Karacabey yumuşak killerindeki konsolidasyon oturmalarının değerlendirilmesi: Tahmin edilen ve gözlemlenen davranışı

Settlement of highway embankments constructed over clayey soft soils is a major problem encountered in maintaining highway facilities. Accurate estimation of consolidation settlement amounts and times has been a challenge for engineers in practice. In this study, field settlement measurements of 26 stations between 600 and 750 days of durations in Karacabey NC clays and comparison of these measured magnitudes of settlements with calculated settlements from oedometer tests are assessed. The correlation between predicted settlements using oedometer test data and observed settlements in the field is proposed. Stroud approaches are compared with the coefficients of volume compressibility back calculated and their trend is presented. The relationship between tip resistance (qc) of cone penetration test and constrained modulus is investigated. The magnitudes of final settlements are estimated by using Asaoka and Horn's extrapolation methods including 70% of the monitored settlement data. Furthermore, time data versus field settlement are used to predict the primary consolidation amounts. Equations providing correction factors to the magnitudes of settlements, calculated by oedometer results, are formed to estimate the magnitudes of settlements that would occur in the field. Karacabey clays exhibit typical secondary consolidation behaviors. Tertiary consolidation behaviors are also observed in 11 of total 26 stations. Cs/Cc and Ct/Cc ranges are recommended for engineering practices to predict the secondary and tertiary consolidation settlements. In addition, the relationship between the compression index (Cc) and the secondary and tertiary consolidation coefficients (Cs-Ct) is investigated, and relations, in which laboratory data and idealized geological profile geometry are evaluated as numerical parameters, are proposed. Studies have shown that there is a nonlinear relationship rather than a linear one between independent variables and targeted dependent variables, and iterative non-linear regression analysis are performed to drive the assumed equation model.