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arXiv · 1903.03356

Kinematic and dynamic forcing strategies for predicting the transport of inertial capsules via a combined lattice Boltzmann-Immersed Boundary method

A. Coclite·S. Ranaldo·M. D. De Tullio·P. Decuzzi·G. Pascazio
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Abstract

Modeling the transport of deformable capsules under different flow regimens is crucial in a variety of fields, including oil rheology, blood flow and the dispersion of pollutants. The aim of this study is twofold. Firstly, a combined Lattice Boltzmann-Immersed Boundary (LBM-IB) approach is developed for predicting the transport of inertial deformable capsules. A Moving Least Squares (MLS) scheme has been implemented to correlate the pressure, velocity and force fields of the fluid domain with the capsule dynamics. This computational strategy has been named LBM Dynamic IB. Secondly, this strategy is directly compared with a more conventional approach, named LBM Kinematic IB, where capsules move with the same velocity of the surrounding fluid. Multiple test cases have been considered for assessing the accuracy and efficiency of the Dynamic over Kinematic IB scheme, including the stretching of circular capsules in shear flow, the transport in a plane Poiseuille flow of circular and biconcave capsules, with and without inertia. By monitoring the capsule geometry over time, the two schemes have been documented to be in excellent agreement, especially for low Capillary numbers (Ca $\leq$ 0.01), in the case of non-inertial capsules. Despite a moderate increase in computational burden, the presented LBM Dynamic IB scheme is the sole capable of predicting the dynamics of both non-inertial and inertial deformable capsules. The proposed approach can be efficiently employed for studying the transport of blood cells, cancer cells and nano/micro capsules within a capillary flow.

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A. Coclite, S. Ranaldo, M. D. De Tullio, P. Decuzzi, G. Pascazio. 2019-03-08. Kinematic and dynamic forcing strategies for predicting the transport of inertial capsules via a combined lattice Boltzmann-Immersed Boundary method. https://doi.org/10.1016/j.compfluid.2018.12.014

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