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Effect of feathers on drag in plunge‐diving birds.

  • Published In: Annals of the New York Academy of Sciences, 2024, v. 1537, n. 1. P. 74 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Debenedetti, Florent; Jung, Sunghwan 3 of 3

Abstract

This study explores the impact of feathers on the hydrodynamic drag experienced by diving birds, which is critical to their foraging efficiency and survival. Employing a novel experimental approach, we analyzed the kinematics of both feathered and nonfeathered projectiles during their transition from air to water using high‐speed imaging and an onboard accelerometer. The drag coefficients were determined through two methods: a direct calculation from the acceleration data and a theoretical approach fitted to the observed velocity profiles. Our results indicate that feathers significantly increase the drag force during water entry, with feathered projectiles exhibiting approximately double the drag coefficient of their smooth counterparts. These findings provide new insights into the role of avian feather morphology in diving mechanics and have potential implications for the design of bioinspired aquatic vehicles in engineering. The study also discusses the biological implications of increased drag due to feathers and suggests that factors such as body shape might play a more critical role in the diving capabilities of birds than previously understood. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Annals of the New York Academy of Sciences. 2024/07, Vol. 1537, Issue 1, p74
  • Document Type:Article
  • Subject Area:Technology
  • Publication Date:2024
  • ISSN:0077-8923
  • DOI:10.1111/nyas.15181
  • Accession Number:178468428
  • Copyright Statement:Copyright of Annals of the New York Academy of Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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