Schlieren Imaging Systems for Flow Visualization | UNSW Canberra

Non-intrusive measurement techniques use optics and lasers to measure fluid flow properties without physically placing probes in the flow. These include laser-induced fluorescence for measuring species concentration, temperature, and pressure by exciting molecules at specific wavelengths and detecting resulting signals. Particle tracking velocimetry seeds particles into flows and tracks their movement to determine velocity. These techniques were originally developed for combustion research but have been adopted by fluid mechanics communities for studying hypersonic flows where intrusive methods are challenging due to extreme conditions.

Particle Image Velocimetry (PIV) is a non-intrusive whole-field flow measurement technique that tracks tracer particles seeded in a fluid to measure velocity; the technique uses double-pulsed laser illumination to capture particle images at two time instants, followed by cross-correlation analysis to determine particle displacement and calculate local fluid velocity, with tracer particle selection requiring careful balance between Stokes number considerations (for faithful flow following) and optical scattering properties (Rayleigh or Mie scattering regimes).

Particle Image Velocimetry (PIV) is a non-intrusive optical measurement technique that visualizes and quantifies fluid flow by illuminating tracer particles seeded in the flow with laser pulses separated by a controlled time interval, then recording their displacement between pulses to calculate velocity fields; unlike point-based probes that disturb the flow and provide single-location measurements, PIV captures whole-field velocity data simultaneously, making it ideal for studying complex transient flow structures such as those around aerodynamic surfaces, boundary layers, and shock waves.

Dispersed multi-phase flows involve particles suspended in turbulent fluid flows, where particles can be solid, liquid, or gaseous. Examples include air bubbles in liquids, sprays, and slurries. The carrier phase transports these particles, and the stochastic nature of both turbulence and particle distribution makes these flows significantly more complex than single-phase flows. Particle Image Velocimetry (PIV) measures fluid velocity by tracking tracer particles seeded in the flow. The technique requires tracer particles with Stokes numbers much less than 0.1 to follow fluid motion across all turbulent scales. Laser systems use pulsed lasers (nanosecond duration) to freeze flow motion instantaneously, with laser sheet optics creating thin illumination planes. Advanced PIV configurations include stereo PIV for three-component velocity measurement, tomographic PIV for volumetric 3D reconstruction, high-speed PIV for transient events, and micro PIV for microscopic flows. When applying PIV to dispersed phases, significant challenges arise: PIV yields size-averaged velocities rather than size-resolved data. Phase separation challenges occur when particle size distributions overlap, causing crosstalk between phases. Laser Induced Fluorescence (LIF) provides robust phase separation by adding fluorescent dye to one phase, enabling optical separation through wavelength filtering and enabling droplet sizing through intensity ratios.

Laser-based diagnostics address the limitations of conventional methods by providing non-intrusive, high-resolution measurements. The main techniques include Laser Doppler Velocimetry (LDV) for velocity field measurement, Laser-Induced Fluorescence (LIF) for temperature and species field measurement, Particle Image Velocimetry (PIV) for velocity field measurement, Rayleigh scattering for thermography and temperature measurement, Mie scattering for size measurement, Spontaneous Raman scattering for species measurement, and Emission and Absorption Spectroscopy for species fields. These techniques enable multi-parameter measurements with high spatial and temporal resolution in combustion systems, providing comprehensive characterization of both chemistry and fluid mechanics.

The computational fluid dynamics simulation process involves four main steps: (1) defining or importing the geometry into the computer, (2) discretizing the flow field around the configuration into small computational cells, (3) applying a flow solver algorithm to compute the fluid behavior, and (4) using graphics workstations to visualize and analyze the resulting data. Once validated against experimental data, this technology is disseminated for industry use to help design safer, more fuel-efficient aircraft at reduced costs.

This segment demonstrates CFD results visualization and validation against analytical solutions. The process includes: (1) visualizing simulation results through velocity and pressure plots, (2) creating line plots to show pressure drops along the flow direction, (3) extracting point pressure values at specific locations, and (4) comparing CFD results with analytical calculations. The validation shows excellent agreement between CFD-calculated kinematic pressure (61.9) and analytical result (61,000.81 Pascal), confirming simulation accuracy. This validation step is essential for establishing confidence in CFD results before applying them to more complex real-world scenarios.

This video presents a comprehensive methodology for validating CFD simulations of turbulent flows when experimental data is unavailable. The core approach involves analyzing the U+ vs y+ plot, which shows dimensionless velocity versus dimensionless wall distance in logarithmic scale. This universal tool works for any geometry and Reynolds number as long as the flow is fully developed and attached. Key validation criteria include: laminar shear stress contributions existing only in the viscous sublayer (y+ < 5), turbulence production peaking in the buffer layer (y+ = 10-30), and turbulent viscosity increasing from zero at the wall before decreasing in the outer layer. Two modeling approaches exist: wall-resolving (fine meshes, y+ < 1, high accuracy, high cost) and wall-modeling (coarse meshes, y+ > 30, lower accuracy, lower cost). The law of the wall correlation enables wall-modeling by relating wall shear stresses to friction velocity. Proper validation requires ensuring the flow is fully turbulent (y+ > 30) and that production-dissipation balances match theoretical expectations.

This tutorial demonstrates how to visualize and analyze CFD simulation results using ParaView, covering surface visualization techniques (pressure, velocity, wall shear stress, and streamlines using Surface LIC), volume visualization methods (slices and 3D streamlines), and quantitative analysis (calculating forces and torques through surface integrals and total pressure coefficient contours).

This segment covers simulation results and flow visualization for CFD. Results include flow field data, forces, and moments on the vehicle, including pressure distributions, velocity fields, and aerodynamic forces. Visualization tools provide contour plots, vector plots, and streamline plots to analyze flow features. The instructor demonstrates how to visualize results, extract key metrics, and analyze flow patterns. Results are typically compared with experimental data or known solutions to validate the simulation. The segment emphasizes the importance of proper visualization for extracting meaningful insights from CFD simulations.

A polarization-based focusing schlieren system that uses a single Ronchi ruling as both the source and cutoff grid, combined with a retro-reflective background, enabling self-aligned imaging without requiring separate source and cutoff grids or optical access through both wind tunnel windows; this design allows for rapid setup, sensitivity adjustment via prism positioning, and high-speed imaging up to 1 MHz, making it suitable for challenging wind tunnel and arc jet facility environments.

Traditional schlieren setups use a knife edge to block deflected light, but cell phone cameras work adequately because their small aperture naturally blocks deflected light. Alignment requires turning on the phone's flashlight while recording and observing the tiny spot of light cast back by the mirror. This spot must be perfectly aligned with the camera center, achieved by adjusting mirror adjustment screws while watching the phone display.

Successful schlieren experiments require precise adherence to geometric optics principles and meticulous alignment procedures. The fundamental equations governing two-lens systems are 1/X1 + 1/X2 = 1/f1 and 1/X3 + 1/X4 = 1/f2, with total magnification M = (X4 × X2)/(X3 × X1). Real image formation requires X1 > f1 and X3 > f2, with all components fitting within the optical table. Practical setup involves calculating distances beforehand, aligning laser beams precisely along the optical axis, adjusting mirrors to direct light to the test section center, verifying perpendicularity to windows, and positioning the knife edge at the focal point. Alignment is critically important because small angular or positional errors significantly degrade measurements due to the weak dependence of refractive index on density. The real work begins after initial alignment, requiring patience and fine-tuning to achieve optimal results.

Schlieren imaging is a technique used in wind tunnel testing to visualize shock waves around aircraft models by exploiting the physics principle that light bends when passing through changes in fluid density; parallel light rays are sent through the test section, and when they encounter shock waves (regions of sharp density changes), they get deflected and blocked by a knife edge, appearing as dark lines in the captured image.

Shadowgraphy and Schlieren imaging exploit light propagation through optical media. Light travels uniformly through homogeneous media but changes speed when encountering inhomogeneities, creating small refractive index differences (as small as third/fourth decimal places). These schlieren can occur in solids, liquids, or gases. Shadowgraphy produces non-focused images providing qualitative insights, while Schlieren creates focused conjugate images enabling quantitative evaluation. Schlieren requires parabolic mirrors or lenses with a knife edge. The Z-type two mirror system uses a diverging illuminator beam and converging analyzer beam. Post-processing includes contrast stretching and histogram equalization without distorting images. These techniques visualize flow inhomogeneities invisible to the naked eye.