A fully partitioned Lagrangian framework for FSI problems characterized by free surfaces, large solid deformations and displacements, and strong added-mass effects

Cerquaglia, Marco Lucio; Thomas, David M.; Boman, Romain; Terrapon, Vincent; Ponthot, Jean‐Philippe

doi:10.1016/j.cma.2019.01.021

Cited by 35 publications

(46 citation statements)

References 81 publications

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“…Fluid structure interaction coupling was performed using NASTRAN, an in-house MATLAB [54] code, or CUPyDO [55][56][57], depending on the software used to calculate the aerodynamic loads. The NASTRAN computations were performed by means of the elastic trim analysis, also known as SOL 144, which projects the loads directly on the structural model.…”

Section: Fluid-structure Couplingmentioning

confidence: 99%

Effect of Levels of Fidelity on Steady Aerodynamic and Static Aeroelastic Computations

et al. 2020

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Static aeroelastic deformations are nowadays considered as early as in the preliminary aircraft design stage, where low-fidelity linear aerodynamic modeling is favored because of its low computational cost. However, transonic flows are essentially nonlinear. The present work aims at assessing the impact of the aerodynamic level of fidelity used in preliminary aircraft design. Several fluid models ranging from the linear potential to the Navier–Stokes formulations were used to solve transonic flows for steady rigid aerodynamic and static aeroelastic computations on two benchmark wings: the Onera M6 and a generic airliner wing. The lift and moment loading distributions, as well as the bending and twisting deformations predicted by the different models, were examined, along with the computational costs of the various solutions. The results illustrate that a nonlinear method is required to reliably perform steady aerodynamic computations on rigid wings. For such computations, the best tradeoff between accuracy and computational cost is achieved by the full potential formulation. On the other hand, static aeroelastic computations are usually performed on optimized wings for which transonic effects are weak. In such cases, linear potential methods were found to yield sufficiently reliable results. If the linear method of choice is the doublet lattice approach, it must be corrected using a nonlinear solution.

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Section: Fluid-structure Couplingmentioning

confidence: 99%

Effect of Levels of Fidelity on Steady Aerodynamic and Static Aeroelastic Computations

et al. 2020

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“…15 Collapse of a water column on a elastic object. Comparisons of the PFEM results of Idelsohn et al [44], Zhu and Scott [113], Meduri et al [73], and Cerquaglia et al [14] remeshing and neither is affected by remapping operations. This solution appears to be a good way to preserve the historical variables information in a PFEM-solid formulation.…”

Section: Historical Variable Recoverymentioning

confidence: 99%

“…The Bingham law can be expressed with the following piecewise equations: being The incrementally discontinuous behaviour of Eqs. (14) and (15) and the unbounded value of viscosity, introduce numerical difficulties in the solution scheme which can be avoided using an exponential smoothing approximation [98]:…”

Section: Rheological Lawmentioning

confidence: 99%

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A State of the Art Review of the Particle Finite Element Method (PFEM)

Cremonesi

Franci

Idelsohn

et al. 2020

Arch Computat Methods Eng

118

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The particle finite element method (PFEM) is a powerful and robust numerical tool for the simulation of multi-physics problems in evolving domains. The PFEM exploits the Lagrangian framework to automatically identify and follow interfaces between different materials (e.g. fluid–fluid, fluid–solid or free surfaces). The method solves the governing equations with the standard finite element method and overcomes mesh distortion issues using a fast and efficient remeshing procedure. The flexibility and robustness of the method together with its capability for dealing with large topological variations of the computational domains, explain its success for solving a wide range of industrial and engineering problems. This paper provides an extended overview of the theory and applications of the method, giving the tools required to understand the PFEM from its basic ideas to the more advanced applications. Moreover, this work aims to confirm the flexibility and robustness of the PFEM for a broad range of engineering applications. Furthermore, presenting the advantages and disadvantages of the method, this overview can be the starting point for improvements of PFEM technology and for widening its application fields.

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“…The particle finite element method (PFEM) is a hybrid method combining the flexibility of a Lagrangian particle method with the robustness of a classical finite element method (FEM) formulation [1]. It has been recently introduced to treat free-surface fluid flow problems, including polymer melt flows [2] or nuclear melt-downs [3] and fluid-structure interaction [4], but also applications such as metal forming [5] and ground excavation [6]. The ability to treat solids ESAFORM 2021.…”

Section: Intr Introduction Oductionmentioning

confidence: 99%

Phase change driven adaptive mesh refinement in PFEM

et al. 2021

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The particle finite element method (PFEM) is used to simulate a simple phase change problem. This is a first step towards the simulation of additive manufacturing (AM) processes at the meso-scale, where the liquid melt pool interacts with the surrounding solid material and undergoes phase change. The focus of this paper lies on strategies to deal with the release or absorption of latent heat in the PFEM, especially with regard to mesh refinement. We briefly describe how mesh refinement in PFEM works and how it can be chosen specifically to achieve convergence despite the highly non-linear latent heat term. It is found that good agreement with the literature can be achieved on a simple 1D phase change test case, while using an automatic local mesh refinement.

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A fully partitioned Lagrangian framework for FSI problems characterized by free surfaces, large solid deformations and displacements, and strong added-mass effects

Cited by 35 publications

References 81 publications

Effect of Levels of Fidelity on Steady Aerodynamic and Static Aeroelastic Computations

Effect of Levels of Fidelity on Steady Aerodynamic and Static Aeroelastic Computations

A State of the Art Review of the Particle Finite Element Method (PFEM)

Phase change driven adaptive mesh refinement in PFEM

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