scholarly journals Data-driven closure of projection-based reduced order models for unsteady compressible flows

2021 ◽  
Vol 386 ◽  
pp. 114120
Author(s):  
Victor Zucatti ◽  
William Wolf
Keyword(s):  
Compressible Flows ◽  
Data Driven ◽  
Reduced Order Models ◽  
Reduced Order

scholarly journals Data-driven variational multiscale reduced order models

2021 ◽  
Vol 373 ◽  
pp. 113470 ◽  
Author(s):  
Changhong Mou ◽  
Birgul Koc ◽  
Omer San ◽  
Leo G. Rebholz ◽  
Traian Iliescu
Keyword(s):  
Data Driven ◽  
Reduced Order Models ◽  
Reduced Order ◽  
Variational Multiscale

scholarly journals Data-driven reduced-order models for rank-ordering the high cycle fatigue performance of polycrystalline microstructures

2018 ◽  
Vol 154 ◽  
pp. 170-183 ◽  
Author(s):  
Noah H. Paulson ◽  
Matthew W. Priddy ◽  
David L. McDowell ◽  
Surya R. Kalidindi
Keyword(s):  
High Cycle Fatigue ◽  
Fatigue Performance ◽  
Data Driven ◽  
Reduced Order Models ◽  
Cycle Fatigue ◽  
Reduced Order ◽  
Rank Ordering

Data-driven construction of a reduced-order model for supersonic boundary layer transition

2019 ◽  
Vol 874 ◽  
pp. 1096-1114 ◽  
Author(s):  
Ming Yu ◽  
Wei-Xi Huang ◽  
Chun-Xiao Xu
Keyword(s):  
Compressible Flows ◽  
Incompressible Flows ◽  
Temporal Evolution ◽  
Reduced Order Model ◽  
Boundary Layer Transition ◽  
Galerkin Projection ◽  
Data Driven ◽  
Dynamic Mode ◽  
Order Model ◽  
Reduced Order

In this study, a data-driven method for the construction of a reduced-order model (ROM) for complex flows is proposed. The method uses the proper orthogonal decomposition (POD) modes as the orthogonal basis and the dynamic mode decomposition method to obtain linear equations for the temporal evolution coefficients of the modes. This method eliminates the need for the governing equations of the flows involved, and therefore saves the effort of deriving the projected equations and proving their consistency, convergence and stability, as required by the conventional Galerkin projection method, which has been successfully applied to incompressible flows but is hard to extend to compressible flows. Using a sparsity-promoting algorithm, the dimensionality of the ROM is further reduced to a minimum. The ROMs of the natural and bypass transitions of supersonic boundary layers at $Ma=2.25$ are constructed by the proposed data-driven method. The temporal evolution of the POD modes shows good agreement with that obtained by direct numerical simulations in both cases.

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