International Conference on Transportation and Development 2022: Pavements

Unlike other countries, Australia continues to construct flexible aircraft pavements with thin asphalt surfaces over multiple layers of fine crushed rock base and sub-base. Furthermore, many Australian airports are in coastal areas where marine clays dominate the naturally occurring soils and commonly incorporate hydraulically placed deep sand fills. Flexible Australian aircraft pavement performance depends on the ability to compact and prove the crushed rock and sand fill layers. This was historically done with macro rollers and supercompactors; however, in recent years the availability and performance of these rollers has decreased. This has created a gap in the ability to prove these granular materials, which has been exacerbated by aircraft tyre pressure and wheel loads increasing. A suitable method of addressing this gap must be determined to ensure thin asphalt pavements can continue to be constructed for Australian airports.

A well-known gap in current pavement design methodologies is quantifying strength contributions from geogrid reinforcement. A popular method for modeling geogrid reinforcement is through “sub-layering,” where the region within the vicinity of the proposed geogrid is modified by the inclusion of stiffer elastic moduli. However, it is difficult to characterize the stiffness and extent of the sub-layering around the geogrid. Another method is proposed, which implements a Pasternak-type interface model within a layered elastic framework to simulate the effect of a geogrid. The model was tested against measured data collected from small-scale cyclic plate load tests of geogrid-reinforced asphalt pavement structures where the effect of a rigid plate load was simulated using a non-uniform loading function. Results showed that the proposed analytic model matched measured deformation and stress responses reasonably well. Findings suggested that the response model should be considered in future developments of a geogrid mechanistic-empirical performance model.

In order to ensure good quality and well-maintained road, regular maintenance and rehabilitation (M&R) of pavement is mandatory. The Long Term Pavement Performance (LTPP) database has the most comprehensive pavement performance data along with its M&R history for more than 2,500 pavement sections throughout the United States and Canada. The artificial neural networks (ANNs) modeling approach has been used in recent years for the prediction of pavement performance. However, most pavement performance modeling does not consider the M&R history in the model development. As such, this paper aims to exhibit a methodology to determine pavement performance incorporating maintenance and rehabilitation history using the LTPP database and ANN modeling approach. The models will be developed using data collected from the LTPP database for jointed plain concrete pavement (JPCP) from the wet, non-freeze climatic region. The M&R history is denoted as construction number (CN) in the LTPP database. The hypothesis testing demonstrated M&R treatment has a significant effect on pavement performance. Several models will be attempted to evaluate the best way to include M&R history by changing the CN variable from the LTPP database. The use of M&R history in pavement performance modeling reflects more realistic pavement conditions in the model development process. The developed models will establish better accuracy in the prediction of future pavement conditions. This can be beneficial to the policymaker for short-term and long-term budget allocation in the M&R treatment of highway pavements.

Efficient and well-maintained pavement systems are crucial to ensure appropriate conditions for the road networks. If timely maintenance and rehabilitation (M&R) is not performed, the pavement deterioration may lead to poor conditions that affect the comfort and safety of road users. The effectiveness of any M&R actions essentially depends on the time of treatment. This paper presents the development of pavement roughness models using the artificial neural networks (ANNs) approach for composite pavements using the Long-Term Performance Pavement (LTPP) program database for the wet, non-freeze climate region. A total of 49 composite pavement sections with 353 data points were analyzed. The use of an M&R variable in the model development resulted in more realistic and accurate models to predict future pavement conditions, identify M&R actions, and simulate interventions for future years. The developed models could be used by transportation agencies as a valuable tool for more effective M&R scheduling prioritizing worst condition pavement sections.

Climate change is expected to affect the performance of highway pavements. However, the literature review to date does not consider how the pavement performance will be affected by extreme weather (i.e., extreme temperature and extreme rainfall). The quantification of pavement deterioration due to extreme weather can be beneficial to evaluate the effect of climate change on pavement performance. This study aims to develop a pavement deterioration model for jointed plain concrete pavement (JPCP) using the artificial neural network (ANN) modeling techniques. The models will be developed using data collected from the Long Term Pavement Performance (LTPP) database for wet, freeze climatic region. The input variables are initial pavement condition (i.e., initial IRI), pavement structural and mechanical properties (i.e., age, concrete pavement thickness, base/subbase thickness, average contraction spacing, and base/subbase materials type), traffic [Cumulative ESAL (CESAL)], and climate attributes (i.e., average annual air temperature, total annual precipitation, annual freezing index, and annual freeze-thaw), and the output is pavement deterioration indicator [international roughness index (IRI)]. The effect of different climate scenarios can be examined by conducting several models with inputs that reflect several climate scenarios. The best model will be used to investigate how much more pavement will deteriorate if climate attributes change to extreme conditions. This research will address a few gaps in the literature, including the scarcity of studies on long-term IRI prediction using LTPP data and studies on the effect of climate attributes in pavement deterioration. This analysis can be beneficial to the long-term policymaking in road infrastructure.

The present study is aimed at using unmanned aerial vehicles (UAVs) for pavement monitoring. It was taken up as an initial pilot study to develop a network level asset management framework for South Korean conditions. A varying pavement stretch containing a bridge, culvert, streams, and merging traffic junctions was selected for the study. Using a quadcopter UAV, 139 overlapping images were acquired and processed using a structure from motion (SfM) program to develop a digital twin of the pavement. The generated orthomosaic and 3D digital twin were used to identify pavement damage and other infrastructural assets. UAV-based image acquisition was found to provide sufficient resolution, exposure, and key point matches, enabling an accurate 3D model generation with detailed feature extraction. Geometric measurements of various features depicted the potential and efficiency of UAV surveys. The research work is expected to aid in effective contactless pavement monitoring and asset management during regular surveys as well as disasters.

One of the major goals of pavement management and design is to increase pavement life considering the effects of materials, environment, traffic, and rehabilitation actions. Billions of dollars are required every year for the maintenance and rehabilitation (M&R) of road networks. However, transportation agencies are required to prioritize their M&R actions due to the rate of pavement deterioration and limited budget allocation. Therefore, there is a need for reliable and accurate pavement performance models that can estimate future pavement conditions, identify rehabilitation needs, and analyze rehabilitation impacts. However, the literature review showed that M&R actions are challenging to be incorporated into modeling. This study developed performance models for asphalt pavements considering traffic and climate loads, pavement age, initial roughness condition, and M&R interventions. The data was retrieved from the Long-Term Performance Pavement (LTPP) program database and an artificial neural networks (ANNs) technique was used for the model development. The developed models efficiently characterized the deterioration behavior of asphalt pavements over time, and effectively capture the effect of M&R interventions. The predicted international roughness index (IRI) values were in good agreement with observed values, and the developed models were found to be reasonably accurate. Therefore, the models developed in this study are suitable for transportation agencies to assess pavement conditions to schedule and prioritize M&R actions for the critical asphalt pavement sections.

Oklahoma State University (OSU) developed an airport runway near Elgin, Oklahoma, to evaluate lightweight unmanned aerial vehicles (UAV). This paper documents the construction and evaluation of the asphalt pavement testing runway for the UAV facility. The preparation and construction of the runway was first discussed. Four asphalt mixtures were sampled and tested for the 2-in. surface lifts using a foamed warm mix asphalt (WMA) technology and hot mix asphalt pavements with reclaimed asphalt pavement (RAP). The dynamic modulus and semi-circular bend (SCB) testing were performed to evaluate the four experimental mixtures used in the facility. Subsequently, runway surface characterization and performance evaluation results, in terms of pavement cracking, longitudinal profiling and roughness, surface texture, and pavement friction, were presented based on the field data collection performed using four state-of-the-art instruments. The results from this study demonstrated that the UAV testing runway with the mixes evaluated met the material requirements and had a superior short-term field performance.

Frost action (heaving and thawing) is a perennial problem encountered in the design, construction, and management of civil engineering structures, particularly road pavements in cold regions and areas that experience seasonal sub-freezing temperatures. This paper reviews the existing methods for frost heave mitigation and proposes an innovative approach through engineered water repellency. Soil was collected from a test plot at the Charlotte Douglas International Airport and treated with a commercially available organosilane. Preliminary results indicate an increase in the maximum dry density from 17.54 kN/m³ to 17.66 kN/m³ and a decrease in the optimum moisture content from 17.36% to 11.75% after treatment. Data obtained from performance tests carried out under sub-freezing weather conditions indicated that the treatment was effective in limiting the infiltration and migration of water into the soil matrix when compared with the untreated soil. As such, engineered water repellency may be a viable solution for airports and Departments of Transportation seeking methods to mitigate frost action.

Subgrade stabilization sometimes becomes essential to improve the bearing capacity of the natural soil to achieve the pavement’s design life. This study evaluates the strength characteristics of subgrade soil using various combinations of alkali-activated medical waste-based incineration ash and coal power plant based fly ash, which is termed geo-polymer. Samples are prepared by the modified Proctor method at the optimum moisture content (OMC) for geo-polymer contents (GPC) of 0%, 5%, 10%, 15%, and 20%. Unconfined compressive strength (UCS) tests are conducted to evaluate the development of strength of the stabilized subgrade soil at a curing period of 14 days at OMC and soaked conditions. It is observed that unconfined compressive value increases with the increase of geo-polymer content, and soaking does not reduce the strength of treated soil after 10% of GPC. A maximum strength value of 2,314 kPa are obtained for 20% geo-polymer content, almost three times of untreated soil. The research findings will lead road engineers to use incineration ash for subgrade improvement.

In contemporary pavement engineering parlance, a “transfer function” is a statistical-empirical formula that is used to determine the number of cycles or repetitions of a specified loading condition to which a pavement system may be subjected before it develops a particular distress of a specified extent. The significance of the transfer function in modern pavement engineering is unmatched by any other aspect of the design process. At the same time, it is generally recognized that the transfer function is the weakest component in a pavement design, reflecting the shortcomings of the current state-of-the-art and being fraught with statistical uncertainty. This paper will demonstrate that this has not always been so. In earlier times, transfer functions served the purpose of providing a safety factor, an indispensable tool for engineering design. How from such relatively humble beginnings, grounded in time-honored engineering practices, the transfer function has evolved to its current widely questioned but hardly ever challenged crucial role in pavement design is a topic that is explored in depth in this paper, through the critical review of the pertinent published literature. It is concluded that the transfer function has always been a tool for implementing policy, rather than a data driven algorithm. Consequently, it is suggested that reliance on transfer function use in pavement design must be supplemented by a careful assessment of the rational foundation of pavement design policies.

This paper reports the results of laboratory investigation carried out on soft soil collected from Padma Bridge Rail Link Project site to determine an optimum mix ratio of two stockpiled industrial waste by-products fly ash and LRF slag-based geopolymers for cement soil mixing piles. A total of six combinations were investigated for strength evaluation following specific patterns of soil-cement-binder mixtures on samples with 14 and 28 days’ curing conditions. It was observed that B15C5 (15% slag and fly ash +5% cement) gained the highest compressive strength in both at molding water and dry conditions in each age. The maximum strength of this combination was found at 4,158 kPa in dry condition and 792 kPa in wet condition in 28 days. With the increment of binder contents in alkali activated samples, compressive strength reaches a peak value of 407 kPa and 3,987 kPa at molding water and oven dry conditions, respectively, for B25 (25% geopolymer) and gradually decreases with more use of geopolymer noticeable in both conditions and ages. The findings of the study with alkali activated fly ash and slag may lead to a durable soil stabilization solution along with a solution to waste management.

Understanding asphalt pavement permeability is important to mitigate the rate of oxidation and intrusion of water. However, instead of direct measurement, permeability is often approximated using commonly measured properties such as air voids (V_a). Unfortunately, in instances such as surface treatment applications or longitudinal joint treatments, traditional volumetric measures may not capture improvements to permeability. This research presents enhancements to the Mississippi permeameter (MSP), which has previously produced reasonable results compared to existing permeameters and utilizes the same equipment for field and laboratory measurements. Equipment modifications evaluated include additional standpipe diameters and contact area diameters. Data was collected on conventional dense-graded asphalt, fog-sealed pavement, and longitudinal joints with and without joint adhesive treatments. Results indicate the MSP device is a promising option for assessing permeability of multiple pavement surface types, particularly those for which density measurements are not well-suited.

3D pavement imaging has become the mainstream technology adopted by highway agencies for automated pavement condition evaluation. The high-resolution and high-accuracy imaging systems collect 3D pavement image data that enables cracking distress identification at a fine granularity to support the agencies’ maintenance and rehabilitation planning. However, there is currently no standard procedure for the evaluation of the systems’ image data quality and performance in cracking distress identification. The objective of this study is to propose a simplified methodology for evaluating the cracking identification capability of a 3D pavement imaging system using a manufactured verification board with known dimensions. This board was designed with linear gaps representing different ranging from 1 mm to 5 mm. The evaluation method utilizes objective indicators and consistent procedures to evaluate the system’s crack identification capability in terms of (1) crack detectability for different crack widths, (2) crack width measurement error, and (3) the overall image quality. A case study was conducted to demonstrate the feasibility of the proposed method by performing a sample evaluation using test images of the scanned board, collected by different 3D imaging systems, and a ground reference image of the board, which was obtained using “FARO Arm Quantum S” scanner, with an accuracy of ±30 μm and minimum point spacing of 20 μm. This paper presents the preliminary findings of the case study and the proposed standardized procedure of crack identification evaluation using the verification board. This study is sponsored by the ongoing NCHRP 01-60 research project.

Polymer modification techniques of asphalt binders have received significant attention as it includes economical value and most importantly adds improvement to the performance of asphalt pavements. Research has shown that the polymer’s presence offers additional elastic recovery and viscosity to the neat binder based on the type of modification technology. This study investigated the effects of a specific polymer-coated rubber (PCR) through both dry and wet technologies on asphalt mixtures. Advanced laboratory tests on binder and mixture levels were conducted. In addition, to better understand the long-term performance of the modification techniques, mechanistic-empirical (ME) analyses were performed. The mechanistic empirical asphalt pavement analysis (MEAPA), a web-based mechanistic-empirical pavement analysis software, was used in this study. The results were compared to a conventional polymer (SBS) modified mixture. Although experimental results showed that SBS modified mixture performed better, overall ME long-term performance predictions implied that PCR modified mixtures would perform well in the field. Among the two technologies adopted in the study, PCR wet modified mixtures perform slightly better than PCR dry.

Incorporating waste polymers into reclaimed asphalt is promising because of the large volume of asphalt produced and utilized worldwide. In this study, the effects of low-density polyethylene (LDPE) on the microstructure, viscosity, and self-diffusion of the aged asphalt were studied through molecular dynamics (MD) simulation. The aged asphalt model was constructed by including four characteristic components of saturates, aromatics, resins, and asphaltenes. An 8 wt% of LDPE was then added to the aged asphalt model, and the properties of the mixture were collected at 298 K. Our results reveal that LDPE has preferentially interactions with less polarized saturates and aromatics of the aged asphalt. From the radial distribution functional analysis, the low concentration of LDPE additives obviously changed the aggregation of saturates. However, the effect on the distributions of other compositions (aromatic/aromatic, resin/resin, and asphaltene/asphaltene) was found to be negligible. In addition, the viscosity and self-diffusion of the aged asphalt model remained almost unchanged by the addition of LDPE. This finding supports the common experimental practice of treating asphalt by 2–10 wt% LDPE.

Some of the major distresses in asphalt pavements are high-temperature rutting, low-temperature cracking, and load-associated fatigue cracking. Modifiers can stiffen the binder and provide a more elastic material; therefore, we used elastic polymer (SBS—styrene–butadiene–styrene) and nano TiO₂ (titanium dioxide) to modify the PG 58-28 binders. TiO₂ nanoparticles were chosen for their potential to accelerate the process of trapping and degrading organic and inorganic particles from the air while removing harmful air pollutants, such as nitrogen oxide (NOx), sulfur oxide (SOx), and volatile organic compounds (VOCs) in the presence of ultraviolet light. Rolling thin film oven (RTFO) and pressure aging vessel (PAV) techniques were used to simulate the binder’s short- and long-term aging. Dynamic shear rheometer (DSR) was used to determine the rheological properties of unaged and short- and long-term aged binders. An optimum TiO₂ content in 12% SBS was determined based on binder test results. Hot mix asphalt (HMA) was designed with a virgin binder (control) and a binder modified with SBS and TiO₂. A superpave gyratory compactor was used to compact mix specimens. Asphalt pavement analyzer (APA), disk-shaped compact tension (DCT), and semi-circular bend (SCB) tests were used to determine rutting, low-temperature cracking, and fatigue cracking resistance. Our results indicated that the 1 wt.% TiO₂+12% SBS modified PG 58-28 binder and corresponding mix performed satisfactorily.

Among different recycled materials, use of post-consumer recycled (PCR) plastics in asphalt mixes provides several benefits, including economic, environmental, and improvement in performance. Resistance to fatigue cracking of asphalt mixes is used in the design and performance assessment of asphalt pavements. The purpose of this study was to evaluate the effect of PCR plastics on the stiffness and resistance to fatigue cracking of asphalt mixes. Specifically, this study addressed the changes in the dynamic modulus, cracking tolerance index (CT_Index) and percent loss (%Loss) from Cantabro abrasion test with the addition of PCR plastic in different amounts. For this purpose, a surface mix (NMAS of 9.5-mm) with PG 64-22 binder was modified using three different percentages (0.25%, 0.5%, and 1% of aggregate) of PCR plastic. Two different PCR plastics, namely low-density polyethylene (LDPE) and linear low-density polyethylene (LLDPE), were incorporated in the asphalt mix using the dry process. Dynamic modulus test, indirect asphalt cracking test (IDEAL-CT), and Cantabro test were performed on both control and plastic-modified mixes. The stiffness, resistance to fatigue cracking, and %Loss of plastic-modified mixes were compared with those of the control mix as well as between mixes with two different types and amounts of PCR plastics. In addition, laboratory performance of the plastic-modified mixes was compared with performance of a typical pavement under traffic loading analyzed using the AASHTOWare Pavement Mechanistic-Empirical Design (PMED) software. The findings of this study are presented in this paper.

In this study, a method that can be used to replicate the fine aggregate matrix (FAM) in the field condition as accurately as possible was experimentally validated, and the low temperature performance was measured and evaluated. First, an AC 22 TS mixture is selected as the reference material. The method based on a shift of the grading curve by a mathematic adaptation to the boundary sieve (D_FAIB) is used to generate the grading curves of the FAM. Next, small sample beams of asphalt binder, mastic, FAM, and mixture are tested with the bending beam rheometer to evaluate the material’s response at low temperatures across the different phases. The results of the BBR study show that the FAM phase has a higher stiffness than binder and mastic with a close behavior to the mixture. The results suggest that the FAM could be potentially adapted for discriminating among different mixtures.

The performance of a WIM site mainly depends on sensor technology, pavement conditions, calibration, and maintenance practices. An adequate pavement structure is required to install and accommodate WIM system sensors throughout their service life. WIM sensor manufacturers suggest that the plate-based sensors [load cells (LC) and bending plate (BP)] should only be installed in Portland cement concrete (PCC) pavements, while the linear or strip type sensors [such as polymer piezo (PP) or piezo cable (PC), and quartz piezo (QP)] could be installed on both PCC and asphalt concrete (AC) pavements. This paper evaluates the influence of pavement surface thickness on WIM accuracy data for different sensor types and suggests adequate thicknesses for WIM stations installed in PCC and AC pavements based on the data. Data from ninety-four (94) WIM stations in the United States and Canada are used for WIM accuracy and pavement thickness analyses. For 18 sites, BP sensors are installed in PCC pavements. Out of 29 total QP sensor sites, 6 and 23 had PCC and AC pavements. In contrast, 19 PC sites have PCC pavements, and the remaining 28 sites have AC pavements. The results show that BP sensors can be installed in 10 in. or thicker PCC slabs to yield ASTM type I accuracy. Irrespective of pavement type, 8 in. or above (PCC or HMA thickness) is recommended for QP sensors to obtain highly accurate WIM data. No consistent trends were observed for PC sensors, as the sites showed significantly higher gross vehicle weight error even after calibration in both AC and PCC pavements.

California Department of Transportation (Caltrans) and the industry identified concerns with test variability experienced with the Hamburg wheel-track (HWT) test relating to rubberized hot mix asphalt-gap graded (RHMA-G) mixtures in asphalt pavement. Thus, changes were made to the American Association of State Highway and Transportation Officials (AASHTO) test method T 324 (as modified according to the 2018 Caltrans Standard Specifications), and a new test procedure, California Test (CT) 389, was developed by Caltrans. The effectiveness of the CT 389 test procedure in reducing HWT test variability was investigated through an interlaboratory study. A total of 24 Caltrans and industry laboratories participated in the study. Half of the participants performed AASHTO T 324 combined with sample reduction using AASHTO R 47. The other half performed CT 389 using the CT 306 sampling method developed by Caltrans. Data consistency was evaluated according to the American Society for Testing and Materials (ASTM) test method C802, calculating single operator and multi-laboratory variability. Corresponding precision estimates were developed according to ASTM C670. Changes to the HWT test implemented through CT 389 along with CT 306 sample reduction method showed significant improvement in variability at all milestone passes compared to AASHTO T 324. At the 20,000 passes threshold, for single operator, the results of two properly conducted tests on specimens with the same material are not expected to differ by more than 38.6% when performing CT 389, compared to 43.8% when performing AASHTO T 324. For multi-laboratory, the difference is 66.4% when performing CT 389 compared to 88.0% when performing AASHTO T 324. Thus, CT 389 provides better precision than AASHTO T 324 when testing replicate samples of RHMA-G.

Asphalt concrete mixtures are susceptible to moisture-induced damage, which has been identified as one of the major distresses of the pavement structure. The addition of tire rubber has shown to increase the resistance of the asphalt mixture to cracking and moisture damage. The American Association of State Highway and Transportation Officials (AASHTO) test method T 283 is an established process to evaluate the moisture susceptibility of asphalt mixtures. The high variability of T 283 in predicting moisture susceptibility of dense graded hot mix asphalt (HMA) mixtures led to the development of precision estimates under National Cooperative Highway Research Program (NCHRP) Project 9-26A. The performance of rubberized hot mix asphalt-gap graded (RHMA-G) varies from dense graded HMA because of significant differences in their characteristics. Thus, directly applying the precision estimates of T 283 developed for HMA to RHMA-G may lead to even higher variability. To investigate these discrepancies, the California Department of Transportation developed precision estimates for T 283 using a ½ in. RHMA-G mix through an interlaboratory study program and compared the results to the precision estimates developed in NCHRP Project 9-26A. The tensile strength ratios (TSR) were developed from dry and conditioned (wet) indirect tensile strengths measured in accordance with T 283 on replicate samples conducted by 53 participating laboratories. The precision estimates along with the allowable range for single operator and multi-laboratory of TSR results as well as both dry and wet indirect tensile strengths in RHMA-G mixtures measured per T 283 are presented in this paper.

The use of deicer chemicals for highway winter maintenance operations is an essential strategy for ensuring a reasonably high level of service. It’s critical to quantify their effectiveness and potentially detrimental effects on transportation infrastructure (i.e., asphalt and concrete pavements). In this study, nine deicer chemicals used in the state of Missouri were collected. The ice-melting test was conducted to quantify the performance characteristics of deicer chemicals. Freeze-thaw (F-T) test of concrete in the presence of deicer was conducted to quantify the negative effects of deicers to concrete. Low-temperature behavior of asphalt mixture affected by deicers was quantified by asphalt mixture indirect tensile (IDT) tests. The results showed that the calcium chloride (liquid) treated rock salt had the best ice melting capacity among all the studied products, while the calcium chloride (flake/pellet) treated rock salt showed the lowest ice melting capacity. The IDT creep compliance and strength of asphalt mixture results indicated brine treated rock salt and “Top Film” treated rock salt had insignificant effects on the creep compliance of asphalt mixture, regardless of testing temperatures. The deicer chemicals had different scaling effects on concrete beams after F-T cycles. The calcium chloride (liquid) treated rock salt had little scaling effect on the concrete beams. However, concrete beams with the presence of brine treated rock salt showed the highest mass loss values.

This paper reports on the impacts that different sources of asphalt binders, which satisfactorily met the grading requirements of a PG 70-22 binder, have on the mechanical performance of two Superpave mixtures, namely a traditional mix design and a balanced mix design. Five asphalt binders were acquired from different asphalt suppliers. Superpave mixtures were designed and produced with two different aggregate gradations, and similar recycled material content following both volumetric-based and performance-based design approaches. For performance testing, the Hamburg wheel tracking device and Texas overlay tester tests were used as the main rutting and cracking tests, respectively, during the design process. The Illinois Flexibility Index Test and indirect tensile asphalt cracking tests were performed as surrogate cracking tests. From this study, the voids in the mineral aggregate parameter does not differentiate the impact of changing the asphalt binder source. The mechanical tests were sensitive to changes in binder source, which demonstrated the importance of incorporating a performance testing stage to current design specifications. The asphalt mixtures denoted as balanced mix designs in this study yielded acceptable mechanical and volumetric properties regardless of the binder source.

The present case study discusses the subgrade enhancement strategies for highly saline marine soils located at Bhavnagar District, Gujarat, India. In addition to the presence of various salts, the saturation levels of these soils were observed to vary throughout the year due to several climatic and geographical factors. Initially, the unsaturated behaviour is evaluated using the standard filter paper method. Due to the low in situ California bearing ratio (CBR) value (1.62%), locally available fly ash (10%–30% by weight) was used to improve the strength and stiffness of the soil. Addition of fly ash resulted in the considerable reduction of salinity and suction levels at all dosages of fly ash. The unconfined compressive strength (UCS) and CBR have increased until 20% fly ash and reduced from thereof. The maximum CBR obtained was about 9%, which can withstand low to medium volumes of traffic. However, the UCS developed at seven days was observed to reduce at 28 days. This may be due to the secondary reactions and change of form of salts present in the matrix. Henceforth, further investigations on interactions at micro-level, formation of secondary compounds, and suction levels were recommended to prepare a sustainable subgrade in this terrain.

We were studied tire and pavement interactions using finite element method. Several researchers’ studies have focused on prediction to fully understand of tire-pavement contacts which has implication on flexible pavement damage predictions and life cycle assessments. The primary purpose of this study was to analyze and fully understand the interactions between deformable pavement and tires using the validated finite element model. A full tire-pavement interaction model was developed where flexible pavement was subdued to a monotonic and cyclic behavior of tire loading, 40 kN in measure dual-tires, and proper tire pressure, 700 kPa. A rolling resistance free body investigation was also executed using a finite element model to understand fully the interaction between tire and flexible pavement. A vehicle contact speed, 95 km/h, was applied where load was withdrawn for 1 s during cyclic time. Axisymmetric and tire-pavement interactions were developed using a 3D finite element model. We revolved the axisymmetric analysis in Abaqus with respect to the tire axis on the vehicle so that the 3D tire model could be generated, then a contact load was placed to model. The total cyclic time was 10 s with a loading of 0.1 s and 0.9 s of resting. The contact area and deflection of thin and thick flexible pavements were also developed. Finally, results’ analyses were compared to fully understand the modeling and its consequences on pavements.

Cement stabilization of reclaimed and marginal materials provides a sustainable means for the construction of new roadways and the rehabilitation of old pavement structures. The strength and resilient properties of cement-treated materials are essential for the design and performance evaluation of roadways. Reliable estimations of unconfined compressive strength (UCS), indirect diametrical tensile (IDT) strength, and resilient modulus (Mr) are paramount for the mechanistic characterization of the structural capacity of layers. With the ever-growing popularity of rapid turn-around design approaches, estimation of all required design parameters is impractical. Therefore, pavement engineers often rely on experience or correlations to estimate material properties obtained from time-consuming and cost-prohibiting laboratory efforts. This research focused on developing relationships between IDT strength and UCS, as well as correlations between Mr and UCS of cement-treated materials considering different aggregate sources and different stabilizer contents, incorporating moisture susceptibility conditions. To achieve this objective, 480 cylindrical specimens were fabricated, cured for seven days, and subjected to the UCS test, IDT strength test, and submaximal modulus test at two levels of strength ratios. As a result, two sets of material models were developed. The first set of models considers cement content, UCS, and height-to-diameter ratio to predict tensile strength properties using different compaction methods. The second set of models predicts the Mr in terms of cement content, UCS, and strength ratio. The findings of this investigation can be beneficial for practicing engineers and design agencies to improve the predictions of IDT strength and Mr of virgin and marginal cement-treated materials.

The term “e-waste” is used for the electronic modules at the end of their life cycle or defected items rejected in their production process. With only 20% recycled out of about 45 million tons of annually generated e-waste, it has become an environmental challenge and a health concern. In the absence of an economical and safe recycling technique, the utilization of e-waste in construction materials can effectively encapsulate it and reduce landfills. To this end, this study was undertaken to investigate the feasibility of utilizing a specific stream of e-waste, consisting of ground electronic boards, plastic fixtures, and sealants, used in large video screens in Portland cement concrete (PCC). For this purpose, electronic modules were collected and crushed in an industrial grinder. Crushed particles were fractionated based on their particle sizes and used to produce PCC samples while replacing about 15% (by volume) of mineral aggregates. Additionally, control PCC samples without any e-waste were prepared. Samples were tested after seven days of curing, and their skid resistance, compressive strength, and modulus of rupture were determined. The findings of this study are expected to help reduce landfilled e-waste and promote sustainability.