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Cited by 311Advanced Multi-Objective Optimization AlgorithmsProbabilistic and Robust Engineering DesignComputational Fluid Dynamics and Aerodynamics

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A review on design of experiments and surrogate models in aircraft real-time and many-query aerodynamic analyses

Yondo, Raul, Andrés, Esther, Valero, Eusebio·2018·Progress in Aerospace Sciences
DOI 10.1016/j.paerosci.2017.11.003
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Research works printed but not linked: 40

  1. Koziel, 2011, 45(1–3), 33
  2. Viana, 2014, Metamodeling in multidisciplinary design optimization: how far have we really come?, J. Prog. Aerosp. Sci., 52, 670
  3. Koehler, 1996, Computer experiments, J. Prog. Aerosp. Sci., 261
  4. Finney, 1945, vol. 12, 291
  5. Fries, 1980, Minimum aberration 2k–p designs, Technometrics, 22, 601
  6. Rechtschaffner, 2005, Saturated fractions of 2n and 3n factorial designs, Technometrics, 9, 569
  7. Box, 1961, The 2k–p fractional factorial designs, Part I, Technometrics, 3, 311
  8. Box, 1961, The 2k–p fractional factorial designs, Part II, Technometrics, 3, 449
  9. Yue, 1999, Robust optimal designs for fitting approximately linear models, Stat. Sin., 9, 1053
  10. Owen, 1992, Randomly orthogonal arrays for computer experiments, integration and visualization, Stat. Sin., 2, 439
  11. Fang, 1980, The uniform design: application of number theoretic methods in experimental design, Acta Math. Appl. Sin., 3, 362
  12. S. Mak and V. R. Joseph, Minimax designs using clustering. J. Comput. Graph. Stat., submitted for publication, arxiv.org/abs/1602.03938. · arXiv
  13. B.G.M. Husslage, reportMaximin Designs for Computer Experiments. (Doctoral dissertation), Tilburg University, Tilburg, Netherlands.
  14. Husslage, 2006, vol. 18
  15. Yondo, 2016, A 2D numerical study of the influence of a priori sampling methods on surrogate models accuracy in aircraft aerodynamic design optimization, vol. 510
  16. Klein, 1983, vol. 2126
  17. Jouke H.S. de Baar, Thomas P. Scholcz, Clemens V. Verhoosel, Richard P. Dwight, Alexander H. van Zuijlen and Hester Bijl, Efficient uncertainty quantification with gradient-enhanced Kriging: applications in FSI, In J. Eberhardsteiner et al (eds.). European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2012), 51, Vienna, Austria, September 10-14, 2012.
  18. Le Gratiet, 2013, vol. 2
  19. Broomhead, 1988, Multivariate functional interpolation and adaptative networks, J. Complex Syst., 2, 321
  20. Quarteroni, 2014, vol. 9
  21. Kroll, 2012, CEAS Aeronaut. J., 151
  22. Loéve, 1945, Functions Aleatoire de Second Ordre, C. R. Acad. Sci. Paris, 220
  23. Obukbov, 1954, Statistical description of continuous fields, Tr. Geophys. Int. Akad. Nauk. SSSR, 24, 3
  24. Pougachev, 1953, General theory of the correlations of random functions, Izv. Akud. Nauk. SSSR, Set. Mat., 17
  25. Chen, 2012, Support-vector-machine-based reduced-order model for limit cycle oscillation prediction of nonlinear aeroelastic system, Math. Prob. Eng., 10.1155/2012/152123 · DOI
  26. Iuliano, 2013, Proper orthogonal decomposition, surrogate Modelling and evolutionary optimization in aerodynamic design, J. Comput. Fluids, 84, 327, 10.1016/j.compfluid.2013.06.007 · DOI
  27. Chinesta, 2011, Recent advances and new challenges in the use of the proper generalized decomposition for solving multidimensional models, J. Fluids Eng., 18, 395
  28. Amsallem, 2008, Interpolation method for adapting reduced-order models and application to aeroelasticity, AIAA J., 46, 1803, 10.2514/1.35374 · DOI
  29. Amsallem, 2012, Nonlinear model order reduction based on local reduced-order bases, Int. J. Numer. Methods Eng., 92, 891, 10.1002/nme.4371 · DOI
  30. Wirtz, 2014, A posteriori error estimation for DEIM reduced nonlinear dynamical systems, SIAM J. Sci. Comput., 36, A311, 10.1137/120899042 · DOI
  31. Zhong-Hua Han, Stefan Görtz and Ralf Zimmermann, On improving efficiency and accuracy of variable-fidelity surrogate modeling in aero-data for loads context. CEAS 2009 European Air and Space Conference, Manchester U. K., 26–29 Oct. 2009.
  32. Craig, 1998, Constructing partial prior specifications for models of complex physical systems, Appl. Stat., 47, 37
  33. Zimmermann, 2012, Gradient-enhanced surrogate modeling based on proper orthogonal decomposition, Struct. Multidiscip. Optim., 237, 403
  34. Laurenceau, 2010, Comparison of gradient-based and gradient-enhanced response-surface-based optimizers, AIAA J., 48, 981, 10.2514/1.45331 · DOI
  35. Han, 2010, Towards efficient high-dimensional aerodynamic shape optimization: surrogate modeling via gradient-enhanced Kriging, vol. 1
  36. Voutchkov, 2010, vol. 7, 155
  37. James Parr, C. M. E. Holden, A. I. J. Forrester and A. J. Keane, Review of efficient surrogate infill sampling criteria with constraint handling. 2nd International Conference on Engineering Optimization, 1–10, Portugal, 06-10 Sep 2011.
  38. Huang, 2013, Research on multi-fidelity aerodynamic optimization methods, Chin. J. Aeronaut., 26, 279, 10.1016/j.cja.2013.02.004 · DOI
  39. Zahr, 2015, Progressive construction of a parametric reduced-order model for PDE-constrained optimization, Int. J. Numer. Methods Eng., 102, 1111, 10.1002/nme.4770 · DOI
  40. Allaire, 2010, Surrogate modeling for uncertainty assessment with application to aviation environmental system models, AIAA J., 48, 1791, 10.2514/1.J050247 · DOI

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Metadata

Authors
Yondo, R., Andrés, E., & Valero, E.
Affiliations
  • Universidad Politécnica de Madrid (ES)
  • Ingeniería de Sistemas para la Defensa de España (ES)
Corresponding author
Yondo, Raul
ORCID
Venue
Progress in Aerospace Sciences
Publisher
Elsevier BV
Published
2018-01
Volume
96
Pages
23-61
ISSN
0376-0421 (ISSN-L)
DOI
10.1016/j.paerosci.2017.11.003
OpenAlex
W2776493547
Cited by
311
References
548
Citations by year
2026: 29 · 2025: 50 · 2024: 44 · 2023: 32 · 2022: 49 · 2021: 41 · 2020: 39 · 2019: 26 · 2018: 1
FWCI
13.56
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
Progress in Aerospace Sciences (publishedVersion)
Funders
European Commission Seventh Framework Programme (FP7-PEOPLE-2013-ITN, 608087)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
  • Physical Sciences › Engineering › Computational Mechanics › Probabilistic and Robust Engineering Design
  • Physical Sciences › Engineering › Computational Mechanics › Computational Fluid Dynamics and Aerodynamics
Keywords
surrogate models, aircraft aerodynamic design, surrogate-based optimization, experimental design, sampling strategy, dimensionality reduction, sensitivity analysis, uncertainty quantification, multi-fidelity modeling, civil transport aircraft, computational complexity reduction

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