Stiffness Properties of Composite Pavements Using Artificial Neural Network-Based Methodologies

Details

• Alternative Title:
  Development of a Comprehensive, Rational Method for Determination of Remaining Life of an Existing Pavement Project title from cover
• Creators:
  Abdallah, Imad N. ; Ferregut, Carlos ; Melchor-Lucero, Octavio ; Nazarian, Soheil
• Corporate Creators:
  University of Texas at El Paso. Center for Highway Materials Research
• Corporate Contributors:
  Texas Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Composite pavements
  • Neural networks
  • Nondestructive tests
  • Mechanistic-empirical pavement design
  • Falling weight deflectometers
  • Pavement layers
• Publication/ Report Number:
  TX-99 l 71 l-3F
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas ; United States
• Edition:
  Interim Report: Sept. 1, 1999 -Aug 31, 2000
• Corporate Publisher:
  University of Texas at El Paso. Center for Highway Materials Research
• Abstract:
  Most mechanistic-empirical methods for determining the remaining life of an existing pavement rely on the use of deflection-based nondestructive evaluation (NDE) devices. This report describes a methodology based on Artificial Neural Networks (ANN) techniques to estimate moduli of different layers in a composite pavement. The inputs to all the models are the best estimates of the thickness of each layer and the surface deflections obtained from a Falling Weight Deflectometer test. The outcome of the study is a computer program that estimates the moduli of different pavement layers in a more robust manner.
• Format:
  PDF
• Funding:
  0-1711
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/82933/dot_82933_DS1.pdf
• File Type:
  [PDF - 1.41 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:67814db906341389e82d85fdf2f13863810749f5e7d2b1062619c2a1dcf46190311653b0406ae051de16bd9639195d4bc94117903e2bc43da05dd21e708578a0