Smart airport pavement instrumentation and health monitoring

Realistic characterization of pavement layer properties and responses under in-situ field conditions is critical for accurate airport pavement life predictions, planning pavement management activities as well as for calibration and validation of mechanistic-based pavement response prediction models. The recent advancements in Micro-Electro-Mechanical Sensor (MEMS)/Nano-Electro-Mechanical Sensor (NEMS) technologies and wireless sensor networks combined with efficient energy scavenging paradigms provide opportunities for long-term, continuous, real-time response measurement and health monitoring of transportation infrastructure systems. This paper presents a summary review of some recent studies that have focused on the development of advanced smart sensing and monitoring systems for highway pavement system with potential applications for long-term airport pavement health monitoring. Some examples of these potential applications include: the use of wireless Radio-Frequency Identification (RFID) tags for determining thermal gradients in pavement layers; self-powered MEMS/NEMS multifunction sensor system capable of real-time, remote monitoring of localized strain, temperature and moisture content in airport pavement that will eventually prevent catastrophic failures such as blow-ups on runways during heat waves

Heated Transportation Infrastructure Systems: Existing ande Emerging Technologies

Ice and snow on pavement surfaces cost the U.S. national economy in snow removal, damaged pavement and lost man-hours due to travel delay. Common practices for removing ice and snow from pavement surfaces include spraying anti-ice chemicals on the ground and deploying snowplowing vehicles. These methods are labor-intensive, occasionally ineffective at extremely low temperatures and have associated environmental concerns with possible contamination of nearby water bodies. Heated pavement systems (i.e., the concept of supplying heat to the pavement through an external or internal source) melt snow and ice without the need for anti-ice chemicals and snowplowing vehicles. A vast majority of the existing heated pavement systems utilize electrical or geothermal (hydronic) heating technologies. The use of anti-icing coatings and mix designs to deter ice formation is a closely related, but distinct concept. The objective of this paper is to provide a comprehensive review of the current state of practice and research of existing heated transportation infrastructure systems (highway pavement, bridges and airport pavement) as well as provide an overview of the emerging technologies

Calibration of Pavement ME Design and Mechanistic-Empirical Pavement Design Guide Performance Prediction Models for Iowa Pavement Systems

The AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance models and the associated AASHTOWare® Pavement ME Design software are nationally calibrated using design inputs and distress data largely from the national Long-Term Pavement Performance (LTPP). Further calibration and validation studies are necessary for local highway agencies’ implementation by taking into account local materials, traffic information, and environmental conditions. This study aims to improve the accuracy of MEPDG/Pavement ME Design pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 70 sites from Iowa representing both jointed plain concrete pavements (JPCPs) and Hot Mix Asphalt (HMA) pavements were selected. The accuracy of the nationally calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified using both linear and nonlinear optimization approaches. Local calibration of the MEPDG performance prediction models seems to have improved the accuracy of JPCP performance predictions and HMA rutting predictions. A comparison of MEPDG predictions with those from Pavement ME Design was also performed to assess if the local calibration coefficients determined from MEPDG version 1.1 software are acceptable with the use of Pavement ME Design version 1.1 software, which has not been addressed before. Few differences are observed between Pavement ME Design and MEPDG predictions with nationally and locally calibrated models for: (1) faulting and transverse cracking predictions for JPCP, and (2) rutting, alligator cracking and smoothness predictions for HMA. With the use of locally calibrated JPCP smoothness (IRI) prediction model for Iowa conditions, the prediction differences between Pavement ME Design and MEPDG are reduced. Finally, recommendations are presented on the use of identified local calibration coefficients with MEPDG/Pavement ME Design for Iowa pavement systems

Sensitivity analysis of rigid pavement systems using the mechanistic-empirical design guide software

Initiatives are underway to implement the new mechanistic-empirical pavement design guide (MEPDG) in Iowa. This paper focuses on the sensitivity study of jointed plain concrete pavements (JPCP) and continuously reinforced concrete pavements (CRCP) in Iowa using the MEPDG software. In this comprehensive study, the effect of MEPDG input parameters on the rigid pavement performance is evaluated using the different versions of the MEPDG software (0.7, 0.9, and 1.0) available to date. Representative JPCP and CRCP sections in Iowa were selected for analysis. Based on the sensitivity plots obtained from the MEPDG runs, the design input parameters were categorized as being most sensitive, moderately sensitive, or least sensitive in terms of their relative effect on distresses. In this study, the curl/warp effective temperature difference, the PCC coefficient of thermal expansion, and PCC thermal conductivity had the greatest impact on the JPCP and CRCP distresses. Compared to the original version of MEPDG software (Version 0.7), the updated versions (Versions 0.9 and 1.0) are more sensitive to inputs, which shows the evolution of engineering reasonableness

Use of Pavement Management Information System for Verification of Mechanistic-Empirical Pavement Design Guide Performance Predictions

The performance models used in the Mechanistic-Empirical Pavement Design Guide (MEPDG) are nationally calibrated with design inputs and performance data obtained primarily from the national Long-Term Pavement Performance database. It is necessary to verify and calibrate MEPDG performance models for local highway agencies\u27 implementation by taking into account local materials, traffic information, and environmental conditions. This paper discusses the existing pavement management information system (PMIS) with respect to the MEPDG and the accuracy of the nationally calibrated MEPDG prediction models for Iowa highway conditions. All the available PMIS data for Interstate and primary road systems in Iowa were retrieved from the Iowa Department of Transportation (DOT) PMIS. The retrieved databases were then compared and evaluated with respect to the input requirements and outputs for Version 1.0 of the MEPDG software. Using Iowa DOT\u27s comprehensive PMIS database, researchers selected 16 types of pavement sections across Iowa (not used for national calibration in the NCHRP 1-37A study). A database of MEPDG inputs and the actual pavement performance measures for the selected pavement sites were prepared for verification. The accuracy of the MEPDG performance models for Iowa conditions was statistically evaluated. The verification testing showed promising results in terms of MEPDG\u27s performance prediction accuracy for Iowa conditions. Recalibrating the MEPDG performance models for Iowa conditions is recommended to improve the accuracy of pavement performance predictions

Greenhouse gas emission analysis for heated pavement system

Anthropogenic greenhouse gas (GHG) emissions have become significant environmental indicators in analyzing the comparative environmental impacts of conventional and newly developed alternative systems or techniques. Life Cycle Assessment (LCA) is considered an accepted and systematic methodology to calculate the amount of carbon released from all the processes of a system/technique, helping users select the best environmental-friendly alternative. The use of automated heating based snow removal systems is gaining attention as an alternative strategy to traditional ice and snow removal practices such as the use of anti-icing chemicals and snowplowing vehicles. Most previous studies on heated pavement systems have focused on their efficiency and economic evaluation, but few studies have investigated their environmental impacts in a systematic manner. Considering the energy consumptions associated with heated pavement systems, their environmental impacts should be assessed over the life cycle before they could be implemented in airport pavement applications. This study employs a partial LCA methodology to assess the GHG emissions from various operations of energy sources used in geothermal heated pavement systems and their environmental impacts in contrast with traditional snow removal operations, Detailed discussions are presented in the context of developing an environment assessment framework to help users select the most environmental-friendly snow removal system

Performance Evaluation of Roadway Subdrain Outlets in Iowa

The bearing capacity and service life of a pavement are adversely affected by the presence of undrained water in the pavement layers. In cold winter climates, such as in Iowa, this problem is magnified further by the risk of frost damage when water is present. Therefore, wellperforming subsurface drainage systems form an important aspect of pavement design by the Iowa Department of Transportation (DOT). However, there was a need to determine the impacts of not maintaining the subdrain outlets on pavement performance in Iowa in light of the recent Iowa DOT field maintenance staff reductions and budget cuts and the implications on subdrain outlet maintenance. Consequently, a research study was initiated to conduct a performance review of primary interstate pavement subdrains in Iowa and determine the cause of the problem if there were drains that were not functioning properly. Field investigations were conducted on 64 selected (jointed plain concrete pavement and hot-mix asphalt) pavement sites during the 2012 fall season. The study was mainly focused on the drainage outlet conditions. Findings and observations based on an extensive literature review and forensic testing are discussed in this paper. Gate and mesh screen-type rodent guards are not recommended for Iowa subdrainage systems because they tend to catalyze outlet blockage and end up potentially doing more harm (i.e., requiring more frequent maintenance) than good (i.e., protection against rodent intrusion)

Effects of moisture damage on asphalt mixtures

The reduction in the ability of bitumen to bond with the aggregate surface due to the infiltration of moisture has been recognised for years, and this deterioration phenomenon is called moisture damage. In general, the loss of bonding between bitumen and aggregate shortens the service life of the top layer of the pavement. Many investigations have been conducted to understand the mechanisms of moisture damage due to the loss of bonding strength between bitumen and aggregate and to find ways to improve and strengthen the bond to mitigate the effect of moisture. This paper reviews the extensive literature on the loss of bitumen-aggregate bonding strength due to moisture damage in asphalt mixtures. The general description of the theories and mechanisms that explain the effect of the thermodynamic, chemical, physical and mechanical characteristics of the bitumen and aggregate on the bonding phenomenon are discussed in this paper. In addition, the causes of and contributing factors to moisture damage and methods to improve the bond between bitumen and aggregates are also discussed. Moreover, a description of the test methods that can be used to evaluate moisture damage in poorly bonded and compacted mixtures are also presented. Special attention is given to a well-known method, known as the pull-off test, which has been successfully used to evaluate aggregate-binder bond strength, both for laboratory and in-situ tests. This includes the test methods, the factors that affect the bonding strength results and their correlation with other test method. A review of the failure mode of bitumen under the pull-off loading test is discussed in the final section of this paper

Investigation of AASHTOWare Pavement ME Design/DARWin-MEPerformance Prediction Models for Iowa Pavement Analysis and Design

The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models