Search Results (21)

The effect of moisture on the fracture resistance of asphalt concrete is a significant concern in pavement engineering. To investigate the effect of the water vapor concentration on the fracture properties of asphalt concrete, this study first designed a humidity conditioning program at the relative humidity (RH) levels of 2%, 50%, 80%, and 100% for the three types of asphalt concrete mixtures (AC-13C, AC-20C, and AC-25C).The finite element model was developed to simulate the water vapor diffusion and determine the duration of the conditioning period. The semi-circular bending (SCB) test was then performed at varying temperatures of 5 °C, 15 °C, and 25 °C to evaluate the fracture energy and tensile strength of the humidity-conditioned specimens. The test results showed that the increasing temperature and the RH levels resulted in a lower peak load but greater displacement of the mixtures. Both the fracture energy and tensile strength tended to diminish with the rising temperature. It was also found that moisture had a significant effect on the tensile strength and fracture energy of asphalt concrete. Specifically, as the RH level increased from 2% to 100% (i.e., the water vapor concentration rose from 0.35 g/m³ to 17.27 g/m³), the tensile strength of the three types of mixtures was reduced by 34.84% on average, which revealed that the water vapor led to the loss of adhesion and cohesion within the mixture. The genetic expression programming (GEP) model was developed to quantify the effect of water vapor concentrations and temperature on the fracture indices. Full article

This manuscript presents an examination of the impact of geometrical and physical parameters on highway design speeds, critical for traffic safety and efficiency. Originating from a classical dynamics discussion in an undergraduate automotive technology engineering class, an exploration of the consequences of different geometrophysical considerations on a vehicle’s dynamics over pavement surfaces is developed. Considering various analytical models, an assessment of their principles and the significance of geometric and physical concepts involved in the problem is made, such as plane of motion and trajectory curvature radius, on safe (non slippage) operational speeds. The subsequent comparative study shows that one of the most accepted models in highway design regulations in México, when used as reference, yields percentage error differences respect to others of $0\lesssim \%E_{Max}\lesssim 5$, as well as a consistent trend for relatively underestimating safe highway operational speeds. A discussion of the immediate implications of these findings, emphasizing the necessity of experimental studies to validate theoretical predictions, is presented. This work contributes to the field by providing a detailed comparison of analytical models under a general applied science perspective, suggesting modifications to current highway design practices in México based on geometrophysical insights. In summary, this work’s main aim is to shed light on the intricacies of determining safe design speeds from an applied sciences point of view, while also calling for a reevaluation of the existing guidelines to enhance highway design and safety. Full article

As the main cause of asphalt pavement distress, rutting severely affects pavement safety. Establishing an accurate rutting prediction model is crucial for asphalt pavement maintenance, pavement structure design, and pavement repair. This study explores five machine learning methods, namely Support Vector Regression (SVR), Artificial Neural Network (ANN), Gradient Boosting Decision Tree (GBDT), Random Forest (RF), and Extra Trees, to predict the development of rutting depth using data from RIOHTRack. The model’s performance is measured by comparing the performance evaluation indicators of different models, such as the coefficient of determination, root mean square error, mean absolute error, and mean absolute percentage error. The results demonstrate that integrated learning techniques such as RF, GBDT, and Extra Trees works best with R² = 0.9761, 0.9833, and 0.9747. Moreover, the GBFT model can capture the trend of the measured rutting progression curve better than the mechanistic-empirical (M-E) model. The analysis of feature importance reveals that, in addition to external factors such as temperature and axle load, the aggregate of the asphalt concrete layer and air void crucially affect rutting. The higher the base strength, the smaller the rutting depth. The proposed model is highly straightforward and serves as an accessible analysis tool for engineers in practice. Full article

Airport pavements have always evolved to keep pace with the demands of new aircraft. As aircraft weights and tyre pressures increase, stronger, new pavements are designed and existing pavements are rehabilitated or upgraded. The narrow-body commercial jet aircraft, including the A320 and B737 families, are examples of aircraft that have retained the same number of wheels, with the same wheel spacing and the same wingspan, but have increased in weight and tyre pressure by approximately 50%. This places significant demand on airport pavements that were designed for the lighter variants but now face the introduction of the newer, heavier and more demanding variants. This research quantified the impact of the new A320 and B737 narrow-body aircraft variants on rigid and flexible regional airport pavements, where these are the critical aircraft, as well as demonstrating the importance of understanding the operational weight limitations of these aircraft, which is often well below the published maximum weight. Within the context of the pavements considered, the additional pavement thickness required for the heaviest aircraft variants, compared to the lightest variants, was 51%. Based on four examples from real regional airports in Australia, it was found that the additional embodied carbon associated with these new aircraft variants was 2.1–85.3 kg·eCO₂/m² of pavement, while the additional financial cost was AUD 6–219/m² of pavement. It was concluded that airport pavement thickness designers must challenge the weight of the design aircraft and not take the simple and conservative approach of adopting the maximum weight of the heaviest variant within each aircraft family. By doing so, significant additional pavement thickness will be constructed for no practical benefit, creating an environmental (embodied carbon) and economic (financial cost) burden. Full article

The subgrade soil stiffness, which depends on the in-situ moisture content and soil index characteristics, is a key factor in pavement rutting. Due to variations in the compaction process used during construction and seasonal changes, the subgrade soil moisture content may deviate from the desired condition. The resilient modulus (M_R), an important parameter of the Mechanistic-Empirical (M-E) pavement design process, is used to specify the subgrade soil stiffness. Repeated load triaxial tests, which can be challenging and time-consuming to execute, are often used to determine M_R. As a result, correlations between M_R and more accessible stiffness metrics and index qualities are frequently used. California bearing ratio (CBR) and repeated load triaxial tests were carried out in this investigation. Soil specimens were fabricated at moisture levels that were both above and below the optimum moisture content ($w_{opt}$). The results of the two tests were correlated, and statistical models were created to correlate the parameters of the generalized constitutive resilient modulus model with the characteristics of the soil index. Additionally, utilizing the M_R found for subgrade soils compacted at $w_{opt}$ and ±2%$w_{opt}$, pavement rutting was analyzed for three base layer types. The results demonstrated that a laboratory-measured M_R (M_R(Lab)) decreases as the moisture content increases. Specimens compacted at −2%$w_{opt}$ showed higher M_R(Lab) than specimens compacted at $w_{opt}$. Specimens compacted at +2%$w_{opt}$ showed lower M_R(Lab) than specimens compacted at $w_{opt}$. Results also indicated that the M_R(Lab) predicted higher pavement rutting compared to field measured M_R (M_R(Lab)). If a stabilized aggregate foundation layer was employed instead of an untreated granular base, subgrade soil moisture condition showed a significant impact on rutting. Full article

Dry-processed rubberized asphalt mixture has recently attracted a lot of attention as an alternative to conventional asphalt mixtures. Dry-processed rubberized asphalt pavement has improved the overall performance characteristics compared to the conventional asphalt road. The objective of this research is to demonstrate the reconstruction of rubberized asphalt pavement and evaluate the pavement performance of dry-processed rubberized asphalt mixture based on laboratory and field tests. The noise mitigation effect of dry-processed rubberized asphalt pavement was evaluated at the field construction sites. A prediction of pavement distresses and long-term performance was also conducted using mechanistic-empirical pavement design. In terms of experimental evaluation, the dynamic modulus was estimated using materials test system (MTS) equipment, the low-temperature crack resistance was characterized by the fracture energy from the indirect tensile strength test (IDT), and the asphalt aging was assessed with the rolling thin-film oven (RTFO) test and the pressure aging vessel (PAV) test. The rheology properties of asphalt were estimated by a dynamic shear rheometer (DSR). Based on the test results: (1) The dry-processed rubberized asphalt mixture presented better resistance to cracking, as the fracture energy was enhanced by 29–50% compared to that of conventional hot mix asphalt (HMA); and (2) the high-temperature anti-rutting performance of the rubberized pavement increased. The dynamic modulus increased up to 19%. The findings of the noise test showed that at different vehicle speeds, the rubberized asphalt pavement greatly reduced the noise level by 2–3 dB. The pavement M-E (mechanistic-empirical) design-predicted distress illustrated that the rubberized asphalt pavement could reduce the IRI, rutting, and bottom-up fatigue-cracking distress based on a comparison of prediction results. To sum up, the dry-processed rubber-modified asphalt pavement has better pavement performance compared to the conventional asphalt pavement. Full article

The rheological properties of warm-mix recycled asphalt binders are critical to enhancing design quality and interpreting the performance mechanisms of the corresponding mixtures. This study investigated the rheological behavior of warm-mix recycled asphalt binders with high percentages of RAP binder. The effects of two warm-mix additives [wax-based Sasobit (S) and surfactant-based Evotherm-M1 (E)], a rejuvenating aging [ZGSB (Z)], four RAP binder contents (0%, 30%, 50% and 70%), and three aging states (unaged, short-term aged and long-term aged) were evaluated in detail using the dynamic shear rheometer (DSR), bending beam rheometer (BBR) and Brookfield rotational viscometer tests as well as conventional performance tests over the whole range of temperatures. The results showed that the rejuvenating agent Z effectively alleviated the aging effect of the RAP binder; however, it could hardly eliminate entirely this negative impact, especially at higher RAP binder contents. The addition of S remarkably lowered the apparent viscosity of the warm-mix recycled binders by up to 35.0%, whereas E had little influence on the binder viscosity due to its surfactant nature. Besides, S performed much better in improving rutting resistance (with the increase of up to 411.3% in |G*|/sinδ) than E, while E exhibited superior fatigue performance (with the reduction of up to 42.3% in |G*|·sinδ) to that of S. In terms of the thermal cracking resistance, E had very slight influence and S even yielded an adverse impact (with the increase of up to 70.2% in S_a and the decrease of up to 34.1% in m-value). Further, S broadened the ranges of pavement service temperatures by about 12 °C, whereas E almost did not change the PG grades of the binders. Finally, regarding the characteristics of viscoelastic master curves, S considerably improved the dynamic modulus and lowered the phase angle of the binders over a wide range of frequencies and temperatures but led to the failure of the time-temperature superposition principle due to its thermorheologically complex nature. Nevertheless, in this regard, the effect of E was found very mild. Full article

The porosity of porous media is a key factor affecting cement slurry diffusion. In this paper, a theoretical model of cement slurry diffusion in porous media considering the variation of porosity is proposed. The model is validated through comparison with the experimental results in the literature. The influence of injection parameters (i.e., the water–cement ratio and the pore fractal dimension) on the porosity and strength of porous media is analyzed. The results indicate that: under the same pore fractal dimension, the porosity of the specimen increases gradually with the increase in diffusion distance, and the rate increases rapidly in the later stage. However, when the fractal dimension of porosity increases to 2.1, the porosity of the consolidated body after grouting does not change with the diffusion distance. The water–cement ratio also affects the porosity of the sample. At a distance below 1.0 m, the sample porosity is larger at a larger water–cement ratio of 1.5. When the distance is more than 1.0 m, the smaller the porosity decreases with increasing water–cement ratios. With the increase in distance, the compressive strength of the specimen first decreases slowly, and then rapidly from 90 kPa to 0 kPa. This is further verified by the pore variation law obtained by SEM. The model is applied to selecting grouting parameter design in road maintenance. The pavement deflection after grouting is effectively reduced, verifying the theoretical model’s applicability. Full article

Pavement maintenance plays a significant role in megacities. Managing complaints and scheduling road reviews are the two maintenance concerns under the intelligent pavement management system (PMS) plan. In contrast, if the damages are not treated immediately, they will increase over time. By leveraging accurate data from sensors, smart PMS will improve management capability, support sustainability, and drive economic growth in the road network. This research aimed to elaborate on the different modules of an intelligent city pavement network to advance to a sustainable city. First, a 3D mobile light detection and ranging (LiDAR) sensor, accompanied by a camera, was applied as the data collection tool. Although 3D mobile LiDAR data have gained popularity, they lack precise detection of pavement distresses, including cracks. As a result, utilizing RGB imaging may help to detect distresses properly. Two approaches were integrated alongside conducting the data analysis in this paper: (1) ArcGIS pro, developed by Esri Inc., which includes noise removal, digital elevation model (DEM) generation, and pavement and building footprint extraction; (2) the Mechanistic-Empirical Pavement Design Guide (AASHTOWare PMED), which was used to assess site specifications such as traffic, weather, subbase, and current pavement conditions in an effort to design the most appropriate pavement for each road section. For the 3D visualization module, CityEngine (a software from Esri) was used to provide the 3D city model. After implementing the research methodology, we drew the following conclusions: (1) using the AASHTOWare PMED method to make decisions about road maintenance and rehabilitation(M&R) actions can significantly speed up the decision-making process, essentially saving time and money and shortening the project’s duration; and (2) if the road conditions are similar, the smart geographical information system (GIS)-based PMS can make consistent decisions about road M&R strategies, i.e., the interference from human factors is less significant. Full article

Pavement design is a long-term structural analysis that is required to distribute traffic loads throughout all road levels. To construct roads for rising traffic volumes while preserving natural resources and materials, a better knowledge of road paving materials is required. The current study focused on the prediction of Marshall stability of asphalt mixes constituted of glass, carbon, and glass-carbon combination fibers to exploit the best potential of the hybrid asphalt mix by applying five machine learning models, i.e., artificial neural networks, Gaussian processes, M5P, random tree, and multiple linear regression model and further determined the optimum model suitable for prediction of the Marshall stability in hybrid asphalt mixes. It was equally important to determine the suitability of each mix for flexible pavements. Five types of asphalt mixes, i.e., glass fiber asphalt mix, carbon fiber asphalt mix, and three modified asphalt mixes of glass-carbon fiber combination in the proportions of 75:25, 50:50, and 25:75 were utilized in the investigation. To measure the efficiency of the applied models, five statistical indices, i.e., coefficient of correlation, mean absolute error, root mean square error, relative absolute error, and root relative squared error were used in machine learning models. The results indicated that the artificial neural network outperformed other models in predicting the Marshall stability of modified asphalt mix with a higher value of the coefficient of correlation (0.8392), R² (0.7042), a lower mean absolute error value (1.4996), and root mean square error value (1.8315) in the testing stage with small error band and provided the best optimal fit. Results of the feature importance analysis showed that the first five input variables, i.e., carbon fiber diameter, bitumen content, hybrid asphalt mix of glass-carbon fiber at 75:25 percent, carbon fiber content, and hybrid asphalt mix of glass-carbon fiber at 50:50 percent, are highly sensitive parameters which influence the Marshall strength of the modified asphalt mixes to a greater extent. Full article

The objective of this study is to compare the long-term aging performance of dry-processed rubber-modified asphalt mixture with styrene–butadiene–styrene polymer-modified asphalt mixture on heavy traffic volume roads in the wet-freeze environment of Michigan. The rutting performance was evaluated using the Hamburg wheel track device. The disc-shaped compact tension test was used to assess the fracture energy. The dynamic modulus experiment was used to estimate the load and displacement relationship. The asphalt binder properties were evaluated using multiple stress creep recovery and the linear amplitude sweep test. The pavement distresses were evaluated using the pavement mechanistic–empirical design. All three types of asphalt mixture show excellent rutting resistance after long-term aging conditions, while the fracture energy of the rubber mix is 17.1% to 30.5% higher than that of the control mix and 6.8% to 9.1% higher than that of the polymer mix. The rubber and polymer incorporated with the asphalt binder improved the resistance to permanent deformation and improved the fatigue life of the asphalt binder. In summary, the rubberized asphalt technology using the dry process shows better cracking resistance and fatigue life. Therefore, rubberized asphalt using the dry process will exhibit adequate performance when used for high-volume roads in the wet-freeze environment of Michigan. Full article

The present study explores the structural pavement design techniques related to pavement distresses in terms of pavement rutting, cracking and International Roughness Index (IRI) based on the materials properties, roadbed characteristics, climate and traffic loads for highway network of Saudi Arabia (KSA). The study was focused on selected site conditions at four regions in KSA: Central (Riyadh); Eastern (Al-Ahsa); Western (Jeddah) and Northern (Arar). Mechanistic-Empirical Pavement Design Guide (MEPDG) software was used to calibrate and predict pavement design life according to the mentioned distresses for different regions in the KSA. This is the first time where the exact weather stations were selected to run analysis on the software determining realistic pavement distresses. In the study, the pavement structure design is different for low traffic (700 AADTT) and high traffic (2000, 6000, and 10,000 AADTT). The tests were run on the MEPDG software to analyze the distresses predicted by the software for an interval of 5, 10, 15, and 20 years. The results predicted by the software show that the preliminary example design satisfies all the target distresses for the mentioned design life, even for 20 years. The study provides a base pavement design for pavement designers that can be modified as per project requirements using the specific data for traffic, material properties, thickness, and distress limit to achieve target design life. Full article

The use of concrete in road construction has grown over the past decade due to the material’s great durability. However, concrete has poor tensile strength, ductility, and energy absorption. This paper aims to investigate the utilization of plastic waste, namely polypropylene (PP), to create a novel fiber to enhance the engineering properties of fiber reinforced concrete (FRC), an eco-friendly concrete that can reduce environmental problems. The 28-day design strengths of 28 and 32 MPa were used in this study because the compressive strength requirements for concrete footpaths and pavement specified by Austroads and the Department of Highways, Thailand, were at least 25 and 32 MPa, respectively. The fiber (F) was a mixture of virgin PP and recycled PP (RPP). The study used F contents of 0.25, 0.50, 0.75, and 1% by weight of cement and PP:RPP ratios of 100:0, 75:25, 50:50, 25:75, and 0:100. The compressive strength, flexural strength, leaching, and CO₂ emissions savings of FRC were evaluated. Improvements in the compressive strength, flexural strength, and toughness of the samples with F were observed in comparison to the control concrete samples for all design strengths. All mixtures met the compressive strength requirements for concrete footpaths, except for F contents of 0.75 and 1% and a PP:RPP ratio of 0:100. By contrast, the 32 MPa FRC samples with F contents of 0.25 and 0.5% and all PP:RPP ratios met the requirements for rigid pavement. From an environmental perspective, the heavy metal contaminants of the 32 MPa FRC sample were within the allowable limits for all mixtures. Regarding incineration disposal, the maximum CO₂ emissions savings of 28 MPa and 32 MPa FRC with an F content of 0.5% and a PP:RPP ratio of 0:100 were 1.0 and 1.11 kg CO₂-e/m³, respectively. This research will enable plastic waste, traditionally destined for incineration and landfill disposal, to be used as a sustainable fiber in the construction industry. Full article

From the perspective of sustainable waste management and its environmental impact, waste biomass bottom ash (BA) remains problematic and challenging to use as a recycling material for civil engineering infrastructures. This study evaluated the performance of lateritic soil (LS), stabilized with cement and biomass BA, as a subbase material. BA has been considered a replacement material in LS prior to the introduction of hydraulic cement stabilization means. The geotechnical engineering tests comprised the modified Proctor test, the California Bearing Ratio (CBR) test, and the unconfined compression test. X-ray fluorescence (XRF) and X-ray diffraction (XRD) tests were conducted to investigate the mineralogical properties of the stabilized soil samples. The leachate test was performed with a permeability mold to measure the release of heavy metals. Finally, the benefits of using the stabilized subbase material were assessed using the mechanistic–empirical (M–E) pavement design approach. Based on the results obtained, the strength and stiffness characteristics of the stabilized soils indicate that the efficiency of the mix satisfied the Thailand highway specification. The admixture of 80% BA and 5% cement is suggested for use as a soil–cement subbase material for flexible pavements, due to its good engineering and environmental properties. The results of the M–E design demonstrate the effectiveness of the stabilized soil presented herein. The study’s outcomes are predicted to promote the utilization of waste BA as a promising pavement material. Full article

The sound absorption of a road pavement depends not only on geometric and volumetric factors but also on pore shape factors. In turn, pore shape factors mainly refer to thermal and viscous factors (i.e., thermal and viscous effects that usually occur inside porous materials). Despite the presence of a number of studies and researches, there is a lack of information about how to predict or estimate pore shape factors. This greatly affects mixture design, where a physical-based or correlation-based link between volumetrics and acoustics is vital and plays an important role also during quality assurance and quality control (QA/QC) procedures. Based on the above, the objective of this study is to link mixture volumetrics and pore shape factors. In particular, 10 samples of a porous asphalt concrete were tested in order to estimate their thickness, air voids content (vacuum-sealing method, ASTM D6857/D6857M), sound absorption coefficient (Kundt’s tube, ISO 10354-2), airflow resistivity (ISO 9053-2), and permeability (ASTM PS 129). Subsequently, two models (herein called STIN and JCAL) were used to derive both volumetrics and pore shape factors from the estimated parameters listed above, and statistical analysis was carried out to define correlations among the parameters and models performance. Results confirm the complexity of the tasks and point out that estimates of the pore shape factors can be derived based on mixture volumetrics. Results can benefit researchers (in acoustic and pavement mixtures) and practitioners involved in mix design and pavement acceptance processes. Full article