About the research
Iowa has three classes of public roads: state primary highways, county (secondary) roads, and city streets. Among these, Iowa county roads serve rural Iowa transport needs by assuring a public road connection (i.e., to local access roads) for serving as conduits that channel the flow of people and commodities to and from towns and terminals (i.e., farm-to-market roads). Many Iowa county pavement systems are multilayered structures that have experienced multiple cycles of construction and renewal that make it more complex to estimate pavement structures’ current structural capacities.
This study developed a Microsoft Excel macro and Visual Basic for Applications (VBA)-based automated Pavement Structural Analysis Tool (PSAT) with three analyzing options—asphalt concrete (AC) pavement systems with 1 to 10 layers on a (1) stabilized base, (2) granular base, and (3) stabilized base and granular base—to estimate the current structural capacities of in-service pavement systems by following consecutive sections within the user-friendly platform. To address this aim, a systematic approach to develop a highly realistic annotated synthetic database was created for use in artificial neural network (ANN)-based pavement response prediction models that required inputs of pavement materials and structural features and outputs of pavement responses, deflections, and strains at critical locations within the pavement structure. In addition, the equivalent layer theory (ELT) concept was integrated into the PSAT to simplify multilayered pavement systems into three-layered systems—an asphalt layer, a base layer, and a subgrade layer. Thus, it could make it easier for an Iowa county engineer to understand the current structural capacities of in-service county pavements. Mechanistic- and empirical-based approaches were also integrated into the tool to estimate the remaining service life (RSL) associated with two types of major failures for flexible pavements, namely fatigue and rutting failures, by relating pavement responses predicted by the ANN models through transfer functions. The PSAT is expected to be used as part of routine pavement analysis, design, and asset management practices for better prioritization and allocation of resources, as well as to support effective communication related to pavement needs both with the public and with elected officials.