaller the aging degree reflected by the ductility change of the material asphalt is, and the stronger the anti-aging performance of the material asphalt in terms of ductility change is. is the ductility weight, which indicates the importance of ductility and anti-aging performance in actual application scenarios. It indicates the performance of weighted asphalt in terms of ductility and anti-aging; is the viscosity increase ratio of the asphalt material in the kth experimental cycle, The larger it is, the smaller the aging degree reflected by the viscosity change of the asphalt material is, and the stronger the anti-aging performance of the asphalt material in terms of ductility change is. is the viscosity weight, which indicates the importance of viscosity anti-aging performance in actual application scenarios. It represents the performance of weighted asphalt material in terms of ductility and anti-aging.

[0045] According to one embodiment of the present invention, It means that the anti-aging coefficient is determined based on the four aspects of the asphalt material's anti-aging properties: penetration anti-aging, softening point anti-aging, ductility anti-aging and viscosity anti-aging.

[0046] In this way, the anti-aging coefficient can be determined based on the penetration decrease ratio, softening point increase ratio, ductility decrease ratio, viscosity increase ratio and core parameter weights. During the calculation process, the anti-aging performance of the material asphalt in the application environment can be evaluated in four aspects: penetration anti-aging, softening point anti-aging, ductility anti-aging and viscosity anti-aging, thereby improving the comprehensiveness and accuracy of the anti-aging coefficient.

[0047] According to one embodiment of the present invention, in step S8, the application environment historical data is processed according to the trained asphalt aging time prediction model to determine the predicted aging time.

[0048] For example, determine the preset anti-aging coefficient threshold, such as 0.5 When the anti-aging coefficient of asphalt drops to a preset anti-aging coefficient threshold, it means that the asphalt no longer meets the actual usage requirements. The preset anti-aging coefficient threshold and the application environment historical data are processed according to the trained asphalt aging time prediction model to predict the time required for the anti-aging coefficient of asphalt to drop to the preset anti-aging coefficient threshold under the application environment historical data, that is, the predicted aging time.

[0049] According to one embodiment of the present invention, the training step of the asphalt aging time prediction model includes: Processing the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity, and the anti-aging coefficient according to the asphalt aging time prediction model to determine the predicted aging time of the sample; Determining a training loss function of an asphalt aging time prediction model based on the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity, and the anti-aging coefficient; The asphalt aging time prediction model is trained according to the training loss function to obtain a trained asphalt aging time prediction model.

[0050] For example, according to the asphalt aging time prediction model, the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient are processed to predict the time required for the asphalt anti-aging coefficient to drop from the initial anti-aging coefficient to the current anti-aging coefficient under the current experimental environment, that is, the sample predicted aging time; according to the sample predicted aging time, experimental aging time, experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient, the training loss function of the asphalt aging time prediction model is determined; according to the training loss function, the asphalt aging time prediction model is trained to improve the accuracy of the asphalt aging time prediction model for asphalt aging time prediction, and obtain a trained asphalt aging time prediction model.

[0051] According to one embodiment of the present invention, the training loss function of the asphalt aging time prediction model is determined based on the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient, including: determining the training loss function of the asphalt aging time prediction model according to formula (2): , (2) in, is the experimental aging time of the kth experimental cycle, Predict the aging time for the samples of the kth experimental cycle, is the experimental aging temperature of the kth experimental cycle, is the preset experimental temperature threshold, is the experimental aging temperature difference of the kth experimental cycle, To preset the experimental temperature difference threshold, is the experimental ultraviolet intensity of the kth experimental cycle, To preset the experimental ultraviolet intensity threshold, is the experimental load intensity of the kth experimental cycle, is the preset experimental load intensity threshold, is the anti-aging coefficient of the asphalt material in the kth experimental cycle, is the needle penetration weight, is the softening point weight, is the extension weight, is the viscosity weight, K is the number of experimental cycles, k≤K, and both k and K are positive integers.

[0052] According to one embodiment of the present invention, is the sum of the penetration weight, softening point weight, ductility weight and viscosity weight, which represents the anti-aging coefficient of the asphalt material at the initial moment of the experimental period. It is the ratio of the anti-aging coefficient of the material asphalt in the kth experimental cycle to the anti-aging coefficient of the material asphalt at the initial moment of the experimental cycle. The larger the ratio, the greater the anti-aging coefficient of the material asphalt in the kth experimental cycle. is the relative difference between the experimental aging temperature of the kth experimental cycle and the preset experimental temperature threshold. The larger the ratio, the greater the difference between the experimental aging temperature and the preset experimental temperature threshold. The preset experimental temperature threshold can be set to 10 degrees Celsius. The ratio of the experimental aging temperature difference of the kth experimental cycle to the preset experimental temperature difference threshold. The larger the ratio, the larger the experimental aging temperature difference. The preset experimental temperature difference threshold can be 10 degrees Celsius. is the ratio of the experimental ultraviolet intensity of the kth experimental cycle to the preset experimental ultraviolet intensity threshold. The larger the ratio, the greater the experimental ultraviolet intensity. The preset experimental ultraviolet intensity threshold can be set to 5. It is the ratio of the experimental load intensity of the kth experimental cycle to the preset experimental load intensity threshold. The larger the ratio is, the greater the experimental load intensity of the kth experimental cycle is. The preset experimental load intensity threshold can be set to 0.5MPa. It indicates that the relative difference between the experimental aging temperature and the preset experimental temperature threshold, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient are negatively correlated with the experimental aging time. For example, the higher the experimental aging temperature, the faster the oxygen diffusion rate at high temperature, the faster the asphalt aging speed, and the shorter the experimental aging time required to reach a certain aging degree. The lower the experimental aging temperature, the lower the temperature, the loss of molecular fluidity, and the more likely it is to cause cracking. The faster the asphalt aging speed, the shorter the experimental aging time required to reach a certain aging degree. The greater the experimental aging temperature difference, the more likely it is to cause repeated stress changes inside the asphalt material. The faster the asphalt aging speed, the shorter the experimental aging time required to reach a certain aging degree. The shorter the experimental aging time required for the degree of aging, the greater the experimental ultraviolet intensity, the more direct the UV photon energy breaks the weak bonds in the asphalt molecules, the faster the asphalt ages, and the shorter the experimental aging time required to reach a certain aging degree. The greater the experimental load intensity, the greater the micro-strain energy generated inside the asphalt, the faster the asphalt ages, and the shorter the experimental aging time required to reach a certain aging degree. The greater the anti-aging coefficient of the material asphalt, the smaller the aging degree of the asphalt, and the shorter the required experimental aging time. Therefore, the items related to the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient are placed in the denominator to express 、 、 、 and The larger the value of , the smaller the sample prediction aging time.

[0053] According to one embodiment of the present invention, is the experimental aging time of the kth experimental cycle and the relative error of the sample predicted aging time, using The training loss function is obtained by taking a weighted average of the relative errors between the experimental aging time and the sample-predicted aging time for each experimental cycle. During training, this training loss function is reduced, thereby reducing the error between the experimental aging time and the sample-predicted aging time. This improves the accuracy of the asphalt aging time prediction model.

[0054] In this way, the training loss function of the asphalt aging time prediction model can be determined based on the sample predicted aging time, experimental aging time, experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient. During the calculation process, the influence of the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient on the aging time can be used to determine the influence of the above data on the error of the sample predicted aging time, and based on this influence and the relative error of the sample predicted aging time, the training loss function is set to reduce the training loss function of the asphalt aging time prediction model during the training process, and to improve the accuracy of the asphalt aging time prediction model in a more targeted manner.

[0055] According to one embodiment of the present invention, in step S9, an analysis report is generated based on the predicted aging time.

[0056] For example, if the predicted aging time is greater than or equal to the expected service time (e.g., 10 years), it means that the asphalt anti-aging performance is qualified; if the predicted aging time is less than the expected service time, it means that the asphalt anti-aging performance is unqualified.

[0057] According to an embodiment of the present invention, the asphalt anti-aging performance simulation and analysis method can accurately analyze the requirements of the asphalt application environment for the physical properties of asphalt based on historical data of the asphalt application environment, determine core parameter weights, and evaluate the asphalt material's anti-aging performance under simulated aging during the experimental cycle based on the core parameter weights to determine the anti-aging coefficient. Furthermore, the asphalt aging time prediction model, trained on the application environment historical data, predicts the predicted aging time for the asphalt to reach a certain aging degree in the application environment, and generates an analysis report based on the predicted aging time, thereby improving the accuracy of the asphalt anti-aging performance simulation analysis. When determining the anti-aging coefficient, the anti-aging coefficient can be determined based on the penetration reduction ratio, softening point increase ratio, ductility reduction ratio, viscosity increase ratio, and core parameter weights. During the calculation process, the asphalt material's anti-aging performance in the application environment can be evaluated based on four aspects: penetration anti-aging, softening point anti-aging, ductility anti-aging, and viscosity anti-aging, thereby improving the comprehensiveness and accuracy of the anti-aging coefficient. When determining the training loss function, the training loss function of the asphalt aging time prediction model can be determined based on the sample predicted aging time, experimental aging time, experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient. During the calculation process, the influence of the experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and anti-aging coefficient on the aging time can be used to determine the influence of the above data on the error of the sample predicted aging time, and based on this influence and the relative error of the sample predicted aging time, the training loss function is set to reduce the training loss function of the asphalt aging time prediction model during the training process, and to improve the accuracy of the asphalt aging time prediction model in a more targeted manner.

[0058] Figure 5The block diagram of the asphalt anti-aging performance simulation and analysis system according to an embodiment of the present invention is exemplarily shown, and the system includes: a historical data module for obtaining application environment historical data; a parameter weight module for determining core parameter weights according to the application environment historical data, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; an experimental threshold module for determining experimental aging data thresholds according to the application environment historical data; a simulation experiment module for performing aging simulation experiments on the material asphalt in multiple experimental cycles according to the experimental aging data thresholds; an aging data module for obtaining experimental aging data of multiple experimental cycles, wherein the experimental The test aging data includes: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; a physical data module, which is used to obtain the initial physical property data and the final physical property data of the material asphalt at the start and end times of multiple experimental cycles; an anti-aging coefficient module, which is used to determine the anti-aging coefficient of the material asphalt for multiple experimental cycles based on the initial physical property data, the final physical property data and the core parameter weights; a prediction time module, which is used to process the application environment historical data according to the trained asphalt aging time prediction model to determine the predicted aging time; an analysis report module, which is used to generate an analysis report based on the predicted aging time.

[0059] The present invention may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0060] Those skilled in the art will appreciate that the embodiments of the present invention described above and shown in the accompanying drawings are intended to be illustrative only and are not intended to limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and illustrated in the embodiments. Any variations or modifications may be made to the embodiments of the present invention without departing from the principles described.

Claims

1. A simulation analysis method for asphalt anti-aging performance, characterized in that: include: Obtain historical data of the application environment; According to the application environment historical data, the core parameter weights are determined, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; according to the application environment historical data, the experimental aging data threshold is determined; according to the experimental aging data threshold, an aging simulation experiment is performed on the material asphalt in multiple experimental cycles; the experimental aging data of the multiple experimental cycles are obtained, wherein the experimental aging data include: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; at the start and end times of the multiple experimental cycles, the initial physical property data and the ending physical property data of the material asphalt are obtained; according to the initial physical property data, the ending physical property data and the core parameter weights, the anti-aging coefficient of the material asphalt of the multiple experimental cycles is determined; according to the trained asphalt aging time prediction model, the application environment historical data is processed to determine the predicted aging time; according to the predicted aging time, an analysis report is generated.

2. The asphalt anti-aging performance simulation analysis method according to claim 1, characterized in that: Determine core parameter weights based on the application environment historical data, including: determining the historical environment ultraviolet intensity, historical environment temperature, historical application environment traffic volume and historical application environment scenarios based on the application environment historical data; determine the application environment requirement coefficient based on the historical application environment scenarios; determine core parameter weights based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature and the historical application environment traffic volume.

3. The asphalt anti-aging performance simulation analysis method according to claim 2, characterized in that: The core parameter weights are determined based on the application environment requirement coefficient, the historical environment ultraviolet intensity, the historical environment temperature and the historical application environment traffic volume, including: determining the high temperature area identification result and the low temperature area identification result based on the historical environment temperature; determining the historical environment temperature difference based on the historical environment temperature; determining the large temperature difference area identification result based on the historical environment temperature difference; determining the strong ultraviolet area identification result based on the historical application environment traffic volume; determining the high traffic area identification result based on the low temperature area identification result, the large temperature difference area identification result and the strong ultraviolet area identification result; determining the elongation weight based on the low temperature area identification result and the large temperature difference area identification result; determining the softening point weight based on the high traffic area identification result, the high temperature area identification result and the application environment requirement coefficient; and determining the viscosity weight based on the high traffic area identification result and the high temperature area identification result.

4. The asphalt anti-aging performance simulation analysis method according to claim 3, characterized in that: Determine the experimental aging data threshold based on the application environment historical data, including: determining the experimental aging temperature threshold based on the historical environment temperature; determining the experimental aging temperature difference threshold based on the historical environment temperature difference; determining the experimental ultraviolet intensity threshold based on the historical environment ultraviolet intensity; determining the application road type based on the historical application environment scenario; and determining the experimental load intensity threshold based on the application road type.

5. The asphalt anti-aging performance simulation analysis method according to claim 4, characterized in that: According to the initial physical property data, the ending physical property data and the core parameter weights, the anti-aging coefficient of the material asphalt for multiple experimental cycles is determined, including: determining the initial needle penetration, initial softening point, initial ductility and initial viscosity according to the initial physical property data; determining the ending needle penetration, ending softening point, ending ductility and ending viscosity according to the ending physical property data; determining the needle penetration decrease ratio according to the initial needle penetration and the ending needle penetration; determining the softening point increase ratio according to the initial softening point and the ending softening point; determining the ductility decrease ratio according to the initial ductility and the ending ductility; determining the viscosity increase ratio according to the initial viscosity and the ending viscosity; determining the anti-aging coefficient of the material asphalt for multiple experimental cycles according to the needle penetration decrease ratio, the softening point increase ratio, the ductility decrease ratio, the viscosity increase ratio and the core parameter weights.

6. The asphalt anti-aging performance simulation analysis method according to claim 5, characterized in that: According to the penetration decrease ratio, the softening point increase ratio, the ductility decrease ratio, the viscosity increase ratio and the core parameter weight, the anti-aging coefficient of the asphalt material of multiple experimental cycles is determined, including: according to the formula Determine the anti-aging coefficient of the material asphalt in the kth experimental cycle ,in, is the penetration reduction ratio of the asphalt material in the kth experimental cycle, is the penetration weight, is the softening point increase ratio of the asphalt material in the kth experimental cycle, is the softening point weight, is the ductility reduction ratio of the asphalt material in the kth experimental cycle, is the extension weight, is the viscosity increase ratio of the asphalt material in the kth experimental cycle, is the viscosity weight.

7. The asphalt anti-aging performance simulation analysis method according to claim 6, characterized in that: The training steps of the asphalt aging time prediction model include: processing the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient according to the asphalt aging time prediction model to determine the sample predicted aging time; determining the training loss function of the asphalt aging time prediction model according to the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient; training the asphalt aging time prediction model according to the training loss function to obtain a trained asphalt aging time prediction model.

8. The asphalt anti-aging performance simulation analysis method according to claim 7, characterized in that: According to the sample predicted aging time, the experimental aging time, the experimental aging temperature, the experimental aging temperature difference, the experimental ultraviolet intensity, the experimental load intensity and the anti-aging coefficient, the training loss function of the asphalt aging time prediction model is determined, including: according to the formula Determining the training loss function for the asphalt aging time prediction model ,in, is the experimental aging time of the kth experimental cycle, Predict the aging time for the samples of the kth experimental cycle, is the experimental aging temperature of the kth experimental cycle, is the preset experimental temperature threshold, is the experimental aging temperature difference of the kth experimental cycle, To preset the experimental temperature difference threshold, is the experimental ultraviolet intensity of the kth experimental cycle, To preset the experimental ultraviolet intensity threshold, is the experimental load intensity of the kth experimental cycle, is the preset experimental load intensity threshold, is the anti-aging coefficient of the asphalt material in the kth experimental cycle, is the needle penetration weight, is the softening point weight, is the extension weight, is the viscosity weight, K is the number of experimental cycles, k≤K, and both k and K are positive integers.

9. A simulation and analysis system for asphalt anti-aging performance, characterized in that: include: Historical data module, used to obtain historical data of application environment; a parameter weight module for determining core parameter weights based on the application environment historical data, wherein the core parameter weights include: needle penetration weight, softening point weight, ductility weight and viscosity weight; an experimental threshold module for determining an experimental aging data threshold based on the application environment historical data; a simulation experiment module for performing aging simulation experiments on the asphalt material in multiple experimental cycles based on the experimental aging data threshold; an aging data module for obtaining experimental aging data for multiple experimental cycles, wherein the experimental aging data include: experimental aging temperature, experimental aging temperature difference, experimental ultraviolet intensity, experimental load intensity and experimental aging time; a physical data module for obtaining initial physical property data and ending physical property data of the asphalt material at the start and end times of multiple experimental cycles; an anti-aging coefficient module for determining the anti-aging coefficient of the asphalt material for multiple experimental cycles based on the initial physical property data, the ending physical property data and the core parameter weights; a prediction time module for processing the application environment historical data based on a trained asphalt aging time prediction model to determine a predicted aging time; and an analysis report module for generating an analysis report based on the predicted aging time.

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