Journal Article10.2514/1.36414
Using Automatic Differentiation to Create a Nonlinear Reduced-Order-Model Aerodynamic Solver
TL;DR: In this article, a nonlinear reduced-order-modeling technique for computational aerodynamics and aeroelasticity is presented based on a Taylor series expansion of a frequency-domain harmonic balance computational fluid dynamics residual.
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Abstract: A novel nonlinear reduced-order-modeling technique for computational aerodynamics and aeroelasticity is presented. The method is based on a Taylor series expansion of a frequency-domain harmonic balance computational fluid dynamicsolver residual.The first- andsecond-order gradientmatrices andtensorsof the Taylorseries expansion are computed using automatic differentiation via FORTRAN 90=95 operator overloading. A Ritz-type expansion using proper orthogonal decomposition shapes is then used in the Taylor series expansion to create the nonlinearreduced-order model. The nonlinear reduced-order-modeling technique is applied to a viscous flow about anaeroelastic NLR 7301 airfoil modelto determine limit cycle oscillations. Computational times are decreased from hours to seconds using the nonlinear reduced-order model.
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Citations
Reduced-Order Nonlinear Unsteady Aerodynamic Modeling Using a Surrogate-Based Recurrence Framework
TL;DR: In this article, a reduced-order nonlinear unsteady aerodynamic modeling approach suitable for analyzing pitching/plunging airfoils subject to fixed or time-varying freestream Mach numbers is described.
Nonlinear aeroelastic reduced order modeling by recurrent neural networks
TL;DR: In this article, the authors developed a reduction scheme based on the identification of continuous time recursive neural networks from input-output data obtained through high fidelity simulations of a nonlinear aerodynamic model at hand.
Reduced-Order Modeling of Flutter and Limit-Cycle Oscillations Using the Sparse Volterra Series
Maciej Balajewicz,Earl H. Dowell +1 more
TL;DR: In this paper, a sparse representation of the Volterra series is explored for aerodynamic induced limit-cycle oscillations, for which identification costs are significantly lower than the identification costs of the full VOLTERRA series.
98
Local POD Plus Galerkin Projection in the Unsteady Lid-Driven Cavity Problem
TL;DR: A local proper orthogonal decomposition (POD) plus Galerkin projection method is applied to the unsteady lid-driven cavity problem, namely the incompressible fluid flow in a two-dimensional box whose upper wall is moved back and forth at moderately large values of the Reynolds number.
70
Nonlinear aeroelastic reduced order modeling by recurrent neural networks
A. Mannarino,Paolo Mantegazza +1 more
- 01 Jul 2014
TL;DR: A reduction scheme based on the identification of continuous time recursive neural networks from input–output data obtained through high fidelity simulations of a nonlinear aerodynamic model at hand is developed.
54
References
•Book
Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation
Andreas Griewank,Andrea Walther +1 more
- 01 Jan 1987
TL;DR: This second edition has been updated and expanded to cover recent developments in applications and theory, including an elegant NP completeness argument by Uwe Naumann and a brief introduction to scarcity, a generalization of sparsity.
3.3K
Balanced Model Reduction via the Proper Orthogonal Decomposition
Karen Willcox,Jaime Peraire +1 more
TL;DR: A new method for performing a balanced reduction of a high-order linear system is presented, which combines the proper orthogonal decomposition and concepts from balanced realization theory and extends to nonlinear systems.
Reduced-order modeling: new approaches for computational physics
TL;DR: In this paper, the authors review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics, including aerodynamic and aeroelastic behaviors of two-dimensional and three-dimensional geometries.
867
Computation of Unsteady Nonlinear Flows in Cascades Using a Harmonic Balance Technique
TL;DR: In this paper, a harmonic balance technique for modeling unsteady nonlinear e ows in turbomachinery is presented, which exploits the fact that many unstaidy e ow variables are periodic in time.
Modeling of Fluid-Structure Interaction
Earl H. Dowell,Kenneth C. Hall +1 more
TL;DR: In this article, the authors present a review of the physical models for a fluid undergoing time-dependent motes and their applications in many fields of engineering, such as aeronautic and structural engineering.
655