Abstract
The structural condition of pavements can be evaluated properly by non-destructive surface deflection testing. Based on measured deflection responses of pavements to impact load, it is possible to estimate layer moduli through back analyses. For that purpose, typical constant values of Poisson’s ratio are commonly assumed for each layer material. In this work a thorough investigation to assess Poisson´s ratio influence on pavements response modeling is carried out. To this end, Artificial Neural Networks are proposed to Poisson´s ratio estimation from deflection testing data. A comparative analysis of pavement responses obtained under constant and variable conditions of Poisson’s ratio is performed.
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Beltrán, G., Romo, M. (2012). Analysis of Poisson’s Ratio Effect on Pavement Layer Moduli Estimation - A Neural Network Based Approach from Non-destructive Testing. In: Pavón, J., Duque-Méndez, N.D., Fuentes-Fernández, R. (eds) Advances in Artificial Intelligence – IBERAMIA 2012. IBERAMIA 2012. Lecture Notes in Computer Science(), vol 7637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34654-5_38
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DOI: https://doi.org/10.1007/978-3-642-34654-5_38
Publisher Name: Springer, Berlin, Heidelberg
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