Distortion of passive scalar structure during suction-based plume sampling

• Published in: Sensors and actuators. B, Chemical Vol. 367; p. 132018
• Main Authors: True, Aaron C., Crimaldi, John P.
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 15-09-2022; Elsevier Science Ltd
• Subjects: Computational fluid dynamics; Dimensional analysis; Distortion; Dynamic structural analysis; Filaments; Fluid flow; Mathematical models; Odors; Odors, MSC 0000, 1111; Parameters; Passive scalars; Photoionization; Photoionization detector; Plume dynamics; Pulse duration; Pulse shape; Reynolds number; Sampling; Scalars; Suction; Suction flow; Odors, MSC 0000, 1111; 0000; 1111; Plume dynamics; Suction flow; Passive scalars; Distortion; Photoionization detector
• ISSN: 0925-4005; 1873-3077
• DOI: 10.1016/j.snb.2022.132018

Studies of plume dynamics and olfaction often rely on photoionization detectors (PID) to quantify spatiotemporal distributions of passive scalars (gases, vapors, odors). However, the potential for PID suction to distort filaments and to modify the resulting sensed time record remains unclear. We used computational fluid dynamics to model a widely-used PID to quantify and parameterize suction distortion by considering how sensed concentration records compare to those registered by an ideal probe absent distorting effects. Models cover a range of realistic plume conditions, and we show that PID can modify the peak concentration and pulse shape of sensed records, with peak amplitude reduced by up to 45% and pulse width increased by up to 100% for the cases considered here. We quantified how distortion varies in three key nondimensional parameters describing PID geometry and plume sampling conditions: relative suction rate, relative filament size, and ambient flow Reynolds number. We combined analytical and numerical tools with dimensional analysis and scaling arguments to interpret results and discuss when distortion is likely and what drives it. We built a dimensionless distortion scaling parameter and simple regressions capable of predicting distortion levels, and our results enable PID users to estimate distortion levels and to employ mitigation strategies through suction velocity tuning. We show that an ideal relative suction rate (ratio of suction-to-ambient velocities) near 30 minimizes distortion universally for the Aurora Scientific miniPID. The findings and discussion herein can inform distortion-mitigating design principles and best sampling practices for other suction-based passive scalar sensing schemes.
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•Modeled photoionization detector (PID) gas sampling using computational fluid dynamics.•Parameterized PID distortion levels for a range of realistic plume conditions.•Created regressions that predict distortion levels given PID operational parameters.•Identified distortion mitigation strategies for a common commercially-available PID through suction velocity tuning.•Informed other suction-based sensing schemes through dimensionless distortion scaling parameter and prediction regressions.