Terzioglu, F. orcid.org/0000-0002-2639-2992, Rongong, J. and Lord, C. (2023) Motional phase maps for estimating the effectiveness of granular dampers. Mechanical Systems and Signal Processing, 188. 110038. ISSN 0888-3270
Abstract
This paper evaluates simple but general links between the operating dynamic motional phases and the non-linear energy dissipation characteristics of granular dampers. The Discrete Element Method is used to simulate a typical granular medium consisting of spherical particles in a cylindrical enclosure subjected to harmonic vibrations aligned both parallel and perpendicular with gravity. A set of equivalent experiments is conducted to verify the numerical model. A wide range of excitation frequency and amplitude are considered, to obtain many different motional phases, along with particle size and volume fill ratio. Granular motional phase maps are produced over amplitude-frequency plane that defines where the various motion phases are present providing rich information for the effectiveness of granular dampers. Findings show that high granular damping effectiveness is found in two distinct zones: where collective collisions with the enclosure are optimised and where fluidisation without convection is maximised. The most significant factors affecting these high effectiveness zones are identified and can be used to provide guidance for those seeking to design granular dampers to reduce vibrations in structures.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Granular energy dissipation; Particle damper; Particle motion; Granular motion phase; Particle fluidisation; Bouncing bed |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Dec 2022 14:42 |
Last Modified: | 19 Dec 2022 14:42 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ymssp.2022.110038 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:194345 |