FYFD

Tag: CFD

  • Hammerhead Hydrodynamics

    Hammerhead Hydrodynamics

    Hammerhead sharks have some of the most distinctive craniums in the ocean, which begs the question: how do they swim with that head? New computational fluid dynamics studies suggest that their long foil-shaped heads help the sharks maneuver swiftly, but they come at the cost of substantially higher drag. The researchers found that drag on the hammerhead’s cranium required energy expenditures more than 10 times higher than other sharks, but since the study looked at heads only, it’s possible that the rest of the shark’s positioning helps mitigate that cost. (Image credit: shark – J. Allert, CFD – M. Gaylord et al.; research credit: M. Gaylord et al.; via NYTimes; submitted by Kam-Yung Soh)

    Pressure contours and streamlines around a hammerhead shark head.
  • The Structure of the Blue Whirl

    The Structure of the Blue Whirl

    Several years ago, researchers discovered a new type of flame, the blue whirl. Now computational simulations have helped them untangle the complex structure of this clean-burning flame. Their work shows that the blue whirl is made up of three types of flames, which meet to form a fourth.

    The conical base of the whirl is a fuel-rich flame in which the fuel and oxygen are initially well-mixed. Above that is a diffusion flame, where the fuel and oxygen are initially separate and the flame’s ability to burn is limited by how readily the two mix. Along the sides of the blue whirl is a third flame type, visible only as a faint wisp. Like the first flame, this one is premixed, but it contains much less fuel than oxygen. Finally, those three flames meet in the bright blue ring of the whirl, where the ratio of fuel and oxygen is just right to burn the fuel completely. (Image and research credit: J. Chung et al.; via Science News; submitted by Kam-Yung Soh)

  • COVID-19 and Outdoor Exercise

    COVID-19 and Outdoor Exercise

    By now you’ve probably come across some blog posts and news articles about a new pre-print study looking at the aerodynamics of running and the potential exposure to exhaled droplets. And you may also have seen articles questioning the accuracy and validity of such simulations. I’ve had several readers submit questions about this, so I dug into both the research and the criticisms, and here are my thoughts:

    Is this study scientifically valid?

    I’ve seen a number of complaints that since this paper hasn’t been peer-reviewed, we shouldn’t trust anything about it. That seems like an unreasonable overreaction to me considering how many studies receive press attention prior to their actual peer-reviewed publication. This is not a random CFD simulation produced by someone who just downloaded a copy of ANSYS Fluent. This work comes from a well-established group of engineers specializing in sports aerodynamics, and long-time readers will no doubt recognize some of their previous publications. Over the past decade, Blocken and his colleagues have become well-known for detailed experimental and simulation work that indicates larger aerodynamic effects in slipstreams than what we generally recognize.

    In this paper, they lay out previous (biological) studies related to SARS and droplet exhalation; they use those papers and several wind tunnel studies to validate computational models of droplet evaporation and runner aerodynamics; and then they use those inputs to simulate how a cloud of exhaled droplets from one runner affects someone running alongside, behind, or in a staggered position relative to the first runner.

    In other words, their work includes all the components one would expect of a scientific study, and it makes scientifically justifiable assumptions with regard to its methods. (That’s not, mind you, to say that no one can disagree with some of those choices, but that’s true of plenty of peer-reviewed work as well.) All in all, yes, this is a scientifically valid study, even if it has not yet undergone formal peer-review*.

    Can simulations actually tell us anything about virus transmission?

    One complaint I’ve seen from both biologists and engineers is that simulations like these don’t actually capture the full physics and biology involved in virus transmission. While I agree with that general sentiment, I would point out two important facts:

    1) Blocken et al. acknowledge that this is not a virology study and confine their scientific results to looking at what happens physically to droplets when two people are moving relative to one another. Whether those droplets can transmit disease or not is a question left to biological researchers.

    2) Most medical and biological research also does not account for the physics of droplet transmission and transport. For the past century, this research has focused almost exclusively on droplet sizes, with the assumption that large droplets fall quickly and small droplets persist a little longer. To my knowledge, some of the only work done on the actual physics of the turbulent cloud produced by coughing or sneezing comes from Lydia Bourouiba’s lab at MIT. And, to me, one of the fundamental conclusions from her work is that droplets (especially small ones) can persist a lot longer and farther than previously assumed. Can those droplets facilitate transmission of COVID-19? The general consensus I’ve seen expressed by medical experts is no, but, to my knowledge, that is based on opinion and assumption, not on an actual scientific study.

    The bottom line

    In my opinion, there’s a big disconnect right now between the medical/biological community and the engineering community. To truly capture the physics and biology of COVID-19 transmission requires the expertise and cooperation of both. Right now both sides are making potentially dangerous assertions.

    Honestly, based on what I know about aerodynamics, I am personally skeptical as to whether 6 ft of physical separation is truly enough; whether it is or not seems to depend on how transmissible the novel coronavirus is through small droplets, which, again, to my knowledge, is unestablished.

    Should we leave more distance than 6ft between us when exercising outdoors? Absolutely. Aerodynamically, it makes perfect sense that following in someone’s slipstream would put you inside their droplet cloud, which needs time and space to disperse. Personally, I’ve sidestepped the question entirely by doing all my cycling indoors while quarantined.

    tl;dr: There are a lot of open questions right now about COVID-19 transmission and what qualifies as safe distancing, but it’s smarter to err on the side of more distancing. Don’t hang close to others when running or cycling outdoors.

    (Image and research credit: B. Blocken et al.; submitted by Corky W. and Wendy H.)

    *I will add that, with my training, I have and do occasionally peer-review studies such as this one, and I read the full paper with the same sort of critical eye I would turn to a paper I was asked to review.

  • Replacing Injections With Pills

    Replacing Injections With Pills

    In medicine, many medications contain molecules too large to be easily absorbed through the intestinal wall, so these so-called biologics — like the insulin administered to diabetics — are injected into the body. Researchers are studying ways that such injections could eventually be replaced with pills, but there are plenty of challenges involved.

    Some substances, known as transient permeability enhancers, allow the intestines to absorb larger molecules, but they work for only tens of minutes, which means researchers must understand how and when to administer them relative to the medication they help patients absorb. To do so, researchers are building computational fluid dynamics models of the human digestive system so that they can better understand how and when different kinds of pills break down in the body. (Image credit: Macro Room, source; via CU Engineering; submitted by Jenny B.)

  • Kneading Dough

    Kneading Dough

    Kneading bread dough is something of an art. The process binds flour, water, salt, and yeast into a network that is both elastic and viscous. It also traps pockets of air that will determine the texture of the final loaf. Underknead and the bubbles won’t form; overknead and the result will be a dense loaf that doesn’t rise in the oven.

    Capturing all of that physics in a realistic model is tough, but researchers have done so and validated their digital dough against experiments. The group focused on simulating industrial mixers, which knead dough with a moving, spiral-shaped rod rotating around a stationary vertical one. They found the industrial set-up did not mix as well as kneading by hand, but that could be improved by swapping the stationary rod for a second spiral one. (Image credit: G. Perricone; research credit: L. Abu-Farah et al.; via Physics World; submitted by Kam-Yung Soh)

  • Adapting to the Flow

    Adapting to the Flow

    Simulating fluid dynamics computationally is no simple task. One of the major challenges is that flows typically consist of many different lengthscales, from the very large to the extremely tiny. In theory, correctly capturing the physics of the flow requires computing all of those scales, and that means having a very close, dense grid of points at which the physics must be calculated during every time step of a simulation. Even for a relatively simple flow, this quickly balloons into a prohibitively expensive problem. It simply takes a computer far too long to calculate solutions for so many points.

    One technique that’s been developed to save time is Adaptive Mesh Refinement. You can see an example of it above. The background is a grid of points that are far from one another in places where the flow isn’t changing and are tightly spaced in areas where the rising flames are most changeable. Adaptive Mesh Refinement algorithms automatically change these grid points on the fly, adding more where they’re needed and subtracting them where they aren’t. The end result is a much faster computational result that doesn’t sacrifice accuracy. Check out the videos below for some examples of this technique in action. (Video and image credit: N. Wimer et al.)

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    Creating Biofuel

    One production technique for biofuel converts agricultural waste through pyrolysis. These systems heat biomass particles in a mixture of sand and nitrogen gas until the biomass particles release tar and syngas, a key ingredient of biofuel. All this heating and mixing takes place in a fluidized bed, where the injected nitrogen gas helps the particle mixture move like a fluid.

    Building prototypes of these systems can be costly, so industry has largely relied on computational studies to predict performance. But capturing the complicated physics behind turbulent gas and particle interactions is tough, and some models discard key information in favor of faster and cheaper simulations. In this study, the authors found that clustering between particles has a major effect on syngas production, something that industrial studies must account for. 

    This is one of the challenges of computational fluid dynamics; although the codes have become more and more accessible over time, getting reliable results still requires a solid understanding of the strengths and limitations of each model used. (Image, video, and research credit: S. Beetham and J. Capecelatro, source; submitted by Jesse C.)

  • Bay of Fundy Tides

    Bay of Fundy Tides

    Canada’s Bay of Fundy has some of the wildest tidal flows in the world. Every six hours, the flow direction through the strait shifts and tidal currents rise to several meters per second. This creates distinct jets a couple kilometers long that pour from one side of the strait to the other. 

    What you see here is a numerical simulation of the flow using a technique called Large Eddy Simulation (or LES, for short). It’s one method used by fluid dynamicists to model turbulent flows without taking on the complexity of the full Navier-Stokes equations. At large lengthscales, like those of the jets and eddies we see above, LES uses the exact physics. But when it comes to the smaller scales – like the flow nearest the shores or the bottom of the strait – the simulation will approximate the physics in order to make calculations quicker and easier. Models like these make large-scale problems – including modeling our daily weather patterns – possible. (Image credit: A. Creech, source)

  • Prehistoric Filter Feeders

    Prehistoric Filter Feeders

    Earth’s earlier ages are filled with enduring mysteries about the plants and creatures that lived and died long before humanity. Many of these organisms, like the aquatic Ernietta shown above, are known only from scattered fossil remains. Yet fluid dynamics is helping us understand how Ernietta lived and fed some 545 million years ago.

    Ernietta were sack-like organisms consisting of stitched-together tubular elements. They had no way to move around and no obvious method for transporting nutrients into their bodies. Scientists hypothesized that they likely used one of two feeding methods: either Ernietta relied on its surface area to extract nutrients directly from the water or its shape enabled it to trap larger particles to feed on from the flow. To decide between these modes, scientists turned to computational fluid dynamics.

    By modelling both single Ernietta and small groups, they found that the shape of the organism generates a rotating current inside the bag that pulls flow down along one side and back up the other. Moreover, being near one another enhanced this effect, helping downstream Ernietta catch more particles than they otherwise would. All in all, the results suggest not only Ernietta’s likely feeding method but also that they lived in colonies and practiced one of the earliest known examples of communal feeding! (Image credit: D. Mazierski, source; research credit: B. Gibson et al.; via ArsTechnica; submitted by Kam-Yung Soh)

  • Featured Video Play Icon

    Breaking

    As waves fold over and break, they trap air, creating bubbles of many sizes. The smallest of these bubbles can be only a few microns across and persist for long times compared to larger bubbles. When they burst, they create tiny droplets that can carry sea salt up into the atmosphere to seed rain. Understanding how these bubbles form and how many there are of a given size is key to predicting both oceanic and atmospheric behaviors. Numerical simulations like the one featured in the video above reveal the dynamic collisions that create these tiny bubbles and help researchers learn how to model the tiniest bubbles so that future simulations can be faster. (Image and video credit: W. Chan et al.)