l1-based calibration of POD-Galerkin models of two-dimensional unsteady flows

Rubini, Riccardo; Lasagna, Davide; Ronch, Andrea Da

doi:10.1016/j.cja.2020.10.009

Cited by 2 publications

(2 citation statements)

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“…This suggests that including in the optimisation information on how modal structures are supposed to interact with each other to satisfy the overall power budget is key to obtaining sparse Galerkin models with adequate predictive ability. Note that the long-term performance of the models obtained in the present work is generally superior to that of models sparsified a posteriori, using a LASSO-based approach (Rubini et al 2020b;Rubini, Lasagna & Da Ronch 2020a). More specifically, LASSO-based models have been found to be temporally accurate over a time span comparable to that of the data used for the sparsification.…”

Section: Interactions Identified In the Sparse Modelmentioning

confidence: 65%

“…Note that the long-term performance of the models obtained in the present work is generally superior to that of models sparsified a posteriori , using a LASSO-based approach (Rubini et al. 2020 b ; Rubini, Lasagna & Da Ronch 2020 a ). More specifically, LASSO-based models have been found to be temporally accurate over a time span comparable to that of the data used for the sparsification.…”

Section: Demonstration: Two-dimensional Lid-driven Unsteady Cavity Flowmentioning

confidence: 68%

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A priorisparsification of Galerkin models

2022

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A methodology to generate sparse Galerkin models of chaotic/unsteady fluid flows containing a minimal number of active triadic interactions is proposed. The key idea is to find an appropriate set of basis functions for the projection representing elementary flow structures that interact minimally one with the other, resulting in a triadic interaction coefficient tensor with sparse structure. Interpretable and computationally efficient Galerkin models are obtained, since a reduced number of triadic interactions are computed to evaluate the right-hand side of the model. To find the basis functions, a subspace rotation technique is used, whereby a set of proper orthogonal decomposition (POD) modes is rotated into a POD subspace of larger dimension using coordinates associated with low-energy dissipative scales to alter energy paths and the structure of the triadic interaction coefficient tensor. This rotation is obtained as the solution of a non-convex optimisation problem that maximises the energy captured by the new basis, promotes sparsity and ensures long-term temporal stability of the sparse Galerkin system. We demonstrate the approach on two-dimensional lid-driven cavity flow at $Re = 2 \times 10^4$ where the motion is chaotic and energy interactions are scattered in modal space. We show that the procedure generates Galerkin models with a reduced set of active triadic interactions, distributed in modal space according to established knowledge of scale interactions in two-dimensional flows. This property, however, is observed only if long-term temporal stability is included explicitly in the formulation, indicating that a dynamical constraint is necessary to obtain a physically consistent sparsification.

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Section: Interactions Identified In the Sparse Modelmentioning

confidence: 65%

Section: Demonstration: Two-dimensional Lid-driven Unsteady Cavity Flowmentioning

confidence: 68%