Unsteady physics-based reduced order modeling for large-scale compressible aerodynamic applications
From MaRDI portal
Publication:2139580
DOI10.1016/j.compfluid.2022.105385OpenAlexW4220977206MaRDI QIDQ2139580
Publication date: 18 May 2022
Published in: Computers and Fluids (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.compfluid.2022.105385
computational fluid dynamicsunsteady motionlarge-scale civil aircraftphysics-based reduced order modelunsteady reduced order model
Related Items (1)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The GNAT method for nonlinear model reduction: effective implementation and application to computational fluid dynamics and turbulent flows
- Data-driven POD-Galerkin reduced order model for turbulent flows
- Model order reduction: Theory, research aspects and applications. Selected papers based on the presentations at the workshop `Model order reduction, coupled problems and optimization', Leiden, The Netherlands, September 19--23, 2005.
- Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier-Stokes equations
- A flexible symmetry-preserving Galerkin/POD reduced order model applied to a convective instability problem
- An `empirical interpolation' method: Application to efficient reduced-basis discretization of partial differential equations
- Windowed space-time least-squares Petrov-Galerkin model order reduction for nonlinear dynamical systems
- A hybrid reduced order method for modelling turbulent heat transfer problems
- A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
- An Accelerated Greedy Missing Point Estimation Procedure
- Nonlinear Model Reduction via Discrete Empirical Interpolation
- Dynamic mode decomposition of numerical and experimental data
- 1 Model order reduction: basic concepts and notation
- A linearized unsteady aerodynamic analysis for transonic cascades
- Turbulence and the dynamics of coherent structures. I. Coherent structures
- Data-Driven Science and Engineering
- Missing Point Estimation in Models Described by Proper Orthogonal Decomposition
- Interpolation-based reduced-order modelling for steady transonic flows via manifold learning
- Deep learning in fluid dynamics
- Localized Discrete Empirical Interpolation Method
This page was built for publication: Unsteady physics-based reduced order modeling for large-scale compressible aerodynamic applications