Numerical analysis of an elasto-flexible membrane blade using steady-state fluid–structure interaction simulations

Purpose The purpose of this exhaustive experimental study is to investigate the fluid-structure interaction in the flexible membrane wings over a range of angles of attack for various Reynolds numbers. Design/methodology/approach In this paper, an experimental study on fluid-structure interaction of flexible membrane wings was presented at Reynolds numbers of 2.5 × 104, 5 × 104 and 7.5 × 104. In the experimental studies, flow visualization, velocity and deformation measurements for flexible membrane wings were performed by the smoke-wire technique, multichannel constant temperature anemometer and digital image correlation system, respectively. All experimental results were combined and fluid-structure interaction was discussed. Findings In the flexible wings with the higher aspect ratio, higher vibration modes were noticed because the leading-edge separation was dominant at lower angles of attack. As both Reynolds number and the aspect ratio increased, the maximum membrane deformations increased and the vibrations became visible, secondary vibration modes were observed with growing the leading-edge vortices at moderate angles of attack. Moreover, in the graphs of the spectral analysis of the membrane displacement and the velocity; the dominant frequencies coincided because of the interaction of the flow over the wings and the membrane deformations. Originality/value Unlike available literature, obtained results were presented comparatively using the sketches of the smoke-wire photographs with deformation measurement or turbulence statistics from the velocity measurements. In this study, fluid-structure interaction and leading-edge vortices of membrane wings were investigated in detail with increasing both Reynolds number and the aspect ratio.

Download Full-text

Numerical Analysis of Fluid–Structure Interaction of Blood Flow Through a Flexible Tube with 90-Degree Bend Using OpenFOAM

Advances in Applied Mechanical Engineering - Lecture Notes in Mechanical Engineering ◽

10.1007/978-981-15-1201-8_35 ◽

2020 ◽

pp. 303-309

Author(s):

Rishabh N. Jaiswal ◽

Trushar B. Gohil

Keyword(s):

Blood Flow ◽

Numerical Analysis ◽

Fluid Structure Interaction ◽

Fluid Structure ◽

Structure Interaction ◽

Flexible Tube ◽

Flow Through

Download Full-text

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

Journal of Fluids Engineering ◽

10.1115/1.4045575 ◽

2020 ◽

Vol 142 (5) ◽

Cited By ~ 2

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.

Download Full-text