Document Type

Thesis

Degree

Master of Science (MS)

Department

Civil Engineering

First Advisor's Name

Sylvan C. Jolibois

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Nii Busby Attoh-Okine

Third Advisor's Name

L. David Shen

Date of Defense

4-10-1996

Abstract

The estimation of pavement layer moduli through the use of an artificial neural network is a new concept which provides a less strenuous strategy for backcalculation procedures. Artificial Neural Networks are biologically inspired models of the human nervous system. They are specifically designed to carry out a mapping characteristic. This study demonstrates how an artificial neural network uses non-destructive pavement test data in determining flexible pavement layer moduli. The input parameters include plate loadings, corresponding sensor deflections, temperature of pavement surface, pavement layer thicknesses and independently deduced pavement layer moduli.

Identifier

FI13101529

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