ANNs-Based Prediction Models for Consistency and Compaction Characteristics of Bentonite–Sand Mixtures

Yücel M., AKBAY ARAMA Z., Gençdal H. B., BAŞBUĞ B., SEÇKİN E.

1st International conference on Mediterranean Geosciences Union, MedGU 2021, İstanbul, Turkey, 25 - 28 November 2021, pp.71-74, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1007/978-3-031-43218-7_17
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.71-74
  • Keywords: Artificial neural networks (ANNs), Bentonite–sand mixtures, Compaction, Consistency, Prediction
  • Istanbul University-Cerrahpasa Affiliated: Yes

Abstract

This study is fictionalized with the use of ANNs logic to estimate the compaction parameters of bentonite–sand mixtures. Totally 230 sets of tests were digitized from the nine well-accepted literature sources to specify the grain size, consistency, and compaction parameters of the bentonite–sand mixtures. Matlab R2018a software is used to perform the estimation process of the compaction parameters, and representative expressions were derived to ease the determination process of mixtures. Consequently, the applicability of the suggested expressions has been checked by the determination and comparison of well-known international metric measurements.