scholarly journals Bayesian Calibration for Large‐Scale Fluid Structure Interaction Problems Under Embedded/Immersed Boundary Framework

2022 ◽  
Author(s):  
Shunxiang Cao ◽  
Daniel Zhengyu Huang
Keyword(s):  
Large Scale ◽  
Fluid Structure Interaction ◽  
Immersed Boundary ◽  
Bayesian Calibration ◽  
Fluid Structure ◽  
Structure Interaction

Analysis of a Nonlinear Friction Damping Mechanism in a Fluid-Structure Interaction System

1995 ◽  
Author(s):  
Oded Gottlieb ◽  
Michael Feldman ◽  
Solomon C. S. Yim
Keyword(s):  
Large Scale ◽  
Fluid Structure Interaction ◽  
Simulated Data ◽  
Identification Algorithm ◽  
Nonlinear Friction ◽  
Friction Damping ◽  
Restoring Force ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Interaction System

Abstract Analysis of a nonlinear friction damping mechanism in a fluid-structure interaction system is performed by combining a generalized averaging procedure with a recently developed identification algorithm based on the Hilbert transform. The system considered includes a nonlinear restoring force and a nonlinear dissipation force incorporating both viscous and structural damping. Frequency and damping response backbone curves obtained from simulated data are compared with analytical and approximate solutions and are found to be accurate. An example large scale experiment exhibiting viscous and Coulomb damping is also analyzed resulting in identification of system parameters.

Sequential Fluid-Structure Interaction of a Large-Scale Gas Control Valve

2010 ◽  
Vol 455 ◽  
pp. 146-150
Author(s):  
Fang Cao ◽  
Yong Wang ◽  
Y.T. An
Keyword(s):  
Large Scale ◽  
Fluid Structure Interaction ◽  
Fluid Pressure ◽  
Control Valve ◽  
Practical Significance ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Gas Control ◽  
Stress And Deformation ◽  
Pressure Stress

According to the real structure and work condition of a large-scale gas control valve used in recycling generating electricity project, a sequential fluid-structure interaction system model of control valve is set up, the coupling of fluid and valve plug is studied. The complicated fluid pressure, stress and deformation of balanced valve plug and stem at different control valve openings are investigated. The root cause of plug vibration by fluid is revealed. The natural frequency and modes of vibration are obtained, which could verify whether the design overcomes resonance. All of these are in favor of realizing design optimization in fluid-structure interaction and are of great practical significance for advancing study on large-scale control valves.

Numerical investigation of nonlinear fluid–structure interaction dynamic behaviors under a general Immersed Boundary-Lattice Boltzmann-Finite Element method

2018 ◽  
Vol 29 (04) ◽  
pp. 1850038 ◽  
Author(s):  
Chun-Lin Gong ◽  
Zhe Fang ◽  
Gang Chen
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Lattice Boltzmann ◽  
Fluid Structure Interaction ◽  
Numerical Approach ◽  
Immersed Boundary ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Flexible Objects ◽  
Element Method

A numerical approach based on the immersed boundary (IB), lattice Boltzmann and nonlinear finite element method (FEM) is proposed to simulate hydrodynamic interactions of very flexible objects. In the present simulation framework, the motion of fluid is obtained by solving the discrete lattice Boltzmann equations on Eulerian grid, the behaviors of flexible objects are calculated through nonlinear dynamic finite element method, and the interactive forces between them are implicitly obtained using velocity correction IB method which satisfies the no-slip conditions well at the boundary points. The efficiency and accuracy of the proposed Immersed Boundary-Lattice Boltzmann-Finite Element method is first validated by a fluid–structure interaction (F-SI) benchmark case, in which a flexible filament flaps behind a cylinder in channel flow, then the nonlinear vibration mechanism of the cylinder-filament system is investigated by altering the Reynolds number of flow and the material properties of filament. The interactions between two tandem and side-by-side identical objects in a uniform flow are also investigated, and the in-phase and out-of-phase flapping behaviors are captured by the proposed method.

Fluid–Structure Interaction Study and Flowrate Prediction Past a Flexible Membrane Using Immersed Boundary Method and Artificial Neural Network Techniques

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Mithun Kanchan ◽  
Ranjith Maniyeri
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Immersed Boundary Method ◽  
Fluid Structure Interaction ◽  
Immersed Boundary ◽  
Flexible Membrane ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Boundary Method ◽  
Artificial Neural

Abstract Many microfluidics-based applications involve fluid–structure interaction (FSI) of flexible membranes. Thin flexible membranes are now being widely used for mixing enhancement, particle segregation, flowrate control, drug delivery, etc. The FSI simulations related to these applications are challenging to numerically implement. In this direction, techniques like immersed boundary method (IBM) have been successful. In this study, two-dimensional numerical simulation of flexible membrane fixed at two end points in a rectangular channel subjected to uniform fluid flow is carried out at low Reynolds number using a finite volume based IBM. A staggered Cartesian grid system is used and SIMPLE algorithm is used to solve the governing continuity and Navier–Stokes equations. The developed model is validated using the previous research work and numerical simulations are carried out for different parametric test cases. Different membrane mode shapes are observed due to the complex interplay between the hydrodynamics and structural elastic forces. Since the membrane undergoes deformation with respect to inlet fluid conditions, a variation in flowrate past the flexible structure is confirmed. It is found that, by changing the membrane length, bending rigidity, and its initial position in the channel, flowrate can be controlled. Also, for membranes that are placed at the channel midplane undergoing self-excited oscillations, there exists a critical dimensionless membrane length condition L ≥ 1.0 that governs this behavior. Finally, an artificial neural network (ANN) model is developed that successfully predicts flowrate in the channel for different membrane parameters.

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