Asphalt concrete stability estimation from non-destructive test methods with artificial neural networks


TERZİ S., Karaşahin M., Gökova S., Tahta M., Morova N., UZUN İ.

Neural Computing and Applications, vol.23, no.3-4, pp.989-997, 2013 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 3-4
  • Publication Date: 2013
  • Doi Number: 10.1007/s00521-012-1023-1
  • Journal Name: Neural Computing and Applications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.989-997
  • Keywords: Light weight deflectometer, Marshall stability, Non-destructive testing, Nuclear Gauge
  • Istanbul Gelisim University Affiliated: No

Abstract

The core drilling method has often been used to determine the current status of asphalt concretes. However, this method is destructive so causes damage to the asphalt concretes. In addition, this method causes localized points of weakness in the asphalt concretes and is time consuming. In recent years, non-destructive testing methods have been used for pavement thickness estimation, determination of elasticity modulus, and density and moisture measurements. In this study, the above-mentioned non-destructive and destructive tests with data obtained by applying the Marshall stability to the same asphalt concretes were estimated using the artificial neural networks approach. © 2012 Springer-Verlag London Limited.