Pavement Moduli Research Articles

Relationship between deflection basin parameters and backcalculated pavement layer moduli

In the case analysed, a glass fibre mesh was applied under the asphalt layer during a rehabilitation treatment. Because only one lane was reinforced, the test section can be used to observe the influence of glass fibre mesh on the relationship between the selected deflection basin parameters (RoC, BLI, MLI, and LLI) and back-calculated pavement layer moduli. The FWD measures were used to determine the bowl of deflection indicators and to back-calculate the layer’s moduli. The values of DBP-s allowed confirmation of the technical condition of pavement construction. The first measures were carried out in 2019 and repeated in 2021; the results were then compared and analysed. Influence was observed on the relationship between the deflection basin and moduli, especially for the base course and subgrade. The reinforced lane showed a better coefficient of determination between DBPs and moduli in 2019, but in 2021 relationships were observed only for LLI and subgrade moduli. The unreinforced lane, however, showed the mentioned relationships in both 2019 and 2021. Because of a relatively small number of measurement points, the presented analyses and observations should be considered as preliminary. Presented results and relationships are another step into developing an alternative approach to determining the initial pavement moduli i.e. to use as a seed moduli.

Effects of pavement roughness on shakedown limits under moving traffic loadings

This study proposes a lower-bound shakedown analysis method for pavement systems under moving traffic loadings considering pavement roughness. The effects of key variables, including moving speed, wavelength irregularity, and the modulus and thickness of pavements, on the shakedown limit are discussed. The calculation results indicate that pavement roughness has a considerable effect on shakedown limits, which can be overestimated in some cases when the pavement roughness is not considered. The effect of pavement roughness on the shakedown limit of a homogeneous subgrade layer gradually decreases with increasing speed. Additionally, the shakedown limit decreases with wavelength irregularity, particularly under high-speed traffic loadings. Furthermore, the effect of pavement roughness on the shakedown limit of a two-layered pavement system is more pronounced for a larger pavement modulus and thickness and a lower moving speed.

Experimental Study on the Mechanical Properties of Reinforced Pervious Concrete

Pervious concrete (PC) has gained popularity as an environmentally friendly solution for mitigating the urban heat island effect and promoting sustainable construction. However, its lower compressive strength, attributed to its higher porosity required for permeability, poses challenges for withstanding heavy vehicle loads on pavements. Our study aims to improve the flexural strength of regular PC by adding advanced reinforcing materials like steel wire mesh or glass fiber mesh. This results in reinforced pervious concrete, referred to as RPC, which offers enhanced strength and durability. The primary objective of our research is to investigate the mechanical behavior of RPC, with a specific emphasis on essential design parameters such as PC elastic modulus, modulus of rupture, and stress–strain characteristics under both single and repeated loading conditions. Our findings reveal that the influence of repeated loading on the compressive strength and elastic modulus of PC pavement is negligible, as there are no significant differences observed between the two loading protocols. Notably, our statistical analysis indicates that the PC strength (fc′) averages around 15 MPa. Moreover, empirical formulas for the elastic modulus (Ec = 3072fc′) and modulus of rupture (fr = 0.86fc′) are derived from our research. Furthermore, our study establishes that the stress–strain behavior of PC closely aligns with the general concrete model proposed by a previous scholar, providing valuable insights into the material’s structural performance. These findings contribute to a better understanding of RPC’s mechanical properties and offer potential solutions for improving its suitability for heavier vehicular loads.

Coupled dynamic and piezoelectric response of RPEHs embedded in road under traffic load via multiscale finite element models

Road Piezoelectric Energy Harvesting Systems (RPEHs) effectively collect and convert mechanical energy from road surface into electrical energy for intelligent traffic guidance and monitoring. To accurately evaluate the energy harvesting efficiency of RPEHs under traffic loads and road conditions, a multiscale finite element model of traffic load-road-RPEHs is developed. The model encompasses a encapsulated stacked piezoelectric transducer embedded in an large-scale road model. This approach addresses the limitations of previous studies that neglected the effect of RPEHs structure on the dynamic and piezoelectric response. The large-scale model provides the dynamic response of RPEHs for an independent small-scale model of the stacked piezoelectric transducer to enable coupled dynamic and piezoelectric behavior. Furthermore, a piezoelectric output theory considering the loss impedance is formulated. Combining this theory with the open-circuit voltage obtained from the multiscale models, we determine the output voltage and power of RPEHs under various conditions, such as vehicle speeds, axle weights, burial depths. The results demonstrate that the loss impedance undergoes significant changes under different conditions, exerting a substantial impact on the output of RPEHs, which should be considered during analysis. RPEHs positioned closer to the road surface produce higher output but also exhibit increased stress concentration. The pavement modulus is inversely proportional to the piezoelectric output, while the subgrade modulus has a comparatively smaller impact due to the stiffness of RPEHs.

Proposing Binary Gravitational Search Algorithm Parameters for Back-calculation of Road Pavement Moduli

A Falling Weight Deflectometer is popular equipment to measure surface deflections under imposed loadings, providing the necessary parameters for back-calculating the elastic moduli of road pavements. There are several back-calculation programs available that accurately back-calculate pavement layer moduli. The Gravitational Search Algorithm (GSA), a metaheuristic optimization algorithm inspired by Newton’s law of universal gravitation, is one such algorithm. The Binary Gravitational Search Algorithm (BGSA) is an enhancement algorithm based on GSA that can be used as an efficient search algorithm for back-calculating pavement moduli based on matching measured and calculated surface deflection of road pavements. Choosing the best BGSA parameters is critical for accurate back-calculation of road pavement moduli. Nevertheless, there has not been much study on selecting the best BGSA parameters for back-calculating road pavement moduli in the literature. Therefore, this study proposes strategies for selecting BGSA parameters based on the least computational effort and the least root mean square error between measured and calculated road pavement surface deflections. In this study, the Burmister theory is discussed and the Richardson extrapolation is adopted to improve the accuracy of the calculated points near the pavement surface; the best parameter of BGSA including the agent size A of 50 and an iteration step T of 300 are suggested to back-calculating the road pavement moduli.

Falling weight deflectometer dispersion curve method for pavement modulus calculation.

The falling weight deflectometer (FWD) test is a common non-destructive testing method for evaluating the structural capacity of pavements. At present, data processing of the FWD test mainly focuses on the deflection data, while paying less attention to the deflection-time history. Because a FWD is equipped with impulse loads and geophones, which allow for the generation and capture of surface wave signal propagation, it is hypothesized that Rayleigh wave dispersion theory can be applied to calculate the modulus profile along the pavement depth by analysing the dispersive properties of the deflection signal measured during FWD tests. To test this hypothesis, we develop a new methodology for the FWD test and data analysis, referred to as the FWD dispersion curve method. We first introduce the concept of the new method, followed by an illustration of the procedure and the experimental set-up. Case studies on three concrete pavement segments are then presented to evaluate the effectiveness of the FWD dispersion curve method. Modifications to the existing FWD device are further recommended for the impact loading sources and signal collection process so that the modulus of a much shallower layer, such as the concrete slab and upper asphalt layers, can be obtained. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Optimal time-frequency equivalency factor for approximate interconversion between the dynamic and relaxation moduli

The viscoelastic stiffness of asphalt concrete is commonly represented using relaxation modulus and dynamic modulus, which are functions of loading time and loading frequency, respectively. They are typically measured via experimental testing whereby only one of the moduli is determined, and interconversion techniques can be used to obtain the other modulus if needed. Although exact approaches exist for pavement modulus interconversion, they can be difficult to implement in practice, and approximate conversion techniques have therefore been developed for conventional use. A popular approach is to approximate a direct relationship between the time and frequency domains via an equivalency factor, but there is no apparent consensus on its proper value. In this paper, a new numerical technique is applied to experimental data to ascertain the optimal value of the time-frequency equivalency factor. Approximate conversions from dynamic modulus to relaxation modulus are conducted using the optimal factor, and results are compared to popular alternative approaches. The optimal factor is determined to be with 95% confidence. Using the mean value of 0.0673 produced conversion errors of 1.41% on average among 30 samples of hot mix asphalt.

Real-time monitoring of strain and modulus of asphalt pavement using built-in strain sensor cluster

Pavement health monitoring is helpful to understand the structural state of interlayer and make reasonable maintenance decisions. This study aims to propose a real-time strain and modulus monitoring method using built-in strain sensor cluster. First, the four-point bending beam test was conducted to demonstrate the possible poor deformation compatibility between a single built-in strain sensor with asphalt mixture under different temperature. Then, the potential mapping relationship between the output of the built-in strain sensor and the real strain of the matrix material was explored by mechanical derivation. Subsequently, the real-time strain and modulus monitoring method based on built-in strain sensor cluster was discussed and proposed. Finally, a three-dimensional finite element model was developed to validate the applicability of the proposed method to the dynamic response monitoring of elastic and viscoelastic pavement systems. The results indicate that the difference in modulus between the built-in strain sensor and the asphalt mixture causes the sensor output to deviate from the true value. The modulus ratio and strain ratio between the built-in strain sensor and the asphalt mixture satisfy the mapping relationship. The monitoring method based on the built-in strain sensor cluster can overcome the strain measurement errors caused by the poor deformation compatibility and also enables real-time monitoring of pavement modulus. In general, this work provides a new framework for real-time evaluation of strain and modulus in pavement health monitoring.

Lateral and longitudinal variations in dynamic modulus of asphalt pavement: Surface layer and base layer

The dynamic modulus of asphalt pavement is a significant factor used for predicting the pavement life. However, the service situations of asphalt pavement in lateral and longitudinal directions are different, which induces variation in the dynamic modulus of asphalt pavement. Given this background, this study aims to investigate the variations in dynamic modulus and phase angle in the longitudinal and lateral directions. Four road sections comprising surface layer and base layer were selected. For each road section, core samples were taken from three profiles along the longitudinal direction and four cores from different locations along the lateral direction were taken. The dynamic modulus and phase angle of specimen were characterised by indirect tensile test. The variations of dynamic modulus and phase angle in the lateral and longitudinal directions were analysed and compared with reference samples prepared in laboratory using master curve and coefficient of variation. The results show that the lateral and longitudinal differences induce more severe variations in dynamic modulus and phase angle compared with laboratory samples. Moreover, for the surface layer, the variation in the lateral direction is higher than in the longitudinal difference likely due to the inhomogeneity of asphalt mixture, variation in traffic loading, loading distribution, and the specific geometric structure of Norwegian pavement. In comparison with the surface layer, similar results caused by lateral and longitudinal differences are found for dynamic modulus and phase angle of the base layer because of its lower position and complicated stress distribution. Besides, a correlation between service life and the variations in dynamic modulus and phase angle is found for lateral samples.

Modulus attenuation of semi-rigid asphalt pavement layer in accelerated pavement testing with MLS66

This research aimed to investigate the attenuation mode of the layer modulus of asphalt pavement in accelerated pavement testing (APT). A full-scale experimental section was constructed and tested using the APT facility. Two non-destructive testing (NDT) methods, named falling weight deflectometer (FWD) technique and portable seismic property analyzer (PSPA) test, were used to obtain the layer moduli of asphalt pavement during the APT test. The variation patterns of layer moduli obtained by FWD and PSPA tests were calculated and compared after the temperature was corrected to 20 ℃. It was found that the variation pattern of surface layer modulus based on field FWD measurements was consistent with the one measured from PSPA tests. That is the modulus of the surface layer increases with the APT load repetitions firstly and then decreases with the rise of the repetitions. The modulus values of the surface layer measured from PSPA tests are obviously larger than those backcalculated based on deflection basins. The ratio of the measured surface layer modulus based on the PSPA test to the backcalculated one based on the FWD test ranges between 2.06 and 2.71. The backcalculated base layer modulus always declines with the increasing loading repetitions. The attenuation patterns of the surface layer modulus and the base layer modulus in the damage stage are described as Ea=421100*N-0.6119 and Eb=128000*N-0.1096, respectively.

Evaluation of Performance of Pavement Founded on the Reinforced Earth Sections along Outer Ring Road, Nairobi

There are no existing local design manuals and construction guidelines for reinforced earth structures in Kenya. The objective of this study was to evaluate the performance of the pavement found on reinforced earth sections along Outer Ring Road. The structural evaluation was determined from deflection measurements using Falling Weight Deflectometer (FWD), while the functional evaluation was by visual condition survey, roughness, and rut depth measurements. Classified traffic counts and axle load surveys were undertaken. It was established that the design traffic would be exceeded in year 10 after opening the road. The surface condition survey indicated that the pavement surface for the entire road was generally in good condition. The roughness rating for the entire road was rated "Good", while ten sections of reinforced earth embankment were rated "Fair". The characteristic rut depths on the reinforced earth sections were higher than the lane characteristic rut depth for the entire road. Three sections of the reinforced earth showed low severity, while the rest had no rutting. The PCI for the pavement on reinforced earth sections were lower than pavement on other sections of the road due to a higher International Roughness Index (IRI). The FWD deflections were higher on reinforced earth sections. It was found that the mean pavement moduli for surfacing and base, crack relief and subbase layers at reinforced earth sections were lower than for the pavement in other sections hence requiring thicker overlays. The overall residual life of the road was 17 years, while for the reinforced earth sections was 15 years. Based on the findings, monitoring of the traffic and performance of pavement on the reinforced earth embankments is vital for interventions to prevent premature pavement failure. There is a necessity to develop a design manual and construction guidelines for reinforced earth structures based on the local conditions in Kenya.

Deformation behavior of flexible pavements by finite element simulation

Flexible pavement is usually designed based on certain axle load limits and climatic conditions. The Iraqi code has specified certain load limits per each axle type that should not be exceeded. However, many trucks violate these limits by carrying additional weights to decrease the transportation cost. These overweight trucks cause severe deterioration to the pavement and thus reduce its life. The Iraqi authorities generally charges the violating trucks a penalty based on their weights. This penalty could be very small compared to the damage occurring to the pavement based on these over weights. Also, some trucks may carry huge weights that the pavement may not support, so unloading such trucks could be a suitable solution rather than paying few amounts of money and deteriorating the pavement. The study aims at studying the effect of axle load increase, and the variation in pavement moduli, on the overall pavement life. It also aims to estimate the overweight truck limits that could be penalized or unloaded. The research uses the ABAQUS software conditions to estimate the tensile strains occurring under the asphalt concrete (AC) layer and the compressive strains above the subgrade surface. These computed strains are incorporated in the fatigue cracking and rutting models to estimate the pavement life for different axle weights. Results showed that violating trucks should be unloaded when their weights exceed certain limits.

Real-time assessment of asphalt pavement moduli and traffic loads using monitoring data from Built-in Sensors: Optimal sensor placement and identification algorithm

Asphalt pavement performance is gradually attenuated subjected to repeated traffic loads. Grasping the relationship between the repeated traffic loads and pavement modulus attenuation is crucial for understanding pavement mechanical behavior, improving pavement design methods, and guiding maintenance decisions. However, the current bottleneck is that neither the existing non-destructive testing nor monitoring methods can simultaneously obtain the information of traffic loads and pavement moduli. To fill this gap, an innovative real-time assessment method of asphalt pavement moduli and traffic loads from the aspect of structural health monitoring was proposed. On the one hand, the optimal sensor placement was determined by the theoretical relationships between moduli, loads, and mechanical responses based on elastic multi-layered theory. On the other hand, the corresponding algorithm for stepwise decoupling identification of asphalt pavement moduli and traffic loads to match the optimal sensor placement was developed. Therefrom, the validity of the proposed assessment method was theoretically verified, and the effects of the viscoelastic property of asphalt materials, measurement errors, and layer thickness on the identification accuracy were comprehensively discussed. The proposed assessment method was applied to the realistic pavement to further prove its applicability. Results show that the proposed assessment method can both evaluate pavement moduli and traffic loads accurately. The proposed assessment method has application prospects for simultaneous real-time monitoring of the pavement modulus attenuation and traffic loads, which helps understand the pavement damage behavior, improve pavement design methods, and guide maintenance decisions.

Determining In-situ Frequency Independent Attenuation and Complex Modulus of Pavement Materials using Wavelet Power Density of Vibration Method

The features of vibration sources, site characteristics, the propagation of surface and body waves in the ground, and the reaction of structures are all important to consider when analyzing vibration-related issues, including those caused by traffic loading. Pavement vibration analysis can be used to determine the impact of damaging vibrations on the road and surrounding buildings or structures. Furthermore, this vibration can be utilized to calculate the dynamic properties of road pavement materials, such as the attenuation factor and damping ratio of the material, as well as the complex modulus of the pavement material. To minimize vibration damage, an environmental zone that is effective in reducing ground vibration amplitude is frequently used. However, estimating the degree of decrease in vibration amplitude at a given distance is challenging. In general, vibration attenuation with distance is made up of two components: geometric damping and material damping. Geometric damping is related to the qualities of the ground and the magnitude of the vibration, while material damping is dependent on the nature of the source of the vibration. The majority of ground vibrations are now monitored mainly at the ground surface, rather than in deep layers, and propagation patterns are not properly considered. The wavelet power density of vibration technique was used in this study to quantify the frequency-dependent attenuation of geometric damping at a variety of pavement structures in Malaysia and Indonesia. At each location, the energy in a seismic wave signal was calculated as a function of the Gaussian of the derivative wavelet in signal amplitude. The vibration source's propagating waves were described by examining the recorded particle motions and significant energy components in the time-frequency domain. The complex modulus of pavement materials was then calculated using the frequency-dependent attenuation factors. The results reveal that the wavelet power density of vibration method can properly define the physical properties of the dynamic pavement material, such as attenuation frequency, damping ratio, and complex pavement modulus. This approach has the advantages of being quick, cost-effective, and nondestructive.

Affirmation of Elastic Modulus Derived from Spectral Analysis of Surface Waves Method using Artificial Neural Network

Pavement modulus is believed as one of the important features to characterize the pavement condition, specifically the pavement stiffness. The value of pavement modulus may be calculated using the existing Witczak mathematical dynamic pavement modulus prediction formulae. However, the equation developed by Witczak is heavily impacted by temperature while underestimating the impact of other mixing factors thus, only offering an adequate approximation for the circumstances for which they were designed. In this study, the Spectral Analysis of Surface Wave (SASW) test data was used to develop an Artificial Neural Network (ANN) that accurately backcalculates pavement profiles in real-time. The pavement modulus calculated from the equation was validated by using ANN developed in Matlab software to avoid any mistakes during calculation based on the equation. Three parameters, shear wave velocity, depth and thickness from SASW test data were used as inputs and elastic modulus calculated using Witczak pavement modulus equation was used as an output to train the models developed in ANN. Five segments of pavement are presented in this paper where almost compromise that the greater the depth, the lesser the shear wave velocity as well as pavement modulus. Nine neural network models were developed in this study. The network architecture of 4-80-4 is the most optimized network with the highest correlation coefficient of 0.9992, 0.9994, 1.0, 0.9996 for validation, testing, training and all respectively. The created ANN models’ final outputs were reasonable and relatively similar to the real output.

Backcalculation of flexible pavement moduli including interlayer bonding conditions – numerical analysis

Backcalculation of flexible pavement moduli including interlayer bonding conditions – numerical analysis

NUMERICALLY PREDICTING SETTLEMENTS OF WASTE COCONUT FIBER (WCF) MIXED FLEXIBLE PAVEMENT IN HOMOGENEOUS SANDY SOIL BY USING PLAXIS 3D

Surface settlement of flexible pavement in coastal reason occurs for the movement of heavy vehicle, liquefaction of soil layer during seismic shaking, land sliding etc. In coastal area, surface settlement is higher than other geographical area because several sandy layers present in the coastal reason. Surface settlement disturbs the longevity of flexible pavement in homogeneous sandy layer. Waste coconut fiber (WCF), fly ash, coir etc. are suitable additives for reducing such types of settlement. In the present study, numerical analysis performs PLAXIS 3D and various (5, 10, 15, 20, 25) percentages of WCF mix with the asphalt by weight for reducing surface settlement of flexible pavement. Mohr-Coulomb failure criterion uses in the numerical analysis and liquefaction has not considered in the present study. However, WCF increases elastic modulus of flexible pavement and it reduces settlement of the pavement. Minimum surface settlement occurs at the maximum percentage of WCF and it is 1.68mm. Therefore, mixer of WCF protects the flexible pavement against severe damage.

Tensile Strength and Dynamic Modulus of Pervious Polymer Concrete with Freezing and Thawing Cycles

The expansion of impervious areas owing to urbanization has adverse effects on water circulation. The application of low-impact development techniques to solve these problems is gaining popularity. Among others, Permeable pavements are the most widely employed low-impact development techniques. In this study, the dynamic modulus and tensile strength of pervious polymer concrete pavement were evaluated before and after freezing-thawing cycles. A tensile strength test, performed to check the soundness of the pervious polymer concrete, yielded a tensile strength and tensile strength ratio of 0.66 to 0.96 MPa, and 72 to 83%, respectively. The ultrasonic pulse velocity was measured to determine the dynamic modulus according to the freezing-thawing cycles. When 300 freezing-thawing cycles were performed, the dynamic modulus was analyzed to drop to a level of 77~85% of the initial value. The standards for freezing and thawing tests of pervious concrete have not yet been established. It is necessary to develop test standards for freezing-thawing resistance of pervious concretes considering climate change.

Investigation of Mechanical and Hydrologic Characteristics of Porous Asphalt Pavement with a Geocell Composite.

Porous asphalt pavement is a part of the permeable pavement system, which can be used to mitigate the negative impacts of urbanisation on the water hydrological cycle and environment. This study aims to assess the mechanical and hydrologic characteristics of porous asphalt pavements, with and without geocell composites, using a plate load test, falling weight deflectometer test, and rainfall simulation test. The corresponding results indicate that the elastic modulus of the unreinforced pavement is lower than that of the reinforced pavement. The analysis demonstrates that the use of geocell composites effectively increases the load-bearing capacity of the pavement. When the base layer is reinforced with geocells, its load-bearing capacity increases. Observation of the rainfall simulation tests on the reinforced pavement indicates that the reinforced pavement effectively handles the surface runoff.

Pavement moduli back-calculation using artificial neural network and genetic algorithms

An Artificial Neural Network (ANN)-based back-calculating program combined with a Genetic Algorithm (GA) optimization algorithm was developed for the back-calculation of flexible pavement layer moduli. Deflections measured using geophones on a model pavement structure under accelerated pavement testing (APT) with the MLS30 were utilized for back-calculating the pavement layer moduli. As theoretically expected of visco-elastic materials that are temperature dependent, the back-calculated moduli of the asphaltic layers, namely the surfacing and base, exhibited a decreasing trend with an increase in the temperature and number of APT load cycles. By contrast, the moduli of the unbound base layer and subgrade exhited insensitivity to temperature changes and did not decay significantly as a function of the APT loading. Overall, the integrated GABP algorithm (based ANN formulation) exhibited potential in satisfactorily back-calculating the pavement layer moduli form geophone measured deflections with acceptable accuracy. The splitting fatigue test results show that the fatigue life of asphalt mixture decreases with the increase of loading cycles, which can verify the feasibility of back-calcultion model.