Some emprical equations for predicting standard penetration test blow counts in clayey soils: a case study in Mersin, Turkey


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Kayabaşı A.

ARABIAN JOURNAL OF GEOSCIENCES, cilt.8, ss.7643-7654, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1007/s12517-014-1694-2
  • Dergi Adı: ARABIAN JOURNAL OF GEOSCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.7643-7654
  • Anahtar Kelimeler: Regression, Activity, Consistency, SPT, Clayey soil, SHEAR-WAVE VELOCITY, UNIAXIAL COMPRESSIVE STRENGTH, ROCK, RESISTANCE, PRESSURE, SIZE, SPT
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

The standard penetration test (SPT) is a widespread test used in situ. Soil mechanical properties such as grain-size content, moisture content, atterberg limits, activity of clay, and consistency of clay determine the SPT blow count. In addition, the SPT blow count reflects the soil mechanical and compressibility parameters. The purpose of this study is to determine the clayey soil states that determine the SPT blow count number; 220 data points derived from a foundation investigation of a sewerage project in Mersin City were used in the study. The Mersin sewerage project includes the sewerage station, central pumping station, and west pumping station in Mersin city, Turkey. The corrected SPT blow counts (N (60)) and corresponding parameters (fine-grain size percent, liquid limit, plastic limit, plasticity index, moisture content, activity, and consistency) of the clayey soil from these locations were used in a series of simple and nonlinear multiple regression analyses. Based on the analyses, the acceptable results have been determined by a simple regression analyses between the corrected SPT blow counts and the following input parameters: activity, moisture content (in percent), fine-grained percent (in percent). The simple regression analyses for N (60)-LL (in percent), N (60)-PL (in percent), and N (60)-PI (in percent) are considered unacceptable so these parameters are not evaluated as input parameters in the multiple regression analyses. Multiple regression analyses with two independent input parameters produces acceptable results. The optimal equation is determined with multiple regression analyses using activity and moisture content as the input parameters; this equation has a coefficient of determination of R (2) = 0.78. The prediction capability of the developed equations is also acceptable. However, the prediction equations proposed in this study are developed with a limited number of data points. For this reason, a cross-check should be performed before using these empirical equations for design purposes.