Cyclic Direct Shear Testing of a Sand with Waste Tires

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Yıldız Ö., Cabalar A. F.

Sustainability (Switzerland), cilt.14, sa.24, 2022 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 24
  • Basım Tarihi: 2022
  • Doi Numarası: 10.3390/su142416850
  • Dergi Adı: Sustainability (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Aerospace Database, CAB Abstracts, Communication Abstracts, Food Science & Technology Abstracts, Geobase, INSPEC, Metadex, Veterinary Science Database, Directory of Open Access Journals, Civil Engineering Abstracts
  • Anahtar Kelimeler: cyclic direct shear test, prediction model, sand, waste tire
  • Yıldız Teknik Üniversitesi Adresli: Hayır

Özet

This study investigates the cyclic behavior of sand mixed with waste tires by using a series of strain-controlled cyclic direct shear tests under constant normal load (CNL) conditions. Crushed Stone Sand (CSS) was used in the experimental studies. The sand grains have angular shapes and sizes changing from 1.0 mm to 2.0 mm. Two different types of waste tires were used in the experiments; (i) tire crumb (TC), and (ii) tire buffing (TB). The TC grains have an angular shape and size between 1.0 mm and 2.0 mm, whereas TB grains used were found to be fiber-shaped, with dimensions changing from 1 mm to 9 mm, and an aspect ratio of about 1:5. The tests were carried out under 100 kPa vertical effective stress on the sand with 0%, 2.5%, 5%, 7.5%, and 10% waste tire contents. The testing results were found to be highly dependent on both the type and amount of waste tires in the mixtures. Furthermore, the behavior of the mixtures was estimated by the Bayesian Regularization Neural Network (BRNN) prediction model, for further use by researchers. The performance of the proposed BRNN model was found to provide a quite high correlation coefficient (R2 = 0.96).