Download or read book Improving the Sustainability of Asphalt Pavements Through Developing a Predictive Model with Fundamental Material Properties written by Rashid Kamel Abu Al-Rub and published by . This book was released on 2009 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study presents the numerical implementation and validation of general constitutive relationships for describing the nonlinear behavior of asphalt concrete mixes. These constitutive relationships incorporate nonlinear viscoelasticity and viscoplasticity to predict the recoverable and irrecoverable responses, respectively. The nonlinear viscoelastic deformation is modeled using Schapery's model; while the irrecoverable component is represented using Perzyna's viscoplasticity theory with an extended Drucker-Prager yield surface and plastic potential that is modified to capture the distinction between the compressive and extension behavior of asphalt mixes. The nonlinear viscoelastic and viscoplastic model is represented in a numerical formulation and implemented in a finite element (FE) code using a recursive-iterative algorithm for nonlinear viscoelasticity and the radial return algorithm for viscoplasticity. Then, the model is used to analyze the nonlinear viscoelastic and viscoplastic behavior of asphalt mixtures subjected to single creep recovery tests at different stress levels and temperatures. This experimental analysis includes the separation of the viscoelastic and viscoplastic strain components. Based on this separation, a systematic procedure is presented for the identification of the material parameters associated with the nonlinear viscoelastic and viscoplastic constitutive equations. Finally, the model is applied and verified against a set of creep-recovery tests on hot mix asphalt at different stress levels and temperatures.

Download or read book Advances in Materials and Pavement Prediction written by Eyad Masad and published by CRC Press. This book was released on 2018-07-16 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Materials and Pavement Performance Prediction contains the papers presented at the International Conference on Advances in Materials and Pavement Performance Prediction (AM3P, Doha, Qatar, 16- 18 April 2018). There has been an increasing emphasis internationally in the design and construction of sustainable pavement systems. Advances in Materials and Pavement Prediction reflects this development highlighting various approaches to predict pavement performance. The contributions discuss links and interactions between material characterization methods, empirical predictions, mechanistic modeling, and statistically-sound calibration and validation methods. There is also emphasis on comparisons between modeling results and observed performance. The topics of the book include (but are not limited to): • Experimental laboratory material characterization • Field measurements and in situ material characterization • Constitutive modeling and simulation • Innovative pavement materials and interface systems • Non-destructive measurement techniques • Surface characterization, tire-surface interaction, pavement noise • Pavement rehabilitation • Case studies Advances in Materials and Pavement Performance Prediction will be of interest to academics and engineers involved in pavement engineering.

Download or read book Green and Intelligent Technologies for Sustainable and Smart Asphalt Pavements written by Xueyan Liu and published by CRC Press. This book was released on 2021-11-25 with total page 1727 pages. Available in PDF, EPUB and Kindle. Book excerpt: Green and Intelligent Technologies for Sustainable and Smart Asphalt Pavements contains 124 papers from 14 different countries which were presented at the 5th International Symposium on Frontiers of Road and Airport Engineering (IFRAE 2021, Delft, the Netherlands, 12-14 July 2021). The contributions focus on research in the areas of "Circular, Sustainable and Smart Airport and Highway Pavement" and collects the state-of-the-art and state-of-practice areas of long-life and circular materials for sustainable, cost-effective smart airport and highway pavement design and construction. The main areas covered by the book include: • Green and sustainable pavement materials • Recycling technology • Warm & cold mix asphalt materials • Functional pavement design • Self-healing pavement materials • Eco-efficiency pavement materials • Pavement preservation, maintenance and rehabilitation • Smart pavement materials and structures • Safety technology for smart roads • Pavement monitoring and big data analysis • Role of transportation engineering in future pavements Green and Intelligent Technologies for Sustainable and Smart Asphalt Pavements aims at researchers, practitioners, and administrators interested in new materials and innovative technologies for achieving sustainable and renewable pavement materials and design methods, and for those involved or working in the broader field of pavement engineering.

Download or read book Strategies for Improving the Sustainability of Asphalt Pavements written by United States. Federal Highway Administration. Office of Asset Management, Pavements and Construction and published by . This book was released on 2016 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Tech Brief summarizes guidance to the pavement community on sustainability considerations for asphalt pavement systems, as presented in greater detail in the recently published Towards Sustainable Pavement Systems: A Reference Document (FHWA 2015b). Sustainability considerations throughout the entire pavement life cycle are examined (from material extraction and processing through the design, construction, use, maintenance/rehabilitation, and end-of-life phases) and the importance of recognizing context sensitivity and assessing trade-offs in developing sustainable solutions is emphasized. This Tech Brief focuses exclusively on sustainability considerations associated with asphalt-surfaced pavement structures and the materials used in their construction. For the purposes of this document, all permanent surfaces constructed with asphalt concrete are generically referred to as 'asphalt' pavements. The primary audience for this document is practitioners doing work within and for government transportation agencies, and it is intended for designers, maintenance, material and construction engineers, inspectors, and planners who are responsible for the design, construction and preservation of the nation's highway network.

Download or read book MODELING OF ASPHALT CONCRETE written by Y. Richard Kim and published by McGraw Hill Professional. This book was released on 2007-09-22 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Expert Guide to Developing More-Durable and Cost-Effective Asphalt Pavements Written by distinguished experts from countries around the world, Modeling of Asphalt Concrete presents in-depth coverage of the current materials, methods, and models used for asphalt pavements. Included is state-of-the-art information on fundamental material properties and mechanisms affecting the performance of asphalt concrete, new rheological testing and analysis techniques, constitutive models, and performance prediction methodologies for asphalt concrete and asphalt pavements. Emphasis is placed on the modeling of asphalt mixes for specific geographic/climatic requirements. In light of America's crumbling infrastructure and our heavy usage of asphalt as a paving material, this timely reference is essential for the development of more-durable and cost-effective asphalt materials for both new construction and rehabilitation. Harness the Latest Breakthroughs in Asphalt Concrete Technology: • Asphalt Rheology • Constitutive Models • Stiffness Characterization • Models for Low-Temperature Cracking • Models for Fatigue Cracking and Moisture Damage • Models for Rutting and Aging

Download or read book Recent Developments in Pavement Design Modeling and Performance written by Sherif El-Badawy and published by Springer. This book was released on 2018-10-30 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume includes a collection of research and practical papers from an international research and technology activities on recent developments in pavement design, modeling and performance, and effects on infrastructure, green energy, technology and integration. Sustainability is increasingly a key priority in engineering practices. With the aging transportation infrastructure and renewed emphasis on infrastructure renovation by transportation agencies, innovations are urgently needed to develop materials, designs, and practices to ensure the sustainability of transportation infrastructure. The volume is based on the best contributions to the 2nd GeoMEast International Congress and Exhibition on Sustainable Civil Infrastructures, Egypt 2018 – The official international congress of the Soil-Structure Interaction Group in Egypt (SSIGE).

Download or read book Advances in Materials and Pavement Performance Prediction II written by K. Anupam and published by CRC Press. This book was released on 2020-12-08 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inspired from the legacy of the previous four 3DFEM conferences held in Delft and Athens as well as the successful 2018 AM3P conference held in Doha, the 2020 AM3P conference continues the pavement mechanics theme including pavement models, experimental methods to estimate model parameters, and their implementation in predicting pavement performance. The AM3P conference is organized by the Standing International Advisory Committee (SIAC), at the time of this publication chaired by Professors Tom Scarpas, Eyad Masad, and Amit Bhasin. Advances in Materials and Pavement Performance Prediction II includes over 111 papers presented at the 2020 AM3P Conference. The technical topics covered include: - rigid pavements - pavement geotechnics - statistical and data tools in pavement engineering - pavement structures - asphalt mixtures - asphalt binders The book will be invaluable to academics and engineers involved or interested in pavement engineering, pavement models, experimental methods to estimate model parameters, and their implementation in predicting pavement performance.

Download or read book Advancement in the Design and Performance of Sustainable Asphalt Pavements written by Louay Mohammad and published by Springer. This book was released on 2017-07-11 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume on “Advancement in the Design and Performance of Sustainable Asphalt Pavements” includes a collection of research and practical papers from an international research and technology activities on Mixture Design Innovation, Structural Pavement Design, Advancement in Production and Construction, Climate Changes and Effects on Infrastructure, Green Energy, Technology and Integration. The volume constitutes an important contribution in view of the urgent need to develop materials, designs, and practices to ensure the sustainability of transportation infrastructure. This volume is part of the proceedings of the 1st GeoMEast International Congress and Exhibition on Sustainable Civil Infrastructures, Egypt 2017.

Download or read book Development Assessment and Modeling of an Anti Icing Asphalt Pavement written by Yan Zhang and published by . This book was released on 2021 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asphalt pavement incorporating salt-storage additive (APSSA) is a type of effective anti-icing pavement used for winter road safety and mobility in cold regions. However, some limitations of conventional APSSA have been identified and are impeding its wider acceptance, including low anti-icing capacity, low anti-icing effectiveness, short anti-icing longevity, and reduced engineering properties of asphalt pavement. The research develops a novel type of functional additives for anti-icing asphalt pavement, to improve the anti-icing capacity and effectiveness and extend the anti-icing longevity. A hypothesis is proposed that the microporous surface structure of the additives could benefit the engineering properties through the interaction between asphalt binder and the salt-encapsulating material - epoxy resin. In addition, the customized design aimed to achieve a performance balance among anti-icing effectiveness and engineering properties. The laboratory study revealed that an asphalt pavement with 5.1% functional additives (by weight of asphalt mixture) features an excellent anti-icing capacity, low-temperature anti-icing effectiveness, and superior anti-icing longevity. Meanwhile, this pavement presents enhanced resistance to rutting, fatigue cracking, and thermal cracking, relative to its conventional asphalt pavement counterpart. The incorporation of 5.1 wt% functional additives showed limited effects on the moisture susceptibility of asphalt mixture, whereas the incorporation of 15.1 wt% functional additives increased the moisture susceptibility and this risk could be compensated by nanomodification of the binder (4 wt% montmorillonite nanoclay). Scanning electron microscopy analysis (SEM), Fourier transform infrared spectrometry (FTIR) analysis, and differential scanning calorimetry (DSC) were employed to shed light on why the pavement has a superior anti-icing longevity and improved engineering properties and durability performances.This work also pioneers a numerical simulation to predict the anti-icing longevity of a thin overlay of APSSA under a comprehensive consideration of influential factors (using an Interstate highway near Pullman, WA as case study). The COMSOL Multiphysics software (a Finite Element Method software) was employed to develop the predictive model, based on some parameters obtained from laboratory experiments, data from literature, and some assumptions. The model serves to provide a fundamental understanding of water and chloride transport in the pavement, enabling an estimation of its "effective anti-icing life" under the given service environment.

Download or read book C Characterization Model for Design of Asphalt Mixtures and Asphalt Pavements written by SA. Tan and published by . This book was released on 2006 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper reports the results of a research effort initiated in the early 1990s to develop a C-? (cohesion-angle of friction) characterization model for the design of asphalt mixtures and asphalt pavements. It is demonstrated that, since the model is based on the fundamental material properties represented by C and ?, it can derive analytically other asphalt mix design parameters such as Marshall stability and flow, and indirect tensile strength. The C-? characterization model therefore offers a useful basis for the development of a comprehensive design framework that integrates asphalt mix design with asphalt pavement structural design. To demonstrate this capability, the research developed an empirical-mechanistic rutting prediction model of asphalt pavement layer using the C-? characterization model. In addition, the model allows stresses and strains under design loading to be computed, which can be applied as input to structural analysis for asphalt material selection and pavement thickness design.

Download or read book Asphalt Material Design Inputs for Use with the Mechanistic empirical Pavement Design Guide in Virginia written by Alex K. Apeagyei and published by . This book was released on 2011 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Guide for the Mechanistic-Empirical Design of New & Rehabilitated Pavement Structures (MEPDG), developed under NCHRP Project 1-37A and recently adopted by the American Association of State Highway and Transportation Officials (AASHTO), offers an improved methodology for pavement design and evaluation. To achieve this improved prediction capability, the MEPDG procedure requires fundamental material properties in addition to certain empirically determined binder and mixture properties as design inputs. One of the key tasks identified by the Virginia Department of Transportation's (VDOT) Asphalt Concrete MEPDG Committee was the laboratory characterization of asphalt mixtures commonly used in Virginia to generate a catalog of the MEPDG-required design inputs. The purpose of this study was to evaluate, compile, and present asphalt material properties in a format that could be readily used in the MEPDG software and to develop a comprehensive catalog of MEPDG design input parameters for pavement design in Virginia. To achieve this objective, 18 asphalt concrete mixtures, sampled from seven of the nine VDOT districts, were tested using a battery of MEPDG-required tests including dynamic modulus (E*), flow number (FN), creep compliance, tensile strength, and beam fatigue tests. Testing involving binder and volumetric properties of the mixtures was also conducted. Finally, rut tests using the asphalt pavement analyzer (APA), a standard VDOT test protocol, were conducted to enable a direct comparison of the APA and FN test results. On the basis of these tests, suggestions for additional studies were made. The results of the study were presented in a form matching the MEPDG input format, and a catalog of design input parameters was developed for the 18 asphalt concrete mixtures. Included in the catalog were binder stiffness, mixture E*, mixture gradation, and mixture volumetric properties that would enable a designer the flexibility to select the desired input level (1, 2, or 3) depending on the pavement type. An illustrative example of how the developed inputs could be implemented using the MEPDG software was also provided. The results showed that E* master curves of asphalt mixtures obtained using the five standard testing temperatures described in AASHTO TP 62 could be obtained by testing at only three temperatures, which could result in a substantial reduction of testing time. The results also showed that the FN test was a sensitive test for evaluating rutting susceptibility of asphalt mixtures in the laboratory. The FN test was found to be sensitive to binder stiffness, mixture stiffness, mixture volumetric properties, aggregate gradation, and amount of recycled asphalt pavement (RAP) for the mixtures considered in this study. The study recommends that the catalog of input data for typical asphalt mixtures developed in this study be considered for pavement design in Virginia. The data followed expected trends and compared quite well with those reported in previous studies. Further studies should be conducted to evaluate the FN test as an additional tool for evaluating rutting in asphalt mixtures. Mixtures containing higher amounts of RAP (>20%) exhibited comparatively lower rutting resistance than those with 20% or less RAP. This phenomenon was unexpected since it is generally believed that adding more RAP should result in stiffer and hence more rut-resistant mixtures. Additional research should be conducted to investigate this phenomenon further.

Download or read book In situ Evaluation of Asphalt Pavement Modulus with Embedded Wireless Sensors written by Cheng Zhang and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The in-situ dynamic modulus properties of asphalt mixture play a significant role in assessing pavement mechanical responses under traffic loading, determining the pavement performance and condition, and making optimized maintenance decisions. Several methods, such as the falling weight deflectometer (FWD), have been utilized as a non-destructive test to back-calculate the in-situ pavement modulus and conditions; however, the FWD test can only be performed periodically and has the disadvantage of disturbing traffic due to lane-closure needs. With the recent advancement in data science and sensing technologies, the application of micro-electromechanical system (MEMS) sensors and machine learning techniques in pavement nondestructive tests has attracted more research attention. This research aims to develop an in-situ evaluation system that can automatically collect, process, and interpret data to determine the in-situ dynamic modulus of the asphalt mixture under traffic loads using embedded wireless sensors and machine learning techniques. The proposed system is a self-adaptive process and can predict in-situ dynamic modulus based only on mechanical responses and environmental conditions. Ultimately, the well-trained predictive model can be integrated into the pavement management system for the automated and cost-effective assessment of pavement conditions, facilitating informed decision-making. The research program encompasses three types of dynamic modulus experiments: laboratory uniaxial dynamic modulus tests, the one-third scale model mobile load simulator (MMLS3) tests, and in-situ dynamic modulus tests. Particle-size wireless sensors, SmartKli sensors, were implemented in the laboratory specimens and the pavements to collect data from sine wave loads and moving loads. Finite element models (FEM) were also developed and calibrated to generate pavement mechanical response data for more pavement types. The collected data and the FEM simulations were integrated into a database for a proposed adaptive data processing procedure. In addition, because the data collected by embedded sensors in infrastructure health monitoring are inevitably contaminated with noise, and the data features have a distinct discrepancy in different types of tests, a secondary objective of this research is to propose a data processing method capable of removing noises, recognizing data feature discrepancies, and extracting hidden features. An adaptive data processing procedure was developed by combining an empirical mode decomposition (EMD) method and an intrinsic mode function (IMF) selection processing to enhance the reliability of the pavement dynamic modulus prediction. Different EMD techniques were applied to decompose signals from wireless sensors embedded in the pavements. The maximum normalized cross-correlation (MNCC) and signal noise ratio (SNR) were selected as indices in the K-means classification to select the effective IMFs. The results indicated that ensemble EMD (EEMD) and multivariant EMD (MEMD) methods can extract more information from the mechanical responses and extend data dimensions. The EEMD method gives the lowest mean relative error (MRE). Therefore, the EEMD method was recommended for infrastructure data processing. The K-means method can adaptively select the effective IMFs based on the MNCC and SNR. Finally, three dynamic modulus predictive models were developed for different situations. An artificial neural network (ANN) model was developed based on the laboratory test data. This model verified that the ANN model can predict in-situ dynamic modulus. The second dynamic modulus predictive model was developed using the ensemble ANN model to improve the stability of the ANN model, which was trained and tested by the data collected from the MMLS3 test. The third model was developed to predict the dynamic modulus of various asphalt mixtures by fusing a transfer learning approach and Transformer architecture. Besides, the training database was extended with the FEM simulations. The results indicated that the ensemble ANN model is feasible and robust in predicting the dynamic modulus of the asphalt mixture in the MMLS3 test. The transfer learning model is reasonable and robust in predicting the in-situ dynamic modulus of the asphalt pavement.

Download or read book Incorporating Sustainable Practices in Asphalt Industry written by Mohammadsoroush Tafazzoli and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shrink of nonrenewable natural resources and the pollution generated by many manufacturing industries have initiated a global determination for pushing the industry toward more sustainable products. Asphalt as the principal element of almost any street and highway pavement is integral in transportation development, which, in turn, is pivotal for sustainable development. On the other hand, the material consumption and pollution generated in the asphalt industry pose significant threats to the environment and, therefore, to sustainability. This chapter reflects some of the sustainability concerns of the asphalt industry and discusses some of the possible solutions to mitigate them. The sustainability considerations are categorized into four phases of asphalt life cycle namely: (1) extraction of materials, (2) processing of raw materials, (3) transportation of asphalt raw materials and products, and (4) reusing and recycling at the end of a pavement,Äôs life. In each phase, best practices to improve and maintain the sustainability of asphalt pavements are discussed. This chapter also discusses sustainable approaches and technologies in the asphalt industry such as warm mixes, permeable asphalt pavements as well as the potentials for improving the mechanical properties of asphalt pavements particularly in terms of resisting heavy load traffic, clogging, and freeze-thaw.

Download or read book Analysis of the Mechanistic empirical Pavement Design Guide Performance Predictions written by Stacey D. Diefenderfer and published by . This book was released on 2010 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures (MEPDG) is an improved methodology for pavement design and the evaluation of paving materials. The Virginia Department of Transportation (VDOT) is expecting to transition to using the MEPDG methodology in the near future. The purpose of this research was to support this implementation effort. A catalog of mixture properties from 11 asphalt mixtures (3 surface mixtures, 4 intermediate mixtures, and 4 base mixtures) was compiled along with the associated asphalt binder properties to provide input values. The predicted fatigue and rutting distresses were used to evaluate the sensitivity of the MEPDG software to differences in the mixture properties and to assess the future needs for implementation of the MEPDG. Two pavement sections were modeled: one on a primary roadway and one on an interstate roadway. The MEPDG was used with the default calibration factors. Pavement distress data were compiled for the interstate and primary route corresponding to the modeled sections and were compared to the MEPDG-predicted distresses. Predicted distress quantities for fatigue cracking and rutting were compared to the calculated distress model predictive errors to determine if there were significant differences between material property input levels. There were differences between all rutting and fatigue predictions using Level 1, 2, and 3 asphalt material inputs, although not statistically significant. Various combinations of Level 3 inputs showed expected trends in rutting predictions when increased binder grades were used, but the differences were not statistically significant when the calibration model error was considered. Pavement condition data indicated that fatigue distress predictions were approximately comparable to the pavement condition data for the interstate pavement structure, but fatigue was over-predicted for the primary route structure. Fatigue model predictive errors were greater than the distress predictions for all predictions. Based on the findings of this study, further refinement or calibration of the predictive models is necessary before the benefits associated with their use can be realized. A local calibration process should be performed to provide calibration and verification of the predictive models so that they may accurately predict the conditions of Virginia roadways. Until then, implementation using Level 3 inputs is recommended. If the models are modified, additional evaluation will be necessary to determine if the other recommendations of this study are impacted. Further studies should be performed using Level 1 and Level 2 input properties of additional asphalt mixtures to validate the trends seen in the Level 3 input predictions and isolate the effects of binder grade changes on the predicted distresses. Further, additional asphalt mixture and binder properties should be collected to populate fully a catalog for VDOT's future implementation use. The implementation of these recommendations and use of the MEPDG are expected to provide VDOT with a more efficient and effective means for pavement design and analysis. The use of optimal pavement designs will provide economic benefits in terms of initial construction and lifetime maintenance costs.

Download or read book DATA DRIVEN MODELING OF IN SERVICE PERFORMANCE OF FLEXIBLE PAVEMENTS USING LIFE CYCLE INFORMATION written by Arash Mohammad Hosseini and published by . This book was released on 2019 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current pavement performance prediction models are based on the parameters such as climate, traffic, environment, material properties, etc. while all these factors are playing important roles in the performance of pavements, the quality of construction and production are also as important as the other factors. The designed properties of Hot Mix Asphalt (HMA) pavements, known as flexible pavements, are subjected to change during production and construction stages. Therefore, most of the times the final product is not the exact reflection of the design. In almost any highway project, these changes are common and likely to occur from different sources, by various causes, and at any stage. These changes often have considerable impacts on the long-term performance of a project. The uncertainty of the traffic and environmental factors, as well as the variability of material properties and pavement structural systems, are obstacles for precise prediction of pavement performance. Therefore, it is essential to adopt a hybrid approach in pavement performance prediction and design; in which deterministic values work along with stochastic ones. Despite the advancement of technology, it is natural to observe variability during the production and construction stages of flexible pavements. Quality control programs are trying to minimize and control these variations and keep them at the desired levels. Utilizing the information gathered at the production and construction stages is beneficial for managers and researchers. This information enables performing analysis and investigations of pavements based on the as-produced and as-constructed values, rather than focusing on design values. This study describes a geo-relational framework to connect the pavement life-cycle information. This framework allows more intelligent and data-driven decisions for the pavements. The constructed geo-relational database can pave the way for artificial intelligence tools to help both researchers and practitioners having more accurate pavement design, quality control programs, and maintenance activities. This study utilizes data collected as part of quality control programs to develop more accurate deterioration and performance models. This data is not only providing the true perspective of actual measurements from different pavement properties but also answers how they are distributed over the length of the pavement. This study develops and utilizes different distribution functions of pavement properties and incorporate them into the general performance prediction models. These prediction models consist of different elements that are working together to produce an accurate and detailed prediction of performance. The model predicts occurrence and intensity of four common flexible pavement distresses; such as rutting, alligator, longitudinal and transverse cracking along with the total deterioration rate at different ages and locations of pavement based on material properties, traffic, and climate of a given highway. The uniqueness of the suggested models compared to the conventional pavement models in the literature is that; it carries out a multiscale and multiphysics approach which is believed to be essential for analyzing a complex system such as flexible pavements. This approach encompasses the discretization of the system into subsystems to employ the proper computational tools required to treat them. This approach is suitable for problems with a wide range of spatial and temporal scales as well as a wide variety of different coupled physical phenomena such as pavements. Moreover, the suggested framework in this study relies on using stochastic and machine learning techniques in the analysis along with the conventional deterministic methods. In addition, this study utilizes mechanical testing to provide better insights into the behavior of the pavement. A series of performance tests are conducted on field core samples with a variety of different material properties at different ages. These tests allow connecting the lab test results with the field performance survey and the material, environmental and loading properties. Moreover, the mix volumetrics extracted from the cores assisted verifying the distribution function models. Finally, the deterioration of flexible pavements as a result of four different distresses is individually investigated and based on the findings; different models are suggested. Dividing the roadway into small sections allowed predicting finer resolution of performance. These models are proposed to assist the highway agencies s in their pavement management process and quality control programs. The resulting models showed a strong ability to predict field performance at any age during the pavements service life. The results of this study highlighted the benefits of highway agencies in adopting a geo-relational framework for their pavement network. This study provides information and guidance to evolve towards data-driven pavement life cycle management consisted of quality pre-construction, quality during construction, and deterioration post-construction.

Download or read book Development of a Prediction Model for Skid Resistance of Asphalt Pavements written by Arash Rezaei and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The skid resistance of asphalt pavement is a major characteristic that determines the driving safety on a road, especially under wet surface conditions. Skid resistance is primarily a function of the microtexture and macrotexture of a pavement surface. Microtexture is influenced by aggregate surface characteristics and is required to disrupt the continuity of surface water film and attain frictional resistance between the tire and the pavement surface. Macrotexture is affected mostly by mixture design or aggregate gradation and contributes to skid resistance by providing drainage paths of water that can be otherwise trapped between a tire and a pavement surface. The increase in macrotexture contributes to preventing hydroplaning and improving wet frictional resistance, particularly at high speeds. While much research has been conducted in the past to identify material factors that affect skid resistance, there is still a need to develop a model for predicting asphalt pavement skid resistance as a function of mixture characteristics and traffic level. The purpose of this study was to develop such a model based on extensive laboratory experiments and field measurements involving different mixture types and aggregate sources. The model incorporates functions that describe the resistance of aggregates to polishing and aggregate size distribution. The aggregate resistance to polishing was quantified by measuring aggregate texture using the Aggregate Imaging System (AIMS) before and after polishing in the Micro-Deval device. The analysis in this dissertation demonstrates how this model can be used to design mixtures and classify aggregates that provide desirable skid resistance levels.

Download or read book Modeling and Design of Flexible Pavements and Materials written by Dallas N. Little and published by Springer. This book was released on 2018-05-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook lays out the state of the art for modeling of asphalt concrete as the major structural component of flexible pavements. The text adopts a pedagogy in which a scientific approach, based on materials science and continuum mechanics, predicts the performance of any configuration of flexible roadways subjected to cyclic loadings. The authors incorporate state-of the-art computational mechanics to predict the evolution of material properties, stresses and strains, and roadway deterioration. Designed specifically for both students and practitioners, the book presents fundamentally complex concepts in a clear and concise way that aids the roadway design community to assimilate the tools for designing sustainable roadways using both traditional and innovative technologies.