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Experimental trajectory optimization of a flapping fin propulsor using an evolutionary strategy

Martin, Nathan and Gharib, Morteza (2019) Experimental trajectory optimization of a flapping fin propulsor using an evolutionary strategy. Bioinspiration and Biomimetics, 14 (1). Art. No. 016010. ISSN 1748-3182. doi:10.1088/1748-3190/aaefa5.

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The experimental optimization of bio-inspired flapping fin trajectories are demonstrated for potential applications as a side or a rear propulsor of an autonomous underwater vehicle. The trajectories are scored based upon their difference from a force set-point and upon their efficiency and are parameterized by 10 variables inspired by fish swimming. The flapping fin is a generic rectangular rigid flat plate with a tapered edge. Optimization occurs as follows. First, a generation of trajectories is created. Second, the trajectories are executed by a spherical parallel manipulator, during which the forces are acquired. Third, the trajectories are scored and a new generation of trajectories is created using the covariance matrix adaptive evolutionary strategy. This loop repeats ad-infinitum until the search converges. Within the first set of searches, two trajectories for optimal side-force generation are found, one is fully three-dimensional while the other is artificially constrained to a line, and one trajectory for optimal thrust generation is found. All searches demonstrate good convergence properties and match the desired force set-point almost immediately. Additional generations primarily improve the efficiency of the maneuver. The two trajectories for generating side-force have a similar efficiency, which shows potential in utilizing a simple trajectory limited to a line. Comparison between the trajectories for generating side-force and thrust suggests that side-force generation is more efficient around Re ~1000, based on the average tip velocity and length of the fin. The second set of searches explores the behavior of the optimal trajectories for generating side-force at a lower force set-point and the third set of searches explores the sensitivity and repeatability of the optimization.

Item Type:Article
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URLURL TypeDescription
Martin, Nathan0000-0001-6038-6177
Gharib, Morteza0000-0002-2204-9302
Additional Information:© 2018 IOP Publishing. Received 4 August 2018. Accepted 9 November 2018. Published 29 November 2018.
Issue or Number:1
Record Number:CaltechAUTHORS:20181016-153601512
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Official Citation:Nathan Martin and Morteza Gharib 2019 Bioinspir. Biomim. 14 016010
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90286
Deposited By: George Porter
Deposited On:29 Nov 2018 19:06
Last Modified:12 Jul 2022 19:52

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