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A data-driven adaptive reduced order modelling approach is presented for the reconstruction of impulsively started and vortex-dominated flows. A residual-based error metric is presented for the first time in the framework of the adaptive approach. The residual-based adaptive Reduced Order Modelling selects locally in time the most accurate reduced model approach on the basis of the lowest residual produced by substituting the reconstructed flow field into a finite volume discretisation of the Navier−Stokes equations. A study of such an error metric was performed to assess the performance of the resulting residual-based adaptive framework with respect to a single-ROM approach based on the classical proper orthogonal decomposition, as the number of modes is varied. Two- and three-dimensional unsteady flows were considered to demonstrate the key features of the method and its performance.
|Number of pages||30|
|Early online date||6 Apr 2022|
|Publication status||Published - 6 Apr 2022|
- data-driven reduced order modelling
- unsteady aerodynamics
- vortex-dominated flows
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- 1 Active
Robust- and sustainable-by-design ultra-higH aspEct ratio wing and Airframe (RHEA) H2020
European Commission - Horizon 2020
1/07/20 → 31/12/23