Flowfield Reconstruction Method Using Artificial Neural Network

Multidimensional aerodynamic database development has become more and more important for the design, control, and guidance of modern aircraft. To relieve the curse of the dimensionality, a novel fl...

[1]  Christine A. Shoemaker,et al.  ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions , 2008, SIAM J. Sci. Comput..

[2]  Karen Willcox,et al.  Provably Convergent Multifidelity Optimization Algorithm Not Requiring High-Fidelity Derivatives , 2012 .

[3]  A. Velazquez,et al.  Generation of Aerodynamics Databases Using High-Order Singular Value Decomposition , 2008 .

[4]  Karen Willcox,et al.  A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems , 2015, SIAM Rev..

[5]  A. Velazquez,et al.  Reduced-Order Model for Viscous Aerodynamic Flow Past an Airfoil , 2010 .

[6]  K. Willcox,et al.  Aerodynamic Data Reconstruction and Inverse Design Using Proper Orthogonal Decomposition , 2004 .

[7]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[8]  Lawrence Sirovich,et al.  Karhunen–Loève procedure for gappy data , 1995 .

[9]  Heng Xiao,et al.  Quantifying and reducing model-form uncertainties in Reynolds-averaged Navier-Stokes simulations: A data-driven, physics-informed Bayesian approach , 2015, J. Comput. Phys..

[10]  J. H. Starnes,et al.  Construction of Response Surface Approximations for Design Optimization , 1998 .

[11]  David G. MacManus,et al.  A variable‐fidelity aerodynamic model using proper orthogonal decomposition , 2016 .

[12]  A. A. Shah,et al.  Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models , 2017, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[13]  Gianluigi Rozza,et al.  Reduced Basis Methods , 2016 .

[14]  Brendan D. Tracey,et al.  A Machine Learning Strategy to Assist Turbulence Model Development , 2015 .

[15]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[16]  T. V. Geetha,et al.  Indian Logic Ontology based Automatic Query Refinement , 2008 .

[17]  Benjamin Stamm,et al.  EFFICIENT GREEDY ALGORITHMS FOR HIGH-DIMENSIONAL PARAMETER SPACES WITH APPLICATIONS TO EMPIRICAL INTERPOLATION AND REDUCED BASIS METHODS ∗ , 2014 .

[18]  Eitan Tadmor,et al.  Solution of two‐dimensional Riemann problems for gas dynamics without Riemann problem solvers , 2002 .

[19]  Dilek Funda Kurtulus,et al.  Ability to forecast unsteady aerodynamic forces of flapping airfoils by artificial neural network , 2009, Neural Computing and Applications.

[20]  Karthik Duraisamy,et al.  A paradigm for data-driven predictive modeling using field inversion and machine learning , 2016, J. Comput. Phys..

[21]  K. Willcox.  Unsteady Flow Sensing and Estimation via the Gappy Proper Orthogonal Decomposition , 2004 .

[22]  Kadir Aydin,et al.  Comparison of linear regression and artificial neural network model of a diesel engine fueled with biodiesel-alcohol mixtures , 2016 .

[23]  Daniel M. Dunlavy,et al.  Formulations for Surrogate-Based Optimization with Data Fit, Multifidelity, and Reduced-Order Models , 2006 .

[24]  R. Goodman,et al.  Application of neural networks to turbulence control for drag reduction , 1997 .

[25]  Anand Pratap Singh,et al.  New Approaches in Turbulence and Transition Modeling Using Data-driven Techniques , 2015 .

[26]  Erich Novak,et al.  High dimensional polynomial interpolation on sparse grids , 2000, Adv. Comput. Math..

[27]  J. Templeton,et al.  Reynolds averaged turbulence modelling using deep neural networks with embedded invariance , 2016, Journal of Fluid Mechanics.

[28]  Benjamin Peherstorfer,et al.  Dynamic data-driven reduced-order models , 2015 .

[29]  H. P. Lee,et al.  PROPER ORTHOGONAL DECOMPOSITION AND ITS APPLICATIONS—PART I: THEORY , 2002 .

[30]  Shigeya Watanabe,et al.  Aerodynamic Characteristics Evaluation of Hypersonic Flight Experiment Vehicle Based on Flight Data , 1997 .

[31]  Vassilios Theofilis,et al.  Modal Analysis of Fluid Flows: An Overview , 2017, 1702.01453.

[32]  Mario A. Rotea,et al.  Data-driven Reduced Order Model for prediction of wind turbine wakes , 2015 .

[33]  Scott T. M. Dawson,et al.  Model Reduction for Flow Analysis and Control , 2017 .

[34]  J. Alonso,et al.  SU2: An Open-Source Suite for Multiphysics Simulation and Design , 2016 .