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Improving Ultrasonic Melt Treatment Efficiency Through Flow Management: Acoustic Pressure Measurements and Numerical Simulations

Improving Ultrasonic Melt Treatment Efficiency Through Flow Management: Acoustic Pressure Measurements and Numerical Simulations

Subroto, Tungky, Eskin, Dmitry, Beckwith, Christopher, Tzanakis, Iakovos, Djambazov, Georgi ORCID: 0000-0001-8812-1269 and Pericleous, Koulis ORCID: 0000-0002-7426-9999 (2020) Improving Ultrasonic Melt Treatment Efficiency Through Flow Management: Acoustic Pressure Measurements and Numerical Simulations. In: Light Metals 2020. The Minerals, Metals & Materials Book Series (MMSS) . Springer, Cham, Switzerland, pp. 981-987. ISBN 978-3-030-36408-3 ISSN 2367-1181 (Print), 2367-1696 (Online) (doi:https://doi.org/10.1007/978-3-030-36408-3_132)

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Abstract

The current challenge for upscaling the ultrasonic melt processing (USP) technology to industrial scale is in improving the treatment efficiency using a single-sonotrode setup. To achieve this, we suggest two innovative approaches: increasing the melt residence time and exploiting acoustic resonance. This can be achieved through flow management in a launder by partitions where the resonance length within the partitions is equal or at integer steps to the wavelength of the incident sound wave. This study focuses on acoustic pressure measurements at different partition configurations and flow conditions combined with numerical modelling of the process. The measurements are done both in liquid aluminum and in water as its transparent analogue. The acoustic pressure measurements are then used to assess melt treatment improvement through cavitation activity and pressure distribution in the launder as well as to verify and further develop the numerical model.

Item Type: Conference Proceedings
Title of Proceedings: Light Metals 2020
Uncontrolled Keywords: Ultrasonic melt processing, Acoustic pressure, Aluminum, Numerical modeling
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Liberal Arts & Sciences > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Science & Engineering Group (CSEG)
Faculty of Liberal Arts & Sciences > Department of Mathematical Sciences
Last Modified: 05 Feb 2020 16:21
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/26867

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