This paper presents the use of three dimensional (3D) finite element modeling (FEM) techniques to determine asphalt pavement response to loading. In mechanistic-empirical pavement design, the properties of materials used in pavement layers must be specified before the pavement response to imposed loads can be determined. A numerical method is used to obtain the relaxation modulus of linear viscoelastic materials, such as asphalt concrete, from the dynamic modulus measured on specimens procured from the field. Linear elastic behavior is assumed for granular materials. In addition, regarding finite element modeling, key factors such as model geometry, material properties, load and boundary conditions, element type, and mesh refinement are discussed in detail. The adopted Global-Local (GL) FEM approach is capable of simulating pavement responses to multiple axle loads with different load configurations, speed, and temperatures.

Rigid pavement structure typically consists of a surface layer (concrete), underlying granular layers (subbase and/or base), and a compacted subgrade soil layer. Because the subgrade is saturated during wet seasons, cyclic loading caused by heavy traffic may lead to pumping of fine particles from the subgrade into the granular layers, redistribution of materials underneath the slabs, and gradual ejection of materials through pavement joints. This phenomenon results in faulting and can be a major contributor to pavement failure in wet regions. The objective of this study was to simulate and quantify the migration of subgrade soil into the subbase at rigid pavement joints. The cyclic traffic loading was simulated on a geometrically scaled model of rigid interstate highway pavement using a one-third-scale model mobile load simulator (MMLS3), an accelerated pavement testing device. Nonplastic saturated silt and partially saturated aggregate subbase were used as subgrade and subbase layers, respectively. The results indicated a significant amount of fines migration into the subbase under repeated traffic loading. The subgrade soil migration in mass percentage increased with the simulated traffic loading cycles. More fines accumulated in the subbase beneath the approach slab than beneath the leave slab. Faulting was observed and is another indication of fine particles migration. The migration of subgrade soil into the subbase also varied with the depth in the subbase; more fines accumulated in the lower section (closer to the subgrade) than in the upper section of the subbase.

Over the decades, geogrids have been increasingly used in flexible pavements primarily for base reinforcement and subgrade improvement. Yet most of the existing methods for designing a geogrid-modified pavement are largely empirically based and limited to the type of geogrid products and certain conditions. With the recent release of the new pavement design program by AASHTO, DARWin-ME, the mechanistic-empirical (ME) approach is becoming a routine practice for pavement analysis and design. Recognizing that the ME concept provides a more rational and realistic methodology than a purely empirical approach, the study presented in this paper is aimed to characterize the permanent deformation of geogrid-modified soft soil subgrade by using the ME approach. Based on both experimental measurements and results of numerical modeling, ME models were adapted and customized to predict permanent deformation of geogrid-modified soft soil subgrade.

The exclusive effects of microsurfacing on thermal cracks were quantified in terms of IRI. In addition, vehicle operating costs related to the IRI were estimated. For the MnROAD project, using a measurement device with high resolution, pavement surfaces with thermal cracks were profiled before and after microsurfacing. The crack profiles were transferred into longitudinal profiles with no cracks so that the exclusive contribution of original and microsurfaced cracks to roughness could be analyzed. Then, vehicle operating costs corresponding to the exclusive roughness were evaluated. Applying the given amount of microsurfacing materials, the IRI resulting from cracks with 0.7 cm depth and 0.58 m width was reduced by about 80 percent for serviceable roughness levels. The IRI resulting from cracks with 1.5 cm depth and 0.61 m, and 1.8 cm depth and 0.80 m width were decreased by about 60 percent and about 45 percent, respectively. By examining vehicle operating costs, it was found that a small difference in crack severities results in a greater increase in cost. Therefore, it was concluded that prompt operation of microsurfacing for any crack severity levels is no less important than earlier operation for low severity cracks. In addition, it was concluded that microsurfacing can be a cost-effective maintenance technique for cracks for a year. If more than 3 cracks would be detected in the field, microsurfacing would be still a cost-effective maintenance method for any severity crack level.

Typically pavement structure is comprised of a surface layer (i.e., asphalt or concrete), underlying granular layers known as subbase and/or base, and a compacted subgrade soil layer. During wet seasons when the subgrade becomes saturated, cyclic loading caused by the moving traffic may result in pumping of fine particles from the subgrade up into the subbase. This presents a serious challenge to the pavement structure and may lead to failure of the pavement. The objective of this research is to investigate occurrence of migration of fine particles and to quantify the magnitude and rate of such migration. One-third scale model mobile load simulator (MMLS3), a type of accelerated pavement testing (APT) device, is utilized to simulate the cyclic traffic loading on scaled flexible pavement that simulates interstate highways. Kenlayer linear elastic program is used to determine the equivalent scaled pavement in the laboratory. The pavement section is constructed on a bed of non-plastic saturated silt as subgrade soil and partially saturated aggregate subbase. The lab testing reveals that under cyclic loading condition considerable amount of fine particles migrated into the subbase. The migrated soil in mass percentage increases with the simulated traffic loading cycles. The migration of subgrade soil into the subbase also varies with the depth in the subbase: more migration occurred in the lower section (closer to the subgrade) than in the upper section of the subbase.

One aspect of pavement management systems (PMS) that has begun to receive increased attention is that of data quality and variability. This paper provides recommendations for quantifying and controlling the variability of longitudinal profile data, and the resulting International Roughness Index (IRI) values. The recommendations were determined from an analysis of the profile data collected by the Long-Term Pavement Performance Program (LTPP). In particular, the effort was focused on developing quantifications of variability that could be useful and economical for network-level pavement management. In the first phase of the variability analysis, the effects of region and season were evaluated using the screened profile data, because the quality of data used in the analysis is crucial to the resulting statistical conclusions. The relationship between the standard deviation and the mean of repeated profile measurements was further modeled using raw profiles; these raw measurements are more relevant to the typical conditions of single-pass network-level data collection. The second phase of the variability analysis was concentrated on quantifying run-to-run variability, such as can be used for frequent checks on control sections and device acceptance, or for project-level data collection. It was found that a run-to-run d2s percent varies between 6 percent and 8 percent for asphalt concrete (AC) pavements and 6 percent and 9 percent for portland cement concrete (PCC) pavements. The final phase of the variability analysis was to develop measures of the variability between routine network-level profile visits to a site, thus enabling a level of cost-effective quality control. While high visit-to-visit variabilities were observed, these values may still be useful for flagging potential data collection problems. The values also indicate the need to use long-term trends for planning, as opposed to single measurements.