Overview of activities in stochastic data assimilation for applications in aerodynamics

Dwight, R P
De Baar, J H S
Sciacchitano, A
Perçin, Mustafa
Bijl, Hester
Scarano, Fulvio
In this conspectus paper we present a brief summary of a variety of recent activities in data assimilation performed at the Aerodynamics Section of the TU Delft. We hope to demonstrate a few of the exciting possibilities for combining experimental data and numerical models, improving the capability of both. Our activities are bound by a common theme of combining experimental wind-tunnel measurements and CFD simulations in order to (i) improve fidelity of experimental data, (ii) obtain estimates of unmeasured quantities, (iii) estimate modeling error and parametric uncertainty in simulation. The methodologies we use depends strongly on the application, but all have Bayesian inference at their root with some statistical model representing the relation between measurement and simulation. Bayesian statistics offers a coherent and flexible framework for describing solutions of the ill-posed problems that arise in this analysis of data, but new numerical methods are needed to find these solutions efficiently.


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Citation Formats
R. P. Dwight, J. H. S. De Baar, A. Sciacchitano, M. Perçin, H. Bijl, and F. Scarano, “Overview of activities in stochastic data assimilation for applications in aerodynamics,” Tokyo, Japonya, 2012, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/88126.