Robust aircraft conceptual design using automatic differentiation in Matlab

Lecture Notes in Computational Science and Engineering

Volumn 64 LNCSE, Issue , 2008, Pages 271-280

  Padulo, Mattia ^a   Forth, Shaun A ^b   Guenov, Marin D ^a  

^a CRANFIELD UNIVERSITY   (United Kingdom)

^b CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Aircraft conceptual design; Forward mode; Higher derivatives; MAD; Uncertainty estimation

Indexed keywords

AIRCRAFT CONCEPTUAL DESIGN; FORWARD MODE; HIGHER DERIVATIVES; MAD; UNCERTAINTY ESTIMATION;

AIRCRAFT; CONCEPTUAL DESIGN; DESIGN; DIFFERENTIATION (CALCULUS); FIGHTER AIRCRAFT; GRADIENT METHODS; MATHEMATICAL MODELS; MATLAB; PARAMETER ESTIMATION; STOCHASTIC MODELS; STOCHASTIC PROGRAMMING; UNCERTAINTY ANALYSIS;

METHOD OF MOMENTS;

EID: 78650021872     PISSN: 14397358     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-68942-3_24     Document Type: Conference Paper

References (18)

1. Barthelemy, J.F., Hall, L.E.: Automatic Differentiation as a Tool in Engineering Desing. TM 107661, NASA (1992)
2. Bischof, C.H., Griewank, A.: Computational Differentiation and Multidisciplinary Design. In: H. Engl, J. McLaughlin (eds.) Inverse Problems and Optimal Design in Industry, pp. 187-211. Teubner Verlag, Stuttgart (1994)
3. Chen,W., Allen, J.: A procedure for robust design: Minimizing variations caused by noise factors and control factors. Journal of Mechanical Design 118(4), 478-493 (1996)
4. Du, X., Chen, W.: Efficient Uncertainty Analysis Methods for Multidisciplinary Robust Design. AIAA Journal 40(3), 545-552 (2002)
5. Forth, S.A.: An efficient overloaded implementation of forward mode automatic differentiation in MATLAB. ACM Trans. Math. Softw. 32(2), 195-222 (2006). DOI:http://doi.acm.org/10.1145/1141885.1141888
6. Griewank, A.: Evaluating Derivatives: Principles and Techniques of Algorithmic Differentiation. No. 19 in Frontiers in Applied Mathematics. SIAM, Philadelphia, PA (2000)
7. Helton, J.C., Davis, F.J.: Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Eng. System Safety 81(1), 23-69 (2003)
8. Huang, B., Du, X.: Uncertainty analysis by dimension reduction integration and saddlepoint approximations. Transactions of the ASME 18, 26-33 (2006)
9. Lewis, L., Parkinson, A.: Robust optimal design using a second order tolerance model. Research in Engineering Design 6(1), 25-37 (1994)
10. The MathWorks, Inc., 3 Apple Hill Drive, Natick, MA 01760-2098: MATLAB Optimization Toolbox 3 - User's guide (2007)
11. Padulo, M., Campobasso, M.S., Guenov, M.D.: Comparative Analysis of Uncertainty Propagation methods for Robust Engineering Design. In: International Conference on Engineering Design ICED07. Paris (2007)
12. Park, G.J., Lee, T.H., Lee, K.H., Hwang, K.H.: Robust Design: An Overview. AIAA Journal 44(1), 181-191 (2006)
13. Parkinson, A., Sorensen, C., Pourhassan: A General Approach for Robust Optimal Design. J. mech. Des 115(1), 74-80 (1993)
14. th AIAA Computational Fluid Dynamics Conference. Anaheim CA (2001). AIAA 2001-2528
15. Su, J., Renaud, J.E.: Automatic Differentiation in Robust Optimization. AIAA Journal 5(6), 1072-1079 (1996)
16. Tari, M., Dahmani, A.: Refined descriptive sampling: A better approach to Monte Carlo simulation. Simulation Modelling Practice and Theory 14(2), 143-160 (2006)
17. Torenbeek, E.: Synthesis of Subsonic Airplane Design. Delft University Press, Delft, Holland (1982)
18. Xiu, D., Karniadakis, E.M.: Modeling uncertainty in flow simulations via generalized polynomial chaos. Journal of Computational Physics 187, 137-167 (2003)