A POD-based reduced-order model for uncertainty analyses in shallow water flows

2018 ◽  
Vol 32 (6-7) ◽  
pp. 278-292 ◽  
Author(s):  
Jean-Marie Zokagoa ◽  
Azzeddine Soulaïmani
Keyword(s):  
Shallow Water ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Water Flows ◽  
Shallow Water Flows ◽  
Uncertainty Analyses

scholarly journals POD-DEIM Based Model Order Reduction for the Spherical Shallow Water Equations with Turkel-Zwas Finite Difference Discretization

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Pengfei Zhao ◽  
Cai Liu ◽  
Xuan Feng
Keyword(s):  
Computational Complexity ◽  
Shallow Water ◽  
Shallow Water Equations ◽  
Model Order Reduction ◽  
Order Reduction ◽  
Reduced Order Model ◽  
Order Model ◽  
Time Step ◽  
Model Order ◽  
Reduced Order

We consider the shallow water equations (SWE) in spherical coordinates solved by Turkel-Zwas (T-Z) explicit large time-step scheme. To reduce the dimension of the SWE model, we use a well-known model order reduction method, a proper orthogonal decomposition (POD). As the computational complexity still depends on the number of variables of the full spherical SWE model, we use discrete empirical interpolation method (DEIM) proposed by Sorensen to reduce the computational complexity of the reduced-order model. DEIM is very helpful in evaluating quadratically nonlinear terms in the reduced-order model. The numerical results show that POD-DEIM is computationally very efficient for implementing model order reduction for spherical SWE.

scholarly journals A greedy non-intrusive reduced order model for shallow water equations

2021 ◽  
pp. 110378
Author(s):  
Sourav Dutta ◽  
Matthew W. Farthing ◽  
Emma Perracchione ◽  
Gaurav Savant ◽  
Mario Putti
Keyword(s):  
Shallow Water ◽  
Shallow Water Equations ◽  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order
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