Method for dynamic testing of asphalt concrete pavement bearing capacity

Abstract

The application discloses a kind of asphalt concrete pavement bearing capacity dynamic test methods, comprising: S1, deployment test vehicle, obtain vehicle source data, construct dynamic test whole vehicle model;S2, obtain asphalt concrete pavement source data, combine dynamic test whole vehicle model, construct vehicle road dynamic response model;S3, establish deflection pavement mathematical model using vehicle road dynamic response model;S4, select test section, obtain road surface deflection value and road surface dynamic reaction data;S5, construct road surface deflection solving framework, inversion obtains base top equivalent resilience modulus, establishes road bearing capacity evaluation system;S6, determine the base top equivalent resilience modulus corresponding to the measured deflection value by road surface dynamic reaction data and road surface deflection value, calculate asphalt pavement modulus index, according to grading criterion, generate road bearing capacity report.The application realizes the combination of multiple factors, uses dynamic test, realizes the quick, accurate asphalt concrete pavement bearing capacity test.

Description

Technical Field

[0001] This invention relates to the field of pavement bearing capacity testing technology, and specifically to a dynamic testing method for the bearing capacity of asphalt concrete pavement. Background Technology

[0002] With the continuous increase in road traffic volume and the growing number of heavy vehicles, ensuring that asphalt concrete pavements have sufficient load-bearing capacity to guarantee driving safety and extend road service life is of paramount importance. However, traditional assessments of pavement load-bearing capacity rely heavily on static testing methods or estimations based on empirical formulas. These methods struggle to accurately reflect the dynamic response characteristics under actual traffic loads, leading to inaccurate assessments of pavement structural health.

[0003] Traditional technical solutions primarily employ static loading tests, such as the Beckman beam method, to measure road surface deformation. While this method can provide deflection values ​​under certain conditions, it cannot simulate real-world driving conditions, failing to consider the influence of vehicle speed, vehicle dynamics, and environmental factors. Furthermore, traditional methods often require closed-loop testing, making them complex and inefficient. In contrast, while some existing dynamic testing techniques consider some dynamic factors, they still fall short in comprehensively simulating vehicle-road interaction, failing to fully reflect the coupling effects of the vehicle-road system, and also have limitations in data acquisition accuracy and processing speed.

[0004] The present invention addresses the current technological situation where, despite the introduction of dynamic elements in road load-bearing capacity assessment, a comprehensive framework is still lacking to integrate the various dynamic responses generated during vehicle operation and how these responses affect the pavement structure. Existing solutions typically focus on single-factor analysis, such as vehicle load or pavement material properties, neglecting the interaction between the two. This not only limits the accuracy of test results but also makes the assessment system difficult to adapt to complex and changing real-world conditions. Therefore, a novel testing method that can comprehensively consider the impact of vehicle-road interaction is urgently needed.

[0005] To address the problems existing in the prior art, this invention proposes a novel dynamic testing method for the bearing capacity of asphalt concrete pavement. Summary of the Invention

[0006] This invention discloses a dynamic testing method for the bearing capacity of asphalt concrete pavement, comprising:

[0007] S1. Deploy test vehicles, acquire vehicle source data, and build a dynamic test vehicle model;

[0008] S2. Obtain source data of asphalt concrete pavement and construct a vehicle-road dynamic response model by combining it with a dynamic test vehicle model.

[0009] S3. Analyze the influence of vehicle speed, vehicle load, asphalt surface properties and base material properties on pavement surface deflection using the vehicle-road dynamic response model, and establish a mathematical model of deflection pavement.

[0010] S4. Select a test section, set up sensor nodes at the wheel track line, and obtain dynamic response data of the road surface and deflection value of the road surface.

[0011] S5. Based on the mathematical model of deflection pavement, a solution framework for pavement deflection is constructed by combining measured data. The equivalent resilient modulus of the base is obtained by inversion through the pavement deflection solution framework, and a road bearing capacity assessment system is established.

[0012] S6. Determine the equivalent resilient modulus of the base top corresponding to the measured deflection value by using the dynamic response data of the pavement and the deflection value of the pavement surface. Compare the actual measured value with the design value, calculate the asphalt pavement modulus index, and generate a pavement bearing capacity report according to the grading criteria.

[0013] Preferably, the construction of the dynamic test vehicle model includes the following steps:

[0014] S1.1 Install multiple types of sensors on the test vehicle to collect dynamic response data of the vehicle during driving;

[0015] S1.2 Based on dynamic response data, combined with the vehicle's static geometric dimensions and mass distribution, a vehicle source database of static structure and dynamic characteristics is formed.

[0016] S1.3. Based on the vehicle source database, a three-dimensional geometric model of the vehicle is created using the finite element analysis mechanism. Nodes and element meshes are defined to discretize the bottom contact structure of the vehicle, forming a dynamic test vehicle model.

[0017] Preferably, the vehicle three-dimensional geometric model in S1.3 incorporates the vehicle's seven-degree-of-freedom dynamic characteristics, road surface smoothness, and random load factors to simulate different dynamic response behaviors of the vehicle driving on the asphalt concrete road surface. At the same time, the dynamic load generated by the vehicle is converted into stress distribution acting on the road structure layer by using the dynamic load transfer function, thereby realizing a comprehensive numerical simulation of vehicle-road interaction.

[0018] Preferably, the construction of the vehicle-road dynamic response model includes the following steps:

[0019] S2.1 Deploy multiple types of sensors on the test section to obtain the stress, strain, temperature and humidity changes of the road surface structure under vehicle load, and use a scanner to record the geometric features of the road surface.

[0020] S2.2 Based on the data collected on site, determine the key mechanical performance parameters of the asphalt surface layer and base material of the road surface, integrate the geometric parameters of the road structure as well as compaction and smoothness, and form a database of road characteristics;

[0021] S2.3. Combine the dynamic test vehicle model with the road surface characteristic database, obtain the wheel track distribution on the vehicle's driving path, and determine the road surface location where the vehicle load is applied.

[0022] S2.4. Use finite element analysis software to create a three-dimensional geometric model of the road structure, define nodes and element meshes to discretize the road structure, and apply vehicle load as input condition to the three-dimensional geometric model of the road structure to form a vehicle-road dynamic response model.

[0023] Preferably, the deflection pavement mathematical model in S3 is constructed by analyzing the vehicle speed v, vehicle load F, and the elastic modulus E of the asphalt pavement properties. s And the resilient modulus E of the substrate material properties b The influence of road surface deflection was investigated by simulating deflection changes under different driving speeds and loads. The deflection calculation formula for these changes is as follows: Where δ represents the surface deflection value of the road surface, a is the radius of influence, and E is the radius of influence. c It is the composite modulus, v is Poisson's ratio, and h is the thickness of the asphalt surface layer; the deflection value of the road surface is embedded into the vehicle-road dynamic response model, and the finite element analysis mechanism is used for numerical solution to obtain the specific deflection response of the road surface, forming a deflection road mathematical model.

[0024] Preferably, in step S4, a test section is selected, and sensor nodes are set at the wheel track lines to acquire dynamic response data of the road surface and the deflection value of the road surface. Specifically, this includes: on the selected test section, high-precision sensor nodes are arranged along the main wheel track lines of the vehicle, including but not limited to deflectometers, strain gauges, accelerometers, and displacement sensors; the sensors are used to collect dynamic response data of the road surface under vehicle load in real time, including but not limited to stress, strain, vibration acceleration, and displacement changes, and to measure the instantaneous deflection value of the road surface before and after the vehicle passes.

[0025] Preferably, the sensor node records and transmits data synchronously via wireless communication, and accurately marks the time and location information of each measurement by means of a synchronous marking unit, thereby obtaining the dynamic response data of the road surface and the surface deflection value at the marked point.

[0026] Preferably, in step S5, a solution framework for road surface deflection is constructed based on a deflection pavement mathematical model and combined with measured data. Specifically, this includes: inputting the measured pavement dynamic response data and surface deflection values ​​into a pre-established deflection pavement mathematical model; comparing the deflection values ​​predicted by the deflection pavement mathematical model with the actual measured deflection values; and using an iterative optimization mechanism to adjust key parameters in the deflection pavement mathematical model, including but not limited to composite modulus, Poisson's ratio, and asphalt surface layer thickness, in order to minimize the error between the deflection values ​​predicted by the deflection pavement mathematical model and the actual measured deflection values, thereby forming a solution framework for simulating the deflection response of the pavement under different working conditions.

[0027] Preferably, in step S5, the equivalent resilient modulus at the base is obtained by inversion using the road surface deflection solution framework, and a road bearing capacity assessment system is established. Specifically, this includes: inputting the road surface deflection value δ and dynamic response data into the road surface deflection solution framework, and obtaining the equivalent resilient modulus E at the base through inversion using the road surface deflection solution framework. t The formula is: Where F(t) is the vehicle load varying with time, δ is the calculated deflection value, a is the radius of influence, β is the correction coefficient for the asphalt pavement properties, and h is the asphalt pavement thickness; the equivalent resilient modulus E at the base is calculated by combining the deflection value and vehicle load data. t The E obtained from the inversion t Based on design standards and specifications, different levels of road carrying capacity indicators are defined to form a road carrying capacity assessment system.

[0028] Preferably, step S6 determines the measured deflection value δ using pavement dynamic response data and pavement surface deflection values. s Based on the corresponding base equivalent resilient modulus, compare the actual measured value with the design value to calculate the asphalt pavement modulus index. The formula is as follows: Where M is the modulus index of asphalt pavement, and E t E0 is the base equivalent resilient modulus obtained by inversion, τ is the design standard resilient modulus, ΔT is the temperature sensitivity coefficient, and ΔT is the temperature difference between the actual measurement and the design conditions. Based on the asphalt pavement modulus index M and a preset grading criterion, a pavement bearing capacity report is generated. The pavement bearing capacity report includes, but is not limited to, the specific parameters of each test section, comparative analysis results, and maintenance recommendations.

[0029] Compared with the prior art, the technical solution of this application has the following technical effects:

[0030] This invention solves the problem that traditional static testing methods cannot simulate the interaction between vehicles and roads under real driving conditions by constructing a dynamic test vehicle model and introducing the vehicle's seven-degree-of-freedom dynamic characteristics, road surface smoothness, and random load factors. It can comprehensively simulate various dynamic response behaviors of vehicles during driving, including the stress distribution generated by the vehicle on the road surface. It can more accurately evaluate the load-bearing capacity of asphalt concrete pavement under actual traffic conditions, providing a more reliable basis for road design and maintenance.

[0031] This invention solves the problems of inaccurate data acquisition and difficulty in real-time monitoring in traditional testing methods by deploying multiple types of sensor nodes on the test road section and using wireless communication to synchronously record and transmit data. It ensures high-precision acquisition of dynamic response data and surface deflection values ​​of the road surface, while accurately marking the time and location information of each measurement, realizing real-time monitoring of road conditions. This helps to promptly identify potential problems and take corresponding measures, thereby improving the response speed and service level of road management.

[0032] This invention solves the problem of discrepancies between model predictions and actual conditions in existing technologies by establishing a mathematical model of pavement deflection and inputting measured data into a pre-established solution framework for iterative optimization. By adjusting key parameters such as composite modulus, Poisson's ratio, and asphalt pavement thickness, the prediction error is minimized, resulting in a more accurate simulation of pavement deflection response. This enhances the model's adaptability and prediction accuracy, providing strong support for the prediction of pavement performance under different working conditions, and further promoting the improvement and development of the road bearing capacity assessment system.

[0033] This invention generates a pavement bearing capacity report by calculating the equivalent resilient modulus of the pavement base and comparing it with design standards. This solves the problem that traditional assessment methods are unable to quantitatively describe the health status of roads. By combining deflection values ​​and vehicle load data, an inversion algorithm is used to calculate indicators reflecting the pavement structural characteristics. Based on this, detailed grading criteria are formulated, providing a scientific and reasonable road bearing capacity evaluation mechanism. This mechanism can not only accurately determine the current pavement condition, but also provide specific maintenance suggestions based on the analysis results, guiding road maintenance work and effectively extending the service life of roads.

[0034] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings.

[0035] The above and other objects, advantages and features of this application will become more apparent to those skilled in the art from the following detailed description of specific embodiments in conjunction with the accompanying drawings. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0037] Figure 1 This is a flowchart of a dynamic testing method for the bearing capacity of asphalt concrete pavement according to the present invention;

[0038] Figure 2 This is a flowchart of a dynamic testing vehicle model for a dynamic testing method of asphalt concrete pavement bearing capacity according to the present invention.

[0039] Figure 3 This is a flowchart of the vehicle-road dynamic response model of a dynamic testing method for the bearing capacity of asphalt concrete pavement according to the present invention.

[0040] Figure 4 This is a schematic diagram of a dynamic testing method for the bearing capacity of asphalt concrete pavement according to the present invention.

[0041] Figure 5 This is a comparison chart of deflection values ​​for a dynamic testing method for the bearing capacity of asphalt concrete pavement according to the present invention.

[0042] Figure 6 This is a comparison diagram of the equivalent resilient modulus of the base plate for a dynamic testing method of bearing capacity of asphalt concrete pavement according to the present invention. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. In the following description, specific details such as specific configurations and components are provided merely to help fully understand the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. In addition, for clarity and brevity, descriptions of known functions and structures are omitted in the embodiments.

[0044] It should be understood that the phrase "an embodiment" or "this embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "an embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0045] Furthermore, reference numerals and / or letters may be repeated in different examples within this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or settings discussed.

[0046] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" in this article describes another type of relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the related objects before and after it are in an "or" relationship.

[0047] In this article, the term "at least one" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, "at least one of A and B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0048] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion.

[0049] Example 1

[0050] This embodiment mainly describes a dynamic testing method for the bearing capacity of asphalt concrete pavement, such as... Figure 1 As shown, it includes:

[0051] S1. Deploy test vehicles, acquire vehicle source data, and build a dynamic test vehicle model;

[0052] S2. Obtain source data of asphalt concrete pavement and construct a vehicle-road dynamic response model by combining it with a dynamic test vehicle model.

[0053] S3. Analyze the influence of vehicle speed, vehicle load, asphalt surface properties and base material properties on pavement surface deflection using the vehicle-road dynamic response model, and establish a mathematical model of deflection pavement.

[0054] S4. Select a test section, set up sensor nodes at the wheel track line, and obtain dynamic response data of the road surface and deflection value of the road surface.

[0055] S5. Based on the mathematical model of deflection pavement, a solution framework for pavement deflection is constructed by combining measured data. The equivalent resilient modulus of the base is obtained by inversion through the pavement deflection solution framework, and a road bearing capacity assessment system is established.

[0056] S6. Determine the equivalent resilient modulus of the base top corresponding to the measured deflection value by using the dynamic response data of the pavement and the deflection value of the pavement surface. Compare the actual measured value with the design value, calculate the asphalt pavement modulus index, and generate a pavement bearing capacity report according to the grading criteria.

[0057] Furthermore, such as Figure 2 As shown, the construction of a dynamic test vehicle model includes the following steps:

[0058] S1.1 Install multiple types of sensors on the test vehicle to collect dynamic response data of the vehicle during driving;

[0059] S1.2 Based on dynamic response data, combined with the vehicle's static geometric dimensions and mass distribution, a vehicle source database of static structure and dynamic characteristics is formed.

[0060] S1.3. Based on the vehicle source database, a three-dimensional geometric model of the vehicle is created using the finite element analysis mechanism. Nodes and element meshes are defined to discretize the bottom contact structure of the vehicle, forming a dynamic test vehicle model.

[0061] Furthermore, the S1.3 vehicle three-dimensional geometric model incorporates the vehicle's seven-degree-of-freedom dynamic characteristics, road surface smoothness, and random load factors to simulate different dynamic response behaviors of vehicles driving on asphalt concrete pavements. At the same time, the dynamic load generated by the vehicle is converted into stress distribution acting on the road structure layer using the dynamic load transfer function, thus realizing a comprehensive numerical simulation of vehicle-road interaction.

[0062] Furthermore, such as Figure 3 As shown, the construction of the vehicle-road dynamic response model includes the following steps:

[0063] S2.1 Deploy multiple types of sensors on the test section to obtain the stress, strain, temperature and humidity changes of the road surface structure under vehicle load, and use a scanner to record the geometric features of the road surface.

[0064] S2.2 Based on the data collected on site, determine the key mechanical performance parameters of the asphalt surface layer and base material of the road surface, integrate the geometric parameters of the road structure as well as compaction and smoothness, and form a database of road characteristics;

[0065] S2.3. Combine the dynamic test vehicle model with the road surface characteristic database, obtain the wheel track distribution on the vehicle's driving path, and determine the road surface location where the vehicle load is applied.

[0066] S2.4. Use finite element analysis software to create a three-dimensional geometric model of the road structure, define nodes and element meshes to discretize the road structure, and apply vehicle load as input condition to the three-dimensional geometric model of the road structure to form a vehicle-road dynamic response model.

[0067] Furthermore, such as Figure 4 As shown, the mathematical model of the deflection pavement in S3 is constructed by analyzing the vehicle speed v, vehicle load F, and elastic modulus E of the asphalt pavement properties. s And the resilient modulus E of the substrate material properties b The influence of road surface deflection was investigated by simulating deflection changes under different driving speeds and loads. The deflection calculation formula is as follows: Where δ represents the surface deflection value of the road surface, a is the radius of influence, and E is the radius of influence. c It is the composite modulus, v is Poisson's ratio, and h is the thickness of the asphalt surface layer; the deflection value of the road surface is embedded into the vehicle-road dynamic response model, and the finite element analysis mechanism is used for numerical solution to obtain the specific deflection response of the road surface, forming a deflection road mathematical model.

[0068] Furthermore, in S4, a test section is selected, and sensor nodes are set at the wheel track lines to acquire dynamic response data of the road surface and the deflection value of the road surface. Specifically, this includes: on the selected test section, high-precision sensor nodes are arranged along the main wheel track lines of the vehicle, including but not limited to deflectometers, strain gauges, accelerometers and displacement sensors; the sensors are used to collect dynamic response data of the road surface under vehicle load in real time, including but not limited to stress, strain, vibration acceleration and displacement changes, and to measure the instantaneous deflection value of the road surface before and after the vehicle passes.

[0069] Furthermore, the sensor nodes synchronously record and transmit data via wireless communication, and accurately mark the time and location information of each measurement by being equipped with a synchronous marking unit, thereby obtaining dynamic response data of the road surface and surface deflection value at the marked point.

[0070] Furthermore, S5 constructs a solution framework for road surface deflection based on a deflection pavement mathematical model and combined with measured data. Specifically, this includes: inputting measured pavement dynamic response data and surface deflection values ​​into a pre-established deflection pavement mathematical model; comparing the deflection values ​​predicted by the deflection pavement mathematical model with the actual measured deflection values; and using an iterative optimization mechanism to adjust key parameters in the deflection pavement mathematical model, including but not limited to composite modulus, Poisson's ratio, and asphalt surface layer thickness, in order to minimize the error between the deflection values ​​predicted by the deflection pavement mathematical model and the actual measured deflection values, thus forming a solution framework for simulating the deflection response of the pavement under different working conditions.

[0071] Furthermore, in S5, the equivalent resilient modulus at the base is obtained through inversion using the pavement surface deflection solution framework, establishing a road bearing capacity assessment system. Specifically, this includes: inputting the pavement surface deflection value δ and dynamic response data into the pavement surface deflection solution framework, and obtaining the equivalent resilient modulus E at the base through inversion using the pavement surface deflection solution framework. t The formula is: Where F(t) is the vehicle load varying with time, δ is the calculated deflection value, a is the radius of influence, β is the correction coefficient for the asphalt pavement properties, and h is the asphalt pavement thickness; by combining the deflection value and vehicle load data, the equivalent resilient modulus E at the base top is calculated. t According to the E obtained from the inversion t Based on design standards and specifications, different levels of road carrying capacity indicators are defined to form a road carrying capacity assessment system.

[0072] Furthermore, S6 determines the measured deflection value δ using pavement dynamic response data and pavement surface deflection values. s Based on the corresponding base equivalent resilient modulus, compare the actual measured value with the design value to calculate the asphalt pavement modulus index. The formula is as follows: Where M is the modulus index of asphalt pavement, and E t E0 is the base equivalent resilient modulus obtained by inversion, τ is the design standard resilient modulus, ΔT is the temperature sensitivity coefficient, and ΔT is the temperature difference between the actual measurement and the design conditions. Based on the asphalt pavement modulus index M and the preset grading criteria, a pavement bearing capacity report is generated. The pavement bearing capacity report includes, but is not limited to, the specific parameters of each test section, the comparative analysis results, and maintenance recommendations.

[0073] This embodiment constructs a vehicle-road dynamic response model, which simultaneously considers multiple factors such as driving speed, vehicle load, asphalt pavement properties, and base material performance, improving the authenticity and reliability of test results. By using high-precision sensors to collect road surface dynamic response data in real time and combining advanced finite element analysis technology and iterative optimization mechanisms, a road bearing capacity assessment system capable of inverting the base top equivalent resilient modulus has been established, thereby enhancing the level of intelligent road management.

[0074] Example 2

[0075] This embodiment describes in detail the grading criteria for a dynamic testing method of the bearing capacity of asphalt concrete pavement, such as... Figure 3 As shown, this specifically includes grading criteria and the generation of pavement bearing capacity reports;

[0076] By comparing actual measured values ​​with design values, the asphalt pavement modulus index is calculated, and a pavement bearing capacity report is generated based on this index and preset grading criteria. The grading criteria are set based on different ranges of the asphalt pavement modulus index (MI) to define the road bearing capacity level. The asphalt pavement modulus index is divided into multiple types of intervals, each interval corresponding to a specific road bearing capacity level, which are A, B, C and D from best to worst. This not only helps to intuitively understand the current bearing condition of the pavement, but also facilitates the formulation of corresponding maintenance strategies.

[0077] For pavements with a high modulus index, i.e., those in Class A, these pavements exhibit excellent load-bearing capacity and structural stability. Their modulus index far exceeds the design standard, indicating that the road section can withstand the expected traffic flow and has a long service life. In the pavement load-bearing capacity report, for Class A pavements, their good performance is emphasized, and regular monitoring is recommended to maintain the status quo. It is also pointed out that the road section does not need large-scale repair or reconstruction work in the future, thereby optimizing resource allocation and reducing unnecessary maintenance costs.

[0078] When the modulus index of asphalt pavement is in the middle range, such as grades B and C, it indicates that the load-bearing capacity of these road sections is between good and average. For grade B pavements, although they can still effectively support the existing traffic load, they are close to the design limit and their changing trends need to be closely monitored, and preventive maintenance measures should be considered. For grade C pavements, since their modulus index is already below the design value, it shows some signs of degradation. The report will recommend more frequent inspections and appropriate reinforcement to prevent further deterioration and ensure driving safety.

[0079] For Class D pavements with a low modulus index, it means that the load-bearing capacity of the road section has significantly decreased and cannot meet current traffic demands, possibly indicating obvious damage or deformation. In this case, the pavement load-bearing capacity report will clearly state that immediate action is necessary, such as arranging emergency repairs or overhauls. Furthermore, the report will detail specific maintenance recommendations, including priority areas, required repair techniques, and expected improvements.

[0080] This embodiment details the grading criteria for dynamic testing methods of pavement bearing capacity. This approach not only enables efficient operational guidance but also ensures that all stakeholders can make timely and accurate decisions based on clear grading criteria to maintain the overall health of the road system.

[0081] Example 3

[0082] This embodiment, based on Embodiment 1, describes in detail the verification of a dynamic testing method for the bearing capacity of asphalt concrete pavement, specifically including:

[0083] Suppose that a major arterial road in a city (hereinafter referred to as the "target road section") faces the need for a road structure health assessment due to high daily traffic volume and frequent heavy vehicle traffic. This application employs both traditional static testing methods and the dynamic testing method described herein to assess this road section.

[0084] The target road section is 10 kilometers long and has an average daily traffic volume of approximately 30,000 vehicles, including about 20% heavy trucks. Due to the consistently high load on this road section, the management decided to conduct a load-bearing capacity assessment to determine whether maintenance or repair work is necessary. Two independent tests were conducted, using both the traditional static Benkelman beam method and the dynamic testing method described in this application.

[0085] Traditional static testing methods employed the Benkelman beam method, conducting static loading tests on the target road section after traffic closure during off-peak hours. Results showed an average pavement deflection of 0.81 mm and a base equivalent resilient modulus calculated using empirical formulas of 50.7 MPa. However, this method fails to account for the dynamic changes in vehicle loads under actual driving conditions and their impact on the pavement, potentially underestimating the actual degree of pavement damage.

[0086] The dynamic testing method described in this application involves arranging high-precision sensor nodes, including deflectometers, strain gauges, accelerometers, and displacement sensors, along the main wheel track locations under normal traffic conditions. These sensors collect real-time dynamic response data of the road surface under vehicle loads, such as stress, strain, vibration acceleration, and displacement changes, and measure the instantaneous deflection of the road surface before and after vehicle passage. Data analysis reveals that at an average driving speed of 60 km / h, the measured deflection value reaches 1.24 mm, and the derived equivalent resilient modulus is 42.3 MPa. Furthermore, the asphalt pavement modulus index MI = 0.75 (assuming a standard resilient modulus of 53.3 MPa, a temperature sensitivity coefficient of 1.0, and a temperature difference of 0°C between the actual measurement and design conditions). According to the grading criteria, this road section is rated as Grade C, indicating that its bearing capacity is approaching a critical state.

[0087] Table 1 Comparative Analysis Table

[0088]

[0089] As shown in Table 1, the data comparison above indicates that the results obtained by the traditional static testing method are relatively optimistic; Figures 4-5 As shown in the figure, the static test method results in a deflection value fixed at approximately 0.81 mm; the dynamic test method deflection curve shows that the deflection value gradually increases with increasing vehicle speed, especially after the speed exceeds 40 km / h, where the growth trend becomes more pronounced; the static Beckman beam method base top equivalent resilient modulus curve shows that the resilient modulus remains around 50.7 MPa; the dynamic test method base top equivalent resilient modulus curve shows that the resilient modulus fluctuates with changes in time and vehicle driving conditions. At higher vehicle speeds, the resilient modulus drops to approximately 42.3 MPa, reflecting the impact of actual traffic load on the pavement structure. The dynamic test method of this application more accurately reflects the bearing capacity of the target road section under actual traffic conditions.

[0090] Meanwhile, the dynamic testing method proposed in this application takes into account various factors under actual driving conditions, avoids errors that may be caused by static testing, and provides a more realistic evaluation of road performance; dynamic testing can be completed without closing traffic, realizing real-time monitoring of road conditions, which helps to identify problems in a timely manner and take measures.

[0091] This embodiment, by calculating the asphalt pavement modulus index and combining it with grading criteria, demonstrates a dynamic testing method that not only quantitatively describes the pavement's health status but also provides a scientific basis for subsequent maintenance strategies, ensuring the effective use of resources. Accurate assessment results can help formulate reasonable maintenance plans, thereby effectively extending the road's service life and reducing long-term maintenance costs. The provided dynamic testing method exhibits significant technical advantages in assessing the load-bearing capacity of asphalt concrete pavements, bringing a more intelligent and precise solution to road management.

[0092] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any changes, modifications, substitutions, integrations, and parameter changes made to these embodiments within the spirit and principles of the present invention, without departing from the principles and spirit of the present invention, through conventional substitutions or to achieve the same function, fall within the scope of protection of the present invention.

Claims

1. A dynamic testing method for the bearing capacity of asphalt concrete pavement, characterized in that, include: S1. Deploy test vehicles, acquire vehicle source data, and build a dynamic test vehicle model; S2. Obtain source data of asphalt concrete pavement and construct a vehicle-road dynamic response model by combining it with a dynamic test vehicle model. S3. Analyze the influence of vehicle speed, vehicle load, asphalt surface properties and base material properties on pavement surface deflection using the vehicle-road dynamic response model, and establish a mathematical model of deflection pavement. S4. Select a test section, set up sensor nodes at the wheel track line, and obtain dynamic response data of the road surface and deflection value of the road surface. S5. Based on the mathematical model of deflection pavement, a solution framework for pavement deflection is constructed by combining measured data. The equivalent resilient modulus of the base is obtained by inversion through the pavement deflection solution framework, and a road bearing capacity assessment system is established. S6. Determine the equivalent resilient modulus of the base top corresponding to the measured deflection value by using pavement dynamic response data and pavement surface deflection value. Compare the actual measured value with the design value, calculate the asphalt pavement modulus index, and generate a pavement bearing capacity report according to the grading criteria. The construction of the dynamic test vehicle model includes the following steps: S1.1 Install multiple types of sensors on the test vehicle to collect dynamic response data of the vehicle during driving; S1.2 Based on dynamic response data, combined with the vehicle's static geometric dimensions and mass distribution, a vehicle source database of static structure and dynamic characteristics is formed. S1.

3. Based on the vehicle source database, a three-dimensional geometric model of the vehicle is created using the finite element analysis mechanism. Nodes and element meshes are defined to discretize the bottom contact structure of the vehicle, forming a dynamic test vehicle model. The construction of the vehicle-road dynamic response model includes the following steps: S2.1 Deploy multiple types of sensors on the test section to obtain the stress, strain, temperature and humidity changes of the road surface structure under vehicle load, and use a scanner to record the geometric features of the road surface. S2.2 Based on the data collected on site, determine the key mechanical performance parameters of the asphalt surface layer and base material of the road surface, integrate the geometric parameters of the road structure as well as compaction and smoothness, and form a database of road characteristics; S2.

3. Combine the dynamic test vehicle model with the road surface characteristic database, obtain the wheel track distribution on the vehicle's driving path, and determine the road surface location where the vehicle load is applied. S2.

4. Use finite element analysis software to create a three-dimensional geometric model of the road structure, define nodes and element meshes to discretize the road structure, and apply vehicle load as input condition to the three-dimensional geometric model of the road structure to form a vehicle-road dynamic response model.

2. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1, characterized in that, The vehicle's three-dimensional geometric model incorporates the vehicle's seven degrees of freedom dynamic characteristics, road surface smoothness, and random load factors to simulate different dynamic response behaviors of the vehicle driving on asphalt concrete pavement. At the same time, the dynamic load generated by the vehicle is converted into stress distribution acting on the road structure layer by using the dynamic load transfer function, thus realizing a comprehensive numerical simulation of vehicle-road interaction.

3. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1, characterized in that, The construction of the deflection road surface mathematical model in S3 is achieved by analyzing vehicle speed. Vehicle load Elastic modulus of asphalt surface layer properties and the resilient modulus of the substrate material. The influence of road surface deflection was investigated by simulating deflection changes under different driving speeds and loads. The deflection calculation formula for these changes is as follows: ,in This indicates the surface deflection value of the road surface. It affects the radius. It is a composite modulus. It is Poisson's ratio. It refers to the thickness of the asphalt surface layer; the deflection value of the road surface is embedded into the vehicle-road dynamic response model, and the finite element analysis mechanism is used for numerical solution to obtain the specific deflection response of the road surface, forming a mathematical model of deflection pavement.

4. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1, characterized in that, In step S4, a test section is selected, and sensor nodes are set at the wheel track lines to acquire dynamic response data and surface deflection values ​​of the road surface. Specifically, this includes: arranging high-precision sensor nodes along the main wheel track lines of the vehicle on the selected test section, including but not limited to deflectometers, strain gauges, accelerometers, and displacement sensors; the sensors are used to collect dynamic response data of the road surface under vehicle load in real time, including but not limited to stress, strain, vibration acceleration, and displacement changes, and measuring the instantaneous deflection values ​​of the road surface before and after the vehicle passes.

5. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 4, characterized in that, The sensor nodes record and transmit data synchronously via wireless communication. They are equipped with a synchronous marking unit to accurately mark the time and location information of each measurement, thereby obtaining dynamic response data of the road surface and surface deflection value at the marked points.

6. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1, characterized in that, S5, based on the deflection pavement mathematical model and combined with measured data, constructs a solution framework for pavement surface deflection. Specifically, this includes: inputting the measured pavement dynamic response data and surface deflection values ​​into the pre-established deflection pavement mathematical model; comparing the deflection values ​​predicted by the deflection pavement mathematical model with the actual measured deflection values; and using an iterative optimization mechanism to adjust key parameters in the deflection pavement mathematical model, including but not limited to composite modulus, Poisson's ratio, and asphalt surface layer thickness, in order to minimize the error between the deflection values ​​predicted by the deflection pavement mathematical model and the actual measured deflection values, thus forming a solution framework for simulating the deflection response of the pavement under different working conditions.

7. A dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1 or 6, characterized in that, In S5, the equivalent resilient modulus of the base is obtained by inversion through the road surface deflection solution framework, and a road bearing capacity assessment system is established. Specifically, this includes: calculating the road surface deflection value... The dynamic response data is input into the road surface deflection solution framework, and the equivalent resilient modulus at the base is obtained through inversion using the road surface deflection solution framework. The formula is: ,in, It is the vehicle load that changes over time. It is the calculated deflection value. It affects the radius. It is a correction factor for the properties of asphalt pavement. It refers to the thickness of the asphalt surface layer; the equivalent resilient modulus of the base is calculated by combining deflection values ​​and vehicle load data. The result obtained from the inversion Based on design standards and specifications, different levels of road carrying capacity indicators are defined to form a road carrying capacity assessment system.

8. The dynamic testing method for the bearing capacity of asphalt concrete pavement according to claim 1, characterized in that, S6 determines the measured deflection value using pavement dynamic response data and pavement surface deflection value. Based on the corresponding base equivalent resilient modulus, compare the actual measured value with the design value to calculate the asphalt pavement modulus index. The formula is as follows: ,in, It is the modulus index of asphalt pavement. It is the base equivalent resilient modulus obtained by inversion. It is the standard spring modulus of design. It is the temperature sensitivity coefficient. It is the temperature difference between the actual measurement and the design conditions, based on the asphalt pavement modulus index. Based on preset grading criteria, a pavement bearing capacity report is generated; the pavement bearing capacity report includes, but is not limited to, specific parameters of each test section, comparative analysis results, and maintenance recommendations.

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