Reduced basis approximation and a posteriori error estimation for affinely parametrized elliptic coercive partial differential equations: Application to transport and continuum mechanics
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A novel method is presented for estimating the elastic and dissipative parameters of composite plates and shells through a mixed numerical-experimental identification procedure based on the natural frequencies, modal damping factors and mode shapes of the ...
We study the problem of distributed estimation, where a set of nodes are required to collectively estimate some parameter of interest from their measurements. Diffusion algorithms have been shown to achieve good performance, increased robustness and are am ...
The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...
This work focuses on the approximation of parametric steady Navier-- Stokes equations by the reduced basis method. For a particular instance of the parameters under consideration, we are able to solve the underlying partial differential equations, compute ...
In this paper we deal with reduced basis techniques applied to Stokes equations. We consider domains with different shape, parametrized by affine and non-affine maps with respect to a reference domain. The proposed method is ideally suited for the repeated ...
In this chapter we describe the basic ideas of reduced basis (RB) approximation methods for rapid and reliable evaluation of input-output relationships in which the output is expressed as a functional of a field variable that is the solution of an input-pa ...
Joint processing of sensor array outputs improves the performance of parameter estimation and hypothesis testing problems beyond the slim of the individual sensor processing results. When the sensors have high data sampling rates, arrays are tethered, crea ...
We propose the reduced basis method for the solution of parametrized optimal control problems described by parabolic partial differential equations in the unconstrained case. The method, which is based on an off-line–on-line decomposition procedure, allows ...
This paper describes the use of an a posteriori error estimator to control anisotropic mesh adaptation for computing inviscid compressible flows. The a posteriori error estimator and the coupling strategy with an anisotropic remesher are first introduced. ...
We have developed a model for pedestrian walking behavior, based on discrete choice modeling. The model is estimated by maximum likelihood estimation on a real data set of pedestrian trajectories, manually tracked from video sequences filmed in Japan. The ...