If you would like to contribute an item for inclusion in the next AFMS newsletter or appear on the gallery page of AFMS website then please contact the secretary of the AFMS at a.lucey [at] curtin.edu.au



Winners of the AFMS video competition 2018

Direct Numerical Simulation of Shock-Induced Turbulent Mixing 1st: Direct Numerical Simulation of Shock-Induced Turbulent Mixing

Direct numerical simulation of a turbulent mixing layer evolving from a three-dimensional, multimode Richtmyer-Meshkov instability. The animation depicts the evolution of volume fraction isosurfaces, showing red bubbles of rising light fluid and blue spikes of penetrating heavy fluid, after the interface between the two fluids is impacted by a shock wave.

Video created by Michael Groom, mentored by A/Prof. Ben Thornber, University of sydney.

Direct numerical simulations of turbulent sheared thermal convection 2nd: Direct numerical simulations of turbulent sheared thermal convection

The visualization reveals the final outcome of clear large scale meandering structures which are significantly more prominent than the large structures already observed in plane Couette flow. Depending on the choice of control parameters, these structures can be varied in thickness, number and wavelength. This type of flow, where buoyancy and shear interact, is a vital process in the area of fluid dynamics and the foundation for many mechanisms in nature.

Video created by Alexander Blass1, Xiaojue Zhu1, Jean M. Favre2, Roberto Verzicco1, Detlef Lohse1, Richard J.A.M. Stevens1; mentored by Prof. Detlef Lohse1.

Institutions: 1Physics of Fluids Group, University of Twente, The Netherlands. 2 Swiss National Supercomputing Center.


Actuator Surface Modelling of the Sikorsky X2 Rotor 3rd: Actuator Surface Modelling of the Sikorsky X2 Rotor

The Sikorsky X2 coaxial rotor was simulated in forward flight using an Actuator Surface Model (ASM). The ASM couples an aerodynamics model for the rotor blades and near wake to a CFD solver, reducing the computational cost and the pre-processing time by eliminating the body-fitted mesh. The X2 is an example of the kind of complex rotors which can be simulated using the ASM. Visualisation of the vortical structures in the wake clearly shows the strong interactions between the wakes of the upper and lower rotors, and the unsteady blade loading predictions reflect the interaction between the rotors.

Video created by Daniel Linton, mentored by A/Prof. Ben Thornber, University of Sydney.

Winners of the AFMS Photo competition 2018

Trailing vortices formed by a gliding delta wing in ground proximity 1st: Trailing vortices formed by a gliding delta wing in ground proximity
Understanding vortex-wall interactions has applications in the context of airplane trailing vortices, as well as in fundamental turbulence. We generate a counter-rotating vortex pair by towing a delta wing through water, supported by thin wires that do not generate a vortex wake. Fluorescein dye is applied to the leading and trailing edge of the delta wing, and made visible by an argon-ion laser. Rather than using a traditional flood-light of the entire wake, we use a technique whereby only a cross-section of the von Kármán vortex street “braid wake” is illuminated, whilst still simultaneously illuminating the out-of- plane vortex pair.

Image prepared by Sarah E. Morris mentored by Prof. C.H.K. Williamson, Cornell University, USA.
Renderings of temperature iso-surfaces from direct numerical simulations of two-phase vertical natural convection of water
2nd: Renderings of temperature iso-surfaces from direct numerical simulations of two-phase vertical natural convection of water.

Top left image: Vertical natural convection without light droplets. Bottom left image: Vertical natural convection with light driplets at 0.5% of the domain volume fraction. Right image: Vertical natural convection with light droplets at 2.0% of the domain volume fraction. The rising droplets disturb the initially quiescent temperature field, increasing mixing of warmer (towards red colour) and cooler (towards blue colour) fluids, which translates to an increase in heat transfer in the system.

Image prepared by Chong Shen Ng, Vamsi Spandan, Detlef Lohse and Roberto Verzicco mentored by Prof. Detlef Lohse and Prof. Roberto Verzicco, University of Twente, The Netherlands.
Direct numerical simulations of turbulent sheared thermal
convection
3rd: Direct numerical simulations of turbulent sheared thermal convection.

Direct numerical simulations of Rayleigh-Bénard flow with induced wall shearing have been performed on a 6912x3456x384 grid. Large coherent thermal structures emerge from the heated plate and meander. The vorticity formations are visualized with the Q-criterion. The zooms show small-scale structures in the flow.

Image prepared by Alexander Blass1, Xiaojue Zhu1, Jean M. Favre2, Roberto Verzicco1, Detlef Lohse1, Richard J.A.M. Stevens1; mentored by Prof. Detlef Lohse1.

Institutions: 1Physics of Fluids Group, University of Twente, The Netherlands. 2 Swiss National Supercomputing Center.



Winners of the 1st AFMS video contest

Dancing with the Stars 1st: Dancing with the Stars

A smoothed particle hydrodynamics simulation of two stars undergoing the common envelope interaction.

Video created by Thomas Reichardt, mentored by Orsola De Marco, Macquarie University.
Turbulence in a linearly stratified body of fluid 2nd: Turbulence in a linearly stratified body of fluid

When disturbance is created by an oscillating grid into a linearly stratified body of fluid, a special instability can be observed.

Video created by Scott Becker, Yanik Salgadoe, Imran Vilcassim, Ceser Daguet; mentored by Jimmy Philip, University of Melbourne.
Visualisation of wake flow induced by a moving manikin 3rd: Visualisation of wake flow induced by a moving manikin

CFD and Experimental techniques used for flow visualisation.

Video created by Yao Tao, mentored by Kiao Inthavong, RMIT.

References: Tao, Y., Inthavong, K., Tu, J. (2016). Computational fluid dynamics study of human-induced wake and particle dispersion in indoor environment. Indoor and Built Environment.
Inthavong, K., Tao, Y., Petersen, P., Mohanarangam, K., Yang, W., Tu, J. (2016) ‘A smoke visualisation technique for wake flow from a moving human manikin’ Journal of Visualization.


Tidal bore of the Garonne River (France) Tidal bore of the Garonne River (France)
A tidal bore is an unsteady rapidly-varied free-surface flow generated by the rapid rise in water elevation during the early flood tide, when the tidal range exceeds 4.5 to 6 m and the channel bathymetry amplifies the flood tidal wave. The photograph shows the tidal bore of the Garonne River at Podensac (France) on 23 August 2013, about 28 km upstream of the city of Bordeaux. Detailed field measurements were conducted in this tidal bore

Image provided by Prof. Hubert Chanson at the University of Queensland
Reference: Reungoat, D., Chanson, H., and Keevil, C.E. (2015), Journal of Hydraulic Research, IAHR, Vol. 53, No. 3, pp. 291-301 (DOI: 10.1080/00221686.2015.1021717)).
Oil film flow visualisation of tubercled, swept wing Oil film flow visualisation of tubercled, swept wing at a Reynolds number of 220,000 based on Mean Aerodynamic Chord.
Flow is from left to right. Talcum powder and oil were painted on the foil surface, revealing the surface streak pattern. The image shows that the flow behind the outboard trough has undergone complete stall, but the inboard progression of the separation zone is limited by the presence of the tubercles. Although the flow behind the tubercle peaks remain attached, the accumulation of powder at the trailing edge behind the troughs demonstrates that these zones undergo separation at a lower angle of attack than a similar wing without tubercles.

Image provided by Micheal Bolzon at University of Adelaide
Direct numerical simulation of a turbulent lifted flame.

The animation depicts a direct numerical simulation of a turbulent, lifted slot-jet flame. Vorticity magnitude is shown in blue/white, while heat release rate is shown in orange/red. The DNS were used to study the stabilisation mechanism of lifted flames, which is a long-standing problem in the combustion community. The analysis, published in the Journal of Fluid mechanics [S. Karami, E. R. Hawkes, M. Talei, J. H. Chen, J. Fluid Mech. 777 (2015), pp. 633-689], shows that the flame is stabilised by the propagation of partially premixed edge flames, moderated by the passage of large eddies. The research was supported by the Australian Research Council, and the simulation was performed on Raijin, operated by the National Computational Infrastructure (NCI).

Image provided by Shahram Karami at University of New South Wales

LES of a supersonic impinging jet.

Dr Shahram Karami and a team of PhD students in a project led by Professor Julio Soria at Laboratory for Turbulence Research in Aerospace and Combustion (LTRAC) within the Department of Mechanical and Aerospace Engineering at Monash University are developing a numerical framework to simulate supersonic free and impinging jets and study the instabilities and complex spatio-temporal structure of these flows. The animation presents the time evolution of the key parameters of one of the large eddy simulations of under-expanded supersonic impinging jets. The visualisation depicts the temporal evolution of isosurface of vorticity magnitude colored by total energy (left), velocity magnitude (right-top) and magnitude of the density gradient (right-bottom) where the quantities are normalised by the speed of sound and jet diameter (D).

Video provided by Dr Shahram Karami and Prof Julio Soria, Laboratory for Turbulence Research in Aerospace & Combustion (LTRAC), Department of Mechanical and Aerospace Engineering, Monash University. The research was supported by the Australian Research Council via Discovery and LIEF grants and National Computational Merit Allocation Scheme (NCMAS) grants. The simulation was performed on Raijin, operated by the National Computational Infrastructure (NCI).



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Schlieren flow visualisation and large eddy simulation (LES) of impinging under-expanded supersonic jet flow at a nozzle pressure ratio of 3.4.

Upper Image: The Schlieren flow visualization by Nick Mason-Smith, Daniel Edgington-Mitchell, Nicolas Buchmann, Damon Honnery and Julio Soria is at a stand-off distance of 2.5 (Mitchell, D. M., Honnery, D. R., & Soria, J. (2012). The visualization of the acoustic feedback loop in impinging underexpanded supersonic jet flows using ultra-high frame rate Schlieren, 15(4), 333–341.). Lower Image: The LES by Paul Stegeman, Andrew Ooi and Julio Soria was computed using a compressible in-house developed code at a standoff-off distance of 2.0, where the blue iso-surface of the second invariant of the velocity gradient tensor represents vortical structures, the red iso-surface represents negative divergence indicating highly compressible regions which are representative of the location of shocks and the planar contour plot represents the density of the fluid.

Image provided by: Prof. Julio Soria at Monash University



Streakline image of acoustic microstreaming Pressure distribution (colour spectrum from: red = 0Pa to blue = -44.3Pa) on the surface of the upper airway, from the nares (nose) to the tracheal-oesophageal branch, during inspiration for a flow-rate of 21L/min. The geometry is reconstructed from CT data and discretised using an unstructured mesh of 6 million cells.

Image provided by: Dr Julien Cisonni of the Fluid Dynamics Research Group at Curtin University



Streakline image of acoustic microstreaming Streakline image of acoustic microstreaming around a 225+/-25 micron diameter bubble excited into n=7 shape modes at 12 kHz.

Image provided by: A/Prof. Richard Manasseh of Swinburne Institute of Technology.
Reference: Tho et al 2007, J. Fluid Mech. Vol. 576, 191-233.



Time-averaged streamlines of a pitched and skewed vortex Time-averaged streamlines of a pitched and skewed vortex generating jet issuing into a turbulent boundary layer.
The streamlines show higher momentum fluid from the outer regions of the boundary layer (red streamlines) being swept into the near-wall region. The simulation was computed using a custom LES boundary-layer code; inlet boundary conditions were provided with a variant of the Lund et al inflow generation condition

Image provided by: Dr James Jewkes of the Fluid Dynamics Research Group at Curtin University
Reference: Jewkes et al., AIAA J. 49(1):247–250, 2011]



CFD flow field over an Austin Mini  CFD flow field (pressure contours and streamlines) over an Austin Mini at 72 km/h computed with RANS k­ω turbulence model using OpenFOAM on a 48‐core commodity cluster

Image provided by: Dr Andrew King of the Fluid Dynamics Research Group at Curtin University