Abstract
In this chapter, we present efficient parametric design optimization and control strategies using data-driven model reduction techniques. In particular, we explore various suppression devices based on passive-based wake stabilization and active-based synthetic jet. A data-driven model reduction approach based on Eigensystem Realization Algorithm (ERA) is used to construct the reduced order model (ROM) in a state-space format.
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Notes
- 1.
Asymptotic range of convergence that is defined as \(\frac{\mathrm {GCI_{12}}}{r^p\times \mathrm {GCI_{23}}}\); where r is the grid refinement ratio and p is the order of convergence presented by Roache [361].
Acknowledgements
Some parts of this Chapter have been taken from the PhD thesis of Sandeep Reddy Bukka carried out at the National University of Singapore and supported by the Ministry of Education, Singapore, and the MASc thesis of Amir Chizfahm at the University of British Columbia supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).
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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Jaiman, R., Li, G., Chizfahm, A. (2023). Data-Driven Passive and Active Control. In: Mechanics of Flow-Induced Vibration. Springer, Singapore. https://doi.org/10.1007/978-981-19-8578-2_10
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DOI: https://doi.org/10.1007/978-981-19-8578-2_10
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Publisher Name: Springer, Singapore
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Online ISBN: 978-981-19-8578-2
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