Showing papers by "Imad L. Al-Qadi published in 2022"
TL;DR: This study presents a framework that improves any analytical pavement damage accumulation approach to take a lateral position of loading as an explicit input and was applied on the state-of-the-practice pavement design approach, Mechanistic-Empirical Pavement Design Guideline (MEPDG).
Abstract: The lateral position of truck loading is a random phenomenon for human-driven trucks because they do not follow a straight path as they travel. Therefore, this variable has been called as w...
29 citations
TL;DR: In this article , a practical approach was proposed to assess vehicle excess fuel consumption due to pavement deflection based on the fundamental energy-deformation principles, whose parameters are truck loading and speed and pavement temperature.
Abstract: The pavement structural rolling resistance (SRR) effect on vehicles' excess fuel consumption (EFC) was investigated. A practical approach was proposed to assess vehicle EFC due to pavement deflection based on the fundamental energy-deformation principles. The proposed model was formulated using a quadratic form of maximum pavement deflection, whose parameters are truck loading and speed and pavement temperature. The proposed model utilizes input used in the current AASHTOWare design methods. This allows the integration of the developed model in pavement design and performance prediction while used in pavement life cycle assessment (LCA). Sensitivity analysis showed the reasonableness of the model over a wide range of loading, temperature, and speed scenarios. The estimated EFC for a heavy truck ranged from 0.03% (half loaded, 0 °C, 115 km/h) and 6.5% (fully loaded, 40 °C, 8 km/h). The truck EFC is highly nonlinear and exponentially grows with decreasing speed and increasing temperature.
7 citations
TL;DR: In this article , an integrated vehicle-tire-pavement approach was presented to evaluate asphalt pavement structure-induced rolling resistance under dynamic loading, where a 3D semi-trailer-truck model was used to calculate dynamic wheel loads on various pavement surface roughness profiles.
Abstract: Pavement-related rolling resistances, caused by pavement–vehicle interaction, are important components of pavement life-cycle assessment (LCA). Structure-induced rolling resistance (SRR) is caused by dissipated vehicle kinetic energy in the pavement structure. This paper presents an integrated vehicle–tire–pavement approach to evaluate asphalt pavement SRR under dynamic loading. A three-dimensional (3D) semitrailer-truck model was used to calculate dynamic wheel loads on various pavement surface-roughness profiles. The dynamic wheel loads were then transformed into 3D tire–pavement contact stresses using a deep-learning tire model. Next, an advanced 3D finite element pavement model, validated in previous studies, was used to simulate pavement structure under moving tire–pavement contact stresses. The dynamic load coefficient of axle forces was found to increase linearly with truck speed. The increasing trend became more significant as pavement roughness increased. Ignoring the dynamic loading effect resulted in 12% error in predicting SRR. A case study was performed to illustrate the computation procedures of asphalt pavement SRR under static and dynamic loading. Dynamic loading accounted for 4.74%, 7.37%, 10.73%, and 14.02% of SRR for four pavement surface-roughness levels at a truck speed of 40 mph. In addition, SRR was found to be highly nonlinear and increased as speed decreased and axle load increased. A modified Illinois Center for Transportation SRR model was developed to quickly assess the SRR component of the pavement LCA’s use stage. This study demonstrates the importance of vehicle–tire–pavement interaction in SRR prediction, which may not be overlooked.
7 citations
TL;DR: In this paper , an expected response framework was introduced to quantify the impact of lateral position on pavement performance, and the platooning of human-driven and autonomous vehicles was analyzed by characterizing lane position as a mixture probability distribution instead of point loads.
Abstract: Truck platooning with autonomous and connected vehicles has several advantages compared with traditional trucking. Platooning improves overall road safety and reduces fuel consumption by up to 15%. This is a result of the advanced control systems and high steering accuracy of autonomous vehicles. These advanced control systems present an opportunity to pavement design engineers, as the lateral positions of the vehicles could be altered to create less damaging loading scenarios. This study introduces an expected response framework to quantify the impact of lateral position on pavement performance. Using the expected response framework, any mixture of human-driven and autonomous vehicles can be analyzed by characterizing lane position as a mixture probability distribution instead of point loads. Pavement damage can subsequently be computed by using the expectation of the responses. This approach requires little computational effort and is easily incorporated in any mechanistic–empirical design or optimization framework. The approach is illustrated by analyzing four flexible pavement sections using the expected response framework. Compared with human-driven trucks, optimized lateral position could decrease pavement damage by 40%. Channelized traffic on the other hand could increase pavement damage by 60%. A simplified approach is introduced alongside a reliability analysis and fragility curves for various pavement structures. Distributed traffic was found to have the lowest probability of failure among all traffic scenarios.
5 citations
TL;DR: In this paper , a constitutive model was developed for confinement-dependent linear viscoelastic (LVE) behavior, which was then incorporated into finite element pavement models using a user material subroutine.
Abstract: The behavior of asphalt concrete (AC) is highly dependent on the temperature and frequency of loading. Traditionally, the modulus of AC materials is characterized by performing creep recovery or complex modulus tests without considering the impact of the lateral confinement level. Because traffic-induced loading generates a multi-axial stress state within the pavement structure, quantifying the effect of the lateral confinement on the global AC behavior becomes a necessity. Studies have shown that the responses of dense-graded AC mixtures are highly dependent on confinement levels, especially at low frequencies and high temperatures. In this study, a constitutive model was developed for confinement-dependent linear viscoelastic (LVE) behavior. The model was then incorporated into finite element pavement models using a user material subroutine. The numerical pavement models were used to quantify the impact of lateral confinement on pavement critical responses under various temperature profiles and tire loadings. Multiple loading levels were selected to consider the effect of road roughness on tire loading amplification. Results show that the effect of confinement depends on the relative position of the moving load. Vertical strains under the tire are significantly reduced by confinement. Finally, the maximum percentage decreases in the compressive and vertical shear strains from incorporating the confinement-dependent LVE model were found to be 31% and 17.5%, respectively, for the highest load–temperature combination.
4 citations
TL;DR: In this paper , a deep residual network is proposed to predict the internal moisture content of asphalt concrete pavement from ground-penetrating radar (GPR) measurements, which can achieve an accuracy of 91% on testing datasets, outperforming conventional machine learning methods.
Abstract: The non-destructive detection and monitoring of moisture content in asphalt concrete (AC) pavement is important, as moisture may cause adhesion failures between aggregates and asphalt, resulting in AC stripping and raveling. This article introduces a novel deep residual network–Mois-ResNets–to predict the internal moisture content of AC pavement from ground-penetrating radar (GPR) measurements. A GPR signal database was established from field tests and numerical simulations. A developed heterogeneous numerical model was used to generate synthetic GPR signals by simulating asphalt pavements at various configurations, moisture contents, volumetrics, and dielectric properties. The Mois-ResNets model, which contains a short-time Fourier transform followed by a deep residual network, was trained to minimize the error between predicted moisture content level and ground-truth data. Testing results show that Mois-ResNets can achieve a classification accuracy of 91% on testing datasets, outperforming conventional machine learning methods. The proposed Mois-ResNets has the potential for using GPR measurements and deep learning methods for pavement internal moisture content prediction.
3 citations
TL;DR: In this paper , a double pressure-aging vessel (PAV) was identified as a suitable laboratory long-term aging protocol to represent eight to 12 years of field aging for flexible pavement in Illinois.
Abstract: Asphalt binder aging accelerates cracking of flexible pavement. Quantifying the extent of binder aging allows the formulation and selection of appropriate binders for flexible pavement applications. Asphalt binder aging depends on climatic exposure, asphalt concrete field-surface density, and binder chemistry. The aim of this work was to select a laboratory-aging protocol to represent realistic field aging in Illinois. Binders were extracted from field cores aged from eight to 31 years. Extracted binders were tested for rheology and chemical characteristics. Small- and large-strain rheological parameters were determined. In addition, chemical functional groups and molecular weight distribution of extracted binders were evaluated. Effects of aging across pavement depth were also investigated. Double pressure-aging vessel (PAV) was identified as a suitable laboratory long-term aging protocol to represent eight to 12 years of aging for flexible pavements in Illinois. Thresholds were proposed for selected small- and large-strain rheological parameters representing realistic field aging. These thresholds may be used for binder selection and procurement to ensure the binder’s long-term performance. Furthermore, chemical analysis on extracted binders showed that only specific carbonyl functional groups are affected by field aging.
3 citations
TL;DR: In this article , an economic and environmental evaluation of the impact on pavement structure of platoon trucks was performed, and four common pavement structures (thick pavement with weak surface layer, thick pavement with strong surface layer and thin pavement with thin surface layer) were considered.
Abstract: Truck platoons can improve traffic efficiency, safety, and driving comfort, while reducing fuel and driving costs. However, continuous channelized trucks may increase pavement damage, therefore increasing maintenance costs. In this study, an economic and environmental evaluation of the impact on pavement structure of platoon trucks was performed. Four common pavement structures—thick pavement with weak surface layer, thick pavement with strong surface layer, thin pavement with weak surface layer, and thin pavement with strong surface layer—were considered. In addition, four platoon schemes (all channelized platoons, all human-driven trucks, mix of platoon and human-driven trucks, and optimized platoons) were utilized in the study. Compared with human-driven traffic, truck platoons optimized with respect to lane position could reduce pavement damage by 60% for fatigue and 33% for rutting; life-cycle cost, energy consumption, and global warming potential could be reduced by 48%, 31%, and 37%, respectively, for the cases studied. A sensitivity analysis was performed to quantify the impacts of pavement roughness on life-cycle cost analysis and life-cycle assessment. Results showed that a 1 in./mi increment increase in the International Roughness Index per year would increase total energy consumption by 1.2% and total cost by 1.9%. The study recommends that an optimized pavement-lane-position strategy be implemented before permitting general truck platoons.
3 citations
TL;DR: In this article , the feasibility of estimating, by using ground-penetrating radar (GPR), the moisture content in asphalt concrete (AC) pavement-construction process is investigated, and a testing protocol for predicting moisture content using GPR is suggested for CIR and CCPR pavement.
Abstract: Ground-penetrating radar (GPR) recently has been used for quality control and quality assurance of the asphalt concrete (AC) pavement-construction process. The objective of this study was to investigate the feasibility of estimating, by using GPR, the moisture content in AC pavement. This application is particularly important for emulsion-stabilized cold in-place recycling (CIR) and cold central-plant recycling (CCPR), where monitoring the moisture content is necessary for deciding the timing of opening the road to traffic, overlay placement, or both. Four field tests were performed using GPR on CIR- or CCPR-treated AC pavement. A numerical simulation model of AC pavement with internal moisture was generated using the information from mix design, and virtual GPR tests were performed using the finite-difference time-domain (FDTD) method. After calibration, a moisture-prediction formula derived from the simulation model was used to correlate the dielectric constant predicted by GPR to the moisture content within cold recycled layers. The GPR signal was “denoised” by improving its stability and mitigating the measured-height mismatch. The in-situ moisture content was predicted using the proposed method and compared with field-collected samples. Results showed that the proposed method is effective in estimating CIR- and CCPR-layer moisture content. The variation of dielectric constants in field tests is also discussed. A testing protocol for predicting moisture content using GPR is suggested for CIR and CCPR pavement.
2 citations
TL;DR: In this paper , a statistical analysis of hot-mix asphalt (HMA) data for quality assurance programs used by the Illinois DOT was conducted, and the aim was to quantify the total amount of incentives and disincentives, and distribution of the measured values, variability of HMA test results and identify significant variations between contractor and agency results.
Abstract: Statistical analysis of hot-mix asphalt (HMA) data for quality assurance programs used by the Illinois DOT was conducted. The aim was to quantify the total amount of incentives and disincentives, and distribution of the measured values, variability of HMA test results and identify significant variations between contractor and agency results. Quality control and quality assurance data for construction projects were collected for the 2015–2017 construction seasons and were statistically analyzed using the Mann-Whitney and Levene’s tests. The results indicated that during 2015 and 2016, approximately 44% to 55% of the produced HMA tonnage received disincentives, averaging $20,000 per project, based on 710 projects analyzed. More than 80% of the construction projects showed no significant difference between the quality assurance results reported by the district and contractor quality control results. HMA density was the most frequent pay parameter–caused contractor disincentive, and air void content was the second. The bulk specific gravity test results, which contribute to air void and voids in mineral aggregates, were found to be the most variable and, hence, the main cause of differences between IDOT and contractor laboratory data.
2 citations
TL;DR: In this article , the impact of rest period on the permanent deformation characteristics of two asphalt concrete (AC) mixes using four different types of binders was investigated. And the results were consistent with the hardening-relaxation or hardeningsoftening mechanisms describing the reorientation of the aggregate structure from a more resistant to less resistant state to deformations as rest duration increases.
TL;DR: In this article , the performance of unmodified and modified asphalt binders were studied at various aging conditions, and the discussed data supports that: (1) Extended aging allows binder distinction beyond performance grading (2) Intermediate-temperature small-strain rheological parameters of binders may be predicted using low-Temperature smallstrain parameters, and vice versa.
Abstract: Asphalt binder modification using various chemically processed synthetic or bio-based additives can be used to reduce cracking potential in asphalt concrete (AC), especially with recycled materials. These modifiers affect rheological properties of asphalt binders. State-of-the-practice parameters obtained within the linear viscoelastic range (LVER) have not successfully predicted their performance. Using a large-strain amplitude and/or novel small-strain parameters at extended aging conditions (double and triple pressure aging vessel cycles) could help. In this study, parameters for unmodified and modified asphalt binders were studied at various aging conditions. The discussed data supports that: (1) Extended aging allows binder distinction beyond performance grading (2) Intermediate-temperature small-strain rheological parameters of binders may be predicted using low-temperature small-strain parameters, and vice versa. (3) Stiffness-dependent parameters must be interpreted based on temperature and frequency of testing. (4) Δ|G*|peak τ is not correalted to small-strain parameters.
TL;DR: In this article , a laboratory study confirmed that abrasion and loss of surface binder is the primary mechanism for the rapid increase in albedo of asphalt concrete pavements.
Abstract: Albedo, or average solar reflectance, is an important property affecting the development of temperature profiles within asphalt concrete (AC) pavements. It influences material durability and has an urban heat island effect. The albedo of new AC pavements ranges from 0.05 to 0.10 but rises rapidly to a stable value ranging from 0.15 to 0.25 within the first year of service. The mechanism of this rapid increase has typically been associated with oxidation of the asphalt binder, loosely referred to as “aging,” but has never been verified in the laboratory. To test this hypothesis, AC mixtures, prepared using PG 64-22 unmodified asphalt binder and aggregates, were subjected to accelerated aging using various techniques. The albedo of the AC mixtures was found to have statistically the same value of about 0.05 regardless of the extent and method of aging. An alternate hypothesis introduced is that the albedo increases as a result of abrasion loss of the surface binder, which has been tested in the laboratory. When this new abrasion procedure was applied to four field cores, the albedo increased in the same way observed in the field. This laboratory study confirmed that abrasion and loss of surface binder is the primary mechanism for the rapid increase in albedo of AC pavements.
TL;DR: In this paper , a generative adversarial network (GAN) was developed to replace the finite element analysis (FEA) for predicting the three-dimensional (3D) non-uniform contact stress.
Abstract: An accurate characterisation of tire-pavement contact stresses is important for pavement structural analysis and performance evaluation. The demand for rapid pavement design and analysis requires a simple, accurate, and robust approach that pavement engineers can easily use. In this study, a generative adversarial network model – ContactGAN – was developed to replace the finite element analysis (FEA), for predicting the three-dimensional (3D) non-uniform contact stress. The ContactGAN model consists of a Generator that generates synthetic stress fields, and a Discriminator that distinguishes synthetic and FEA-generated stress fields. Three finite-element (FE) generated tire contact stress datasets were used. Compared with the previously developed ContactNet model, the ContactGAN model produces a more accurate contact stress distribution in both the overall quality and the most critical values. As part of the deep learning model, a transfer learning method was developed to address the challenges of applying the model to tasks with minimal datasets. After the transfer learning approach is applied, the mean square errors (MAEs) of the 3D contact stress predictions of the cornering tire dataset and the hyper-viscoelastic tire dataset are reduced by 83.8% and 92.9%, respectively. This research delivers a data-driven approach for the rapid and accurate prediction of tire-pavement contact stresses.
TL;DR: In this paper , a fully coupled thermal-stress model was proposed to predict the three-dimensional contact stress distribution that incorporated the thermomechanical interaction between a rolling hyperviscoelastic truck tire and a deformable pavement layer.
Abstract: Combined influence of temperature and mechanical deformations define the resulting contact stresses, heat flow, and rolling loss at the tire–pavement contact. In this study, the thermomechanical coupling of a hyperviscoelastic tire with a deformable pavement layer revealed the impact and extent of temperature influence on the hysteretic loss of a rolling tire. A scheme to predict the three-dimensional contact stress distribution was established that incorporated the thermomechanical interaction between a rolling hyperviscoelastic truck tire and a deformable pavement layer. The fully coupled thermal-stress model addressed two distinct yet intertwined perspectives: (1) establishing a thermomechanical database and prediction tool to generate contact stresses as inputs for pavement structural design, and (2) quantifying the associated rolling loss at the tire–pavement interaction that relates to tire design configurations and environmental impacts. Differences in the resulting contact stresses and rolling energy loss were observed between imposing uniform and nonuniform temperature profiles. Both the range and magnitudes of stresses throughout the tire–pavement contact imprint changed drastically as varying temperature profiles were implemented. Ranking the influence of thermal boundary conditions, the ambient temperature induced the highest impact on the dissipation energy and change in contact stress distribution, followed by the road and inner tire surface conditions. Moreover, the global hysteretic loss within the tire as myriad temperature profiles were imposed did not change significantly; however, the creep dissipation observed within the contact imprint revealed a higher disparity.
01 May 2022
TL;DR: In this paper, the authors investigated the feasibility of using ground-penetrating radar (GPR) for density and moisture content estimation of cold-recycled treatments and developed two models for moisture content: the first based on numerical simulations and the second based on electromagnetic mixing theory and called the Al-Qadi-Cao-Abufares (ACA) model.
Abstract: Cold-recycling treatments are gaining popularity in the United States because of their economic and environmental benefits. Curing is the most critical phase for these treatments. Curing is the process where emulsion breaks and water evaporates, leaving residual binder in the treated material. In this process, the cold-recycled mix gains strength. Sufficient strength is required before opening the cold-treated layer to traffic or placing an overlay. Otherwise, premature failure, related to insufficient strength and trapped moisture, would be expected. However, some challenges arise from the lack of relevant information and specifications to monitor treatment curing. This report presents the outcomes of a research project funded by the Illinois Department for Transportation to investigate the feasibility of using the nondestructive ground-penetrating radar (GPR) for density and moisture content estimation of cold-recycled treatments. Monitoring moisture content is an indicator of curing level; treated layers must meet a threshold of maximum allowable moisture content (2% in Illinois) to be considered sufficiently cured. The methodology followed in this report included GPR numerical simulations and GPR indoor and field tests for data sources. The data were used to correlate moisture content to dielectric properties calculated from GPR measurements. Two models were developed for moisture content estimation: the first is based on numerical simulations and the second is based on electromagnetic mixing theory and called the Al-Qadi-Cao-Abufares (ACA) model. The simulation model had an average error of 0.33% for moisture prediction for five different field projects. The ACA model had an average error of 2% for density prediction and an average root-mean-square error of less than 0.5% for moisture content prediction for both indoor and field tests. The ACA model is presented as part of a developed user-friendly tool that could be used in the future to continuously monitor curing of cold-recycled treatments.
TL;DR: In this article, the authors investigated the pay disincentive sources in QCP and PFP projects and found that mix production, and construction issues were the main cause of pay-disincentives to the contractors.
Abstract: Illinois Department of Transportation (IDOT) developed two HMA pay specifications, quality control for performance (QCP) and pay for performance (PFP). These specifications assign pay incentives and/or disincentives based on air voids, voids in mineral aggregate, and in-place density. The paper investigated the pay disincentive sources in QCP and PFP projects. Eleven construction contracts were evaluated during the 2018 construction season. First, on-site field observations of contracts were conducted to HMA production, construction, sampling, coring, and testing procedures. Then quality acceptance data were analyzed. Results indicate mix production, and construction issues were the main cause of pay disincentives to the contractors. The production issues found were related to aggregate quality, handling, variability, and contamination as well uncontrolled mix switches. However, there were cases that which testing issues compromised the contractor’s pay. The issues observed included: sample reheating, lab-gyratory compaction bias, and inconsistent volumetric test weights.
TL;DR: Optimal traffic patterns were used to develop simple platoon factors that could be applied to the Illinois Mechanistic Design Method to incorporate truck platooning, and optimal lateral position of truck platoons is defined.
Abstract: Truck platooning is one of the upcoming paradigm shifts in roadway-traffic patterns. It is defined as a convoy of trucks moving with short distances between them; truck platoons will change the performance of pavements. This change could practically be realized with the emergence of connected and autonomous trucks, which can control their lateral position. In this study, optimal lateral position of truck platoons is defined. Using an efficient algorithm, pavement damage was estimated assuming a probabilistic position of trucks. Four typical pavement cross-sections were used to apply the algorithm-based optimization developed. The pavement sections varied in thickness and stiffness from thick and strong section to thin and weak. The optimization results showed that different schemes can be optimal for the same cross-section. However, most of these optimal schemes disperse the traffic throughout the lane. Compared with normally distributed truck traffic, up to 18% and 50% reduction in rutting and fatigue cracking, respectively, could be achieved when applying an optimized traffic pattern. When compared with a channelized-platoon traffic pattern, the optimized truck traffic shows prospects of reducing rutting and cracking up to 29% and 70%, respectively. Optimal traffic patterns were used to develop simple platoon factors that could be applied to the Illinois Mechanistic Design Method to incorporate truck platooning.