Chapters authored
Space-Time Finite Element Method for Seismic Analysis of Concrete Dam
Finite element method (FEM) is the most extended approach for analyzing the design of the dams against earthquake motion. In such simulations, time integration schemes are employed to obtain the response of the dam at time tn+1 from the known response at time tn. To this end, it is desirable that such schemes are high-order accurate in time and remain unconditionally stable large time-step size can be employed to decrease the computation cost. Moreover, such schemes should attenuate the high-frequency components from the response of structure being studied. Keeping this in view, this chapter presents the theory of time-discontinuous space-time finite element method (ST/FEM) and its application to obtain the response of dam-reservoir system to seismic loading.
Part of the book: Dam Engineering
An Application of Particle Filter for Parameter Estimation and Prediction in Geotechnical Engineering
This chapter presents an application example of a nonlinear Kalman Filters (KFs), i.e., Particle Filter (PF), for state (or parameters) estimation and prediction of a dynamical system in geotechnical engineering. First key characteristics of dynamical systems in geotechnics, which need to be considered in filtering, are described by showing some figures, and why PF is necessary for geotechnical applications is explained. Then, a detailed algorithm and implementation of PF for geotechnical problems are presented with key equations. The PF is demonstrated through a case history focusing on deformation behavior of a ground due to embankment construction. The PF is applied to estimation of geotechnical parameters and predictions of future settlement behavior of the ground to discuss the effectiveness of the PF in geotechnical engineering. The results of the case history have shown that PF has presented great promise as an accurate parameter identification for a nonlinear dynamic model. The simulation with the identified parameters predicts the actual measurement data with high accuracy even though a limited amount of measurement data was used in identification stage. The PF provides more information on estimates than optimization methods because the estimates are obtained in the form of probability density functions (PDFs). This characteristic can contribute to risk analysis and reliability-based decision-making in geotechnical practice.
Part of the book: Applications and Optimizations of Kalman Filter and Their Variants