Estimation of specific gravity with penetration and penetration index parameters by artificial neural network

Serin S., KARAHANÇER Ş., ERİŞKİN E., MOROVA N., SALTAN M., TERZİ S.

Periodicals of Engineering and Natural Sciences, vol.5, no.2, pp.161-164, 2017 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 5 Issue: 2
  • Publication Date: 2017
  • Doi Number: 10.21533/pen.v5i2.106
  • Journal Name: Periodicals of Engineering and Natural Sciences
  • Journal Indexes: Scopus
  • Page Numbers: pp.161-164
  • Keywords: Artifical neural network, Penetration, Penetration index, Specific gravity
  • Isparta University of Applied Sciences Affiliated: No

Abstract

Specific Gravity of the bitumen changes according to the ambient temperature. Different specific gravity values can be calculated at different temperature. Estimating models like Artificial Neural Network - ANN could be very useful to obtain the specific gravity value uniform. Specific gravity values obtained from Long-Term Pavement Performance - LTPP were estimated with artificial neural networks. Penetration and Penetration Index of binder were used for estimating the specific gravity of the bitumen. As a result, ANN get 84% of R2 between obtained and estimated values.