Journal
JOURNAL OF FLUIDS AND STRUCTURES
Volume 105, Issue -, Pages -Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jfluidstructs.2021.103342
Keywords
Fluid-Structure Interaction; Moving Particle Semi-implicit; Hamiltonian particle method; Elastic structures; Conservation properties; Hyperelastic material
Categories
Funding
- JSPS (Japan Society for the Promotion of Science) KAKENHI [JP18K04368, JP18H03796]
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This paper introduces a 3D Lagrangian meshfree solver for fluid-structure interactions, which combines the MPS and HMPS models and verifies its stability, accuracy, convergence, and conservation properties through multiple benchmark tests. The adaptivity of the proposed solver is also demonstrated through a multi-resolution scheme.
The paper presents a 3D entirely Lagrangian meshfree solver for reproduction of fluid-structure interactions (FSI) corresponding to incompressible fluid flows and elastic structures. A projection-based particle method, namely, Moving Particle Semi-implicit (MPS), is coupled with a Hamiltonian particle-based structure model, referred to as Hamiltonian MPS (HMPS) structure model. The HMPS structure model is configured in the framework of Hamiltonian mechanics through consideration of the Lagrangian for a system of particles from which the motion equation for non-linear elastodynamics is derived via variational principles. The stability, accuracy and energy/momentum conservation properties of HMPS structure model are verified by four benchmark tests. The MPS and HMPS models are then coupled through application of a mathematically-physically compatible coupling scheme. The accuracy, stability, convergence and conservation properties of the presented 3D MPS-HMPS hydroelastic FSI solver are verified by considering four FSI benchmark tests. To the best of our knowledge, the paper presents the first 3D entirely Lagrangian meshfree hydroelastic FSI solver in the context of projection-based particle methods. In addition, through incorporation of a multi-resolution scheme the adaptivity of the proposed solver is also portrayed. (C) 2021 Elsevier Ltd. All rights reserved.
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