Chuangnan Wang
Characterization of ultrasonic bubble clouds in a liquid metal by synchrotron X-ray high speed imaging and statistical analysis
Wang, Chuangnan; Connolley, Thomas; Tzanakis, Iakovos; Eskin, Dmitry; Mi, Jiawei
Authors
Thomas Connolley
Iakovos Tzanakis
Dmitry Eskin
Professor Jiawei Mi J.Mi@hull.ac.uk
Professor of Materials
Abstract
Quantitative understanding of the interactions of ultrasonic waves with liquid and solidifying metals is essential for developing optimal processing strategies for ultrasound processing of metal alloys in the solidification processes. In this research, we used the synchrotron X-ray high-speed imaging facility at Beamline I12 of the Diamond Light Source, UK to study the dynamics of ultrasonic bubbles in a liquid Sn-30wt%Cu alloy. A new method based on the X-ray attenuation for a white X-ray beam was developed to extract quantitative information about the bubble clouds in the chaotic and quasi-static cavitation regions. Statistical analyses were made on the bubble size distribution, and velocity distribution. Such rich statistical data provide more quantitative information about the characteristics of ultrasonic bubble clouds and cavitation in opaque, high-temperature liquid metals.
Citation
Wang, C., Connolley, T., Tzanakis, I., Eskin, D., & Mi, J. (2020). Characterization of ultrasonic bubble clouds in a liquid metal by synchrotron X-ray high speed imaging and statistical analysis. Materials, 13(1), Article 44. https://doi.org/10.3390/ma13010044
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 16, 2019 |
Online Publication Date | Dec 20, 2019 |
Publication Date | Jan 1, 2020 |
Deposit Date | Apr 14, 2022 |
Publicly Available Date | Apr 14, 2022 |
Journal | Materials |
Electronic ISSN | 1996-1944 |
Publisher | MDPI |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Issue | 1 |
Article Number | 44 |
DOI | https://doi.org/10.3390/ma13010044 |
Keywords | Ultrasonic bubble clouds; Synchrotron X-ray imaging; Metal solidification; Ultrasound melt processing |
Public URL | https://hull-repository.worktribe.com/output/3467024 |
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Copyright Statement
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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