Pavement Dynamic Response Research Articles

Analytical Study on the Impact of Nonlinear Foundation Stiffness on Pavement Dynamic Response under Vehicle Action

Analytical Study on the Impact of Nonlinear Foundation Stiffness on Pavement Dynamic Response under Vehicle Action

Research on noise reduction and data mining techniques for pavement dynamic response signals

Purpose This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals. Design/methodology/approach The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently. Findings The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present. Originality/value The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

FEM and field tests to study the dynamic response of composite pavement surrounding embedded tram tracks to moving loading: implications to fatigue cracking

Under long-term tram loads, cracking occurs on the composite pavement surrounding an embedded tram track. However, in the current pavement design of the shared right-of-way section of a tram track, the trackside pavement fatigue characteristics are not considered. The investigation of the real dynamic strain response of the trackside composite pavement under tram loads is crucial for pavement system design. In this paper, a three-dimensional finite element model of tram-track- composite pavement was established. The rationality of this model was verified by a field pavement dynamic test. The influence of the track irregularity and tram speed on the dynamic characteristics of the pavement surrounding the track was explored. The trackside pavement strain distribution along the longitudinal and vertical directions of the track had been studied. The high-frequency strain components caused by the random shortwave track irregularity excitation were found in the strain frequency domain curves in different directions, and the track irregularity amplifies the influence of the tram speed on the surrounding pavement dynamic response. The loading frequency is an important input for determining the dynamic model and fatigue characteristics of asphalt materials. At the same time, the lab test loading frequency and fatigue life corresponding to the mixture were calculated by the mechanistic coupled model and empirical damage evolution equation. It provides an analytical base for the design of pavement surrounding embedded tram tracks.

A Data-Mining Interpretation Method of Pavement Dynamic Response Signal by Combining DBSCAN and Findpeaks Function

During a heavy traffic flow featuring a substantial number of vehicles, the data reflecting the strain response of asphalt pavement under the vehicle load exhibit notable fluctuations with abnormal values, which can be attributed to the complex operating environment. Thus, there is a need to create a real-time anomalous-data diagnosis system which could effectively extract dynamic strain features, such as peak values and peak separation from the large amount of data. This paper presents a dynamic response signal data analysis method that utilizes the DBSCAN clustering algorithm and the findpeaks function. This method is designed to analyze data collected by sensors installed within the pavement. The first step involves denoising the data using low-pass filters and other techniques. Subsequently, the DBSCAN algorithm, which has been improved using the K-Dist method, is used to diagnose abnormal data after denoising. The refined findpeaks function is further implemented to carry out the adaptive feature extraction of the denoised data which is free from anomalies. The enhanced DBSCAN algorithm is tested via simulation and illustrates its effectiveness while detecting abnormal data in the road dynamic response signal. The findpeaks function enables the relatively accurate identification of peak values, thus leading to the identification of strain signal peaks of complex multi-axle lorries. This study is valuable for efficient data processing and effective information utilization in pavement monitoring.

A reduced-plate model transmission method for fast dynamic analysis of vehicle–pavement interaction

A reduced-plate model transmission method is developed in this study to accurately and efficiently analyze the vehicle–pavement interaction dynamics over long travel distances. A wide pavement is reduced to many small areas (referred to as the reduced-plate models) along the vehicle-moving trajectory, and each reduced-plate model accounts for the vibration of the plate structure caused by the moving vehicle in a small period. All reduced-plate models are assumed as stationary in the global coordinate system, and the vehicle moves from one reduced-plate model to another. The dynamic equations of the reduced-plate model are derived using the modal superposition method (MSM) and Lagrange's equations, and the calculation results of one reduced-plate model are considered as the initial conditions of the next reduced-plate model. Because only the reduced-plate model that is located inside the vehicle needs to be calculated in different periods, the number of degrees of freedom of the model is significantly reduced, and its calculation efficiency is increased. In addition, the present model is simple and better reflects the real situation of the vehicle–pavement interaction. After validating the present model, it is used in the vehicle–pavement interaction dynamic analysis during a long-distance travel. The calculation results obtained from the reduced-plate model transmission method are in good agreement with the MSM results for an entire plate, and the calculation time of the reduced-plate model transmission method is only one-third of that using the MSM for the entire plate. The calculation results further show that road roughness has a significant influence on the vehicle–pavement interaction dynamics in different situations. The Young's modulus and thickness of the base course layer also have a leading influence on pavement dynamic responses in the vehicle-pavement interaction system, where the variation of these parameters can lead to excessive responses of the pavement structure.

Theoretical analysis on the measurement accuracy of embedded strain sensor in asphalt pavement dynamic response monitoring based on FEM

Embedded strain sensors are the primary measurement device for strain in the tensile layer of asphalt pavement. The favorable deformation compatibility between embedded strain sensor and asphalt layer is the key to ensure the precise measurement of mechanical response. However, the good deformation coordination may be difficult to maintain under different environments due to the viscoelasticity of asphalt mixture. In this study, 4-point bending beam tests were performed to investigate deformation compatibility between embedded strain sensor and asphalt mixture under different temperature. Then, a quasi-static finite element model (FEM) was employed to simulate static mechanical response of asphalt pavement, and the design requirements for embedded strain sensor were proposed considering deformation coordination. In addition, the rationality of the design requirements of the sensor was further validated in the dynamic response monitoring. The results indicate that the deformation compatibility between embedded strain sensor and pavement material changes at different temperatures. In order to ensure favorable deformation compatibility, the reinforcement of the protective housing should be eliminated and the equivalent modulus (EM) of the sensitive element shall be the same as that of the asphalt mixture. Considering the viscoelasticity of asphalt mixture, the strain sensor with lower EM is recommended in the dynamic response monitoring of pavement structure. This study provides a basis for optimizing the embedded strain sensor of asphalt pavement from the perspective of deformation compatibility.

A distributed pavement monitoring system based on Internet of Things

Pavement is an important part of transportation infrastructure. In order to maintain pavement before the damage and improve the service quality, it is necessary to develop an intelligent and durable pavement information monitoring system. However, the pavement dynamic response monitoring is highly costly, easily obsolete and statistically redundant. The emergence of the Internet of Things (IoT) technology promises to change that. In this paper, an architecture of a distributed road IoT monitoring system is proposed, which has an acquisition layer, a preprocessing layer, a processing layer, an interaction layer, an energy layer and a network layer. Then, a prototype wireless pavement vibration monitoring system based on the IoT is developed, which consists of a number of wireless sensing nodes, a gateway, a remote server and a browser. Finally, data preprocessing, wireless communication, time synchronization, data processing and visualization, which represent the key to an effective system, are tested and discussed. The prototype wireless pavement vibration monitoring system provides a viable scheme for upgrading the IoT system and its application in the road infrastructures. In the future, any smart road will have an IoT wireless monitoring system to monitor the traffic, environment, and pavement information, which help enable traffic guidance, signal control, danger warning, scientific maintenance decision-making.

Viscoelastic dynamic response of asphalt pavement with imperfect interface bonding base on transfer matrix

AbstractThe interface bonding condition between asphalt pavement layers is always imperfect because of the differing material properties of different layers and the limitation of construction techniques. Therefore, designing asphalt pavement by considering the interface to be completely continuous is not precise. The viscoelastic character of the asphalt layer contributes significantly to the performance of asphalt pavement. To explore the influence of the imperfect interface on the viscoelastic dynamic response of asphalt pavement, the Hankel–Laplace transformation was applied to convert the partial differential equations to ordinary differential equations and a transfer matrix was introduced to describe the behavior of the imperfect interface. Based on the boundary condition and integral inverse transformation technique, an analytical solution for the displacement, stress, and strain of the pavement can be obtained. By considering the variation in the interface condition and the viscoelastic characteristics of the asphalt layer, the dynamic response of the pavement was calculated based on a practical example. The results show that the interface condition between the asphalt layer and the base course has a marked influence on the viscoelastic dynamic response of the pavement and that enhancing the strength of this interface can reduce the deflection of the pavement. The series elastic component in the modified Burgers model is another significant factor that affects the calculation results of the pavement dynamic response.

Dynamic response analysis of vehicle and asphalt pavement coupled system with the excitation of road surface unevenness

This study aims to solve the dynamic responses of the vehicle and asphalt pavement coupled system while considering road surface unevenness and deformation. First, an advanced solving procedure is proposed by decoupling the vehicle-pavement coupled system into two subsystems (i.e., quarter vehicle model with two degrees of freedom, and viscoelastic multilayered asphalt pavement) and solving them independently until the surface deformation has converged through an iterative scheme. During the solving procedure, the finite difference method and integral transform techniques are respectively conducted to compute the dynamic responses of vehicle and pavement. Then, the solutions for the dynamic responses of the pavement are verified through finite element simulation, which highlights the accuracy and efficiency of the proposed solution. The convergence study for the iterative procedure of vehicle-pavement coupled system is conducted, and the coupling effect on pavement and vehicle displacements is investigated. Finally, the effects of the vehicle and pavement parameters (i.e., suspension stiffness and damping, tire stiffness and damping, road surface unevenness, and pavement temperature and vehicle speed related to the viscoelasticity of asphalt material) on the pavement dynamic responses and damages are discussed comprehensively. These numerical investigations could prove that the solutions for the dynamic responses of the vehicle-pavement coupled system has the potential to guide road-friendly vehicle design and pavement service life evaluation.

Effects of Random Non-uniform Load on Asphalt Pavement Dynamic Response

Dynamic response analysis of pavement helps with structure and material optimization. The vehicle loading has a significant effect on the pavement dynamic response, which is usually assumed to be concentrated load, uniform load, or harmonic load without considering the space-time characteristics. In this study, a validated quarter vehicle model and finite element road model were developed to obtain the random non-uniform load. The random non-uniform load integrates the randomness characteristics due to the vehicle-road interaction and spatial characteristics caused by the tire pattern. The impacts of the vehicle weight, speed, and road roughness on the vehicle dynamic load were analyzed. The effect of random non-uniform load on pavement dynamic response was investigated by comparing the pavement responses under constant non-uniform load and constant uniform load. Numerical analyses show that the stress extremum along the transverse and longitudinal sections can reflect the time-space characteristics of the loads. The damage of the surface layer is underestimated when the vehicle load is simplified to be a constant uniform load without considering the random and spatial characteristics.

Typical asphalt pavement dynamic response simulation at the action of dynamic load with multi-steps loading method

The dynamic response of a typical pavement subjected to a dynamic load is important. Dynamic moduli of asphalt mixtures, cement treated crushed stone and lime treated soil are tested in the lab. The finite element model is established based on the dynamic modulus. The dynamic load is applied to the pavement structure by the loading steps method and then the pavement response is calculated. The pavement structure model was built in the lab and pavement structure responses are tested under the action of dynamic load which was applied by large size MTS. Compared with the results in the lab, simulation results are verified. By analysis of the simulation results show that: the tensile strain at the bottom of the surface and base under the action of the dynamic load is obviously smaller than the strain under the action of static load, deflection also follows that. In some special cases, the tensile strain at the bottom of the surface and base under the action of the dynamic load may exceed that under the action of static load.

Comparative Evaluation of Asphalt Pavement Dynamic Response with Different Bases under Moving Vehicular Loading

Abstract The horizontal strain at the bottom of asphalt concrete is well accepted as a key influencing factor in pavement performance and is directly related to fatigue cracking. This article presents the results of several studies performed in the field that focused on the evaluation of the effect of the base on the pavement dynamic responses under moving vehicular load through embedded strain gauges. Strain gauges were embedded at the bottom of the asphalt and base layers to measure pavement responses under moving vehicular loading. The investigated types of bases include a semirigid base, inverted base, compound base, and roller compacted concrete (RCC) base asphalt pavements. The effect of axle load level, tire pressure, and vehicle speed on pavement responses were analyzed based on the measured strain. Results showed that the critical horizontal strain at the bottom of the asphalt layer increased as the axle load increased, whereas the influence of the vehicle speed conversely affected the critical horizontal strain. The combined effect of the high temperature on the road surface and overload of the vehicle significantly increased the strain response at the bottom of the asphalt layer. Moreover, it was found that because of the modulus dependency of the pavement base, the horizontal strain at the bottom of both asphalt and base layers for RCC base pavement was smaller than that of the other three base types.

Asphalt pavement dynamic response under different vehicular speeds and pavement roughness

The research attempted to analyse the pavement response under different vehicular speeds and pavement roughness classes. The viscoelastic analysis was conducted using the three-dimensional asphalt pavement structures. Pavement roughness was considered in the moving multiple-axles vehicular load. And the surface strain and deflection responses were investigated based on the dynamic response of vehicular and pavement finite element (FE) model. Results showed that the strain and deflection responses of the FE model captured the main shape of the measured strain and deflection. The prediction errors of surface strains and deflections were both less than 10%. The time history curve shapes of surface longitudinal strains and deflections were similar and the time history curve shapes of surface transverse strains were different at different positions of the asphalt concrete layer. Both longitudinal strain peaks at the surface of the asphalt concrete layer (LSS) and longitudinal strain peaks at the bottom of the asphalt concrete layer (LSB) had the same absolute values and different directions at the same position of the asphalt concrete layer. Both transverse strain peaks at the surface of the asphalt concrete layer (TSS) and transverse strain peaks at the bottom of the asphalt concrete layer (TSB) also had the same absolute values and different directions at the same position of the asphalt concrete layer. The longitudinal strain, transverse strain and surface deflection all decreased with the growth of the vehicular speed and pavement roughness classes (from D to A). The developed simulation models can benefit the use of pavement non-destructive testing for in-situ pavement condition evaluation.

A combined method to predict the long-term settlements of roads on soft soil under cyclic traffic loadings

In order to investigate the mechanism of the long-term settlement of road on the soft soil, an in situ measurement of a highway in southeast China was conducted during both the construction and post-construction stage. In the theoretical analysis, the long-term settlement of the pavement on thick soft soils was divided into three main components: the consolidation settlement, the creep deformation and the traffic load-induced deformation. The equivalent time line model based on the viscous–elastic–plastic theory was adopted to simulate the road settlement caused by the consolidation and creep of the subsoil. A cyclic strain accumulation model, which was obtained from laboratory tests of soil elements, was adopted to consider the road settlement induced by cyclic traffic loadings. A pavement dynamic response model was used to calculate the dynamic stresses in the subsoil generated by moving traffic loads when the road was open to service. It was found that the equivalent time line model combined with the cyclic strain accumulation model could predict the road settlement accurately at both the construction and post-construction stage. Numerical results showed that the traffic speed had limited effect on the post-construction road settlements for the speed range considered. The post-construction settlement of the road, mainly composed of the traffic-induced settlement and soil creep deformation, could be reduced significantly by increasing the embankment surcharge during the construction stage. The creep component accounted for over 10% of the total post-construction settlement, while the percentage of the creep deformation in total post-construction settlement decreased rapidly as the embankment surcharge increased.

A plane model of the interaction of a vehicle with the road infrastructure

In road transportation, bridges´ deck exhibit large deflections when compared with those of the pavements. The interaction of vehicles with these two types of road infrastructures signifies enormous costs for maintaining the whole infrastructure in economic operational conditions. In this paper, an integrated model for simulating the vehicle – infrastructure coupled interaction, is proposed. While the infrastructure model is based upon FEM, the vehicle considers a multibody model. A parametric analysis is carried out to analyse the effect of vehicle and infrastructure operational conditions, as well as vehicle design characteristics, on bridge and flexible pavement dynamic responses.

Full-scale field testing on a highway composite pavement dynamic responses

A series of full-scale field tests were conducted to observe the composite pavement’s dynamic responses subjected to heavy traffic load. The tire contact pressure beneficially influences the dynamic strains and the dynamic stresses of pavement. A typical “M” shape is observed for the distribution of dynamic responses cross lane. The range of dynamic soil stress on roadbed ranges at 20–50kPa, and a non-linear model is presented for the dynamic stress attenuation along subgrade depth. Furthermore, the increasing of truck speed decreases the dynamic responses of composite pavement. This is owing to the viscoelastic property of HMA layer and the resonant frequency. At a lower moving speed, the dominant frequency of heavy truck loading is close to the dominant frequency of HMA layer. This would amplify the vibrations of pavements and consequently result in larger mechanical responses. The experimental findings would be helpful to understand the dynamic performance of composite pavement subjected to heavy traffic load.

Numerical comparison of flexible pavement dynamic response under different axles

A three-dimensional finite element model was utilised to examine the flexible pavement dynamic response under single, tandem and tridem axles at different speeds. Using two different hot-mix asphalt (HMA) layer thicknesses, 15.2 and 25.4 cm, the dynamic effects of moving axles were investigated on critical responses. These responses include the tensile strain at the bottom of asphalt layer, compressive strain on the top of subgrade and tensile and compressive strain on the surface layer. In this study, the HMA layer and other layers were characterised as linear viscoelastic and elastic material, respectively. Since this research focuses specifically on the time and dynamic effects, considering the transient dynamic loading and inertia forces, implicit dynamic analysis was done. The important findings are as follows. (1) Strains induced by tridem axles could be greater than tandem axles or even equal at different speeds. (2) It cannot be stated that axles always induce greater critical response value to road systems at lower speed because at higher speed they can also induce greater critical response value in pavements than that at lower speed. (3) Changing trend and changing rate of strains with speed are strongly affected by pavement thickness. In general, the effects of different axle configurations are strongly affected by moving speed and surface layer thickness.

A 3D Direct Vehicle-Pavement Coupling Dynamic Model and Its Application on Analysis of Asphalt Pavement Dynamic Response

Currently dynamic response of the pavement structure is widely studied in pavement engineering. A 3D direct vehicle-pavement coupling dynamic model was developed to describe the pavement dynamic responses in this paper. The moving vehicle was simplified as spring-dashpot components, and the pavement structure was simulated using three-dimension finite element model. Based on Newton iteration and central difference integration algorithm, the static and dynamic coupling reactions between the pavement structure and vehicle were considered using finite element platform ABAQUS. The numerical results fit analytic results very well in static analysis and fit experiment results in dynamic analysis well too. The simulated results indicate that the dynamic pavement surface deflection is much higher than the situation in static analysis, due to the overlapping effect. This phenomenon enhances when vehicle speed increases. A discontinuous zone of shear stress was observed on the base surface between the location under moving load and the location the moving load just passed. It was also found that the vertical fluctuation exists on the vehicle even if there is no roughness on the pavement surface. In general, the developed 3-D direct vehicle-pavement coupling dynamic model was validated to be effective on evaluating pavement dynamic responses.

Dynamic Response in ALF Aggregate Base Asphalt Pavement

In order to evaluate pavement dynamic responses accurately under truck loading, the full-scale asphalt pavement accelerated loading facility (ALF) was used. 10 strain gauges and 2 soil pressure cells were installed; temperature sensors were also installed in the different depth of the HMA layer. Pavement response was measured under real traffic load with ALF. The measured pavement responses are compared between the pavement sections to evaluate the effects of various experimental factors, such as axle load, speed, et al. Dynamic strain at the bottom of HMA layer and vertical compressive stress on the top of the subgrade were examined in the full-scale testing road, the regression models between dynamic response and axle load, dynamic response and speed were put forward respectively. Studies show that there is not only tensile strain but also compressive strain in the dynamic response, and the strain response is in the station of tension and compression alternation. Under the intermediate temperature, the strain response at the bottom of the asphalt layer is increased linearly with the increase of axle load and the vertical compressive stresses at the top of the subgrade is also increased with the increase of axle load. Speed has a great effect on strain response at the bottom of HMA layer, and has little effect on vertical compressive stress, it affects the loading duration of stress only. The destroy for the pavement by low speed and heavy load is more serious than that is normal.

A Theory Research of Asphalt Pavement Dynamic Response under Vehicle Random Stimulation

In order to study the dynamic response of the asphalt pavement under vehicle random stimulation, the random vibration model of vehicles and the mathematic model of pavement dynamic response in which the base and surface are all viscoelasticity are established respectively. The analytical solution of the stochastic response for the pavement is deduced. The stochastic load acted on the pavement can be gotten by the mathematic model of the vehicle vibration. The numeral feature functions of the random response, such as even function, time-space correlation function, time correlation function and mean square function, are obtained by the analytical solution. The paper provides a theory method for studying the random response of the asphalt pavement.