Open Access Open Access  Restricted Access Subscription or Fee Access

Sensitivity of M-E PDG Level 2 and 3 Inputs Using Statistical Analysis Techniques for New England States

Dinesh Ayyala(1*), Ghassan R. Chehab(2), Jo Sias Daniel(3)

(1) North Carolina State University, Department of Civil, Construction, and Environmental Engineering, United States
(2) American University of Beirut, Department of Civil and Environmental Engineering, Lebanon
(3) University of New Hampshire, Department of Civil and Environmental Engineering, United States
(*) Corresponding author


DOI: https://doi.org/10.15866/irea.v6i5.16631

Abstract


Implementation of the Mechanistic-Empirical Pavement Design Guide (M-E PDG) by state highway design agencies necessitates transition from their currently followed pavement design practices along with additional data collection on the large number of inputs incorporated in the M-E PDG. This paper presents a data collection methodology that is representative of a real pavement section instead of a model pavement section or obtaining data from knowledge of engineering principles and experience. A procedure to design field studies is developed such that state highway design specifications can be adjusted if needed and transformed into M-E design guidelines to aid the implementation process. Statistical analysis of the predicted performance data is conducted to assess the sensitivity of Level 2 and 3 inputs on pavement distresses. A roadmap for documentation of design data is proposed based on case-studies from two states, New Hampshire and Connecticut. Input parameters considered to critically affect pavement distresses are identified from previous research results and literature review. Data sources for the corresponding M-E PDG inputs were identified and values for input parameters were selected based on variations that practically occur during pavement design, including tolerances on material properties. Analysis of variance was conducted on the predicted performance data. Percentage variation in the predicted distresses explained by each input variable was calculated and sensitivity levels were determined. Correlation ratio η^2 was used due to the deterministic nature of M-E PDG output. Independent data collection recommendations were made for both states on the basis of the study.
Copyright © 2018 Praise Worthy Prize - All rights reserved.

Keywords


M-E PDG; Mechanistic-Empirical; Pavement Design

Full Text:

PDF


References


[1] Applied Research Associates Inc. Manual 1 – Introduction, Chapter 1. Publication NCHRP 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, March 2004

[2] US Department of Transportation, Federal Highway Administration. Long Term Pavement Performance (LTPP) Program, LTPP Datapave Online Release 22. January 14, 2008. http://www.ltpp-products.com/index.asp. Accessed - February - December 2008

[3] Applied Research Associates Inc. Manual 3 – Design of New and Reconstructed Flexible Pavements, Chapter 3. Publication NCHRP 1-37A, National Cooperative Highway Research Program, Transportation Research Board, National Research Council, March 2004

[4] Tommy Nantung, Ghassan Chehab, Scott Newbolds, Khaled Galal, Shuo Li, Dae Hyeon Kim. Implementation Initiatives of the Mechanistic – Empirical Pavement Design Guide in Indiana, Transportation Research Record: Journal of the Transportation Research Board, No. 1919, Transportation Research Board of the National Academies, Washington, D.C., 2005, pp. 142–151

[5] Sunghwan Kim, Halil Ceylan, Michael Heitzman. Sensitivity Study of Design Input Parameters for Two Flexible Pavement Systems Using the Mechanistic-Empirical Pavement Design Guide, Proceedings of the 2005 Mid-Continent Transportation Research Symposium, Ames, Iowa, August 2005

[6] Nam H. Tran and Kevin D. Hall. Development and Significance of State-Wide Volume Adjustment Factors in Mechanistic – Empirical Pavement Design Guide, Transportation Research Record: Journal of the Transportation Research Board No. 2037, Transportation Research Board of the National Research Council, Washington D.C., 2007, pp 97-105.

[7] Center for Transportation Research and Education, Iowa State University. Implementing the Mechanistic-Empirical Pavement Design Guide: Technical Report, CTRE Project 03-166, May 2005

[8] Harold L. VonQuintus, James S. Moulthrop. Mechanistic Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models for Montana, Volume III: Field Guide – Calibration and User’s Guide for the M-E PDG. Publication FHWA/MT-07-008/8158-3, Research Programs, Montana Department of Transportation, August 2007

[9] Hao Yin, Ghassan R. Chehab and Shelley M. Stoffels. A Case Study: Assessing the Sensitivity of the Coefficient of Thermal Contraction of AC Mixtures on Thermal Crack Prediction. Asphalt Concrete: Simulation, Modeling, and Experimental Characterization 2006, American Society of Civil Engineers, Oct 25, 2005. pp. 115-123

[10] Applied Pavement Technology, Inc. “Mechanistic – Empirical Pavement Design Guide Implementation Plan, Study SD2005-01 Final Report”, October 2007.

[11] Connecticut DOT. Standard Specifications for Road, Bridge and Incidental Construction, Division III – Materials, Section M04: Bituminous Concrete Materials. Publication Form 816. State of Connecticut, Department of Transportation, 2004

[12] New Hampshire DOT. Standard Specifications for Road and Bridge Construction, Division 400: Pavements. State of New Hampshire, Department of Transportation, 2006.

[13] Jo Sias Daniel and Ghassan Chehab. Use of RAP mixtures in the Mechanistic-Empirical Pavement Design Guide. Presented at the 87th Annual Meeting of the Transportation Research Board, Washington D.C., 2008

[14] Bureau of Planning, Traffic Section, Traffic Reports. Traffic Volume Counts for the state of New Hampshire. State of New Hampshire Department of Transportation, Bureau of Transportation Planning.

http://www.nh.gov/dot/org/operations/traffic/tvr/index.htm. Accessed April 12, 2008

[15] Connecticut DOT. Traffic Monitoring Volume Information – Traffic Count Data, State of Connecticut Department of Transportation. http://www.ct.gov/dot/cwp/view.asp?a=1383&q=330402. Accessed May 27, 2008

[16] United States Geological Survey. Active Groundwater Level Network. http://groundwaterwatch.usgs.gov/default.asp. Accessed May 27, 2008

[17] Asphalt Institute, SP – 1 Superpave Performance Graded Asphalt Binder Specifications and Testing and SP – 2 Superpave Mix Design. Third Edition, revised 2001

[18] United States Federal Highway Administration, LTPPBind software for selecting Superpave asphalt binder grade.

[19] Ramesh B. Malla and Shraddha Joshi. Establish Subgrade Support Values for Typical Soils in New England States. Publication NETCR 57, Report 02-3, The New England Transportation Consortium, April 10, 2006

[20] Paul R. Kinnear and Colin D. Gray. SSPS 12 Made Simple. Psychology Press, Taylor and Francis Group, New York, 2004.

[21] Lee A. Becker. Measures of Effect Size (Strength of Association). November 8, 1999.

http://web.uccs.edu/lbecker/SPSS/glm_effectsize.htm. Accessed November 24, 2008

[22] Swetha Kesiraju, Hussain Bahia, Teresa M. Adams. Development of a Regional Pavement Performance Database for the AASHTO Mechanistic-Empirical Pavement Design Guide, Part 1 – Sensitivity Analysis. Publication Report No. MRUTC 07-01. Midwest Regional University Transportation Center, University of Wisconsin – Madison


Refbacks

  • There are currently no refbacks.



Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2022 Praise Worthy Prize