Reliability-Based Optimization Design of Geosynthetic Reinforced Road Embankment

Road embankments are typically large earth structures, the construction of which requires large amounts of competent fill soil. In order to limit costs, the utilization of geosynthetics in road embankments allows for construction of steep slopes up to 80⁰ - 85⁰ from horizontal, which can save considerable amounts of fill soil in the embankment and usable land at the toe, compared to a traditional unreinforced slope. It then requires for a stability analysis of the geosynthetic-reinforced slope, which is highly dependent on the selection and properties of geosynthetic including tensile strength, transfer efficiency, length and the number of geosynthetic layers placed in embankment, etc. To minimize costs, an optimization design is necessary to select an ideal combination of those design parameters. In this study, reliability-based optimization (RBO) will be implemented on the basis of reliability-based probabilistic slope stability analysis considering the variability of soil properties. RBO intends to minimize the cost involved in geosynthetic reinforced road embankment design while satisfying technical requirements. The limit equilibrium method was embedded to compute the factor of safety (fs), meanwhile, the most-probable-point (MPP)-based first-order reliability method (FORM) was conducted to determine the probability of failure (pf). The cost is assumed as a function of design parameters: the number of geosynthetic layers, embedment length, and tensile strength of the geosynthetic. Coupling with the reliability assessment and some other technical constraints, the combination of design parameters can be optimized to minimize cost.

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  • Supplemental Notes:
    • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
  • Corporate Authors:

    Center for Transportation Infrastructure and Safety/NUTC program

    Missouri University of Science and Technology
    220 Engineering Research Lab
    Rolla, MO  United States  65409

    Research and Innovative Technology Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Luna, Ronaldo
    • He, Xiaoming
    • Deng, Mingyan
  • Publication Date: 2014-7


  • English

Media Info

  • Media Type: Digital/other
  • Edition: Final Report
  • Features: Appendices; Figures; References;
  • Pagination: 46p

Subject/Index Terms

Filing Info

  • Accession Number: 01538328
  • Record Type: Publication
  • Report/Paper Numbers: NUTC R353, 00042706
  • Contract Numbers: DTRT06-G-0014
  • Created Date: Sep 8 2014 10:11AM