Skip to main content

Research Repository

Advanced Search

Identification of particle-laden flow features from wavelet decomposition

Jackson, Andrew M.; Turnbull, Barbara

Authors



Abstract

A wavelet decomposition based technique is applied to air pressure data obtained from laboratory-scale powder snow avalanches. This technique is shown to be a powerful tool for identifying both repeatable and chaotic features at any frequency within the signal. Additionally, this technique is demonstrated to be a robust method for the removal of noise from the signal as well as being capable of removing other contaminants from the signal. Whilst powder snow avalanches are the focus of the experiments analysed here, the features identified can provide insight to other particle-laden gravity currents and the technique described is applicable to a wide variety of experimental signals.

Citation

Jackson, A. M., & Turnbull, B. (2017). Identification of particle-laden flow features from wavelet decomposition. Physica D: Nonlinear Phenomena, 361, https://doi.org/10.1016/j.physd.2017.09.009

Journal Article Type Article
Acceptance Date Sep 28, 2017
Online Publication Date Oct 10, 2017
Publication Date Dec 15, 2017
Deposit Date Oct 9, 2017
Publicly Available Date Oct 11, 2018
Journal Physica D: Nonlinear Phenomena
Print ISSN 0167-2789
Electronic ISSN 0167-2789
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 361
DOI https://doi.org/10.1016/j.physd.2017.09.009
Keywords Wavelet, Particle-laden gravity current, Filtering, Signal processing
Public URL http://eprints.nottingham.ac.uk/id/eprint/47058
Publisher URL http://www.sciencedirect.com/science/article/pii/S0167278917302890
Copyright Statement Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0

Files

paper_accepted.pdf (2.1 Mb)
PDF

Copyright Statement
Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0





You might also like



Downloadable Citations