scholarly journals A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations

2019 ◽  
Author(s):  
Saeid Asgari Taghanaki ◽  
Kumar Abhishek ◽  
Shekoofeh Azizi ◽  
Ghassan Hamarneh
Keyword(s):  
Manifold Mapping

scholarly journals Supersonic Airfoil Shape Optimization by Variable-fidelity Models and Manifold Mapping

2016 ◽  
Vol 80 ◽  
pp. 1103-1113 ◽  
Author(s):  
Jacob Siegler ◽  
Jie Ren ◽  
Leifur Leifsson ◽  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Shape Optimization ◽  
Variable Fidelity ◽  
Manifold Mapping

scholarly journals Surrogate based wind farm layout optimization using manifold mapping

2016 ◽  
Vol 753 ◽  
pp. 092005 ◽  
Author(s):  
Shaafi M Kaja Kamaludeen ◽  
Alexander van Zuijle ◽  
Hester Bijl
Keyword(s):  
Wind Farm ◽  
Layout Optimization ◽  
Wind Farm Layout ◽  
Wind Farm Layout Optimization ◽  
Manifold Mapping

scholarly journals Single- and Multipoint Aerodynamic Shape Optimization Using Multifidelity Models and Manifold Mapping

2021 ◽  
pp. 1-18
Author(s):  
Jethro Nagawkar ◽  
Jie Ren ◽  
Xiaosong Du ◽  
Leifur Leifsson ◽  
Slawomir Koziel
Keyword(s):  
Shape Optimization ◽  
Aerodynamic Shape Optimization ◽  
Aerodynamic Shape ◽  
Manifold Mapping

Workspace Analysis of Multibody Mechanical Systems Using Continuation Methods

1988 ◽  
Author(s):  
D.-Y. Jo ◽  
E. J. Haug
Keyword(s):  
Mechanical Systems ◽  
Point Of View ◽  
Continuation Methods ◽  
Dimensional Manifold ◽  
One Dimensional ◽  
Generalized Coordinates ◽  
Workspace Analysis ◽  
Manifold Mapping ◽  
Manifold Theory

Abstract A new approach to numerical analysis of workspaces of multibody mechanical systems is developed. Numerical techniques that are based on manifold theory and utilize continuation methods are presented and applied to a variety of mechanical systems, including closed-loop mechanisms. Generalized coordinates that define kinematics of a system are classified and interpreted from an input-output point of view. Boundaries of workspaces, which depend on the classification of generalized coordinates, are defined as sets of singular points of Jacobians of the kinematic equations. Numerical methods for tracing one dimensional trajectories on a workspace boundary are outlined and example are analyzed using one dimensional manifold mapping computer programs, such as PITCON and AUTO.

Multifidelity modeling similarity conditions for airfoil dynamic stall prediction with manifold mapping

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishal Raul ◽  
Leifur Leifsson
Keyword(s):  
Prediction Error ◽  
Stokes Equations ◽  
Trust Region ◽  
Simulation Models ◽  
Time Discretization ◽  
Dynamic Stall ◽  
Navier Stokes ◽  
Navier Stokes Equations ◽  
Content Type ◽  
Manifold Mapping

PurposeThe purpose of this work is to investigate the similarity requirements for the application of multifidelity modeling (MFM) for the prediction of airfoil dynamic stall using computational fluid dynamics (CFD) simulations.Design/methodology/approachDynamic stall is modeled using the unsteady Reynolds-averaged Navier–Stokes equations and Menter's shear stress transport turbulence model. Multifidelity models are created by varying the spatial and temporal discretizations. The effectiveness of the MFM method depends on the similarity between the high- (HF) and low-fidelity (LF) models. Their similarity is tested by computing the prediction error with respect to the HF model evaluations. The proposed approach is demonstrated on three airfoil shapes under deep dynamic stall at a Mach number 0.1 and Reynolds number 135,000.FindingsThe results show that varying the trust-region (TR) radius (λ) significantly affects the prediction accuracy of the MFM. The HF and LF simulation models hold similarity within small (λ ≤ 0.12) to medium (0.12 ≤ λ ≤ 0.23) TR radii producing a prediction error less than 5%, whereas for large TR radii (0.23 ≤ λ ≤ 0.41), the similarity is strongly affected by the time discretization and minimally by the spatial discretization.Originality/valueThe findings of this work present new knowledge for the construction of accurate MFMs for dynamic stall performance prediction using LF model spatial- and temporal discretization setup and the TR radius size. The approach used in this work is general and can be used for other unsteady applications involving CFD-based MFM and optimization.

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