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M. Kiran Raj and S. Chakraborty
voltage (limited by the inertia of the solenoid valve) waveform of a specific duty
cycle with the desired frequency sourced from a function generator.
The differential pressure drop across the microchannel length can be measured
using a differential pressure sensor connected to a data acquisition system (DAQ)
which is interfaced with a computer. The DAQ continuously acquires the raw voltage
from the pressure sensor and is converted to physical units (Pa) based on the instrument calibration chart. Usually, a high sampling rate is employed in the DAQ which
is matched with the response time of the pressure sensor.
Estimation of the wall deformation is the most sensitive measurement in such a
study. A three-dimensional scanning technique like the confocal microscope is ideal
for the deformation measurement in usual rectangular glass-PDMS microchannels
[3]. Further, indirect methods utilizing the fluorescent microscopy and dyed fluid
are also used for estimating the deformation of the top wall [4]. However, in a
cylindrical channel, due to the axisymmetric nature of the wall, deformation can be
observed directly under the microscope with a simple phase-contrast microscopy.
Standard edge detection algorithms are applied to the captured images that will give
an accurate location of the wall position. A high-speed camera is used to capture the
real time will deformation using high magnification zoom lenses to focus near the
wall.
For flow visualization, PIV apparatus is utilized. Fluorescent seeding particles
like polystyrene beads of 1–10 µm nominal diameters are used as tracers which are
neutrally buoyant and faithfully follow the streamlines in the flow. The synchronizer
of the PIV is synced with the pressure sensor with Transistor–Transistor Logic (TTL)
signal from a computer for simultaneous measurement of pressure drop and the
velocity field. An iterative multi-pass cross-correlation algorithm using a Fast Fourier
Transform (FFT) is employed to evaluate the final velocity field. For steady flow,
ensembles averaging of a large number of pairs are used and for the pulsatile flow,
phase averaging over multiple cycles is analyzed. Representative images for microPIV and deformation analysis are given in Fig. 11. All the measurements for pressure
drop, deformation, and micro-PIV are recorded after reaching a steady state.
6 Numerical Techniques to Solve FSI Problems
The origin and development of FSI lie in the ocean engineering and aerospace engineering where large-scale structures are subjected to flow of water and air. It is also
crucial in understanding the design considerations of many structures like bridges
and skyscrapers. Failing to foresee the oscillatory interactions with high-speed wind
can be catastrophic for these structures which are subjected to fatigue (e.g., the tragic
failure of Tacoma Bridge in 1940). The equations that define this phenomenon are
too complex in general to solve analytically and experiments and numerical solutions
are the only way out. It can be perceived as a merger between Computational Fluid
Dynamics (CFD) techniques and computational structural dynamics.
M. Kiran Raj and S. Chakraborty
voltage (limited by the inertia of the solenoid valve) waveform of a specific duty
cycle with the desired frequency sourced from a function generator.
The differential pressure drop across the microchannel length can be measured
using a differential pressure sensor connected to a data acquisition system (DAQ)
which is interfaced with a computer. The DAQ continuously acquires the raw voltage
from the pressure sensor and is converted to physical units (Pa) based on the instrument calibration chart. Usually, a high sampling rate is employed in the DAQ which
is matched with the response time of the pressure sensor.
Estimation of the wall deformation is the most sensitive measurement in such a
study. A three-dimensional scanning technique like the confocal microscope is ideal
for the deformation measurement in usual rectangular glass-PDMS microchannels
[3]. Further, indirect methods utilizing the fluorescent microscopy and dyed fluid
are also used for estimating the deformation of the top wall [4]. However, in a
cylindrical channel, due to the axisymmetric nature of the wall, deformation can be
observed directly under the microscope with a simple phase-contrast microscopy.
Standard edge detection algorithms are applied to the captured images that will give
an accurate location of the wall position. A high-speed camera is used to capture the
real time will deformation using high magnification zoom lenses to focus near the
wall.
For flow visualization, PIV apparatus is utilized. Fluorescent seeding particles
like polystyrene beads of 1–10 µm nominal diameters are used as tracers which are
neutrally buoyant and faithfully follow the streamlines in the flow. The synchronizer
of the PIV is synced with the pressure sensor with Transistor–Transistor Logic (TTL)
signal from a computer for simultaneous measurement of pressure drop and the
velocity field. An iterative multi-pass cross-correlation algorithm using a Fast Fourier
Transform (FFT) is employed to evaluate the final velocity field. For steady flow,
ensembles averaging of a large number of pairs are used and for the pulsatile flow,
phase averaging over multiple cycles is analyzed. Representative images for microPIV and deformation analysis are given in Fig. 11. All the measurements for pressure
drop, deformation, and micro-PIV are recorded after reaching a steady state.
6 Numerical Techniques to Solve FSI Problems
The origin and development of FSI lie in the ocean engineering and aerospace engineering where large-scale structures are subjected to flow of water and air. It is also
crucial in understanding the design considerations of many structures like bridges
and skyscrapers. Failing to foresee the oscillatory interactions with high-speed wind
can be catastrophic for these structures which are subjected to fatigue (e.g., the tragic
failure of Tacoma Bridge in 1940). The equations that define this phenomenon are
too complex in general to solve analytically and experiments and numerical solutions
are the only way out. It can be perceived as a merger between Computational Fluid
Dynamics (CFD) techniques and computational structural dynamics.