Concrete Pavement Reliability by Monte Carlo Simulation

The mathematical complexity of reliability analysis can be challenging for pavement engineers. Most engineers, however, are quite experienced in applying the concept of the safety factor, SF, in design. Monte Carlo simulation is used in this paper to show that reliability is related to SF for any given level of assumed variability in material properties and traffic. A range of SF between 1 and 5 is found to be adequate in describing R from 50% to 99.9% for typical concrete pavement sections. The methodology developed is simple to follow and leads to practical values of the overall standard deviation, So, required in AASHTO 86/93 designs. Findings corroborate the stipulation that for rigid pavements, So typically lies between 0.3 and 0.4. The approach described eliminates the shortcomings of the reliability methodology of AASHTO 86/93, which emerges as mathematically and philosophically well-grounded, consistent with broader engineering practice and deserves to be reconsidered.

• Record URL:
  • https://doi.org/10.1061/9780784484913.026
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784484913
• Supplemental Notes:
  • © 2023 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Ioannides, Anastasios M
  • Tingle, Jeb S
• Conference:
  • International Airfield and Highway Pavements Conference 2023
  • Location: Austin Texas, United States
  • Date: 2023-7-14 to 2023-7-17
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 285-297
• Monograph Title: Airfield and Highway Pavements 2023: Testing and Characterization of Pavement Materials

Subject/Index Terms

• TRT Terms: Concrete pavements; Monte Carlo method; Pavement design; Reliability; Safety factors; Simulation
• Subject Areas: Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01891670
• Record Type: Publication
• ISBN: 9780784484913
• Files: TRIS, ASCE
• Created Date: Aug 28 2023 9:34AM