International journal of computational fluid dynamics real-time prediction of unsteady flow based on POD reduced-order model and particle filter

2016 ◽  
Vol 30 (4) ◽  
pp. 285-306 ◽  
Author(s):  
Ryota Kikuchi ◽  
Takashi Misaka ◽  
Shigeru Obayashi
Author(s):  
LM Griffiths ◽  
AL Gaitonde ◽  
DP Jones ◽  
MI Friswell

Reduced order models of computational fluid dynamics codes have been developed to decrease computational costs; however, each reduced order model has a limited range of validity based on the data used in its construction. Further, like the computational fluid dynamics from which it is derived, such models exhibit differences from experimental data due to uncertainty in boundary conditions and numerical accuracy. Model updating provides the opportunity to use small amounts of additional data to modify the behaviour of a reduced order model, which means that the range of validity of the reduced order model can be extended. Whilst here computational fluid dynamics data have been used for updating, the approach offers the possibility that experimental data can be used in future. In this work, the baseline reduced order models are constructed using the Eigensystem realisation algorithm and the steps used to update these models are given in detail. The methods developed are then applied to remove the effects of wind tunnel walls and to include viscous effects.


AIAA Journal ◽  
2018 ◽  
Vol 56 (12) ◽  
pp. 4927-4943 ◽  
Author(s):  
Wang Chen ◽  
Jan S. Hesthaven ◽  
Bai Junqiang ◽  
Yasong Qiu ◽  
Zhang Yang ◽  
...  

2021 ◽  
Vol 54 (3) ◽  
pp. 103-108
Author(s):  
Pedro Reyero ◽  
Xinwei Yu ◽  
Carlos Ocampo-Martinez ◽  
Richard D. Braatz

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