Exploitation of Sensitivity Derivatives for Improving Sampling Methods

AIAA Journal

Volumn 42, Issue 4, 2004, Pages 815-822

  Cao, Yanzhao ^a,d   Hussaini, M Yousuff ^b,e   Zang, Thomas A ^c,d  

^a FLORIDA A AND M UNIVERSITY   (United States)

^b FLORIDA STATE UNIVERSITY   (United States)

^c NASA LANGLEY RESEARCH CENTER   (United States)

^d Department of Mathematics ^*

^e Sch of Compl Sci/Info Technol   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AERODYNAMICS; APPROXIMATION THEORY; FINITE ELEMENT METHOD; MONTE CARLO METHODS; OPTIMAL CONTROL SYSTEMS; SAMPLING; SENSITIVITY ANALYSIS; STOCHASTIC CONTROL SYSTEMS;

GAUSSIAN DISTRIBUTION; LATIN HYPERCUBE; MAGNITUDE REDUCTION; SENSITIVITY DERIVATIVE-ENHANCED SAMPLING (SDES);

FLUID DYNAMICS;

EID: 2342586737     PISSN: 00011452     EISSN: None     Source Type: Journal    
DOI: 10.2514/1.2820     Document Type: Article

References (16)

1. Cao, Y., Hussaini, M. Y., and Zang, T. A., "An Efficient Monte Carlo Method for Optimal Control Problems with Uncertainty," Computational Optimization and Applications, Vol. 26, 2003, pp. 219-230.
2. Fishman, G. S., Monte Carlo: Concepts, Algorithms, and Applications, Springer-Verlag, New York, 1996.
3. Liu, J. S., Monte Carlo Strategies in Scientific Computing, Springer-Verlag, New York, 2001.
4. Cardenas, J., Fruchard, E., Picron, J.-F., Reyes, C., Walters, K., and Yang, W., "Monte Carlo Within a Day," Risk, Vol. 12, No. 2, 1999, pp. 55-59.
5. Glasserman, P., Heidelberger, P., and Shahabuddin, P., "Variance Reduction Techniques for Estimating Value-at-Risk," Management Science, Vol. 46, No. 10, 2000, pp. 1349-1364.
6. Storaasli, O. O., Nguyen, D. T., Baddourah, M. A., and Qin, J., "Computational Mechanics Analysis Tools for Parallel-Vector Supercomputers," Computing Systems in Engineering, Vol. 4, No. 4-6, 1993, pp. 349-354.
7. Carle, A., Fagan, M., and Green, L. L., "Preliminary Results from the Application of Automated Adjoint Code Generation to CFL3D," AIAA Paper 98-4807, 1998.
8. Sundaram, P., Agrawal, S., and Hager, J. O., "Aerospace Vehicle MDO Shape Optimization Using ADIFOR 3.0 Gradients," AIAA Paper 2000-4733, 2000.
9. Mathe, P., "Hilbert Space Analysis of Latin Hypercube Sampling," Proceedings of the American Mathematical Society, Vol. 129, No. 5, 2000, pp. 1477-1492.
10. Novak, E., Deterministic and Stochastic Error Bounds in Numerical Analysis, Lecture Notes in Mathematics 1349, Springer-Verlag, New York, 1988, URL: http://www.mi.uni-erlangen.de/novak.
11. Walters, R. W., and Huyse, L., "Uncertainty Analysis for Fluid Mechanics with Applications," NASA CR 2002-211449, Jan. 2002.
12. Gumbert, C. R., Hou, G. J.-W., and Newman, P. A., "High-Fidelity Computational Optimization for 3-D Flexible Wings: Part I - Simultaneous Aero-Structural Design Optimization (SASDO)," Optimization and Engineering (to be published).
13. Hou, G., Arunkumar, S., and Tiwari, N. S., "First- and Second-Order Sensitivity Analysis of Finite Element Equations via Automatic Differentiation," AIAA Paper 98-4764, 1998.
14. Gumbert, C. R., Newman, P. A., and Hou, G. J.-W., "High-Fidelity Computational Optimization for 3-D Flexible Wings: Part II - Effect of Random Geometric Uncertainty on Design," Optimization and Engineering (to be published).
15. Sherman, L., Taylor, A., Green, L., Newman, P., Hou, G., and Korivi, M., "First- and Second-Order Aerodynamic Sensitivity Derivatives via Automatic Differentiation with Incremental Iterative Methods," Journal of Computational Physics, Vol. 129, 1996, pp. 307-336.
16. Taylor, A. C., III, Putko, M. M., Green, L. L., and Newman, P. A., "Some Advanced Concepts in Discrete. Aerodynamic Sensitivity Analysis," AIAA Journal, Vol. 41, No. 7, 2003, pp. 1224-1229.