3D Computational Fluid and Particle Dynamics Simulations: Metrics of Aerosol Capture by Impaction Filters

• NCJ Number: 307996
• Journal: Journal of Breath Research Volume: 18 Issue: 1 Dated: 2023
• Author(s): Veruska Malavé; Kavita Jeerage; Edward Garboczi; Tara Lovestead
• Date Published: 2023
• Grant Number(s): DJO-NIJ-19-RO-0008
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)
• Award: Chemical Foundations of a Cannabis Breathalyzer

Annotation

The study developed and implemented a 3D multiscale computational fluid and particle dynamics (CFPD) model to explore human factors that could affect metrics of aerosol capture by impaction filters.

Abstract

In this study, the authors developed a 3D multiscale computational fluid and particle dynamics (CFPD) model to provide insight into human factors that could be important to control or measure during sampling. The researchers designed the model to characterize the local transport, spatial distribution, and deposition of polydisperse particles in a single impaction filter of a commercial aerosol collection device. The authors highlight the use of decoupling numerical strategies to simultaneously quantify the influence of filter geometry, fluid flowrate, and particle size. The authors’ numerical models showed the remarkable effect of flowrate on aerosol dynamics. Specifically, aerosol mass deposition, spatial distribution, and deposition mechanisms inside the filter. This work as well as future studies on the effect of filter geometry and human factors on aerosol collection will guide the development, standardization, and validation of breath sampling protocols for current and emerging breath tests for forensic and clinical applications. Human studies provide valuable information on components or analytes recovered from exhaled breath, but there are limitations due to inter-individual and intra-individual variation. Future development and implementation of breath tests based on aerosol analysis require a clear understanding of how human factors interact with device geometry to influence particle transport and deposition. The computational fluid and particle dynamics (CFPD) algorithm combines (i) the Eulerian approach to fluid dynamics and (ii) the Lagrangian approach to single particle transport and deposition to predict how particles are carried in fluids and deposited on surfaces. (Published Abstract Provided)