Past editions of the American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures have served well for several decades; nevertheless, many serious limitations e...Past editions of the American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures have served well for several decades; nevertheless, many serious limitations exist for their continued use as the nation's primary pavement design procedures. Researchers are now incorporating the latest advances in pavement design into the new Mechanistic-Empirical Pavement Design Guide (MEPDG), developed under the National Cooperative Highway Research Program (NCHRP) 1-37A project and adopted and published by AASHTO. The MEPDG procedure offers several dramatic improvements over the current pavement design guide and presents a new paradigm in the way pavement design is performed. However, MEPDG is substantially more complex than the AASHTO Design Guide by considering the input parameters that influence pavement performance, including traffic, climate, pavement structure and material properties, and applying the principles of engineering mechanics to predict critical pavement responses. It requires significantly more input from the designer. Some of the required data are either not tracked previously or are stored in locations not familiar to designers, and many data sets need to be preprocessed for use in the MEPDG. As a result, tremendous research work has been conducted and still more challenges need to be tackled both in federal and state levels for the full implementation of MEPDG. This paper, for the first time, provides a comprehensive bird's eye view for the MEPDG procedure, including the evolvement of the design methodology, an overview of the design philosophy and its components, the research conducted during the development, improvement, and implementation phases, and the challenges remained and future developments directions. It is anticipated that the efforts in this paper aid in enhancing the mechanistic-empirical based pavement design for future continuous improvement to keep up with changes in trucking, materials, construction, design concepts, computers, and so on.展开更多
The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavement...The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavementscompared to conventional design guidelines. It is achieved through optimizing pavement structural andthickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizingeconomic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volumeconcrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative.This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 mm (6 in.). Thispaper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concretepavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performanceanalyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. Thispermits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axlespectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigidpavements with conventional concrete slab thicknesses and enable rational extrapolation of performance predictionfor thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable lowvolumepavement design using optimized ME solutions for Pittsburgh, PA, conditions.展开更多
Dynamic cone penetrometer(DCP) has been used for decades to estimate the shear strength and stiffness properties of the subgrade soils. There are several empirical correlations in the literature to predict the resil...Dynamic cone penetrometer(DCP) has been used for decades to estimate the shear strength and stiffness properties of the subgrade soils. There are several empirical correlations in the literature to predict the resilient modulus values at only a specific stress state from DCP data, corresponding to the predefined thicknesses of pavement layers(a 50 mm asphalt wearing course, a 100 mm asphalt binder course and a200 mm aggregate base course). In this study, field-measured DCP data were utilized to estimate the resilient modulus of low-plasticity subgrade Piedmont residual soil. Piedmont residual soils are in-place weathered soils from igneous and metamorphic rocks, as opposed to transported or compacted soils.Hence the existing empirical correlations might not be applicable for these soils. An experimental program was conducted incorporating field DCP and laboratory resilient modulus tests on "undisturbed" soil specimens. The DCP tests were carried out at various locations in four test sections to evaluate subgrade stiffness variation laterally and with depth. Laboratory resilient modulus test results were analyzed in the context of the mechanistic-empirical pavement design guide(MEPDG) recommended universal constitutive model. A new approach for predicting the resilient modulus from DCP by estimating MEPDG constitutive model coefficients(k;,k;and k;) was developed through statistical analyses. The new model is capable of not only taking into account the in situ soil condition on the basis of field measurements,but also representing the resilient modulus at any stress state which addresses a limitation with existing empirical DCP models and its applicability for a specific case. Validation of the model is demonstrated by using data that were not used for model development, as well as data reported in the literature.展开更多
Longitudinal cracking is one of the most important distresses of asphalt pavement in permafrost regions. The sensitivity analysis of design parameters for asphalt pavement can be used to study the influence of every p...Longitudinal cracking is one of the most important distresses of asphalt pavement in permafrost regions. The sensitivity analysis of design parameters for asphalt pavement can be used to study the influence of every parameter on longitudinal cracking, which can help optimizing the design of the pavement structure. In this study, 20 test sections of Qinghai-Tibet Highway were selected to conduct the sensitivity analysis of longi- tudinal cracking on material parameter based on Mechanistic-Empirical Pavement Design Guide (MEPDG) and single factorial sensitivity analysis method. Some computer aided engineering (CAE) simulation techniques, such as the Latin hypercube sampling (LHS) technique and the multiple regression analysis are used as auxiliary means. Finally, the sensitivity spectrum of material parameter on longitudinal cracking was established. The result shows the multiple regression analysis can be used to determine the remarkable influence factor more efficiently and to process the qualitative analysis when applying the MEPDG software in sensitivity analysis of longitudinal cracking in permafrost regions. The effect weights of the three parameters on longitudinal cracking in descending order are air void, effective binder content and PG grade. The influence of air void on top layer is bigger than that on middle layer and bottom layer. The influence of effective asphalt content on top layer is bigger than that on middle layer and bottom layer, and the influence of bottom layer is slightly bigger than middle layer. The accumulated value of longitudinal cracking on middle layer and bottom layer in the design life would begin to increase when the design temperature of PG grade increased.展开更多
文摘Past editions of the American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures have served well for several decades; nevertheless, many serious limitations exist for their continued use as the nation's primary pavement design procedures. Researchers are now incorporating the latest advances in pavement design into the new Mechanistic-Empirical Pavement Design Guide (MEPDG), developed under the National Cooperative Highway Research Program (NCHRP) 1-37A project and adopted and published by AASHTO. The MEPDG procedure offers several dramatic improvements over the current pavement design guide and presents a new paradigm in the way pavement design is performed. However, MEPDG is substantially more complex than the AASHTO Design Guide by considering the input parameters that influence pavement performance, including traffic, climate, pavement structure and material properties, and applying the principles of engineering mechanics to predict critical pavement responses. It requires significantly more input from the designer. Some of the required data are either not tracked previously or are stored in locations not familiar to designers, and many data sets need to be preprocessed for use in the MEPDG. As a result, tremendous research work has been conducted and still more challenges need to be tackled both in federal and state levels for the full implementation of MEPDG. This paper, for the first time, provides a comprehensive bird's eye view for the MEPDG procedure, including the evolvement of the design methodology, an overview of the design philosophy and its components, the research conducted during the development, improvement, and implementation phases, and the challenges remained and future developments directions. It is anticipated that the efforts in this paper aid in enhancing the mechanistic-empirical based pavement design for future continuous improvement to keep up with changes in trucking, materials, construction, design concepts, computers, and so on.
基金the financial support from the University of Pittsburgh Anthony Gill Chair and the Impactful Resilient Infrastructure Science and Engineering Consortium(IRISE)at University of Pittsburgh.
文摘The American Association of State Highway and Transportation Officials Mechanistic-Empirical Pavement DesignGuide (AASHTO M-E) offers an opportunity to design more economical and sustainable high-volume rigid pavementscompared to conventional design guidelines. It is achieved through optimizing pavement structural andthickness design under specified climate and traffic conditions using advanced M-E principles, thereby minimizingeconomic costs and environmental impact. However, the implementation of AASHTO M-E design for low-volumeconcrete pavements using AASHTOWare Pavement ME Design (Pavement ME) software is often overly conservative.This is because Pavement ME specifies the minimum design thickness of concrete slab as 152.4 mm (6 in.). Thispaper introduces a novel extension of the AASHTO M-E framework for the design of low-volume joint plain concretepavements (JPCPs) without modification of Pavement ME. It utilizes multi-gene genetic programming (MGGP)-based computational models to obtain rapid solutions for JPCP damage accumulation and long-term performanceanalyses. The developed MGGP models simulate the fatigue damage and differential energy accumulations. Thispermits the prediction of transverse cracking and joint faulting for a wide range of design input parameters and axlespectrum. The developed MGGP-based models match Pavement ME-predicted cracking and faulting for rigidpavements with conventional concrete slab thicknesses and enable rational extrapolation of performance predictionfor thinner JPCPs. This paper demonstrates how the developed computational model enables sustainable lowvolumepavement design using optimized ME solutions for Pittsburgh, PA, conditions.
文摘Dynamic cone penetrometer(DCP) has been used for decades to estimate the shear strength and stiffness properties of the subgrade soils. There are several empirical correlations in the literature to predict the resilient modulus values at only a specific stress state from DCP data, corresponding to the predefined thicknesses of pavement layers(a 50 mm asphalt wearing course, a 100 mm asphalt binder course and a200 mm aggregate base course). In this study, field-measured DCP data were utilized to estimate the resilient modulus of low-plasticity subgrade Piedmont residual soil. Piedmont residual soils are in-place weathered soils from igneous and metamorphic rocks, as opposed to transported or compacted soils.Hence the existing empirical correlations might not be applicable for these soils. An experimental program was conducted incorporating field DCP and laboratory resilient modulus tests on "undisturbed" soil specimens. The DCP tests were carried out at various locations in four test sections to evaluate subgrade stiffness variation laterally and with depth. Laboratory resilient modulus test results were analyzed in the context of the mechanistic-empirical pavement design guide(MEPDG) recommended universal constitutive model. A new approach for predicting the resilient modulus from DCP by estimating MEPDG constitutive model coefficients(k;,k;and k;) was developed through statistical analyses. The new model is capable of not only taking into account the in situ soil condition on the basis of field measurements,but also representing the resilient modulus at any stress state which addresses a limitation with existing empirical DCP models and its applicability for a specific case. Validation of the model is demonstrated by using data that were not used for model development, as well as data reported in the literature.
基金supported by research project of Ministry of Science and Technology of China (2014BAG05B04)research project of Ministry of Transport of China (2012319495030)the Special Fund for Basic Scientific Research of Central Colleges, Chang'an University (CHD2013G3212003)
文摘Longitudinal cracking is one of the most important distresses of asphalt pavement in permafrost regions. The sensitivity analysis of design parameters for asphalt pavement can be used to study the influence of every parameter on longitudinal cracking, which can help optimizing the design of the pavement structure. In this study, 20 test sections of Qinghai-Tibet Highway were selected to conduct the sensitivity analysis of longi- tudinal cracking on material parameter based on Mechanistic-Empirical Pavement Design Guide (MEPDG) and single factorial sensitivity analysis method. Some computer aided engineering (CAE) simulation techniques, such as the Latin hypercube sampling (LHS) technique and the multiple regression analysis are used as auxiliary means. Finally, the sensitivity spectrum of material parameter on longitudinal cracking was established. The result shows the multiple regression analysis can be used to determine the remarkable influence factor more efficiently and to process the qualitative analysis when applying the MEPDG software in sensitivity analysis of longitudinal cracking in permafrost regions. The effect weights of the three parameters on longitudinal cracking in descending order are air void, effective binder content and PG grade. The influence of air void on top layer is bigger than that on middle layer and bottom layer. The influence of effective asphalt content on top layer is bigger than that on middle layer and bottom layer, and the influence of bottom layer is slightly bigger than middle layer. The accumulated value of longitudinal cracking on middle layer and bottom layer in the design life would begin to increase when the design temperature of PG grade increased.