Field data based method for predicting long-term settlements
RIS ID
110452
Abstract
The estimation of the long-term foundation settlement in soft soil is very complex, which is attributed to a number of uncertainties associated with various factors, such as: (i) The compressibility parameters obtained in the laboratory from samples of relatively small size that are more homogeneous compared to heterogeneous field sediments in which various soil types may be interlayered at random and may occur without exhibiting any real stratification; (ii) limitations and unrealistic assumptions prevailing in the conventional consolidation analysis. These have often resulted in the large discrepancy between actual in-situ settlements and the predictions from the conventional consolidation models (e.g., Terzaghi's model). In this study, a field data based method inspired from an observational approach is proposed and validated against a number of high quality long-term field settlement data. Moreover, the corresponding geological soil properties obtained from field and laboratory tests have been presented, with the aim of providing useful practical references for other projects with similar geological profile. Furthermore, the proposed model is compared with existing prediction models. The results show that the newly proposed model can provide more reliable and accurate prediction of foundation settlements compared with other methods established in practice.
Publication Details
Jiang, J., Chen, Q. & Nimbalkar, S. (2016). Field data based method for predicting long-term settlements. American Journal of Engineering and Applied Sciences, 9 (3), 466-476.