Computational fluid dynamics (CFD) simulation of a newly designed passive particle sampler

Area of Science:

• Environmental Science
• Atmospheric Science
• Engineering

Background:

• Accurate measurement of airborne particle deposition is crucial for environmental monitoring and health risk assessment.
• Passive dry deposition (Pas-DD) samplers offer a method for collecting airborne particles without active sampling.
• Understanding particle deposition dynamics on sampler surfaces is essential for optimizing sampler design and data interpretation.

Purpose of the Study:

• To computationally predict particle deposition on a novel passive dry deposition (Pas-DD) sampler.
• To investigate the influence of particle size, wind speed, sampler geometry, and angle of attack on deposition velocity.
• To validate simulation results against experimental measurements.

Main Methods:

• Computational fluid dynamics (CFD) simulations using ANSYS-FLUENT.
• Application of the k-ɛ turbulence model for mean flow field evaluation.
• Discrete Random Walk (DRW) model for generating turbulent fluctuating velocities.
• Simulation of particle deposition for sizes ranging from 0.5 to 10 μm.

Main Results:

• Deposition velocity increases with increasing particle size and wind speed.
• Non-zero angles of attack enhance particle deposition.
• Sampler geometry, particularly the leading edge design, significantly affects particle-size and wind-speed dependency.
• Foam roughness has a minor impact on particle deposition.

Conclusions:

• CFD simulations provide a reliable method for predicting particle deposition on Pas-DD samplers.
• Sampler design modifications, especially at the leading edge, can optimize particle capture efficiency.
• The study's findings support the development of improved passive sampling technologies for airborne particles.