On the Formulation of Lagrangian Stochastic Models for Heavy-Particle Trajectories

Area of Science:

• Fluid dynamics
• Turbulence modeling
• Particle transport

Background:

• Existing models for heavy particle dispersion in turbulent flows have limitations.
• Ensuring consistency with Eulerian fluid velocity statistics is crucial for accurate modeling.

Purpose of the Study:

• To extend Lagrangian stochastic modeling for fluid velocities along heavy-particle trajectories.
• To simulate heavy particle trajectories in inhomogeneous turbulent flows.
• To validate model predictions against experimental results.

Main Methods:

• Extended the modeling approach of Sawford and Guest (1990).
• Formulated Lagrangian stochastic models for fluid velocities.
• Used models with heavy particle equations of motion for simulations in vertical turbulent pipe flow.

Main Results:

• Model predictions for particle-velocity statistics, deposition velocities, and mean concentrations agreed well with experiments.
• Predicted a mean particle concentration buildup within the viscous sublayer (y(+) ≈ 0.2).
• Results align with direct numerical simulations, contrasting with eddy-interaction models.

Conclusions:

• Lagrangian stochastic models, with modified timescales, effectively describe fluid velocities along heavy particle trajectories.
• The models offer a robust framework for simulating particle transport in complex turbulent environments.
• The findings highlight the importance of accurate sublayer modeling for particle deposition studies.