Non-Linear reduced order modelling of transonic potential flows for fast aerodynamic analysis
This work presents a physics-based reduced order modelling (ROM) framework for the efficient simulation of steady transonic potential flows around aerodynamic configurations. The approach leverages proper orthogonal decomposition and a least-squares Petrov-Galerkin (LSPG) projection to construct int...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/450926 |
| Acceso en línea: | https://hdl.handle.net/2117/450926 https://dx.doi.org/10.1002/nme.70251 |
| Access Level: | acceso abierto |
| Palabra clave: | Reduced Order Modelling Model Order Reduction Proper Orthogonal Decomposition Least-Squares Petrov-Galerkin Transonic Potential Flow Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics |
| Sumario: | This work presents a physics-based reduced order modelling (ROM) framework for the efficient simulation of steady transonic potential flows around aerodynamic configurations. The approach leverages proper orthogonal decomposition and a least-squares Petrov-Galerkin (LSPG) projection to construct intrusive ROMs for the full potential equation. To improve accuracy in regions affected by strong gradients and shock waves, a spatially weighted LSPG formulation is introduced, yielding enhanced robustness compared to unweighted projection. The ROM training relies on a non-linear -transformed Halton sampling of the parameter space, which concentrates samples in shock-prone regimes and improves generalization without increasing offline cost. The methodology is implemented within the open-source Kratos Multiphysics framework and validated on two benchmark configurations: the 2D NACA 0012 airfoil and the 3D ONERA M6 wing. The resulting ROMs achieve accurate reconstructions of aerodynamic fields and coefficients, with relative errors on the order of , while reducing the dimensionality of the full order models by approximately three orders of magnitude. Although the corresponding speed-ups ( in 2D and in 3D) remain modest for the present linear subspace setting, the results highlight the potential of physics-based intrusive ROMs as reliable surrogates for transonic flows. In the shock-dominated regimes examined, the proposed intrusive ROM provides more accurate and physically consistent solutions than standard data-driven surrogates. The framework provides a solid baseline for future extensions incorporating hyper-reduction and non-linear ROM strategies. |
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