Assessment of liquefaction triggering using strain energy concept and ANN model: Capacity Energy

In the present study, an artificial neural network (ANN) model was developed to establish a correlation between soils initial parameters and the strain energy required to trigger liquefaction in sands and silty sands. A relatively large set of data including 284 previously published cyclic triaxial, torsional shear and simple shear test results were employed to develop the model. A subsequent parametric study was carried out and the trends of the results have been confirmed via some previous laboratory studies. In addition, the data recorded during some real earthquakes at Wildlife, Lotung and Port Island Kobe sites plus some available centrifuge tests data have been utilized in order to validate the proposed ANN-based liquefaction energy model. The results clearly demonstrate the capability of the proposed model and the strain energy concept to assess liquefaction resistance (capacity energy) of soils.