Heuristic Discovery of Improved Rotor Designs
Jeffrey D. Sinsay, U.S. Army; Juan J. Alonso, Stanford University
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- Presented at Forum 74 - Best Paper for this session
- 20 pages
- SKU # : 74-2018-1217
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Heuristic Discovery of Improved Rotor Designs
Authors / Details: Jeffrey D. Sinsay, U.S. Army; Juan J. Alonso, Stanford UniversityAbstract
Selecting the right design parametrization can be critical to finding a rotor design optimum of practical value, and can be highly dependent on the a priori knowledge of the designer. This selection problem is particularly challenging for the human designer when designing a novel configuration or in an operating environment not well understood. A heuristic approach to allow for discovery of better parametrizations as optimization proceeds is described and demonstrated on a representative rotor design problem. The heuristic applies important principles of evolutionary theory including: mutation, competition, and selection in searching for a better parametrization. The principles of parsimony in conjunction with variation in mutation probability are shown to to be important in ensuring efficient use of the degrees of freedom in an optimization problem. Results for the representative rotor design problem demonstrate the value of the heuristic method in exploring the design space.
