Settlements and angular distortions of shallow foundations on liquefiable soil

Abstract

The huge impact caused by liquefaction during past earthquakes has raised the need for predictive formulas applicable at the large scale to forecast the movement in the foundation caused by the seismic liquefaction phenomenon in sands. A method herein developed with this aim to quantify angular distortion of framed low-rise buildings based on simple characterization of the seismic input, subsoil and structure. The analysis moves from past literature criteria introduced to quantify the vulnerability of buildings under static conditions and extends their applicability to liquefaction assessment integrating recent literature predictive formulas, parametric two-dimensional numerical analyses and arti cial neural networks. Numerical calculation, performed for variable stratigraphic and mechanical characteristics of the subsoil, ground motion and equivalent exural stiffness of the building, quanti es the role of each factor on the absolute settlement and angular distortion. Then the dependency on the different factors of the angular distortion is inferred with an arti cial neural network (ANN), grouping parameters to limit the number of input variables and express results with charts that make prediction more accessible.