Influence of Unbound Material Type and Input Level on Pavement Performance Using Mechanistic–Empirical Pavement Design Guide

2016 ◽  
Vol 2578 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Ragaa Abd El-Hakim ◽  
Sherif M. El-Badawy ◽  
Alaa R. Gabr ◽  
Abdelhalim M. Azam
Keyword(s):  
Pavement Design ◽  
Pavement Performance ◽  
Material Type ◽  
Design Guide ◽  
Input Level

Jointed Plain Concrete (JPC) Pavement Variability and Method to Complement JPC Design with 3D Pavement Data

2021 ◽  
pp. 036119812199782
Author(s):  
Georgene Malone Geary ◽  
Yichang (James) Tsai
Keyword(s):  
Crack Detection ◽  
Plain Concrete ◽  
Pavement Design ◽  
Pavement Performance ◽  
Local Calibration ◽  
Design Guide ◽  
Unique Method ◽  
Departments Of Transportation ◽  
Transportation Agencies

3D pavement data are increasing in use and availability and open up new opportunities to evaluate variability in pavements. The majority of information we currently have on existing pavements is the result of the Long Term Pavement Performance Program (LTPP). While the program is comprehensive and the data are immense, the study sections are typically only 500 ft in length, which limits the ability to accurately gauge the variability of the distresses in a pavement over a longer length, especially cracking in Jointed Plain Concrete (JPC) slabs. 3D pavement data already collected by transportation agencies have the opportunity to complement LTPP data to analyze variability and improve the use of LTPP data. This paper presents a unique method to complement LTPP data using 3D pavement data, consisting of four steps: (1) crack detection using 3D pavement data; (2) categorize detected cracks by orientation and extent by slab using 3D slab-based methodology; (3) convert categorized slab level cracking into mechanistic-empirical pavement design guide cracking; and (4) perform local calibration with the 3D converted input values. The method uses 3D pavement data to provide a non-discrete value for percent cracking in GPS-3 LTPP sections for the purposes of local calibration. The proposed method is shown to be feasible using 3D pavement data and two JPC LTPP sections in Georgia. The method could be extended to any of the state Departments of Transportation that have active LTPP sections and are now or will shortly be collecting 3D pavement data.

Impact of Antistrip Additives on Pavement Performance Using Mechanistic-Empirical Pavement Design Guide

2013 ◽  
Vol 25 (3) ◽  
pp. 308-317 ◽  
Author(s):  
Elie Y. Hajj ◽  
Peter E. Sebaaly ◽  
Thileepan Sathanathan ◽  
Sivakulan Shivakolunthar
Keyword(s):  
Pavement Design ◽  
Pavement Performance ◽  
Design Guide ◽  
Antistrip Additives

Implementation Initiatives of the Mechanistic–Empirical Pavement Design Guides in Indiana

2005 ◽  
Vol 1919 (1) ◽  
pp. 142-151 ◽  
Author(s):  
Tommy Nantung ◽  
Ghassan Chehab ◽  
Scott Newbolds ◽  
Khaled Galal ◽  
Shuo Li ◽  
...  
Keyword(s):  
Pavement Design ◽  
Sensitivity Analyses ◽  
Pavement Performance ◽  
Design Parameters ◽  
State Highway ◽  
Design Guide ◽  
Input Parameters ◽  
Pavement Structures ◽  
State Highway Agencies ◽  
Empirical Design

The release of the Mechanistic–Empirical Design Guide for New and Rehabilitated Pavement Structures (M-E design guide) generated a new paradigm for designing and analyzing pavement structures. It is expected to replace the commonly used empirical design methodologies. The M-E design guide uses a comprehensive suite of input parameters deemed necessary to design pavements with high reliability and to predict pavement performance and distresses realistically. However, the considerable amount of input needed and the selection of the corresponding reliability level for each might present state highway agencies with complexities and challenges in its implementation. An overview is presented of ongoing investigative studies, sensitivity analyses, and preimplementation initiatives conducted by the Indiana Department of Transportation (INDOT) in an effort to accelerate the adoption of the new pavement design guide by efficiently using existing design parameters and determining those parameters that influence the predicted performance the most. Once the sensitive inputs are identified, the large amount of other required design input parameters can be significantly reduced to a manageable level for implementation purposes. A matrix of trial runs conducted with the M-E design guide software suggests that a higher design level input does not necessarily guarantee a higher accuracy in predicting pavement performance. The software runs also confirmed the need to use input values obtained from local rather than national calibration. Such findings are important for state highway agencies such as INDOT in drafting initiatives for implementing the M-E design guide.

Comparative Analysis between Modern-Era Retrospective Analysis for Research and Applications and Updated Mechanistic-Empirical Pavement Design Guide Climate Database in the State of Tennessee

2019 ◽  
Vol 2673 (6) ◽  
pp. 279-287
Author(s):  
Abubakr Ziedan ◽  
Mbakisya Onyango ◽  
Weidong Wu ◽  
Sampson Udeh ◽  
Joseph Owino ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Retrospective Analysis ◽  
The State ◽  
Pavement Design ◽  
Pavement Performance ◽  
Climate Data ◽  
Climatic Regions ◽  
Geographic Coverage ◽  
Design Guide ◽  
Modern Era

The Mechanistic-Empirical Pavement Design Guide addresses climate effects on pavement design in a comprehensive way, which allows for investigating the effect of climate on pavement performance. However, it requires detailed climate inputs, which might not be readily available for most of the state departments of transportation. The AASHTOWare Pavement Mechanistic-Empirical Design (PMED) version 2.3 (v2.3) climate database encompasses 12 weather stations in the state of Tennessee, which does not satisfactorily represent all climatic regions in the state. The terrain in Tennessee varies from flat in the west to mountainous in the east. To evaluate the effectiveness of the updated AASHTOWare PMED v2.3 climate data input, this study analyses the performance of selected pavements in the state of Tennessee using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the AASHTOWare PMED v2.3 databases as sources of PMED climate data inputs. A comparative analysis of the two climate data sources is conducted using eight long-term pavement performance (LTPP) sites in the state of Tennessee. The study revealed that MERRA as a climate data source for the state of Tennessee offers better geographic coverage, and therefore provides more precise distress predictions than the AASHTOWare PMED v2.3 climate database.

Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

2003 ◽  
Vol 1855 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Weng On Tam ◽  
Harold Von Quintus
Keyword(s):  
Pavement Design ◽  
Vehicle Classification ◽  
Pavement Performance ◽  
Traffic Data ◽  
Design Procedures ◽  
Load Spectra ◽  
State Highway ◽  
Pavement Structures ◽  
Empirical Design

Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under NCHRP require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

Implementing the Mechanistic–Empirical Design Guide Procedure for a Hot-Mix Asphalt–Rehabilitated Pavement in Indiana

2005 ◽  
Vol 1919 (1) ◽  
pp. 121-133 ◽  
Author(s):  
Khaled A. Galal ◽  
Ghassan R. Chehab
Keyword(s):  
Hot Mix Asphalt ◽  
Pavement Design ◽  
Design Parameters ◽  
Design Procedures ◽  
Design Concepts ◽  
Asphalt Overlay ◽  
Design Guide ◽  
Strategic Goals ◽  
And Performance

One of the Indiana Department of Transportation's (INDOT's) strategic goals is to improve its pavement design procedures. This goal can be accomplished by fully implementing the 2002 mechanistic–empirical (M-E) pavement design guide (M-E PDG) once it is approved by AASHTO. The release of the M-E PDG software has provided a unique opportunity for INDOT engineers to evaluate, calibrate, and validate the new M-E design process. A continuously reinforced concrete pavement on I-65 was rubblized and overlaid with a 13–in.-thick hot-mix asphalt overlay in 1994. The availability of the structural design, material properties, and climatic and traffic conditions, in addition to the availability of performance data, provided a unique opportunity for comparing the predicted performance of this section using the M-E procedure with the in situ performance; calibration efforts were conducted subsequently. The 1993 design of this pavement section was compared with the 2002 M-E design, and performance was predicted with the same design inputs. In addition, design levels and inputs were varied to achieve the following: ( a) assess the functionality of the M-E PDG software and the feasibility of applying M-E design concepts for structural pavement design of Indiana roadways, ( b) determine the sensitivity of the design parameters and the input levels most critical to the M-E PDG predicted distresses and their impact on the implementation strategy that would be recommended to INDOT, and ( c) evaluate the rubblization technique that was implemented on the I-65 pavement section.

Evaluation of Seasonal Effects on Subgrade Soils

2003 ◽  
Vol 1821 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Andrew G. Heydinger
Keyword(s):  
Seasonal Variations ◽  
Resilient Modulus ◽  
Monitoring Program ◽  
Test Site ◽  
Pavement Design ◽  
Seasonal Effects ◽  
Pavement Performance ◽  
Climatic Effects ◽  
Subgrade Soils ◽  
Frost Penetration

One objective of the FHWA’s Long-Term Pavement Performance (LTPP) program is to determine climatic effects on pavement performance. The LTPP instrumentation program includes seasonal monitoring program (SMP) instrumentation to monitor the seasonal variations of moisture, temperature, and frost penetration. Findings from the SMP instrumentation are to be incorporated into future pavement design procedures. Data from SMP instrumentation at the Ohio Strategic Highway Research Program Test Road (US-23, Delaware County, Ohio) and other reported results were analyzed to develop empirical equations. General expressions for the seasonal variations of average daily air temperature and variations of temperature and moisture in the fine-grained subgrade soil at the test site are presented. An expression for the seasonal variation of resilient modulus was derived. Average monthly weighting factors that can be used for pavement design were computed. Other factors such as frost penetration, depth of water table, and drainage conditions are discussed.

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