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OpenFOAM Tutorial #1 - Intro, Installation & First Simulation

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Characteristics of Laminar and Turbulent Flow

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One of the most famous and enduring of all fluid dynamics experiments is Osborne Reynolds' pipe flow experiment, first published in 1883 and recreated in the video above. At the time, it was understood that flows could be laminar or turbulent, though Reynolds’ terminology of direct or sinuous is somewhat more poetic:

Again, the internal motion of water assumes one or other of two broadly distinguishable forms-either the elements of the fluid follow one another along lines of motion which lead in the most direct manner to their destination, or they eddy about in sinuous paths the most indirect possible. #

There had, however, been no direct evidence of these eddies in a pipe. Reynolds built an apparatus that allowed him to control the velocity of flow through a clear pipe and simultaneously introduce a line of dye into the flow. He carefully varied the velocity and temperature (and thus viscosity) in his apparatus and not only documented both laminar and turbulent flow but found that the transition from one to another could be described by a dimensionless number he derived from the Navier-Stokes equation. This number was dependent on the fluid’s velocity and kinematic viscosity as well as the diameter of the pipe. This was the birth of the Reynolds number, one of the most important parameters in all of fluid dynamics. (Video credit: S. dos Santos; research credit: O. Reynolds)

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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)

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fmtulab photos

Fmtulab photos from fmtulab

[fuckyeahfluiddynamics]

When fast-moving liquids encounter regions of slow-moving liquids, they decelerate rapidly, trading their kinetic energy for potential energy and creating a hydraulic jump. Flow in the video above is from left to right. The depth difference between the incoming and outgoing water can be directly related to the velocity of the incoming fluid. Hydraulic jumps in rivers and spillways are often extremely turbulent, like the one in this video, but laminar examples exist as well. In fact, with the right height and flow rate, you can create stable hydraulic jumps right in your kitchen sink. The hydraulic jumps formed from a falling jet are typically circular, but with the right conditions, all sorts of wild shapes can be observed. (Video credit: H. Chanson)

[fuckyeahfluiddynamics]

Vortex shedding frequently happens in the wakes of non-streamlined bodies as a result of flow around the obstacle. Newton’s third law states that forces come in equal and opposite pairs, meaning that the vortex shedding behind an obstacle is accompanied by a force on the obstacle. For a fixed cylinder, this is not always apparent, but for a pendulum, like the ones demonstrated in this video, this vortex-induced vibration causes significant motion. This same effect can make traffic lights and industrial chimneys sway. You’ve likely experienced it yourself as well, if while swimming you’ve ever spread your fingers underwater and spun in place. Try it sometime with your arm out and you’ll feel the vortices make your arm vibrate up and down as you spin.  (Video credit: Harvard Natural Sciences Lecture Demonstrations)

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One of the challenges in large-scale wind energy is that operating wind turbines do not behave exactly as predicted by simulation or wind tunnel experiments. To determine where our models and small-scale experiments are lacking, it’s useful to make measurements using a full-scale working turbine, but making quantitative measurements in such a large-scale, uncontrolled environment is very difficult. Here researchers have used natural snowfall as seeding particles for flow visualization. The regular gaps in the flow are vortices shed from the tip of the passing turbine blades. With a searchlight illuminating a 36 m x 36 m slice of the flow behind a wind turbine, the engineers performed particle image velocimetry, obtaining velocity measurements in that region that could then be correlated to the wind turbine’s power output. Such in situ measurements will help researchers improve wind turbine performance. (Video credit: J. Hong et al.)

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Boeing begins high-speed wind tunnel tests on 777X in Seattle … http://www.aerospace-technology.com/news/newsboeing-begins-high-speed-wind-tunnel-tests-on-777x-in-seattle-4160672

[fuckyeahfluiddynamics]

New research using free-flying northern bald ibises shows that during group flights the birds’ positioning and flapping maximize aerodynamic efficiency. In flight, a bird’s wings generate wingtip vortices, just as a fixed-wing aircraft does. These vortices stretch in the bird’s wake, creating upwash in some regions and downwash in others as the bird flaps. According to theory, to maximize efficiency a trailing bird should exploit upwash and avoid downwash by flying at a 45-degree angle to its leading neighbor and matching its flapping frequency. The researchers found that, on average, this was the formation and timing the flock assumed. In situations where the birds were flying one behind the next in a straight line, the birds tended to offset their flapping by half a cycle relative to the bird ahead of them—another efficient configuration according to theory. Researchers don’t yet know how the birds track and match their neighbors; perhaps, like cyclists in a peloton, they learn by experience how to position themselves for efficiency. For more information, see the researchers’ video and paper. (Photo credit: M. Unsold; research credit: S. Portugal; via Ars Technica; submitted by M. P. van Wyk)

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The Fluid Mechanics Lab at the NASA Ames Research Center.

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GE wind turbines spinning on a California hilltop

Source

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by Vasilis K. Chasiotis

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Wind engineering - Cfd simulation of wind field & pollution dispersion

[fuckyeahfluiddynamics]

Today’s post is largely brought to you by the fact that I have been sick the past four days and my fiance and I have been bingeing on Star Trek Voyager. At some point, we began wondering about the sequence from 0:30-0:49 in which Voyager flies through a nebula and leaves a wake of von Karman vortices. Would a starship really leave that kind of wake in a nebula?

My first question was whether the nebula could be treated as a continuous fluid instead of a collection of particles. This is part of the continuum assumption that allows physicists to treat fluid properties like density, temperature, and velocity as well-defined quantities at all points. The continuum assumption is acceptable in flows where the Knudsen number is small. The Knudsen number is the ratio of the mean free path length to a characteristic flow length, in this case, Voyager's size. The mean free path length is the average distance a particle travels before colliding with another particle. Nebulae are much less dense than our atmosphere, so the mean free path length is larger  (~ 2 cm by my calculation) but still much smaller than Voyager's length of 344 m. So it is reasonable to treat the nebula as a fluid.

As long as the nebula is acting like a fluid, it’s not unreasonable to see alternating vortices shed from Voyager. But are the vortices we see realistic relative to Voyager's size and speed? Physicists use the dimensionless Strouhal number to describe oscillatory flows and vortex shedding. It’s a ratio of the vortex shedding frequency times the characteristic length to the flow’s velocity. We already know Voyager's size, so we just need an estimate of its velocity and the number of vortices shed per second. I visually estimated these as 500 m/s and 2.5 vortices/second, respectively. That gives a Strouhal number of 0.28, very close to the value of 0.2 typically measured in the wake of a cylinder, the classical case for a von Karman vortex street.

So far Voyager's wake is looking quite reasonable indeed. But what about its speed relative to the nebula's speed of sound? If Voyager is moving faster than the local speed of sound, we might still see vortex shedding in the wake, but there would also be a bow shock off the ship’s leading edge. To answer this question, we need to know Voyager's Mach number, its speed relative to the local speed of sound. After some digging through papers on nebulae, I found an equation to estimate speed of sound in a nebula (Eq 9 of Jin and Sui 2010) using the specific gas constant and temperature. Because nebulae are primarily composed of hydrogen, I approximated the nebula’s gas constant with hydrogen’s value and chose a representative temperature of 500 K (also based on Jin and Sui 2010). This gave a local speed of sound of 940 m/s, and set Voyager's Mach number at 0.53, inside the subsonic range and well away from any shock wave formation.

Of course, these are all rough estimates and back-of-the-envelope fluid dynamics calculations, but my end conclusion is that Voyager's vortex shedding wake through the nebula is realistic after all! (Video credit: Paramount; topic also requested by heuste11)

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CAE Linux

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