The increase in population has made it possible for better, more cost-effective vehicular services, which warrants good roadways. The sub-base that serves as a stress-transmitting media and distributes vehicle weight to resist shear and radial deformation is a critical component of the pavement structures. Developing novel techniques that can assess the sub-base soil’s geotechnical characteristics and performance is an urgent need. Laterite soil abundantly available in the West Godavari area of India was employed for this research. Roads and highways construction takes a chunk of geotechnical investigation, particularly, California bearing ratio (CBR) of subgrade soils. Therefore, there is a need for intelligent tool to predict or analyze the CBR value without time-consuming and cumbersome laboratory tests. An integrated extreme learning machine-cooperation search optimizer (ELM-CSO) approach is used herein to predict the CBR values. The correlation coefficient is utilized as cost functions of the CSO to identify the optimal activation weights of the ELM. The statistical measures are separately considered, and best solutions are reported in this article. Comparisons are provided with the standard ELM to show the superiorities of the proposed integrated approach to predict the CBR values. Further, the impact of each input variable is studied separately, and reduced models are proposed with limited and inadequate input data without loss of prediction accuracy. When 70% training and 30% testing data are applied, the ELM-CSO outperforms the CSO with Pearson correlation coefficient (R), coefficient of determination (R²), and root mean square error (RMSE) values of 0.98, 0.97, and 0.84, respectively. Therefore, based on the prediction findings, the newly built ELM-CSO can be considered an alternative method for predicting real-time engineering issues, including the lateritic soil properties.

This study investigates the crack propagation behavior of asphalt materials through the use of damage models using the principles of the disturbed state concept (DSC). Traction–separation crack response, crack initiation, and evolution behavior are investigated by modeling pavement systems consisting of a hot mix asphalt (HMA) overlay on an existing HMA layer and subjected to wheel loading. Pre-existing cracks located within the existing asphalt material are also considered. The extended finite-element method (XFEM) was employed to model mesh-independent cracking. The finite-element model was validated by comparing the results to indirect tensile and direct tensile laboratory testing on asphalt samples. The validated model was then used to examine crack propagation in the pavement system with and without pre-existing cracks.

Hot-mix asphalt (HMA) is a composite material consisting of stone-aggregates, sand, asphalt binder and additives. The properties of this combined material are dependent on the volumetric parameters used in the mix design. This study investigates the effects of volumetric mix factors on the dynamic moduli (E*) of eleven categories of HMAs. For each category of asphalt mixture, the variations in dynamic modulus for different contractors, binder types, effective binder content (V_be), air void (V_a), voids-in-mineral aggregates (VMA), voids-filled-with asphalt (VFA) and asphalt content (AC) are assessed statistically. Results show that the S(100) mixture (nominal size of 19 mm, 100 gyrations) with the Performance Grade (PG) binder of PG 64-22 has the highest value of E* at low temperature or high reduced frequency. At high temperature or lower reduced frequency, S(100) PG 76-28 has the highest E* value. The SX(75) mixture (nominal size of 12.5 mm, 75 gyrations) with the binder of PG 64-28 has the lowest E* value at high temperature or lower reduced frequency. At low temperature or high reduced frequency, SX(75) PG 58-34 has the lowest E* value. The Stone Mix Asphalt (SMA) mix has a lower E* compared to S(100) and SX(100) mixes ((nominal size of 12.5 mm, 100 gyrations) with the Performance Grade (PG) binder of) at low temperature. The E* increases with an increase in V_be, V_a, and VFA, and decreases with an increase in VMA and AC. The E* of a mix can vary from 200 ksi (1380 MPa) to about 1000 ksi (6900 MPa) for a particular frequency (10 Hz) and temperature (21.1 °C), even if samples are from the same contractor.

In the design of pavement infrastructure, the flow number is used to determine the suitability of a hot-mix asphalt mixture (HMA) to resist permanent deformation when used in flexible pavement. This study investigates the sensitivity of the flow numbers to the mix factors of eleven categories of HMAs used in flexible pavements. A total of 105 specimens were studied for these eleven categories of HMAs. For each category of asphalt mixture, the variations in flow number for different contractors, binder types, effective binder contents, air voids, voids in mineral aggregates, voids filled with asphalt, and asphalt contents were assessed statistically. The results show that the flow numbers for different types of HMA used in Colorado vary from 47 to 2272. The same mix may have statistically different flow numbers, regardless of the contractor. The flow number increases with increasing effective binder content, air voids, voids in mineral aggregates, voids filled with asphalt, and asphalt content in the study range of these parameters.

Open graded friction course (OGFC) is used to reduce noise, improve friction, and for faster drainage of surface water of an asphalt pavement. However, OGFC’s contribution to low-temperature transverse cracking has not been documented yet in literature. This study investigates whether OGFC affects the low-temperature transverse cracking performance of asphalt concrete (AC). Cylindrical samples were prepared in the laboratory using an OGFC mix and a conventional AC mix in New Mexico. Laboratory tests, examining dynamic modulus ($E^{*}$ ), indirect tensile strength (ITS), coefficient of thermal contraction (CTC), and creep compliance, were conducted. Low-temperature transverse cracking potentials of both OGFC and AC were evaluated using the test data. Results show that OGFC has less $E^{*}$ and CTC, higher ductility and creep compliance than the AC mix. This means that OGFC is less susceptible to low-temperature transverse cracking compared to the AC mix. This finding is validated using the field survey data. It is found that OGFC prevents the low-temperature transverse crack growth in asphalt pavement. Therefore, OGFC can be considered a good potential material to resist low-temperature transverse cracking, especially in cold regions.

Past studies have determined the effects of the pavement mechanistic-empirical (ME) default (Level 3) values of vehicle class distribution (VCD) and axle load spectra (ALS) on pavement performance. However, it is still not clear how the clustered VCD and ALS affect the ME predicted pavement performance. In this study, traffic data from 10 weigh-in-motion (WIM) stations were gathered and analyzed to develop the VCD and ALS values using arithmetic average and clustering methods (Level 2). Next, using Level 2, Level 3, and site-specific (Level 1) inputs of VCD and ALS, the pavement ME predicted performance was determined. The results show that the predicted performance by the cluster (Level 2) data are very close to those of the site-specific data (Level 1). Performance generated by the ME default values (Level 3) are significantly different from those generated by the site-specific or cluster values. When comparing the performance of the ME design default (Level 3) with those of the statewide averag...