Bias in particle tracking acceleration measurement
Autor: | Michael Wilczek, Eberhard Bodenschatz, John Lawson, Cristian Lalescu |
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Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Fluid Flow and Transfer Processes
Noise (signal processing) Computer science Fluid Dynamics (physics.flu-dyn) Computational Mechanics FOS: Physical sciences General Physics and Astronomy Physics - Fluid Dynamics Lagrangian particle tracking Tracking (particle physics) 01 natural sciences 010305 fluids & plasmas 010309 optics Acceleration Mechanics of Materials Position (vector) Temporal resolution 0103 physical sciences Numerical differentiation Reduction (mathematics) Algorithm |
Popis: | We investigate sources of systematic error (bias) in acceleration statistics derived from Lagrangian particle tracking data and demonstrate techniques to eliminate or minimise these bias errors introduced during processing. Numerical simulations of particle tracking experiments in isotropic turbulence show that the main sources of bias error arise from noise due to random position errors and selection biases introduced during numerical differentiation. We outline the use of independent measurements and filtering schemes to eliminate these biases. Moreover, we test the validity of our approach in estimating the statistical moments and probability densities of the Lagrangian acceleration. Finally, we apply these techniques to experimental particle tracking data and demonstrate their validity in practice with comparisons to available data from the literature. The general approach, which is not limited to acceleration statistics, can be applied with as few as two cameras and permits a substantial reduction in the position accuracy and sampling rate required to adequately measure the statistics of Lagrangian acceleration. Graphical abstract: Sources of bias error in Lagrangian Particle Tracking measurements are explored. Methods are presented and validated to correct acceleration statistics for the main sources of systematic errors introduced by random position error and filtering, allowing for a substantial improvement in the effective temporal resolution of particle tracking measurements. [Figure not available: see fulltext.]. |
Databáze: | OpenAIRE |
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