Using automatic differentiation with the quasi-procedural method for multidisciplinary design optimaization
- Department of Aeronautics and Astronautics, Stanford Univ., Stanford, CA (United States)
- Mathematics and Computer Science Division, Argonne National Lab., Argonne, IL (United States)
As computers have become increasingly powerful, the field of design optimization has moved toward higher fidelity models (involving many more variables) in the early stages of design. One way in which this movement has manifested itself is in the increasing popularity of multidisciplinary design optimization (MDO). Because the models used in MDO are large and very complicated, a modular design is desirable. Because there are many- design parameters to optimize, derivatives must be computed accurately and efficiently. This paper describes how the quasi-procedural program architecture developed by Takai and Kroo [9] and the technique of automatic differentiation [6] can be combined to effectively address these needs. The two techniques are explained, the manner in which they were integrated into a single framework is described, and the result of using this framework for an optimization problem in airplane design is presented.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States); Department of Defense, Washington, DC (United States); National Science Foundation, Washington, DC (United States)
- DOE Contract Number:
- W-31109-ENG-38
- OSTI ID:
- 211239
- Report Number(s):
- ANL/MCS/CP-88419; CONF-960162-2; ON: DE96007262; CNN: NSF Cooperative Agreement CCR-9120008
- Resource Relation:
- Conference: 34. American Institute of Aeronautics and Astronautics (AIAA) aerospace sciences meeting, Reno, NV (United States), 15-18 Jan 1996; Other Information: PBD: [1996]
- Country of Publication:
- United States
- Language:
- English
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