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, Türkiye, 25 - 28 Kasım 2021, ss.71-74, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1007/978-3-031-43218-7_17
  • Basıldığı Şehir: İstanbul
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.71-74
  • Anahtar Kelimeler: Artificial neural networks (ANNs), Bentonite–sand mixtures, Compaction, Consistency, Prediction
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

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.