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TrackFit: Uncertainty Quantification, Optimal Filtering and Onterpolation of Tracks for Time-Resolved Lagrangian Particle Tracking

Gesemann, Sebastian (2021) TrackFit: Uncertainty Quantification, Optimal Filtering and Onterpolation of Tracks for Time-Resolved Lagrangian Particle Tracking. In: Proceedings of 14th International Symposium on Particle Image Velocimetry, 1 (1), pp. 1-8. ILLINOIS Tech / Paul V. Galvin Library. 14th International Symposium on Particle Image Velocimetry 2021, 01.-04.08.2021, Chicago, USA (online). doi: 10.18409/ispiv.v1i1.92.

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Official URL: https://doi.org/10.18409/ispiv.v1i1.92

Abstract

Advanced Lagrangian Particle Tracking methods (such as the STB algorithm (Schanz et al. 2016)) are a very useful tool for uncovering properties of flow. As a measurement technique, the results of such methods are perturbed by different sources of errors and noise. This work addresses the problem of optimal filtering of particle tracks as well as estimating uncertainties of derived quantities such as location, velocity and acceleration of observed particles. The behavior and performance of this new filtering method (“TrackFit”), first introduced at Gesemann et al. 2016 is analyzed and compared to the Savitzky–Golay filter (Savitzky & Golay 1964) which is commonly used for these purposes. The optimal choice of parameters of this filtering method as well as the uncertainty quantification of the reconstructed tracks can be extracted from a spectral analysis of the recorded raw particle tracking data. This is in contrast to a Savitzky–Golay filter where the choice of parameters might often be driven by experience and gut feeling. In addition, we show that regardless of the choice of Savitzky–Golay filter parameters, the resulting filter will not approximate the ideal noise reduction filter well unlike the “TrackFit” described in this work.

Item URL in elib:https://elib.dlr.de/144996/
Document Type:Conference or Workshop Item (Speech)
Additional Information:https://doi.org/10.18409/ispiv.v1i1, https://www.iit.edu/ispiv2021, Paper 271
Title:TrackFit: Uncertainty Quantification, Optimal Filtering and Onterpolation of Tracks for Time-Resolved Lagrangian Particle Tracking
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Gesemann, Sebastiansebastian.gesemann (at) dlr.dehttps://orcid.org/0000-0001-9740-5888
Date:August 2021
Journal or Publication Title:Proceedings of 14th International Symposium on Particle Image Velocimetry
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:1
DOI :10.18409/ispiv.v1i1.92
Page Range:pp. 1-8
Editors:
EditorsEmailEditor's ORCID iD
Christensen, Kenneth T.Kenneth.Christensen@iit.eduUNSPECIFIED
Publisher:ILLINOIS Tech / Paul V. Galvin Library
Series Name:Conference Proceedings
Status:Published
Keywords:Lagrangian Particle Tracking, Uncertainty Quantification, Filtering
Event Title:14th International Symposium on Particle Image Velocimetry 2021
Event Location:Chicago, USA (online)
Event Type:international Conference
Event Dates:01.-04.08.2021
Organizer:Illinois Institute of Technology
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Efficient Vehicle
DLR - Research area:Aeronautics
DLR - Program:L EV - Efficient Vehicle
DLR - Research theme (Project):L - Virtual Aircraft and  Validation
Location: Göttingen
Institutes and Institutions:Institute for Aerodynamics and Flow Technology > Experimental Methods, GO
Deposited By: Micknaus, Ilka
Deposited On:26 Nov 2021 18:35
Last Modified:22 Feb 2022 18:28

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