Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/111265
Title: FEM-Based Time-Reversal Enhanced Ultrasonic Cleaning
Authors: Mustonen, J.
Tommiska, O.
Holmström, A.
Rauhala, T.
Moilanen, P.
Gritsevich, M.
Salmi, A.
Hæggström, E.
Issue Date: 2021
Publisher: Elsevier B.V.
Elsevier BV
Citation: FEM-Based Time-Reversal Enhanced Ultrasonic Cleaning / J. Mustonen, O. Tommiska, A. Holmström et al. // Ultrasonics Sonochemistry. — 2021. — Vol. 79. — 105798.
Abstract: Pipe fouling is a challenging problem in many industrial applications. Current cleaning techniques require halting the production during the cleaning phase and the existing methods are unable to do targeted cleaning, even though fouling is often localized to certain areas inside the pipeline. To address this issue, we use FEM-simulated, time-reversed signals to focus ultrasound power onto a pre-determined location: a fouled pipe residing inside a Plexiglas container. Ultrasound cleaning with similar acoustic power was compared to the time-reversal enhanced method in terms of cleaning efficiency. The cleaning efficiency was determined by measuring how much fouling, by mass, both protocols removed from the surface of a Plexiglas pipe, using similar input electric power and equal cleaning time. Our results indicate that the proposed time-reversal-based technique removes three times more fouling than the standard ultrasound cleaning without focusing. The study extends our previous paper on FEM-based time-reversal focusing [1]. © 2021.
Keywords: EFFICIENCY
FINITE ELEMENT METHOD
ULTRASONIC CLEANING
'CURRENT
ACOUSTIC POWER
CLEANING EFFICIENCY
ELECTRIC POWER
LOCALISED
PLEXIGLAS
PLEXIGLASS PIPES
TIME-REVERSAL
TIME-REVERSED
ULTRASOUND POWER
FOULING
POLY(METHYL METHACRYLATE)
ARTICLE
CLEANING
CONTROLLED STUDY
ELECTRICITY
FINITE ELEMENT ANALYSIS
URI: http://elar.urfu.ru/handle/10995/111265
Access: info:eu-repo/semantics/openAccess
RSCI ID: 47513897
SCOPUS ID: 85117133359
WOS ID: 000714819700001
PURE ID: 23894771
ISSN: 1350-4177
DOI: 10.1016/j.ultsonch.2021.105798
metadata.dc.description.sponsorship: This work was supported by Altum Technologies Oy and Business Finland (project no. 8868/31/2017).
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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