TY - GEN
T1 - An adaptive mesh refinement approach for viscous fluid-structure computations using eulerian vertex-based finite volume methods
AU - Borker, Raunak
AU - Grimberg, Sebastian
AU - Farhat, Charbel
AU - Avery, Philip
AU - Rabinovitch, Jason
N1 - Publisher Copyright:
© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2018
Y1 - 2018
N2 - Embedded Boundary Methods (EBMs) for the solution of fluid and Fluid-Structure Interaction (FSI) problems are typically formulated in the Eulerian setting, which makes them especially attractive when the structure undergoes large structural motions and/or deformations, or topological changes. For viscous problems however, they suffer from a major drawback in that they do not track the boundary layers that form around embedded obstacles and therefore do not maintain them efficiently resolved. In this paper, this drawback is overcome using an Adaptive Mesh Refinement (AMR) approach based on the time-dependent distance from a computational cell to the nearest embedded surface which may deform and evolve in time. The proposed approach features a fast predictor-corrector algorithm for updating the distance to the wall that is particularly efficient for explicit-explicit time-stepping discretizations. These are preferred for highly nonlinear FSI computations such as those associated, for example, with the simulation of parachute inflation dynamics. For vertex-based finite volume computations performed on dual cells, AMR gives rise to non-conforming mesh configurations that complicate the semi-discretization process. The proposed AMR approach addresses this issue by appropriately managing the construction and destruction of edges, primal elements and dual cells, so that mesh conformity can be explicitly enforced during the mesh adaptation process. It is illustrated here with preliminary results obtained for the simulation of the inflation of a membrane in a supersonic airstream using the EBM for FSI computations known as FIVER (Finite Volume method with Exact two-material Riemann problems).
AB - Embedded Boundary Methods (EBMs) for the solution of fluid and Fluid-Structure Interaction (FSI) problems are typically formulated in the Eulerian setting, which makes them especially attractive when the structure undergoes large structural motions and/or deformations, or topological changes. For viscous problems however, they suffer from a major drawback in that they do not track the boundary layers that form around embedded obstacles and therefore do not maintain them efficiently resolved. In this paper, this drawback is overcome using an Adaptive Mesh Refinement (AMR) approach based on the time-dependent distance from a computational cell to the nearest embedded surface which may deform and evolve in time. The proposed approach features a fast predictor-corrector algorithm for updating the distance to the wall that is particularly efficient for explicit-explicit time-stepping discretizations. These are preferred for highly nonlinear FSI computations such as those associated, for example, with the simulation of parachute inflation dynamics. For vertex-based finite volume computations performed on dual cells, AMR gives rise to non-conforming mesh configurations that complicate the semi-discretization process. The proposed AMR approach addresses this issue by appropriately managing the construction and destruction of edges, primal elements and dual cells, so that mesh conformity can be explicitly enforced during the mesh adaptation process. It is illustrated here with preliminary results obtained for the simulation of the inflation of a membrane in a supersonic airstream using the EBM for FSI computations known as FIVER (Finite Volume method with Exact two-material Riemann problems).
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U2 - 10.2514/6.2018-1072
DO - 10.2514/6.2018-1072
M3 - Conference contribution
AN - SCOPUS:85141582622
SN - 9781624105241
T3 - AIAA Aerospace Sciences Meeting, 2018
BT - AIAA Aerospace Sciences Meeting
T2 - AIAA Aerospace Sciences Meeting, 2018
Y2 - 8 January 2018 through 12 January 2018
ER -