1 research outputs found
Multi-level adaptive particle refinement method with large refinement scale ratio and new free-surface detection algorithm for complex fluid-structure interaction problems
Fluid-Structure Interaction (FSI) is a crucial problem in ocean engineering.
The smoothed particle hydrodynamics (SPH) method has been employed recently for
FSI problems in light of its Lagrangian nature and its advantage in handling
multi-physics problems. The efficiency of SPH can be greatly improved with the
Adaptive Particle Refinement (APR) method, which refines particles in the
regions of interest while deploying coarse particles in the left areas. In this
study, the APR method is further improved by developing several new algorithms.
Firstly, a new particle refinement strategy with the refinement scale ratio of
4 is employed for multi-level resolutions, and this dramatically decreases the
computational costs compared to the standard APR method. Secondly, the
regularized transition sub-zone is deployed to render an isotropic particle
distribution, which makes the solutions between the refinement zone and the
non-refinement zone smoother and consequently results in a more accurate
prediction. Thirdly, for complex FSI problems with free surface, a new
free-surface detection method based on the Voronoi diagram is proposed, and the
performance is validated in comparison to the conventional method. The improved
APR method is then applied to a set of challenging FSI cases. Numerical
simulations demonstrate that the results from the refinement with scale ratio 4
are consistent with other studies and experimental data, and also agree well
with those employing the refinement scale ratio 2. A significant reduction in
the computational time is observed for all the considered cases. Overall, the
improved APR method with a large refinement scale ratio and the new
free-surface detection strategy shows great potential in simulating complex FSI
problems efficiently and accurately.Comment: 47 pages, 26 figures, accepted to be published by Journal of
Computational Physic