Evaluation of the relationships between the laboratory and in situ test results carried out on clayey soils with multiple regression analysis: Van (Turkey) reverse fault area


Özvan E. E., Çetin H., Özvan A., Akkaya İ.

ARABIAN JOURNAL OF GEOSCIENCES, cilt.15, ss.1-17, 2022 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 15
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s12517-022-10236-w
  • Dergi Adı: ARABIAN JOURNAL OF GEOSCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aquatic Science & Fisheries Abstracts (ASFA), Geobase, INSPEC
  • Sayfa Sayıları: ss.1-17
  • Van Yüzüncü Yıl Üniversitesi Adresli: Evet

Özet

Many in situ and laboratory tests are being performed to determine the engineering properties of soils. Several relationships

can be established between in situ tests and laboratory tests to ensure that both achieve similar results. In this study, in situ

standard penetration test and Menard pressuremeter tests were performed on the clayey samples that are in high and low

plasticity soil class taken from 6 boreholes reaching to the hanging walls and footwalls of the thrust fault. Disturbed and

undisturbed samples were collected in the field, and their physical and mechanical properties were determined in the laboratory.

Corrected SPT (SPT-N60), Menard deformation modulus (EM), and net limit pressure (PL) values were obtained as part

of in situ tests performed. These values were then compared with physical properties like the liquid limit, plasticity index,

natural moisture content (w), and mechanical properties like the pre-consolidation pressure (σpc) and cohesion (c) that were

determined through laboratory tests, and linear and non-linear multiple regression analyses were performed on them. The

analyses revealed multiple regression equations between dependent variable EM and independent variables SPT-N60, w, c,

and σpc were obtained with a high degree of determination coefficient. The results also indicate that these multiple regression

equations obtained thusly so provided more accurate results compared to simple regression correlations.