On the Ability of Positron Emission Particle Tracking (PEPT) to Track Turbulent Flow Paths with Monte Carlo Simulations in GATE

Positron emission particle tracking (PEPT) has offered important insights into the internal dynamics of multiphase flows. High precision and frequency measurements of the location of the tracer particle are required to resolve individual eddies at the millimetre scale or smaller. To explore the pote...

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Veröffentlicht in:Applied sciences 2023-05, Vol.13 (11), p.6690
Hauptverfasser: Perin, Rayhaan, Cole, Katie, van Heerden, Michael R., Buffler, Andy, Lin, Yi-Yu, Zhang, Jiahao, Brito-Parada, Pablo R., Shock, Jonathan, Peterson, Stephen W.
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Sprache:eng
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Zusammenfassung:Positron emission particle tracking (PEPT) has offered important insights into the internal dynamics of multiphase flows. High precision and frequency measurements of the location of the tracer particle are required to resolve individual eddies at the millimetre scale or smaller. To explore the potential of PEPT to perform these measurements, a model was developed of the Siemens ECAT “EXACT3D” HR++ positron emission tomography (PET) scanner at the PEPT Cape Town facility in South Africa with the software Geant4 Application for Tomographic Emission (GATE) and was used to generate Lagrangian tracks from simulations of moving tracer particles. The model was validated with measurements from both experiment and simulation and was extended to two virtual scenarios inspired by turbulent flows. The location data from the simulation accurately captured linear portions of an oscillating path up to high speeds of 25 m s−1; however, tracking tended to undercut the turning points due to the high tracer acceleration. For a particle moving on a spiral path of decreasing radius, the location data tracked the path above a radius of 2.0 mm with an uncertainty equivalent to the radius of the tracer particle, 300 μm. Improvements to the measurement are required to track sub-millimetre flow structures, such as the application of PET scanners with higher spatial resolution and upgrades to the sampling processes used in location algorithms.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13116690