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An optimal scheme for simulations of colliding, particle-laden flows on unstructured grids
Grant Rydquist1, Mahdi Esmaily1
1Department of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14850, United States.
Journal of Computational Physics
|April 10, 2024
Summary
This study presents an optimal search box strategy to reduce computational costs in tracking Lagrangian particles. The method significantly lowers the expense of particle localization and collision detection in large-scale simulations.
Area of Science:
- Computational physics
- Scientific computing
- Numerical analysis
Background:
- Tracking Lagrangian particles on unstructured grids is computationally expensive.
- Particle localization and binary collision detection dominate simulation costs.
Purpose of the Study:
- To introduce an optimal search box strategy for efficient particle tracking.
- To reduce the computational cost of particle localization and collision detection.
Main Methods:
- Developed an a priori estimation for optimal search box count.
- The strategy is generic and requires minimal tuning.
- Approximated optimal search boxes for collision detection as the number of particles.
Main Results:
- Achieved significant cost reduction for particle localization and collision detection.
- Ensured nearly linear scaling of collision detection cost with particle count.
- Demonstrated method optimality across three diverse geometries.
Conclusions:
- The optimal search box strategy offers a scalable and efficient solution for large-scale particle simulations.
- This method substantially decreases computational overhead in complex simulations.
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