Optimization of sparse sensor placement for estimation of wind direction and surface pressure distribution using time-averaged pressure-sensitive paint data on automobile model
This study proposes a method for predicting the wind direction against the simple automobile model (Ahmed model) and the surface pressure distributions on it by using data-driven optimized sparse pressure sensors. Positions of sparse pressure sensor pairs on the Ahmed model were selected for estimation of the yaw angle and reconstruction of pressure distributions based on the time-averaged surface pressure distributions database of various yaw angles, whereas the symmetric sensors in the left and right sides of the model were assumed. The surface pressure distributions were obtained by pressure-sensitive paint measurements. Three algorithms for sparse sensor selection based on the greedy algorithm were applied, and the sensor positions were optimized. The sensor positions and estimation accuracy of yaw angle and pressure distributions of three algorithms were compared and evaluated. The results show that a few optimized sensors can accurately predict the yaw angle and the pressure distributions.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01676105
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Supplemental Notes:
- © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Inoba, Ryoma
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0000-0001-8084-6599
- Uchida, Kazuki
- Iwasaki, Yuto
- Nagata, Takayuki
- Ozawa, Yuta
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0000-0002-5895-0506
- Saito, Yuji
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0000-0003-2804-8076
- Nonomura, Taku
- Asai, Keisuke
- Publication Date: 2022-8
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References;
- Pagination: 105043
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Serial:
- Journal of Wind Engineering & Industrial Aerodynamics
- Volume: 227
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0167-6105
- Serial URL: https://www.sciencedirect.com/journal/journal-of-wind-engineering-and-industrial-aerodynamics
Subject/Index Terms
- TRT Terms: Aerodynamic force; Automobiles; Sensors; Vehicle dynamics; Wind
- Subject Areas: Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01851289
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 14 2022 11:32AM