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- W2223402934 abstract "Abstract One of the most common end applications of process tomography is acquiring information of the related flow. Usually, the information is accessed indirectly by computing single time-lapse estimates of the parameter that is being imaged, such as conductivity, permittivity or density, and then the sequence of images is analysed to infer some characteristics of the flow. Sometimes correlation information on the measurement stream is also used to obtain information on the mean flow. In this chapter, we focus on the state estimation approach, which can be used to access information on the flow field based on explicit modelling of the related transport phenomena. The state estimation approach separates the model for the measurements and the model for the evolution of all time-varying quantities. As an example, we consider electrical impedance tomography as the imaging, modality and advection-diffusion and Navier–Stokes models as the model for the flow. The central topic here is how to derive the related stochastic versions of the measurement and evolution models. In particular, we consider the problems that are related to unknown boundary conditions and model reduction." @default.
- W2223402934 created "2016-06-24" @default.
- W2223402934 creator A5002584145 @default.
- W2223402934 creator A5019048266 @default.
- W2223402934 creator A5032158182 @default.
- W2223402934 creator A5034132148 @default.
- W2223402934 creator A5037873130 @default.
- W2223402934 creator A5044253587 @default.
- W2223402934 creator A5051527924 @default.
- W2223402934 date "2015-01-01" @default.
- W2223402934 modified "2023-10-17" @default.
- W2223402934 title "Process tomography and estimation of velocity fields" @default.
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