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Uncertainty Quantification (UQ) is highly requested in computational modeling and simulation, especially in an industrial context. A main challenge is related to the fact that computational models are rarely able to represent the true physics perfectly and demonstrate a discrepancy compared to measurement data. Further, an accurate knowledge of considered model parameters is usually not available...
In future the model quality will have an increasing priority in the industrial context and suitable techniques and methods to quantify them have to be developed. In this paper we want to focus on the challenge of selecting the most informative measurement data for a time‐dependent simulation model to infer parameter distributions. Sobol indices are used to give a estimate about the global sensitivity...
We sketch a non‐overlapping domain decomposition method (DDM) for a linear quadratic optimal control problem governed by the Oseen equations. The DDM is applied to the system of necessary and sufficient optimality conditions. The approach extends balanced Neumann Neumann DDMs from single partial differential equations (PDEs) to the optimization control context, and it extends previous work on balanced...
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