Backcalculation of pavement layer parameters using Artificial Neural Networks

In this paper, a new formulation based on Artificial Neural Networks (ANN) is presented for backcalculation of pavement layer moduli. In structural analysis of flexible pavements, the procedures as Layered Elastic Theory, Equivalent Layer Thickness (ELT), and Finite Elements Method (FEM) generally h...

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Bibliographic Details
Published in:Indian journal of engineering and materials sciences 2004-02, Vol.11 (1), p.38-42
Main Authors: Saltan, M, Terzi, S
Format: Article
Language:English
Online Access:Get full text
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Summary:In this paper, a new formulation based on Artificial Neural Networks (ANN) is presented for backcalculation of pavement layer moduli. In structural analysis of flexible pavements, the procedures as Layered Elastic Theory, Equivalent Layer Thickness (ELT), and Finite Elements Method (FEM) generally have complex formulations and give approximate results. Therefore, it is extremely difficult to perform realistic analysis for flexible pavements, especially in view of modelling the material properties of layers in these methods. Setting the finite element mesh and iteration procedure of backcalculation takes rather long time. The proposed ANN procedure requires significantly less computation time. ELT method is used for simplicity. It is impossible or very hard to model the visco-elastic and non-linear behaviour of layer materials in layered elastic theory. The use of ANN is proliferating with high rate in simulation. The ability of ANN is to learn complex nonlinear relationships. A new formulation using ANN is presented here.
ISSN:0971-4588