Investigations into factors influencing the CBR values of some Aegean sands

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Erzin Y., Turkoz D., Tuskan Y., Yilmaz I.

SCIENTIA IRANICA, cilt.23, sa.2, ss.420-428, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 23 Sayı: 2
  • Basım Tarihi: 2016
  • Doi Numarası: 10.24200/sci.2016.2128
  • Dergi Adı: SCIENTIA IRANICA
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.420-428
  • Anahtar Kelimeler: Aegean sands, California bearing ratio, Experimental investigations, Particle morphology, Multiple regression analysis, CALIFORNIA BEARING RATIO, FINE-GRAINED SOILS, NEURAL-NETWORKS, SWELL PRESSURE, PREDICTION, SAFETY, SETTLEMENT, FOOTINGS, MODULUS, MODELS
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

The California Bearing Ratio (CBR) value of the soils is very important for geotechnical engineering and earth structures. A CBR value is affected by the soil type and different soil properties. With this in view, in this paper, an attempt has been made for investigating the factors that affect the CBR values of some Aegean sands collected from nine different locations in Manisa (Turkey). The sand samples were tested for mineralogy, particle shape and size, and specific gravity. The CBR tests were then performed on these samples at different dry densities to examine the influence of dry density, relative density, water content, and particle shape and size on the CBR value. Multiple Regression Analysis (MRA) was performed to predict the CBR value of the sands by using the experimental results. Moreover, several performance indices, such as coefficient of correlation and variance account for mean absolute error and root mean square error, were calculated to check the prediction capacity of the proposed MR equation. The obtained indices make it clear that the equation derived from the samples used in this study applies well, with an acceptable accuracy, to the CBR estimation at the preliminary stage of site investigations. (c) 2016 Sharif University of Technology. All rights reserved.