Prediction Model for Estimating the Immediate Settlement of Foundations Placed on Reinforced Soil

Mahsa Khosrojerdi, Ming Xiao, Tong Qiu, Jennifer Nicks

Research output: Contribution to journalConference articlepeer-review

Abstract

A reinforced soil foundation (RSF) consists of closely-spaced layers of geosynthetic reinforcement and compacted granular fill material used to support bridge piers and abutments. The RSF approach is a fast and economical alternative to traditional shallow foundations. This paper presents a prediction model for estimating settlement of a footing placed on an RSF under service loads. The parameters that are considered in the prediction model include footing geometry (width and length), soil friction angle and cohesion, reinforcement characteristics (stiffness, spacing, and length), and applied static loads from 50 to 600 kPa. In order to develop this prediction model, a parametric study was conducted using a validated finite difference numerical model. The results of the parametric study were used to conduct a regression analysis to derive a prediction model for estimating the maximum settlement of foundation placed on reinforced soil. Such a prediction model will be useful for practitioners in preliminary RSF design.

Original languageEnglish (US)
Pages (from-to)109-118
Number of pages10
JournalGeotechnical Special Publication
Volume2018-March
Issue numberGSP 297
DOIs
StatePublished - Jan 1 2018
Event3rd International Foundation Congress and Equipment Expo 2018: Developments in Earth Retention, Support Systems, and Tunneling, IFCEE 2018 - Orlando, United States
Duration: Mar 5 2018Mar 10 2018

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Architecture
  • Building and Construction
  • Geotechnical Engineering and Engineering Geology

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