Physics-Informed Data-Driven Prediction of Turbulent Reacting Flows with Lyapunov Analysis and Sequential Data Assimilation

Author(s):  
Luca Magri ◽  
Nguyen Anh Khoa Doan
2011 ◽  
Vol 21 (12) ◽  
pp. 3619-3626 ◽  
Author(s):  
ALBERTO CARRASSI ◽  
STÉPHANE VANNITSEM

In this paper, a method to account for model error due to unresolved scales in sequential data assimilation, is proposed. An equation for the model error covariance required in the extended Kalman filter update is derived along with an approximation suitable for application with large scale dynamics typical in environmental modeling. This approach is tested in the context of a low order chaotic dynamical system. The results show that the filter skill is significantly improved by implementing the proposed scheme for the treatment of the unresolved scales.


2001 ◽  
Vol 15 (1) ◽  
pp. 65-86 ◽  
Author(s):  
J. Sénégas ◽  
H. Wackernagel ◽  
W. Rosenthal ◽  
T. Wolf

2012 ◽  
Vol 231 (19) ◽  
pp. 6401-6418 ◽  
Author(s):  
Akil Narayan ◽  
Youssef Marzouk ◽  
Dongbin Xiu

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