Abstract
This paper introduces experiment-based modeling and optimization of a reduced-scale Electromagnetic launcher (EML) using the Design of experiments (DOE) technique. Response surface models describing the velocity and kinetic energy of the launched projectile were developed using the Box–Behnken method with design variable transforms, and an Analysis of variance (ANOVA) was conducted to refine the models by removing statistically insignificant terms. A bi-objective optimization problem with the maximum velocity and maximum kinetic energy as objects was considered, and a Pareto front was obtained using the generated response surfaces as the solution of the problem. Verification tests on the optimal design points were conducted to demonstrate the validity of the developed models.
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Recommended by Associate Editor Gil Ho Yoon
Jihun Kim earned B.S. and M.S. in mechanical design and production engineering from Hanyang University in 1997 and 1999. He is currently a Ph.D. student in the Department of Aerospace Engineering at the Korea Advanced Institute of Technology (KAIST; Daejeon, South Korea) and has been working as a Senior Researcher for the Korea Aerospace Research Institute (2002–present). His research interests are the design and test evaluation of an electromagnetic launcher and a space launch vehicle.
Jaemyung Ahn is currently an Associate Professor of aerospace engineering at the Korea Advanced Institute of Science and Technology (KAIST; Daejeon, South Korea). His research interests include systems engineering, Design of experiments (DOE), and aerospace vehicle controls. He previously worked for the Korea Aerospace Research Institute (1999–2004) as a System Engineer and for Bain & Company (2008–2010) as a Management Consultant. He received his B.S. and M.S. degrees from Seoul National University in 1997 and 1999, and a Ph.D. degree in aeronautics and astronautics from MIT in 2008.
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Kim, J., Ahn, J. Modeling and optimization of a reluctance accelerator using DOE-based response surface methodology. J Mech Sci Technol 31, 1321–1330 (2017). https://doi.org/10.1007/s12206-017-0231-0
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DOI: https://doi.org/10.1007/s12206-017-0231-0