Impact of Wide-Base Tires on Pavements: A National Study

This paper summarizes a multi-year effort comparing the new-generation wide-base tires (NG-WBT) and dual-tire assembly from a holistic point of view. The tires were compared considering not only pavement damage but also environmental impact. Numerical modeling, prediction methods, experimental measurements, and life-cycle assessment were combined to provide recommendations about the use of NG-WBT. A finite element (FE) approach considering variables that are usually omitted in the conventional analysis of flexible pavement was used for modeling pavement structures combining layer thickness, material properties, tire load, tire-inflation pressure, and pavement type (interstate and low volume). A prediction tool, ICT-Wide, was developed based on an artificial neural network to obtain critical pavement responses in cases excluded from the FE analysis matrix. Based on the bottom-up fatigue cracking, permanent deformation, and international roughness index, the life-cycle energy consumption, cost, and green-house gas emissions were estimated. To make this research useful for state departments of transportation and practitioners, a modification to AASHTOware is proposed to account for NG-WBT. The revision is based on two adjustment factors, one accounting for the discrepancy between the AASHTOware approach and the FE model of this study, and the other addressing the impact of NG-WBT. Although greater pavement damage may result from NG-WBT, for the analyzed cases, the extra pavement damage may be outweighed by the environmental benefits when NG-WBT market penetration is considered

Use of soft computing and numerical analysis in design, analysis and management of pavement systems

There are a number of components of pavement engineering, including pavement management, pavement analysis and design, and pavement materials. Historically, the field of pavement management has been interested in monitoring post-construction condition, timing of preventive maintenance and rehabilitation treatments, and economic analysis of alternatives. On the other hand, the field of pavement analysis and design has dealt with optimizing pavement structure; with optimum structure, a pavement system is expected to survive during its service life for given traffic and climate conditions. The performance of pavement materials has been improved to achieve the long-lasting and lower-maintenance pavement systems. A data-driven comprehensive approach considering all aspects of pavement engineering together could be a future direction for advancing pavement engineering practices. In order to achieve a data-driven comprehensive approach considering all aspects of pavement engineering together as outlined above, a data-driven and efficient pavement design, analysis and management concept has been proposed in this study. To serve as elements of this concept, several models related to pavement structural response models, pavement performance prediction models, and pavement remaining service life (RSL) models have been developed. First, to enable faster three-dimensional finite element (3D-FE) computations of design stresses, artificial neural network (ANN)-based surrogate computational pavement structural response models were developed. These models produce an estimate of the top-down bending stress close to that computed by 3D-FE analysis in rigid airport pavements in a fraction of the time. Second, longitudinal cracking mechanisms of widened jointed plain concrete pavements (JPCP) were demonstrated and their longitudinal cracking potential was evaluated using numerical analysis. Third, the Federal Aviation Administration’s (FAA) current rigid airfield pavement design methodology has been evaluated in great detail to better identify research gaps and remaining needs with respect to cracking failure models so that recommendations could be made as to how current methodology could be improved to accommodate top-down and bottom-up cracking failure modes. Fourth, a detailed step-by-step methodology for the development of a framework for pavement performance and RSL prediction models was explained using real pavement performance data obtained from the Iowa Department of Transportation (DOT)’s Pavement Management Information System (PMIS) database

Development of Adjustment Factors for MEPDG Pavement Responses Utilizing Finite-Element Analysis

The Mechanistic-empirical pavement design guide (MEPDG) provides theoretically superior methodology, as compared with its predecessor, for the design and analysis of pavement structures. The mechanistic part refers to simulating pavement–tire interaction to calculate critical responses within pavement. The empirical part means prediction of pavement distress propagation over time using transfer functions that link a critical pavement response to a particular pavement distress. The mechanistic part of MEPDG simulates tire–pavement interaction in three steps: subdivision of pavement layers; complex modulus calculation at the middepth of each sublayer, considering velocity and temperature; and running the multilayered elastic theory (MLET) software, JULEA. Although MEDPG has a grounded methodology for pavement analysis, it has a number of limitations and unrealistic simplifications that result in inaccurate response predictions. These limitations are primarily related to the pavement analysis approach used in the MEPDG framework, MLET. By contrast, finite-element (FE) analysis has proven to be a promising numerical approach for overcoming these limitations and simulating pavement more accurately and realistically. Although comparison of MLET with FE analysis has been studied, the difference between FE and MEPDG simulations has not been quantified. This study fills that gap by developing linear equations that connect pavement responses produced by these two approaches to pavement analysis. The equations are developed for ten different pavement responses, using a total of 336 cases simulated using FE and MEPDG analyses. The cases modeled in simulations were selected to capture extreme conditions, i.e., thick and thin pavement structures with strong and weak material properties. The equations developed can help pavement researchers understand quantitatively the effect of MEPDG limitations. In addition, the equations may be used as adjustment factors for MEPDG to compute pavement responses more realistically without using computationally expensive approaches, such as FE analysis

Optimización del diseño estructural de pavimentos asfálticos para calles y carreteras

gráficos, tablasThe construction of asphalt pavements in streets and highways is an activity that requires optimizing the consumption of significant economic and natural resources. Pavement design optimization meets contradictory objectives according to the availability of resources and users’ needs. This dissertation explores the application of metaheuristics to optimize the design of asphalt pavements using an incremental design based on the prediction of damage and vehicle operating costs (VOC). The costs are proportional to energy and resource consumption and polluting emissions. The evolution of asphalt pavement design and metaheuristic optimization techniques on this topic were reviewed. Four computer programs were developed: (1) UNLEA, a program for the structural analysis of multilayer systems. (2) PSO-UNLEA, a program that uses particle swarm optimization metaheuristic (PSO) for the backcalculation of pavement moduli. (3) UNPAVE, an incremental pavement design program based on the equations of the North American MEPDG and includes the computation of vehicle operating costs based on IRI. (4) PSO-PAVE, a PSO program to search for thicknesses that optimize the design considering construction and vehicle operating costs. The case studies show that the backcalculation and structural design of pavements can be optimized by PSO considering restrictions in the thickness and the selection of materials. Future developments should reduce the computational cost and calibrate the pavement performance and VOC models. (Texto tomado de la fuente)La construcción de pavimentos asfálticos en calles y carreteras es una actividad que requiere la optimización del consumo de cuantiosos recursos económicos y naturales. La optimización del diseño de pavimentos atiende objetivos contradictorios de acuerdo con la disponibilidad de recursos y las necesidades de los usuarios. Este trabajo explora el empleo de metaheurísticas para optimizar el diseño de pavimentos asfálticos empleando el diseño incremental basado en la predicción del deterioro y los costos de operación vehicular (COV). Los costos son proporcionales al consumo energético y de recursos y las emisiones contaminantes. Se revisó la evolución del diseño de pavimentos asfálticos y el desarrollo de técnicas metaheurísticas de optimización en este tema. Se desarrollaron cuatro programas de computador: (1) UNLEA, programa para el análisis estructural de sistemas multicapa. (2) PSO-UNLEA, programa que emplea la metaheurística de optimización con enjambre de partículas (PSO) para el cálculo inverso de módulos de pavimentos. (3) UNPAVE, programa de diseño incremental de pavimentos basado en las ecuaciones de la MEPDG norteamericana, y el cálculo de costos de construcción y operación vehicular basados en el IRI. (4) PSO-PAVE, programa que emplea la PSO en la búsqueda de espesores que permitan optimizar el diseño considerando los costos de construcción y de operación vehicular. Los estudios de caso muestran que el cálculo inverso y el diseño estructural de pavimentos pueden optimizarse mediante PSO considerando restricciones en los espesores y la selección de materiales. Los desarrollos futuros deben enfocarse en reducir el costo computacional y calibrar los modelos de deterioro y COV.DoctoradoDoctor en Ingeniería - Ingeniería AutomáticaDiseño incremental de pavimentosEléctrica, Electrónica, Automatización Y Telecomunicacione

Predicting friction with improved texture characterization

Current methodologies to measure road friction present several disadvantages that make them impractical for field data collection over large highway networks. Thus, it is important to study different ways to estimate surface friction characteristics based on other properties that are easier to measure. The main objective of this study was to analyze surface texture characteristics and to observe their influence on friction. A Line Laser Scanner (LLS) was implemented to make an improved characterization of the road texture which includes macro- and micro-texture description using different texture parameters. Field measurements of friction and texture were collected around Texas using different tests methods. The friction characterization tests included the British Pendulum test (BPT), the Dynamic Friction test (DFT), and the Micro GripTester. Thirty-six different pavement sections were evaluated, including different surface types such as hot-mix asphalt (HMA), surface treatment, and concrete sidewalk. Among the principal conclusions, it was found that there is not a unique relationship between texture and friction. The relationship between texture and friction is strong but it is different for each type of surface, thus, cross-sectional analysis cannot be utilized to quantify the relationship. Additionally, the prediction of friction measures obtained using the BPT and the DFT significantly improved when including information of both macro- and micro-texture into the prediction model. Therefore, a measure of micro-texture should be included into friction models based on texture. Finally, among the study of different texture parameters, the mean profile depth (MPD) was the most significant parameter for macro- and for micro-texture to explain the distinct friction measures.Civil, Architectural, and Environmental Engineerin

Optimized Hot-Mix Asphalt Lift Configuration for Performance

R27-204Researchers conducted eight large-scale laboratory tests to assess the combined impact of hot-mix asphalt (HMA) overlay mix and thickness on its performance to control reflective cracking. Bonding efficiency, flexibility, and stiffness of the HMA mix as well as overlay thickness significantly affect an overlay\u2019s performance against reflective cracking. Researchers developed a generalized 3D finite-element model to predict an overlay\u2019s reflective cracking potential and generated a database of 128 cases. They also developed a data-driven surrogate model to predict reflective cracking potential that engineers can easily use. Life-cycle cost analysis of overlay alternatives was performed using Illinois Department of Transportation\u2019s unit prices from contracts between 2018 and 2019. The researchers identified optimal overlay configurations to control reflective cracking. An overlay composed of a 1.5 in (38.1 mm) SMA-9.5 or 1.25 in (31.8 mm) IL-9.5FG surface course and a 0.75 in (19.1 mm) IL-4.75 binder course had the lowest annual cost per mile among non-interstate projects. For interstate projects, an overlay composed of a 2 in (50.8 mm) SMA-12.5 surface course and a 2.25 in (57.2 mm) IL-19.0 binder course was the most cost-effective. The study concluded that to control reflective cracking and to reduce life-cycle cost, an overlay composed of an SMA-9.5 surface course and an IL-4.75 binder course is recommended for non-interstate projects. An IL-9.5FG surface course and an IL-4.75 binder course are suggested for low-volume and low-speed roads. For interstate projects, an overlay comprised of an SMA-12.5 surface course and an IL-19.0 binder course is recommended. A data-driven surrogate model may be used to design overlay thicknesses

Efficient response models for rigid airfield pavement systems design

The Federal Aviation Administration (FAA) has recognized that its current rigid pavement design model, reflecting a single slab loaded at one edge by a single aircraft landing gear, does not adequately account for top-down cracking, meaning that one of the major observed failure modes for rigid pavements is poorly accounted for in the rigid pavement design procedure FAA Rigid and Flexible Iterative Elastic Layer Design (FAARFIELD). To expand the FAARFIELD design model beyond the currently-used reduced one-slab model, since practical alternatives to running the 3D-FEM stress computation as client software are needed, this study seeks to fill this research gap by developing a surrogate computational response model or procedure (suitable for implementation in FAARFIELD 1.4-TDC) that returns a close estimate of the top-down bending stress computed by the 3D-FE model for combined vehicle and temperature loading of rigid airport pavements. A synthetic database has been generated by conducting batch runs of FAA finite-element analysis software (FEAFAA 2.0), and this database contains data from thousands of multiple-slab rigid pavement cases with associated critical tensile stresses at the slab top induced by either mechanical-only or combined mechanical and temperature loading, with critical responses that include tensile stresses in both x and y directions along with principal tensile stresses. Artificial neural networks (ANNs) have been employed to develop a surrogate top-down slab bending-stress prediction model using non-linear input-output mapping of the database. Surrogate response models were trained for each of the Airbus and Boeing aircraft provided in the FEAFAA 2.0 library. This has been accomplished by developing software for automating entry of the database obtained by conducting FEAFAA batch runs, to train the ANN models using different architectures and algorithms, to control the ANN input parameters, and to collect training results. Both accuracy and robustness of the models were validated through independent testing and sensitivity testing. A new ANN tool for rapid analysis of nine-slab rigid airfield pavements that replicates the top-down critical stresses obtained from direct finite element solutions was developed. In addition, a new airfield pavement design approach was proposed which employs Bayesian optimization along with the trained ANN models

Developing Tack Coat Specification for Long-Lasting Composite Pavement Performance

Pavements are constructed in multiple lifts to efficiently transfer traffic loads from the surface to the underlying layers. It is necessary to apply a tack coat material to ensure complete bonding during the construction of new pavements or rehabilitation processes. Otherwise, the pavement integrity may become compromised. The amount of tack coat and construction quality impact the pavement structure's performance and durability. The required quantity is influenced by factors such as the pavement surface type and condition, preparation of the layer, and appropriate construction practices. The bond strength between layers is also determined by the quality of tack coat and construction/application techniques employed.This research aimed to determine test methods and best practices to develop a specification for tack coat materials used in composite pavements, which can predict their performance in different environmental conditions, construction techniques, and pavement types. The focus was on tack coat properties related to bonding and durability.Establishing optimal tack coat specification thresholds required a comprehensive analysis of various rheological properties and an interlayer shear strength test. Rheological tests are fundamental in determining tack coat response to deformation and flow under different conditions. Additionally, interlayer shear strength tests evaluate the adhesive properties of the tack coat by measuring the required force to separate two pavement layers bonded with the tack coat. By correlating the results of rheological properties and interlayer shear strength test results, acceptable thresholds for bonding and durability performance were determined to improve the longevity of composite pavements.The commonly used parameters of penetration and softening point, for specifying tack coat materials, may not be sensitive enough to reflect the effects of polymer modification. However, the asphalt binder's high-temperature performance grading (PGH) proved to be a good alternative to evaluating tack coat bonding performance. The results suggest that using a tack coat material with a PGH equal to or higher than the binder used in asphalt concrete achieves comparable or better performance than the minimum laboratory-measured ISS of 40 psi required for satisfactory field-level tack coat efficiency based on past research.An aging index was estimated to assess the impact of aging on rheological properties of tack coat materials and make sure they will perform well throughout the pavement life. The results showed that all materials studied demonstrated good resistance to aging, with aging indexes below 4.0. This parameter was chosen based on a broader range of tack coat materials as part of the NCHRP Project 09-64