Download or read book Analysis and Determination of Axle Load Spectra and Traffic Input for the Mechanistic Empirical Pavement Design Guide written by Yi Jiang and published by Purdue University Press. This book was released on 2008-03-01 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: The values of equivalent single axle loads (ESAL) have been used to represent the vehicle loads in pavement design. To improve the pavement design procedures, a new method, called the Mechanistic-Empirical Pavement Design Guide (MEPDG), has been developed to use the axle load spectra to represent the vehicle loads in pavement design. These spectra represent the percentage of the total axle applications within each load interval for single, tandem, tridem, and quad axles. Using axle load spectra as the traffic input, the MEPDG method is able to analyze the impacts of varying traffic loads on pavement and provide an optimal pavement structure design. In addition, the new method can be used to analyze the effects of materials and the impacts of seasons, to compare rehabilitation strategies, and to perform forensic analyses of pavement conditions. The MEPDG utilizes mechanistic-empirical approaches to realistically characterize inservice pavements and allows the full integration of vehicular traffic loadings, climatic features, soil characteristics, and paving materials properties into the detailed analysis of pavement structural behaviors and the resulting pavement performance. In order to provide the traffic data input required by the MEPDG, the Indiana Department of Transportation (INDOT) made an effort to obtain truck traffic information from the traffic data collected through weigh-in-motion (WIM) stations. This study was conducted to create the truck traffic spectra and other traffic inputs for INDOT to implement the new pavement design method. Furthermore, the INDOT AADT data were used in this study to analyze the spatial distributions of the traffic volumes in Indiana and to obtain the spatial distributions of traffic volumes.

Download or read book Improved Characterization of Truck Traffic Volumes and Axle Loads for Mechanistic empirical Pavement Design written by Ala R. Abbas and published by . This book was released on 2012 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recently developed mechanistic-empirical pavement design guide (MEPDG) requires a multitude of traffic inputs to be defined for the design of pavement structures, including the initial two-way annual average daily truck traffic (AADTT), directional and lane distribution factors, vehicle class distribution, monthly adjustment factors, hourly truck distribution factors, traffic growth rate, axle load spectra by truck class (Class 4 to Class 13) and axle type (single, tandem, tridem, and quad), and number of axles per truck. Since it is not always practical to obtain site-specific traffic data, the MEPDG assimilates a hierarchal level concept that allows pavements to be designed using statewide averages and MEPDG default values without compromising the accuracy of the pavement design. In this study, a Visual Basic for Application (VBA) code was developed to analyze continuous traffic monitoring data and generate site-specific and statewide traffic inputs. The traffic monitoring data was collected by 143 permanent traffic monitoring sites (93 automated vehicle classifier (AVC) and 50 weigh-in-motion (WIM) sites) distributed throughout the State of Ohio from 2006 to 2011. The sensitivity of the MEPDG to the various traffic inputs was evaluated using two baseline pavement designs, one for a new flexible pavement and one for a new rigid pavement. Key performance parameters for the flexible pavement included longitudinal (top-down) fatigue cracking, alligator (bottom-up) fatigue cracking, transverse (low-temperature) cracking, rutting, and smoothness (expressed using IRI), while key performance parameters for the rigid pavement included transverse cracking (% slabs cracked), joint faulting, and smoothness. The sensitivity analysis results revealed that flexible pavements are moderately sensitive to AADTT, growth rate, vehicle class distribution, and axle load spectra; and not sensitive to hourly distribution factors, monthly adjustment factors, and number of axles per truck. Furthermore, it was found that rigid pavements are moderately sensitive to AADTT, growth rate, hourly distribution factors, vehicle class distribution, and axle load spectra; and not sensitive to monthly adjustment factors and number of axles per truck. Therefore, it is recommended to estimate the AADTT and the vehicle class distribution from site-specific short-term or continuous counts and obtain the truck growth rate from ODOT Modeling and Forecasting Section (Certified Traffic). As for the other traffic inputs, statewide averages can be used for the hourly distribution factors, axle load spectra, and number of axles per truck; and MEPDG defaults can be used for the monthly adjustment factors.

Download or read book Analysis of Virginia specific Traffic Data Inputs for Use with the Mechanistic empirical Pavement Design Guide written by Bryan C. Smith and published by . This book was released on 2010 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study developed traffic inputs for use with the Guide for the Mechanistic-Empirical Design of New & Rehabilitated Pavement Structures (MEPDG) in Virginia and sought to determine if the predicted distresses showed differences between site-specific and default traffic inputs for flexible and rigid pavements. The axle-load spectra, monthly adjustment factors, vehicle class distribution factors, and number of axles per truck inputs were considered. The predicted distresses based on site-specific traffic inputs from eight interstate and seven primary route weigh-in-motion sites in Virginia were compared to predicted distresses using MEPDG default traffic inputs. These comparisons were performed by use of a normalized difference statistic for each site-specific traffic input and the coefficient of variation for each pavement distress model. In addition, the practical significance for flexible pavements was considered from the difference in the predicted time to failure between site-specific and default traffic inputs. The analysis showed that the effect of the site-specific traffic inputs was generally not statistically significant when the uncertainty of the distress models was considered. However, the site-specific axle-load spectra and vehicle class distribution inputs showed a statistically significant effect on certain predicted distresses for flexible and rigid pavements, respectively. The study recommends that site-specific axle-load spectra data be considered for analysis of flexible pavements. Alternatively, summary (statewide average) axle-load spectra data for analysis of interstate and primary flexible pavements should be considered preferentially over default axle-load spectra. Site-specific vehicle class distribution factors should be considered for analysis of rigid pavements on the interstate system. Alternatively, summary (statewide average) vehicle class distribution factors for analysis of interstate rigid pavements should be considered preferentially over default vehicle class distribution data. Default traffic data are recommended for analysis of primary rigid pavements. This study also recommends that a local calibration process be completed to determine if the predictive models accurately predict the conditions found on Virginia's roadways. If the predictive models are modified, the results may impact the recommendations resulting from this study. The implementation of the recommendations of this study and the use of the MEPDG in general will provide the Virginia Department of Transportation with a more advanced means of designing and analyzing pavements. This should result in optimal designs that are more efficient in terms of initial construction and future maintenance costs.

Download or read book Mechanistic empirical Pavement Design Guide written by American Association of State Highway and Transportation Officials and published by AASHTO. This book was released on 2008 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Characterization for a Mechanistic empirical Pavement Design written by Jorge A. Prozzi and published by . This book was released on 2006 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this research study was to assess and address the implications of the axle load spectra approach proposed by the M-E Design Guide. In addition, recommendations were developed regarding traffic data needs and availability to aid in deciding the installation locations of future WIM stations in Texas. A methodology for specifying the required accuracy of WIM equipment based on the effect that this accuracy has on pavement performance prediction was also developed. Regarding traffic volume forecasting, a methodology is presented that allows optimum use of available data by simultaneously estimating traffic growth and seasonal traffic variability.

Download or read book Development of Traffic Inputs for the Mechanistic empirical Pavement Design Guide in New York State written by Ferdous Intaj and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Proper characterization of traffic data is a prerequisite for the determination of appropriate traffic inputs to Mechanistic-Empirical Pavement Design Guide (MEPDG). The development of proper traffic inputs helps reflect the traffic conditions over the life of pavement which would decrease the maintenance, repair and traffic disruptions and improve the traffic conditions of a road network. The objective of the study was to characterize the traffic data and suggest the sitespecific, regional or state wide average values for traffic inputs to MEPDG for New York State. Vehicle class distribution (VCD), monthly distribution factors (MDF), hourly distribution factors (HDF), average number of axle groups per vehicle (AGPV) and axle load spectra were obtained from vehicle classification and WIM sites in New York State for the years of 2007-2011. These traffic data was processed with TrafLoad software. Cluster analysis was performed on the processed VCD, MDF and HDF data collected during the time period. This statistical analysis could not be done for AGPV values and axle load spectra due to the unavailability of sufficient number of WIM sites. However, MEPDG runs were carried out to investigate the effect of the variability of traffic inputs on the pavement performance of typical new flexible and rigid pavement structures. The statistical analysis showed consistent results for VCD and HDF over the years. However, the results of statistical analysis on MDF were not consistent over the time period. Site specific values for VCD, MDF, AGPV and axle load spectra showed little variation with statewide average values after the cluster analysis and MEPDG runs for the vehicle classification and WIM data of the year of 2010. This was observed for both flexible and rigid pavements. However, HDF did not show any effect on the design of pavement with MEPDG. These findings were also verified from the analysis of vehicle classification and WIM data of the other years.

Download or read book Improved Characterization of Truck Traffic Volumes and Axle Loads for Mechanistic empirical Pavement Design written by Ala R. Abbas and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recently developed mechanistic-empirical pavement design guide (MEPDG) requires a multitude of traffic inputs to be defined for the design of pavement structures, including the initial two-way annual average daily truck traffic (AADTT), directional and lane distribution factors, vehicle class distribution, monthly adjustment factors, hourly truck distribution factors, traffic growth rate, axle load spectra by truck class (Class 4 to Class 13) and axle type (single, tandem, tridem, and quad), and number of axles per truck. Since it is not always practical to obtain site-specific traffic data, the MEPDG assimilates a hierarchal level concept that allows pavements to be designed using statewide averages and MEPDG default values without compromising the accuracy of the pavement design. In this study, a Visual Basic for Application (VBA) code was developed to analyze continuous traffic monitoring data and generate site-specific and statewide traffic inputs. The traffic monitoring data was collected by 143 permanent traffic monitoring sites (93 automated vehicle classifier (AVC) and 50 weigh-in-motion (WIM) sites) distributed throughout the State of Ohio from 2006 to 2011. The sensitivity of the MEPDG to the various traffic inputs was evaluated using two baseline pavement designs, one for a new flexible pavement and one for a new rigid pavement. Key performance parameters for the flexible pavement included longitudinal (top-down) fatigue cracking, alligator (bottom-up) fatigue cracking, transverse (low-temperature) cracking, rutting, and smoothness (expressed using IRI), while key performance parameters for the rigid pavement included transverse cracking (% slabs cracked), joint faulting, and smoothness. The sensitivity analysis results revealed that flexible pavements are moderately sensitive to AADTT, growth rate, vehicle class distribution, and axle load spectra; and not sensitive to hourly distribution factors, monthly adjustment factors, and number of axles per truck. Furthermore, it was found that rigid pavements are moderately sensitive to AADTT, growth rate, hourly distribution factors, vehicle class distribution, and axle load spectra; and not sensitive to monthly adjustment factors and number of axles per truck. Therefore, it is recommended to estimate the AADTT and the vehicle class distribution from site-specific short-term or continuous counts and obtain the truck growth rate from ODOT Modeling and Forecasting Section (Certified Traffic). As for the other traffic inputs, statewide averages can be used for the hourly distribution factors, axle load spectra, and number of axles per truck; and MEPDG defaults can be used for the monthly adjustment factors.

Download or read book Traffic Load Spectra for Implementing and Using the Mechanistic empirical Pavement Design Guide in Georgia written by Olga Selezneva and published by . This book was released on 2014 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GDOT is preparing for implementation of the Mechanistic-Empirical Pavement Design Guide (MEPDG). As part of this preparation, a statewide traffic load spectra program is being developed for gathering truck axle loading data. This final report presents the results of a comprehensive research effort that culminated in recommendations for a statewide Traffic Load Spectra Program for collecting and processing truck axle loading data to support MEPDG implementation in Georgia. The recommendations include an optimal axle loading data collection plan that balances pavement design data needs, cost and number of WIM sites, and types of equipment used in obtaining the data. The report also shows how the available GDOT traffic data and other applicable data resources were used to develop traffic loading inputs and defaults to support local calibration of MEPDG models in Georgia. The available axle loading data were analyzed and the interim traffic loading defaults were developed for different groups of roads designed and maintained by GDOT, along with the recommendations for future updates of the defaults. In addition, user guidelines, decision trees, and software tools were developed to facilitate using the traffic loading defaults in MEPDG applications

Download or read book Truck Traffic and Load Spectra of Indiana Roadways for the Mechanistic Empirical Pavement Design Guide written by Jieyi Bao and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed for pavement design by the Indiana Department of Transportation (INDOT) since 2009 and has generated efficient pavement designs with a lower cost. It has been demonstrated that the success of MEPDG implementation depends largely on a high level of accuracy associated with the information supplied as design inputs. Vehicular traffic loading is one of the key factors that may cause not only pavement structural failures, such as fatigue cracking and rutting, but also functional surface distresses, including friction and smoothness. In particular, truck load spectra play a critical role in all aspects of the pavement structure design. Inaccurate traffic information will yield an incorrect estimate of pavement thickness, which can either make the pavement fail prematurely in the case of under-designed thickness or increase construction cost in the case of over-designed thickness. The primary objective of this study was to update the traffic design input module, and thus to improve the current INDOT pavement design procedures. Efforts were made to reclassify truck traffic categories to accurately account for the specific axle load spectra on two-lane roads with low truck traffic and interstate routes with very high truck traffic. The traffic input module was updated with the most recent data to better reflect the axle load spectra for pavement design. Vehicle platoons were analyzed to better understand the truck traffic characteristics. The unclassified vehicles by traffic recording devices were examined and analyzed to identify possible causes of the inaccurate data collection. Bus traffic in the Indiana urban areas was investigated to provide additional information for highway engineers with respect to city streets as well as highway sections passing through urban areas. New equivalent single axle load (ESAL) values were determined based on the updated traffic data. In addition, a truck traffic data repository and visualization model and a TABLEAU interactive visualization dashboard model were developed for easy access, view, storage, and analysis of MEPDG related traffic data.

Download or read book Testing and Characterization of Asphalt Materials and Pavement Structures written by Kun Zhang and published by Springer. This book was released on 2018-07-11 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents new studies dealing with the attempts made by the scientists and practitioners to address contemporary issues in pavement engineering such as aging and modification of asphalt binders, performance evaluation of warm mix asphalt, and mechanical-based pavement structure analysis, etc.. Asphalt binder and mixture have been widely used to construct flexible pavements. Mechanical and Chemical characterizations of asphalt materials and integration of these properties into pavement structures and distresses analysis are of great importance to design a sustainable flexible pavement. This book includes discusses and new results dealing with these issues. Papers were selected from the 5th GeoChina International Conference 2018 – Civil Infrastructures Confronting Severe Weathers and Climate Changes: From Failure to Sustainability, held on July 23 to 25, 2018 in HangZhou, China.

Download or read book Traffic Data Collection Analysis and Forecasting for Mechanistic Pavement Design written by National Cooperative Highway Research Program and published by . This book was released on 2004 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Traffic Data Collection Analysis and Forecasting for Mechanistic Pavement Design written by Cambridge Systematics and published by Transportation Research Board. This book was released on 2005 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Kansas Rigid Pavement Analysis Following New Mechanistic empirical Design Guide written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The AASHTO Guide for Design of Pavement Structures is the primary document used by the state highway agencies to design new and rehabilitated highway pavements. Currently the Kansas Department of Transportation (KDOT) uses the 1993 edition of the AASHTO pavement design guide, based on empirical performance equations, for the design of Jointed Plain Concrete Pavements (JPCP). However, the newly released Mechanistic-Empirical Pavement Design Guide (MEPDG) provides methodologies for mechanistic-empirical pavement design while accounting for local materials, environmental conditions, and actual highway traffic load distribution by means of axle load spectra. The major objective of this study was to predict pavement distresses from the MEPDG design analysis for selected in-service JPCP projects in Kansas. Five roadway sections designed by KDOT and three long term pavement performance (LTPP) sections in Kansas were analyzed. Project-specific construction, materials, climatic, and traffic data were also generated in the study. Typical examples of axle load spectra calculations from the existing Weigh-in-Motion (WIM) data were provided. Vehicle class and hourly truck traffic distributions were also derived from Automatic Vehicle Classification (AVC) data provided by KDOT. The predicted output variables, IRI, percent slabs cracked, and faulting values, were compared with those obtained during annual pavement management system (PMS) condition survey done by KDOT. A sensitivity analysis was also performed to determine the sensitivity of the output variables due to variations in the key input parameters used in the design process. Finally, the interaction of selected significant factors through statistical analysis was identified to find the effect on current KDOT specifications for rigid pavement construction. The results showed that IRI was the most sensitive output. For most projects in this study, the predicted IRI was similar to the measured values. MEPDG analysis showed minimal or no faulting and was confirmed by visual observation. Only a few projects showed some cracking. It was also observed that the MEPDG outputs were very sensitive to some specific traffic, material, and construction input parameters such as, average daily truck traffic, truck percentages, dowel diameter, tied concrete shoulder, widened lane, slab thickness, coefficient of thermal expansion, compressive strength, base type, etc. Statistical analysis results showed that the current KDOT Percent Within Limits (PWL) specifications for concrete pavement construction are more sensitive to the concrete strength than to the slab thickness. Concrete slab thickness, strength, and truck traffic significantly influence the distresses predicted by MEPDG in most cases. The interactions among these factors are also almost always evident.

Download or read book Traffic Data Collection Analysis and Forecasting for Mechanistic Pavement Design written by Cambridge Systematics and published by Transportation Research Board National Research. This book was released on 2005 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development of a Regional Pavement Performance Database for the AASHTO Mechanistic empiricle sic Pavement Design Guide Sensitivity analysis written by Swetha Kesiraju and published by . This book was released on 2007 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Incorporation of Reliability Into the Minnesota Mechanistic empirical Pavement Design Method written by and published by . This book was released on 1999 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pavement Design Materials Analysis and Highways written by M. Rashad Islam and published by McGraw Hill Professional. This book was released on 2021-02-05 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the principles, analysis, and design in pavement engineering This student-friendly textbook offers comprehensive coverage of pavement design and highways. Written by two seasoned civil engineering educators, the book contains precise explanations of traditional and computerized mechanistic design methods along with detailed examples of real-world pavement and highway projects. Pavement Design: Materials, Analysis, and Highways shows, step by step, how to apply the latest, software-based AASHTOWare Pavement Mechanistic-Empirical Design method. Each design topic is covered in separate, modular chapters, enabling you to tailor a course of study. Fundamentals of Engineering (FE) sample questions are also provided in each chapter. Coverage includes: Stress-strain in pavement Soils, aggregates, asphalt, and portland cement concrete Traffic analysis for pavement design Distresses and distress-prediction models in flexible and rigid pavement Flexible and rigid pavement design by AASHTO 1993 and AASHTOWare Overlay and drainage design Sustainable and rehabilitation pavement design, pavement management, and recycling Geometric design of highways