Encyclopedia of Optimization

2009 Edition
| Editors: Christodoulos A. Floudas, Panos M. Pardalos

Design Optimization in Computational Fluid Dynamics

  • Doyle Knight
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-74759-0_121
How to cite

Article Outline

Keywords

Synonyms

Focus

Framework

Levels of Simulation

The Stages of Design

Emergence of Automated Design Optimization Using CFD

Problem Definition

Algorithms for Optimization

  Gradient Optimizers

  Stochastic Optimizers

Examples

  Sequential Quadratic Programming

  Variational Sensitivity

  Response Surface

  Simulated Annealing

  Genetic Algorithms

Conclusion

See also

References

Keywords

Optimization Computational fluid dynamics 
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Aly S, Ogot M, Pelz R (Sept.–Oct.1996) Stochastic approach to optimal aerodynamic shape design. J Aircraft 33(5):945–961CrossRefGoogle Scholar
  2. 2.
    Anderson W, Venkatakrishnan V (1997) Aerodynamic design optimization on unstructured grids with a continuous adjoint formulation. AIAA Paper 97–0643, (Amer. Inst. Aeronautics and Astronautics, Reston, VA)Google Scholar
  3. 3.
    Berkowitz B (1996) Information age intelligence. Foreign Policy, 103:35–50CrossRefGoogle Scholar
  4. 4.
    Boender C, Romeijn H (1995) Stochastic methods. In: Handbook of Global Optimization. Kluwer, Dordrecht, pp 829–869Google Scholar
  5. 5.
    Cabuk H, Modi V (1992) Optimal plane diffusers in laminar flow. J Fluid Mechanics 237:373–393MATHCrossRefGoogle Scholar
  6. 6.
    Carmichael R, Erickson L (1981) PAN AIR – A higher order panel method for predicting subsonic or supersonic linear potential flows about arbitrary configurations. AIAA Paper 81–1255, (Amer. Inst. Aeronautics and Astronautics, Reston, VA)Google Scholar
  7. 7.
    Caughey D (1982) The computation of transonic potential flows. In: Annual Rev. Fluid Mechanics, 14, pp 261–283Google Scholar
  8. 8.
    Caughey D, Jameson A (Feb. 1979) Numerical calculation of transonic potential flow about wing–body combinations. AIAA J 17(2):175–181MATHCrossRefGoogle Scholar
  9. 9.
    Eyi S, Hager J, Lee K (Dec. 1994) Airfoil design optimization using the Navier–Stokes equations. J Optim Th Appl 83(3):447–461MATHMathSciNetCrossRefGoogle Scholar
  10. 10.
    Gill P, Murray W, Saunders M, Wright M (1986) User's guide for NPSOL: A FORTRAN package for nonlinear programming. SOL Techn Report Dept Oper Res Stanford Univ 86(2)Google Scholar
  11. 11.
    Gill P, Murray W, Wright M (1981) Practical optimization. Acad. Press, New YorkMATHGoogle Scholar
  12. 12.
    Giunta A, Balabanov V, Haim D, Grossman B, Mason W, Watson L (1996) Wing design for a high speed civil transport using a design of experiments methodology. AIAA Paper 96–4001-CP, (Amer. Inst. Aeronautics and Astronautics, Reston, VA)Google Scholar
  13. 13.
    Gnos A, Watson E, Seebaugh W, Sanator R, DeCarlo J (Apr. 1973) Investigation of flow fields within large–scale hypersonic inlet models. Techn Note NASA D–7150Google Scholar
  14. 14.
    Goldberg DE (1989) Genetic algorithms in search, optimization, and machine learning. Addison-Wesley, Reading, MAMATHGoogle Scholar
  15. 15.
    Haas M, Elmquist R, Sobel D (Apr. 1992) NAWC inlet design and analysis (NIDA) code. UTRC Report, R92–970037–1, (United Technologies Res. Center)Google Scholar
  16. 16.
    Haase W, Chaput E, Elsholz E, Leschziner M, Müller U (eds) (1997) ECARP – European computational aerodynamics research project: Validation of CFD codes and assessment of turbulence models. Notes on Numerical Fluid Mechanics. Vieweg, Braunschweig/WiesbadenGoogle Scholar
  17. 17.
    Hess J (1990) Panel methods in computational fluid dynamics. In: Annual Rev. Fluid Mechanics, 22, pp 255–274Google Scholar
  18. 18.
    Hirsch C (1988) Numerical computation of internal and external flows, vol I–II. Wiley, New YorkGoogle Scholar
  19. 19.
    Horst R, Pardalos PM (eds) (1995) Handbook of global optimization. Kluwer, DordrechtMATHGoogle Scholar
  20. 20.
    Ibrahim A, Baysal O (1994) Design optimization using variational methods and CFD. AIAA Paper 94–0093, (Amer. Inst. Aeronautics and Astronautics, Reston, VA)Google Scholar
  21. 21.
    Iollo A, Salas M (1995) Contribution to the optimal shape design of two–dimensional internal flows with embedded shocks. ICASE Report 95–20, (NASA Langley Res. Center, Hampton, VA)Google Scholar
  22. 22.
    Jameson A (1982) Steady–state solution of the Euler equations for transonic flow. In: Transonic, Shock and Multidimensional Flows. Acad. Press, New York, pp 37–70Google Scholar
  23. 23.
    Jameson A (1988) Aerodynamic design via control theory. J Sci Comput 3:33–260CrossRefGoogle Scholar
  24. 24.
    Jameson A, Pierce N, Martinelli L (1997) Optimum aerodynamic design using the Navier–Stokes equations. AIAA Paper 97–0101, (Amer. Inst. Aeronautics and Astronautics, Reston, VA)Google Scholar
  25. 25.
    Khuri A, Cornell J (1987) Response surfaces: Designs and analyses. M. Dekker, New YorkMATHGoogle Scholar
  26. 26.
    Kirkpatrick S, Gelatt C, Vecchi M (1983) Optimization by simulated annealing. Science 220(4598):671–680MathSciNetCrossRefGoogle Scholar
  27. 27.
    van Laarhoven P, Aarts E (1987) Simulated annealing: Theory and Acad. Pressplications. Reidel, LondonGoogle Scholar
  28. 28.
    Lawrence AHGC, Zhou J, Tits A (Nov. 1994) User's guide for CFSQP version 2.3: A C code for solving (large scale) constrained nonlinear (minimax) optimization problems, generating iterates satisfying all inequality constraints. Techn Report Inst Systems Res Univ Maryland 94–16r1Google Scholar
  29. 29.
    Lions JL (1971) Optimal control of systems governed by partial differential equations. Springer, Berlin (translated from the French)MATHGoogle Scholar
  30. 30.
    Lores M, Hinson B (1982) Transonic design using computational aerodynamics. In: Progress in Astronautics and Aeronautics, 81. Am Inst Aeronautics and Astronautics, Reston, VA, pp 377–402Google Scholar
  31. 31.
    McGrory W, Slack D, Pressplebaum M, Walters R (1993) GASP version 2.2: The general aerodynamic simulation program. Aerosoft, Blacksburg, VAGoogle Scholar
  32. 32.
    Metropolis N, Rosenbluth A, Rosenbluth M, Teller A, Teller E (1953) Equations of state calculations by fast computing machines. J Chem Phys 21:1087–1092CrossRefGoogle Scholar
  33. 33.
    Moré J, Wright S (1993) Optimization software guide. SIAM, PhiladelphiaMATHGoogle Scholar
  34. 34.
    Myers R, Montgomery D (1995) Response surface methodology: Process and product optimization using design experiments. Wiley, New YorkGoogle Scholar
  35. 35.
    Narducci R, Grossman B, Valorani M, Dadone A, Haftka R (1995) Optimization methods for non–smooth or noisy objective functions in fluid dynamic design problems. AIAA Paper 95–1648–CP. Am Inst Aeronautics and Astronautics, Reston, VAGoogle Scholar
  36. 36.
    Obayashi S, Tsukahara T (1996) Comparison of optimization algorithms for aerodynamic shape design. AIAA Paper 96–2394–CP. Am Inst Aeronautics and Astronautics, Reston, VAGoogle Scholar
  37. 37.
    Pironneau O (1973) On optimal profiles in Stokes flow. J Fluid Mechanics 59(1):117–128MATHMathSciNetCrossRefGoogle Scholar
  38. 38.
    Pironneau O (1974) On optimal design in fluid mechanics. J Fluid Mechanics 64(1):97–110MATHMathSciNetCrossRefGoogle Scholar
  39. 39.
    Pironneau O (1984) Optimal shape design for elliptic systems. Springer, BerlinMATHGoogle Scholar
  40. 40.
    Press W, Flannery B, Teukolsky S, Vetterling W (1986) Numerical recipes. Cambridge Univ. Press, CambridgeGoogle Scholar
  41. 41.
    Rasheed K, Gelsey A (1996) Adaption of genetic algorithms for continuous design space search. In: Fourth Internat. Conf. Artificial Intelligence in Design: Evolutionary Systems in Design Workshop, Google Scholar
  42. 42.
    Rasheed K, Hirsh H, Gelsey A (1997) A genetic algorithm for continuous design space search. Artif Intell in Eng 11(3):295–305CrossRefGoogle Scholar
  43. 43.
    Schwartz R (1993) Learning Perl. O'Reilly, Sebastopol, CAGoogle Scholar
  44. 44.
    Seddon J, Goldsmith E (eds) (1985) Intake aerodynamics. AIAA Education Ser Amer. Inst. Aeronautics and Astronautics, Reston, VAGoogle Scholar
  45. 45.
    Siclari M, Del Guidice P (Jan 1990) Hybrid finite volume Approach to Euler solutions for supersonic flows. AIAA J 28(1):66–74CrossRefGoogle Scholar
  46. 46.
    Simpson T, Peplinski J, Koch P, Allen J (1997) On the use of statistics in design and the implications for deterministic computer experiments. ASME Paper DETC 97/DTM–3881. Am Soc Mech Engin, New YorkGoogle Scholar
  47. 47.
    Sirbaugh J, Smith C, Towne C, Cooper G, Jones R, Power G (Nov. 1994) A users guide to NPARC version 2.0. NASA Lewis Res. Center and Arnold Engin. Developm. Center, Cleveland, OH/Arnold, TNGoogle Scholar
  48. 48.
    Sobieczky H, Seebass A (1984) Supercritical airfoil and wing design. In: Annual Rev. Fluid Mechanics, 16, pp 337–363Google Scholar
  49. 49.
    Sobieszczanski–Sobieski J, Haftka R (1996) Multidisciplinary aerospace design optimization: Survey of recent developments. AIAA Paper 96–0711. Am Inst Aeronautics and Astronautics, Reston, VAGoogle Scholar
  50. 50.
    Ta'asan S, Kuruvilla K, Salas M (1992) Aerodyamic design and optimization in one shot. AIAA Paper 92–0025. Am Inst Aeronautics and Astronautics, Reston, VAGoogle Scholar
  51. 51.
    Thom A (1933) The flow past circular cylinders at low speeds. Proc Royal Soc London A141:651–666CrossRefGoogle Scholar
  52. 52.
    Vanderplaats G (1984) Numerical optimization techniques for engineering design: With Applications. McGraw-Hill, New YorkMATHGoogle Scholar
  53. 53.
    Zha G, Smith D, Schwabacher M, Rasheed K, Gelsey A, Knight D (Nov.–Dec. 1997) High–performance supersonic missile inlet design using automated optimization. J Aircraft 34(6):697–705CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Doyle Knight
    • 1
  1. 1.Department Mechanical and Aerospace EngineeringRutgers UniversityNew BrunswickUSA