Abstract
Data assimilation is a generic technique which combines numerical simulation results with experimental data. In this paper, the ensemble Kalman filter (EnKF), which is categorized as sequential data assimilation techniques, is investigated when applied in fmite element analysis. The EnKF is a nonlinear extension of the standard Kalman filter, where a priori state estimates are provided by using the Monte Carlo method of nonlinear physical simulations. The estimates obtained in the EnKF can inherit many of the nonlinear properties of a priori state estimates. Through a simple numerical experiment, the effectiveness of the EnKF is examined.
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