Failure Envelopes for Combined Loading of Skirted Foundations in Layered Deposits

Autor: Vali Ghaseminejad, Lars Bo Ibsen, Amin Barari
Rok vydání: 2021
Předmět:
Zdroj: Barari, A, Ghaseminejad, V & Ibsen, L B 2021, ' Failure Envelopes for Combined Loading of Skirted Foundations in Layered Deposits ', Journal of Waterway, Port, Coastal, and Ocean Engineering, vol. 147, no. 4, 04021008 . https://doi.org/10.1061/(ASCE)WW.1943-5460.0000639
ISSN: 1943-5460
0733-950X
DOI: 10.1061/(asce)ww.1943-5460.0000639
Popis: A robust and integrated interpretation of soil data from field investigations can provide valuable insights into the important role of soil deterioration following the installation of suction caissons. Therefore, a field experiment was conducted at a site in Frederikshavn to simulate laterally loaded suction caisson in a layered soil profile. The experiment was performed to validate our modeling approach and to systematically analyze the predictive capabilities of three classes of numerical predictions (Classes A, A1, and C). The Class A1 prediction focused primarily on the trajectory of the rotation center and the capacity of existing failure criteria to predict the bearing strength of shallow foundations under combined loading, despite differences in stress conditions, foundation geometries, and soil weakening due to the installation effect. On the other hand, the Class A prediction was carried out based on wished-in-place conditions. Failure envelopes within the Class C predictions were adopted to be scaled by the pure bearing capacities (given by intersections with the axes). Subsequently, the appropriateness of identical envelopes was examined here by employing three-dimensional finite-element analyses in the presence of the parabolic variations in soil stiffness with depth. An alternative macroelement model of varying failure surface parameters was also represented, which enables the bearing capacity of skirted foundations to be predicted for a wide range of embedment ratios and sand strength inhomogeneities.
Databáze: OpenAIRE