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Artificial Neural Network Models for Assessing Remaining Life of Flexible Pavements
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2000-05-01
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[PDF-1.71 MB]
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Alternative Title:Development of a Comprehensive, Rational Method for Determination of Remaining Life of an Existing Pavement [Project title from cover]
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Edition:Interim Report Sept. 1, 1998 –Aug 31, 1999
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Abstract:Most mechanistic-empirical methods for determining the integrity of an existing pavement rely on the use of deflection-based nondestructive evaluation devices to determine the integrity of a pavement section. To estimate the remaining life associated with two types of distress in a flexible pavement, namely fatigue cracking and rutting, the critical strains and stresses at the interfaces of the layers of the pavement should be known. After the critical strains are calculated, a number of models can be used to estimate the remaining life. This report presents a case study that shows the feasibility of using an algorithm based on artificial neural network technology (ANN) to estimate the remaining life of flexible pavements. The report includes, in detail, the development and results of a system of ANN models that have been developed to predict the critical strains for a wide range of three- and four-layer flexible pavement sections with variable depth to bedrock. The inputs to these ANN models are only the best estimates of the thickness of each layer and the surface deflections obtained from a Falling Weight Deflectometer (FWD).
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