Spend an hour watching the clouds roll overhead and no two of them will be the same. The complexity and dynamic motion of turbulence make these flows fascinating, even mesmerizing, to watch. Humans are a pattern-seeking species. We like to seek order in apparent chaos, and this, perhaps, is what makes turbulence such a captivating subject for scientists and artists alike.
Aerial fireworks are essentially semi-controlled explodingrockets. Here Discovery Channel shares high-speed video of fireworks taking off. The turbulent billowing exhaust on the ground is reminiscent of other rocket launches. The tube-launched firework clip is a great example of an underexpanded nozzle. The pressure of the gases in the tube is higher than the ambient air, so when the gases escape, the exhaust fans out to equalize the pressure. And, finally, the explosion that propels the colorful chemicals outward forms jets that can affect the final form of the display. To my American readers: Happy 4th of July! And be safe! (VIdeo credit: Discovery Slow-Down)
Hi, there is a guy, at my college, who is doing a master’s degree thesis in turbulence. He says he uses fractals and computational methods. Can you explain how fractals can be used in fluid dynamics?
That’s a good question! Fractals are a relatively recent mathematical development, and they have several features that make them an attractive tool, especially in the field of turbulence. Firstly, fractals, especially the Mandelbrot set shown above, demonstrate that great complexity can be generated out of simple rules or equations. Secondly, fractals have a feature known as self-similarity, meaning that they appear essentially the same regardless of scale. If you zoom in on the Mandelbrot set, you keep finding copy after copy of the same pattern. Nature, of course, doesn’t have this perfect infinite self-similarity; at some point things break down into atoms if you keep zooming in. But it is possible to have self-similarity across a large range of scales. This is where turbulence comes in. Take a look at the turbulent plume of the volcanic eruption in the photo above. Physically, it contains scales ranging from hundreds of meters to millimeters, and these scales are connected to one another by their motion and the energy being passed from one scale to another. There have been theories suggested to describe the relationship between these scales, but no one has yet found a theory truly capable of explaining turbulence as we observe it. Both the self-similarity and the complex nature of fractals suggest they could be useful tools in finally unraveling turbulence. In fact, Mandelbrot himself wrote several papers connecting the two concepts. Perhaps your friend will help find the next hints! (Image credit: U.S. Geological Survey, Wikimedia)
Observations show Jupiter’s iconic Great Red Spot is shrinking, most recently at a rate of more than 900 km a year. As it gets smaller, the storm is also changing shape and becoming more circular. Scientists don’t yet have an explanation for the shrinkage or its recent acceleration, but this is unsurprising given the rich complexity of the storm. For example, the source of the Red Spot’s longevity—it may be more than 300 years old—is still an open topic of research. Some of the most recent observations show smaller eddies feeding into the storm; the current hypothesis is that these eddies may be increasing the Red Spot’s dissipation and accelerating its breakup. (Photo credit: NASA/ESA; h/t to io9)
Flow patterns can change dramatically as fluid speed and Reynolds number increase. These visualizations show flow moving from left to right around a circular plunger. The lower Reynolds number flow is on the left, with a large, well-formed, singular vortex spinning off the plunger’s shoulder. The image on the right is from a higher Reynolds number and higher freestream speed. Now the instantaneous flow field is more complicated, with a string of small vortices extending from the plunger and a larger and messier area of recirculation behind the plunger. In general, increasing the Reynolds number of a flow makes it more turbulent, generating a larger range of length scales in the flow and increasing its complexity. (Image credit: S. O’Halloran)
Sneezing and coughing are major contributors to the spread of many pathogens. Both are multiphase flows, consisting of both liquid droplets and gaseous vapors that interact. The image on the left shows a sneeze cloud as a turbulentplume. The kink in the cloud shows that plume is buoyant, which helps it remain aloft. The right image shows trajectories for some of the larger droplets ejected in a sneeze. Like the sneeze cloud, these droplets persist for significant distances. The buoyancy of the cloud also helps keep aloft some of the smaller pathogen-bearing droplets. Researchers are building models for these multiphase flows and their interactions to better predict and counter the spread of such airborne pathogens. For similar examples of fluid dynamics in public health, see what coughing looks like, how hospital toilets may spread pathogens, and how adjusting viscoelastic properties may counter these effects. (Image credit: L. Bourouiba et al.)
Every year Chicago dyes its river green in honor of St. Patrick’s Day. This timelapse video shows this year’s dyeing, including several passes from a boat distributing the green dye. The color is remarkably slow to diffuse. The boat’s passage does little to affect the motion of the dye already in the river. This is because the boat mainly disturbs the surface and most of the color comes from dye spread throughout the water. It’s like if you tried to stir milk into your coffee just by tapping the surface with your spoon. Instead, the slower, large-scale turbulent motion of the river distributes the dye. For more St. Patrick’s Day physics, be sure to check out Guinness physics and why tapping a beer makes it foam. (Video credit: P. Tsai; submitted by Bobby E.)
Though they may appear random at first glance, turbulent flows do possess structure. The video above shows a numerical simulation of a mixing layer, a flow in which two adjacent regions of fluid move with different velocities. The upper third of the frame shows a top view, and the bottom frame shows a side view, in which the upper fluid layer moves faster than the lower one. The difference in velocities creates shear which quickly drives the mixing layer into turbulence. But watch the chaos carefully, and your eye will pick out vortices rolling clockwise in the largest scales of the mixing layer. These features are known as coherent structures, and they are key to current efforts to understand and model turbulent flows. (Video credit: A. McMullan)
Finally, today’s lead image comes from our friends at Think Elephants, who study elephant intelligence over in Thailand and occasionally capture the animals’ mastery of fluid dynamics. Be sure to check them out and follow them on Twitter and Facebook.