Simulation of Large-Amplitude Three-Dimensional Liquid Sloshing in Spherical Tanks

Tang, Yong; Yue, Baozeng

doi:10.2514/1.j055798

Cited by 23 publications

(7 citation statements)

References 22 publications

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“…For larger mesh movements, other techniques need to be used. Numerical approaches such as those proposed using a pseudoelastic formulation (Behr and Abraham, 2002; Charlot et al , 2015; Castorrini et al , 2019), solving a Laplace problem (Löhner and Yang, 1996; Yong and Baozeng, 2017) or minimizing the elemental distortion of the mesh (López et al , 2007; Battaglia et al , 2022) can be adapted either to gas–liquid or solid–liquid interface moving mesh analyses.…”

Section: Numerical Methods For the Fluid–solid Interaction Modelmentioning

confidence: 99%

A numerical and experimental study of a buoy interacting with waves

Núñez Aedo,

Cruchaga,

Storti

2023

HFF

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Purpose This paper aims to report the study of a fluid buoy system that includes wave effects, with particular emphasis on validating the numerical results with experimental data. Design/methodology/approach A fluid–solid coupled algorithm is proposed to describe the motion of a rigid buoy under the effects of waves. The Navier–Stokes equations are solved with the open-source finite volume package Code Saturne, in which a free-surface capture technique and equations of motion for the solid are implemented. An ad hoc experiment on a laboratory scale is built. A buoy is placed into a tank partially filled with water; the tank is mounted into a shake table and subjected to controlled motion that promotes waves. The experiment allows for recording the evolution of the free surface at the control points using the ultrasonic sensors and the movement of the buoy by tracking the markers by postprocessing the recorded videos. The numerical results are validated by comparison with the experimental data. Findings The implemented free-surface technique, developed within the framework of the finite-volume method, is validated. The best-obtained agreement is for small amplitudes compatible with the waves evolving under deep-water conditions. Second, the algorithm proposed to describe rigid-body motion, including wave analysis, is validated. The numerical body motion and wave pattern satisfactorily matched the experimental data. The complete 3D proposed model can realistically describe buoy motions under the effects of stationary waves. Originality/value The novel aspects of this study encompass the implementation of a fluid–structure interaction strategy to describe rigid-body motion, including wave effects in a finite-volume context, and the reported free-surface and buoy position measurements from experiments. To the best of the authors’ knowledge, the numerical strategy, the validation of the computed results and the experimental data are all original contributions of this work.

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Section: Numerical Methods For the Fluid–solid Interaction Modelmentioning

confidence: 99%

A numerical and experimental study of a buoy interacting with waves

Núñez Aedo,

Cruchaga,

Storti

2023

HFF

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“…The pressure gradient projection for stabilized schemes can be treated implicitly or explicitly, and we adopt the explicit format in pursuing computational efficiency. The matrix form equations (Equation (17)(18)(19)) are modified to the stabilized scheme as follows:…”

Section: Pressure Stabilization Based On Pressure Gradient Projectionmentioning

confidence: 99%

“…An effective mesh updating method has been proposed in our earlier article. 18 In this method, the nodes on the free surface and contact line are restricted to move along prescribed semielliptical and semicircular orbits, respectively, the nodes on the container wall are moved by an algebraic mesh-moving algorithm, and the nodes in the interior fluid domain are moved by solving Laplace equation.…”

Section: Mesh Updating Strategymentioning

confidence: 99%

“…Typically, the arbitrary Lagrangian-Eulerian (ALE) framework is widely adopted in moving-grid finite element methods, which has been successfully used to describe a variety of free-boundary flows. [14][15][16][17][18] In this method, the free-surface mesh may evolve with the fluid but the motion of the interior grid can be independent of the physical flow and be defined to minimize the distortion of the volume mesh only.…”

Section: Introductionmentioning

confidence: 99%

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Improved method for implementing contact angle condition in simulation of liquid sloshing under microgravity

Tang

Yue

Yan

2018

Numerical Methods in Fluids

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Summary The finite element simulation of liquid sloshing under microgravity is focused on in this paper. For this class of flows, an important issue is to implement the contact angle boundary condition appropriately. A novel method of adding infinitely small free‐surface mesh just adjacent to the contact line is proposed here, which coincides with the physical definition of the contact angle. This free‐surface mesh has its orientation determined according to the contact angle, and the mean curvature at the contact line can be computed using this orientation. Hence, surface tension force can be computed and incorporated as an essential boundary condition into the pressure solve. This method is convenient to be applied in three‐dimensional simulations, and the use of relatively coarse meshes near the contact line is allowed. In order to validate the proposed method, several numerical simulations of flows in two‐dimensional circular and three‐dimensional cylindrical and spherical containers are presented, including calculation of equilibrium positions of the free surfaces, unsteady flows of liquid reorientation, and large‐amplitude nonlinear liquid sloshing under lateral excitation in microgravity. Parts of the numerical results are compared with the theoretical and published experimental results.

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“…However, when large amplitude sloshing occurs traditional finite element-based methods frequently fail to provide accurate results. To address this issue, advanced numerical methods such as arbitrary Lagrangian-Eulerian elements [17,18] and smoothed particle hydrodynamics [19,20] are introduced, where the former focuses on maintaining a high-quality mesh throughout an analysis when large deformation occurs and the latter is meshless and uses a collection of pseudo-particles to represent a given body. While knowing these equations and using advanced numerical methods allow us to simulate liquid sloshing in a variety of tanks, reliable and high-fidelity PDE-governed models remain elusive in many tank and baffle settings.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning-based Characterization Framework for Parametric Representation of Nonlinear Sloshing

Luo¹,

Kareem²,

Yu³

et al. 2022

Preprint

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The growing interest in creating a parametric representation of liquid sloshing inside a container stems from its practical applications in modern engineering systems. The resonant excitation, on the other hand, can cause unstable and nonlinear water waves, resulting in chaotic motions and non-Gaussian signals. This paper presents a novel machine learning-based framework for nonlinear liquid sloshing representation learning. The proposed method is a parametric modeling technique that is based on sequential learning and sparse regularization. The dynamics are categorized into two parts: linear evolution and nonlinear forcing. The former advances the dynamical system in time on an embedded manifold, while the latter causes divergent behaviors in temporal evolution, such as bursting and switching. The proposed framework's merit is demonstrated using an experimental dataset of liquid sloshing in a tank under horizontal excitation with a wide frequency range and various vertical slat screen settings.

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Simulation of Large-Amplitude Three-Dimensional Liquid Sloshing in Spherical Tanks

Cited by 23 publications

References 22 publications

A numerical and experimental study of a buoy interacting with waves

A numerical and experimental study of a buoy interacting with waves

Improved method for implementing contact angle condition in simulation of liquid sloshing under microgravity

A Machine Learning-based Characterization Framework for Parametric Representation of Nonlinear Sloshing

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