Experimental methodology and uncertainty quantification on full-body rotation measurements of micro-sized curved fibers in turbulence
ORAL
Abstract
This work details the principles of a novel technique for measuring full-body rotation coupled with Lagrangian tracking of anisotropic micro-sized fibers. This method leverages the fiber's geometric anisotropy: its tapered shape enables the measurement of tumbling, while its curvature allows for the quantification of spinning. Existing literature provides comprehensive insights into Lagrangian tracking for estimating point-wise variables such as velocities and acceleration. However, there is a noticeable gap in guidelines pertaining to gyro-tracking, specifically the tumbling and spinning along fiber trajectories.
The analysis explores the influence of fiber geometry and imaging parameters on the measurement of full-body rotation. By combining synthetic data with experimental results, we examine the effects of magnification and sampling frequency on the uncertainty of rotation rate measurements. Additionally, this work compares the rotational matrix and quaternion techniques for computing rotations. A technique based on the iterative closest point algorithm is also proposed to retrieve a posteriori uncertainty quantification of the rotation rates from experimental data.
The analysis explores the influence of fiber geometry and imaging parameters on the measurement of full-body rotation. By combining synthetic data with experimental results, we examine the effects of magnification and sampling frequency on the uncertainty of rotation rate measurements. Additionally, this work compares the rotational matrix and quaternion techniques for computing rotations. A technique based on the iterative closest point algorithm is also proposed to retrieve a posteriori uncertainty quantification of the rotation rates from experimental data.
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Presenters
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Giuseppe Caridi
Technical University of Vienna
Authors
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Giuseppe Caridi
Technical University of Vienna
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Vlad Giurgiu
Technical University of Vienna
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Marco De Paoli
Technical University of Vienna and University of Twente
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Alfredo Soldati
Vienna Univ of Technology, Univ. of Udine, Technical University of Vienna, Vienna Univ of Technology