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 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

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