A numerical investigation of data-driven closure techniques for POD-Galerkin reduced order models

Autor(es)

Zucatti, Victor ; Wolf, William R.

• Tipo de documento: Artigo Científico
• Fonte: AIAA AVIATION 2022 FORUM; v. N/A, p. 13-pg., 2022-01-01.

Resumo

Data-driven closure techniques are assessed for applications in POD-Galerkin reduced order modeling. Closure is based on optimization with respect to temporal modes of the proper orthogonal decomposition (POD) basis and significantly improve the models' performance for computing unsteady compressible flows. Model reduction is obtained via Galerkin projection of the spatial POD modes on the non-conservative compressible Navier-Stokes equations. Closure is performed by adding linear and nonlinear coefficients to the original ROMs and minimizing the error with respect to the POD temporal modes. The effects of adding energy preserving constraints to this minimization problem is also analysed. In this work, the test problems consist of the canonical low Reynolds compressible flow around a circular cylinder and a moderate Reynolds number subsonic flow over an airfoil. In the latter case, boundary layer instabilities are responsible for tonal noise emission at multiple frequencies due to frequency and amplitude modulations induced by a separation bubble developing on the airfoil suction side. Results show that nonlinear calibration coefficients outperform their linear counterparts for the present simulations. (AU)

• Processo FAPESP: 13/08293-7 - CECC - Centro de Engenharia e Ciências Computacionais
• Beneficiário: Munir Salomao Skaf
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 21/06448-0 - Simulações numéricas de alta fidelidade aplicadas em aerodinâmica não-estacionária, turbulência e aeroacústica
• Beneficiário: William Roberto Wolf
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores - Fase 2
• Processo FAPESP: 18/11410-9 - Utilização da análise de componentes principais para a construção de modelos de ordem reduzida
• Beneficiário: Victor Zucatti da Silva
• Modalidade de apoio: Bolsas no Brasil - Mestrado