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Known as a sophisticated phenomenon in civil engineering problems, soil structure interaction has been under deep investigations in the field of Geotechnics. On the other hand, advent of powerful computers has led to development of numerous numerical methods to deal with this phenomenon, resulting in a wide variety of methods trying to simulate the behavior of the soil stratum. This survey studies two common approaches to model the soilâ€™s behavior in a system consisting of a structure with two degrees of freedom, representing a two-storey frame structure made of steel, with the column resting on a pile embedded into sand in laboratory scale. The effect of soil simulation technique on the dynamic behavior of the structure is of major interest in the study. Utilized modeling approaches are the so-called Holistic method, and substitution of soil with respective impedance functions.

In order to minimize the probability of foundation failure resulting from cyclic action on structures, researchers have developed various constitutive models to simulate the foundation response and soil interaction as a result of these complex cyclic loads. The efficiency and effectiveness of these model is majorly influenced by the cyclic constitutive parameters. Although a lot of research is being carried out on these relatively new models, little or no details exist in literature about the model based identification of the cyclic constitutive parameters. This could be attributed to the difficulties and complexities of the inverse modeling of such complex phenomena. A variety of optimization strategies are available for the solution of the sum of least-squares problems as usually done in the field of model calibration. However for the back analysis (calibration) of the soil response to oscillatory load functions, this paper gives insight into the model calibration challenges and also puts forward a method for the inverse modeling of cyclic loaded foundation response such that high quality solutions are obtained with minimum computational effort. Therefore model responses are produced which adequately describes what would otherwise be experienced in the laboratory or field.