An adaptive, formally second order accurate version of the immersed boundary method

By Boyce E. Griffith, R. Hornung, David M. McQueen, Charles S. Peskin. Journal of Computational Physics, 2007

376 citations recorded by the source corpus.

Subfields: Computational Mechanics, Fluid Flow and Transfer Processes

View Paper: https://www.semanticscholar.org/paper/6fe78693cfe0bdb790f101432ed1df0c4f46389c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Fang-Bao Tian
2. James F. Doyle
3. Bernard Rousseau
4. Hu Dai
5. Haoxiang Luo
6. Michael J. Shelley
7. John M. Stockie
8. O. D. Roure

In Fluid Flow and Transfer Processes

1. Michael J. Shelley
2. John M. Stockie
3. David J. Smith

Citations in the corpus

• Fluid–structure interaction involving large deformations: 3D simulations and applications to biological systems (2014, methodology): “On top of the fundamental ideas of the immersed-boundary method, many additional features have been developed to enhance the capability or improve the performance of the method, for example, multi-block and adaptive meshes to enable local refinement [14], curvilinear grids to adapt to the overall ge”
• Dynamics of Flexible Fibers in Viscous Flows and Fluids (2019, methodology): “To overcome this, [97] employed an adaptive-mesh version of the IBM [48] to study the dynamics of flexible fibers as models, in part, for diatom chains (diatoms are unicellular phytoplankton).”
• Modelling and simulation of porous immersed boundaries (2009, methodology): “several extensions to the IB method have been proposed in recent years that address the issues mentioned above, including high-order upwind discretizations of the convection terms which allow simulation of convection-dominated flows [17], and use of adaptive mesh refinement near the boundary to obta”