Turbulent Aggregation and Deposition Mechanism of Respirable Dust Pollutants under Wet Dedusting using a Two-Fluid...

Area of Science:

• Fluid dynamics
• Particle science
• Environmental engineering

Background:

• Wet dedusting is crucial for controlling airborne particulate matter.
• Existing models often lack detailed particle-droplet interaction dynamics.
• Understanding particle size distribution (PSD) is key to optimizing capture efficiency.

Purpose of the Study:

• To develop and validate a mathematical model for the wet dedusting process.
• To investigate the influence of particle size, spray flow, and ventilation on dedusting efficiency.
• To provide insights for optimizing wet dedusting systems.

Main Methods:

• Utilized a two-fluid (Euler-Euler) frame model incorporating particle aggregation (turbulence, Brownian diffusion) and gravitational deposition.
• Employed the population balance model (PBM) to track particle size distribution (PSD) evolution.
• Simulated various wet dedusting conditions and compared results with experimental data.

Main Results:

• The model demonstrated good agreement with experimental data, with dedusting efficiencies within an allowable error range.
• Dedusting efficiency decreases with decreasing particle size.
• Optimal droplet diameter for respirable dust capture is between 15μm and 70μm.
• Increasing droplet volume flow beyond a certain ratio yields diminishing returns in efficiency.

Conclusions:

• The developed model accurately predicts wet dedusting performance.
• Particle size, droplet size, spray flow rate, and ventilation speed are critical parameters influencing efficiency.
• The findings offer practical guidance for designing and operating efficient wet dedusting systems.