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Flow force calculation in the lattice Boltzmann method
Shaurya Kaushal1, Sauro Succi2, Santosh Ansumali1
1Engineering Mechanics Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore 560064, India.
This study introduces a novel, accurate force calculation method for rigid particles in viscous fluids simulated using the lattice Boltzmann method (LBM). The approach simplifies complex geometry analysis and reduces grid size needs for precise fluid dynamics simulations.
Area of Science:
- Computational Fluid Dynamics
- Fluid-Structure Interaction
- Numerical Methods
Background:
- Accurate force evaluation is crucial for simulating rigid particles in viscous fluids using the lattice Boltzmann method (LBM).
- Existing methods face challenges due to the noncommutativity of streaming and collision operators near solid boundaries.
Purpose of the Study:
- To propose a discrete force calculation scheme with enhanced accuracy for LBM simulations.
- To provide a theoretical explanation for operator noncommutativity in force evaluation.
- To develop a method applicable to complex geometries and reduce computational cost.
Main Methods:
- Theoretical analysis of streaming and collision operators in LBM with solid boundaries.
- Development of a discrete force calculation scheme based on a lattice Boltzmann formulation of the Reynolds transport theorem (RTT).
- Benchmark simulations including flow past a cylinder and NACA0012 airfoil.
Main Results:
- The proposed scheme demonstrates enhanced accuracy and reliability.
- The method effectively handles force evaluation on complex geometries.
- Significantly reduced grid size requirements for accurate force evaluation were observed across a range of Reynolds numbers (10^2 to 0.5x10^6).
Conclusions:
- The novel discrete force calculation scheme offers a more accurate and efficient approach for LBM simulations.
- This method simplifies the analysis of fluid-particle interactions, particularly for complex shapes.
- The reduced grid dependency makes LBM simulations more computationally feasible for engineering applications.
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