Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session L32: Immersed Boundary Methods
4:05 PM–6:41 PM,
Monday, November 19, 2018
Georgia World Congress Center
Room: B404
Chair: Haoxiang Luo, Vanderbilt University
Abstract ID: BAPS.2018.DFD.L32.3
Abstract: L32.00003 : Fluid-structure interaction of engineering geometries using a combined immersed finite element method and finite volume incompressible multiphase solver for high density and high shear flows*
4:31 PM–4:44 PM
Presenter:
Nishant Nangia
(Department of Engineering Sciences and Applied Mathematics, Northwestern University)
Authors:
Nishant Nangia
(Department of Engineering Sciences and Applied Mathematics, Northwestern University)
Amneet Pal Singh Bhalla
(Department of Mechanical Engineering, San Diego State University)
Neelesh Ashok Patankar
(Department of Mechanical Engineering, Northwestern University)
Many industrial fluid flow problems involve the interaction between rigid, heavy objects and one or more fluid phases. In the past few years, the constraint-based immersed boundary method (CIB) has been successfully used to simulate a wide range of fluid-structure interaction (FSI) problems. This method is robust since it can simulate arbitrarily moving bodies on regular Cartesian meshes, making use of adaptive mesh refinement near the fluid-solid interface to adequately resolve boundary layers.
In this work, we extend the CIB formulation and method to allow for a finite element based representation of the structure, enabling fully resolved simulation of industrial geometries. The method is coupled to a novel monolithic incompressible multiphase fluid solver. We show preliminary validation cases for both simple and complex geometries. Novel applications of this method include simulation of self-propelled vehicle aerodynamics and wave energy converter devices, in which the density ratio between the fluid and solid regions are more than three orders of magnitude.
*This work is supported by the National Science Foundation (award number SI2-SSI-1450374), the National Science Foundation Graduate Research Fellowship (award number DGE-1324585), and the SDSU start-up package to APSB.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.L32.3
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