Identification of parameters in nonlinear geotechnical models using extenden Kalman filter

Direct measurement of relevant system parameters often represents a problem due to different limitations. In geomechanics, measurement of geotechnical material constants which constitute a material model is usually a very difficult task even with modern test equipment. Back-analysis has proved to be a more efficient and more economic method for identifying material constants because it needs measurement data such as settlements, pore pressures, etc., which are directly measurable, as inputs. Among many model parameter identification methods, the Kalman filter method has been applied very effectively in recent years. In this paper, the extended Kalman filter - local iteration procedure incorporated with finite element analysis (FEA) software has been implemented. In order to prove the efficiency of the method, parameter identification has been performed for a nonlinear geotechnical model.