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Title:

Prediction of Subgrade Resilient Modulus Using Genetic Algorithm and Curve Shifting Methodology as An Alternative to Nonlinear Constitutive Models

Accession Number:

01122397

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

This paper demonstrates the applicability of the genetic algorithm and curve shifting methodology to estimate resilient modulus at various stress states for subgrade soils using the results of triaxial resilient modulus tests. This innovative methodology is proposed as an alternative to conventional nonlinear constitutive relationships. Using the genetic algorithm, laboratory curves for different deviator stress levels at different confining pressures are horizontally shifted to form a final gamma distribution curve which can represent the stress-strain behavior of subgrade soils. Resilient modulus values for a given stress state can be estimated based on this curve and another gamma function which represents the variation of shift values for different confining stresses. To compare the effectiveness of these two approaches, coefficients for the Uzan constitutive model are also determined for each laboratory test and compared with the approach described in this paper. Critical stresses determined by using KENPAVE for a representative pavement section are integrated with both the Uzan and the curve shifting models to determine resilient modulus values for different subgrade soil types. Predicted resilient modulus values from each approach are separately compared with Artificial Neural Network (ANN) model predictions to compare their efficiency and reliability in terms of resilient response prediction. Results of the analysis indicated that curve shifting methodology gives superior estimates with a coefficient of determination 14% higher than the Uzan model predictions when the results are compared with the ANN model outputs. Thus, although it is not a constitutive model, use of the genetic algorithm and curve shifting methodology is proposed as a promising technique for the evaluation of subgrade soils’ stress-strain dependency.

Monograph Accession #:

01120148

Report/Paper Numbers:

09-2375

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Coleri, Erdem
Guler, Murat
Gungor, A. Gurkan
Harvey, John T

Pagination:

23p

Publication Date:

2009

Conference:

Transportation Research Board 88th Annual Meeting

Location: Washington DC, United States
Date: 2009-1-11 to 2009-1-15
Sponsors: Transportation Research Board

Media Type:

DVD

Features:

Figures (6) ; References (24) ; Tables (2)

Uncontrolled Terms:

Resilient modulus

Subject Areas:

Geotechnology; Highways; I42: Soil Mechanics

Source Data:

Transportation Research Board Annual Meeting 2009 Paper #09-2375

Files:

TRIS, TRB

Created Date:

Jan 30 2009 6:43PM