#numericalsimulation — Public Fediverse posts

Representing Rain’s Microphysics

Realistically modeling rainfall remains an extremely difficult problem. To be practical, results have to be on the scale of kilometers; no one is looking to find out whether rain will fall from one specific cloud over their head. But making that prediction depends on physics that happens at the microscale, where droplets tens of microns in size are condensing, colliding, and eventually growing large enough to fall as rain. A new study takes a look at three machine-learning models that could help describe those microscale physics with less computational overhead.

The researchers used three different algorithms, all trained on high-quality simulations of microdroplet physics. The goal here was to represent the complex, nonlinear physics reflected in those results with an algorithm that’s less complicated and less computationally expensive than the methods used to create the training data. The team then tested the trained algorithms to see how they performed in conditions that were different than their training data.

They found that the model with the best performance–in terms of giving more accurate predictions in the test cases–was actually the simplest of the three models. So it may be possible to get reasonable results for rain microphysics from simpler, easier-to-compute algorithms. The team does warn, though, that all of the models need more work before they’d be ready to add to commercial-grade weather prediction software. (Image credit: J. Fowler; research credit: E. de Jong et al.; via Eos)

Ice Giant or Magma Ocean World?

Uranus and Neptune–known as our system’s ice giants–are our least explored planets. Both have received exactly one flyby, from the Voyager 2 spacecraft. The data from those flybys remain our primary source of knowledge about each planet. The traditional model for each planet’s interior (dating back to before the flybys) consists of three layers: a rocky core; an icy mantle made up of water, ammonia, and methane; and a hydrogen/helium-rich atmosphere. That structure is one way to match the limited measurements we have from these planets, but, as today’s preprint study points out, it’s not the only way.

The authors suggest an alternative structure, in which a hydrogen-rich atmosphere overlays a supercritical magma ocean capable of dissolving hydrogen into heavier, metallic elements. Their suggestion is motivated by several factors. First, objects in the outer solar system–including Kuiper Belt objects–have less icy material than originally assumed, which suggests that Uranus and Neptune’s progenitors wouldn’t have been so ice-rich, either. Second, our understanding of how “rocky” materials respond at the temperatures and pressures found in these planet interiors has evolved. In particular, silicate, hydrogen, and iron are actually miscible at these conditions. That means that discrete sub-layers separated by material type are not as likely.

Using the magma ocean model, the team found compositions for both Uranus and Neptune that conformed well to our limited data about their gravitational and magnetic field properties. Time–and more data–will tell as to which interior model best describes these enigmatic giants. (Image credit: NASA; research credit: E. Young et al. (preprint); via Gizmodo)

A Fluidic Space Telescope

A telescope’s resolution is set by the size of its reflective surface. Our largest space telescope, JWST, has a 6.5-meter reflector, the largest we could manage given manufacturing constraints and the need to launch it in a rocket. To reach even larger sizes, researchers are considering a new type of reflector: one made of liquid.

A fluidic telescope has some obvious advantages: surface tension makes it atomically smooth, and liquids can be packed into any convenient shape for launch. But there are challenges, also. Like, what happens to the reflector when you point it in an new direction?

That’s what this study looks at, mathematically. Using a mathematical model of a 50-meter-wide, millimeter-thick fluid, the researchers analyzed how different maneuvers over the telescope’s lifetime would affect the image quality.

Shifting the reflector creates perturbations in the surface, initially at the mirror’s edges. Over time, those perturbations move toward the center of the mirror and, at the same time, decay. The team found that, while typical space telescope operations distorted parts of the mirror beyond the limits of good optical quality, the inner 80% of the mirror could remain undisturbed for twenty or more years. That would be like having a 40-meter telescope in orbit with more than 6x the resolution of JWST. (Image credit: NASA; research credit: I. Gabay et al.)

On Dolphin Turbulence

Dolphins are such fast and agile swimmers that, naturally, scientists have long wanted to understand how they swim so well. A recent study draws on numerical simulation to analyze the flow a dolphin creates when flapping its tail.

The resulting flow is highly turbulent–researchers were only able to simulate up to a fraction of a dolphin’s actual Reynolds number–with both large-scale vortices and a cascade of smaller ones. The largest vortices, shown here in white, form on the upper and lower surface of the dolphin’s tail, then slide off the tail in a vortex ring. It’s these vortex rings, the researchers found, that provide the bulk of a dolphin’s thrust.

The smaller-scale vortices, in contrast, get formed by the large vortices, and they make little to no contribution to the dolphin’s propulsion. Interestingly, these results suggest that we might be able to describe the propulsion of dolphins and other highly turbulent swimmers by focusing only on the largest scales in the flow. (Video, image, and research credit: Y. Motoori et al.; via Ars Technica)

Understanding Pollen Dispersal

When the wind blows, trees shift and sway, reconfiguring their shape and their leaves in response. For parts of the year, that flow can also pluck pollen grains off the tree, carrying them on the winds. A new computational simulation models this pollen dispersal from a tree, with the aim of eventually integrating into a tool for urban planners.

Trees are an important component to fighting climate change, especially in cities, because they cool their surroundings in addition to providing fresh oxygen. But urban planners recognize the downsides to trees, too–allergies, anyone?–and, with the right tools, they could maximize the trees’ advantages while minimizing pollen spread for allergy-sufferers. (Image credit: M. Köles; research credit: T. Dbouk et al.; via Physics World)

Schooling at Scale

Relatively simple visual and hydrodynamic signals are enough to make digital fish school in ways that resemble living ones. Here, researchers look at what happens when well-behaved schools of fish get too big. The researchers first demonstrate that their schools behave reasonably at one hundred members, either in a schooling configuration or a group milling around a central region.

At one thousand fish, the schools are still reasonably coherent and sensible. But at fifty thousand fish, the picture is drastically different. Neither schooling nor milling groups are able to remain together. They fracture and scatter into smaller groupings. (Video and image credit: H. Hang et al.)

Richtmyer-Meshkov Instability

If you send a shock wave through a magnetized plasma–something that happens in both supernova explosions and inertial confinement fusion–it can trigger an instability known as the Richtmyer-Meshkov instability. The image above shows a form of this, taken from a simulation. Rather than treating the plasma as a single idealized fluid, the researchers represented it as two fluids: an ion fluid and an electron fluid. This allowed them to better capture what happens when certain components of the plasma react to changes faster than others do.

The image itself shows the electron number density across the fluid, where darker colors represent higher electron number density. The interface between high and low-densities shows a roll-up instability that resembles the Kelvin-Helmholtz instability, but there are also regions of mushroom-like plumes that more closely resemble Rayleigh-Taylor instabilities.

The authors note that these structures don’t appear in simulations that represent a plasma as a single fluid; you need the two-fluid representation to see them. (Image and research credit: O. Thompson et al.)

Improving Turbulence Models

Calculating turbulent flows like those found in the ocean and atmosphere is extremely expensive computationally. That’s why forecasting models use techniques like Large Eddy Simulation (LES), where large physical scales are calculated according to the governing physical equations while smaller scales are approximated with mathematical models. Researchers are always looking for ways to improve these models–making them more physically accurate, easier to compute, and more computationally stable.

In a new study, researchers used an equation-discovery tool to find new improvements to these models for the smaller turbulent scales. They started by doing a full, computationally expensive calculation of the turbulent flow. The equation-discovery tool then analyzed these results, looking to match them to a library of over 900 possible equations. When it found a form that fit the data, the researchers were then able to show analytically how to derive that equation from the underlying physics. The result is a new equation that models these smaller scales in a way that’s physically accurate and computationally stable, offering possibilities for better LES. (Image credit: CasSa Paintings; research credit: K. Jakhar et al.; via APS)

Icy or Rocky Giants?

On the outskirts of our solar system, two enigmatic giants loom: Uranus and Neptune. In terms of mass and size, both resemble many of the exoplanets discovered in recent years. Within our own solar system, these planets are known as “icy giants,” but a new study suggests that moniker may be wrong.

Pinning down the interior composition of a planet is tough on limited measurements. In the case of these outer planets, our main data is gravitational, recorded from visiting spacecraft. That information cannot tell us directly what the composition of a planet is, but it gives constraints for what materials could produce such a gravitational field.

In their simulation, researchers began with random interior configurations for Uranus and Neptune, then had the model iterate through configurations to simultaneously match the gravitational measurements while satisfying the thermodynamic and physical constraints of a stable planet. By repeating the process several times, the researchers created a catalog of potential interiors for Uranus and Neptune. And while some were water-rich–consistent with the “icy giant” title–others were remarkably rocky.

The team suggests that we may need to retire that moniker and consider the possibility that these worlds are more like our own than we thought. To find out which is true, we will need more spacecraft to visit our frigid neighbors, to provide new gravitational measurements and other observations. (Image credit: NASA/ESA/A. Simon/M. Wong/A. Hsu; research credit: R. Morf and L. Helled; via Physics World)

Inside Cepheid Variable Stars

Cepheid variable stars pulsate in brightness over regular periods. That’s one reason astronomers use them as a standard candle to judge distances–even for stars well outside our galaxy. In this image, researchers display a simulation of convection inside a Cepheid eight times more massive than our sun. The colors represent vorticity, with zero vorticity in white.(Image credit: M. Stuck and J. Pratt)

Thermal Tides Drive Venusian Winds

Venus is a world of extremes. A full rotation of the world takes 243 Earth days, but winds race around the planet at a speed that makes a Category 5 hurricane look sedate. Just what drives these winds has been an ongoing question for planetary scientists. A recent study suggests that tides are a major contributor to this superrotation.

Unlike Earth’s tides, Venus’s are not gravitational in origin. Instead, Venusian tides are thermal, driven by heating in the sunward side of the atmosphere. This creates a diurnal tide, which cycles once per Venusian day and pumps momentum toward the tops of Venus’s clouds. The new analysis–rooted in both observations and numerical simulation–finds that diurnal tides are the primary driver behind the planet’s incredibly fast winds. (Image credit: NASA/JPL-Caltech; research credit: D. Lai et al.; via Eos)

ExaWind Simulation

Large-scale computational fluid dynamics simulations face many challenges. Among them is the need to capture both large physical scales–like those of Earth’s atmospheric boundary layer–and small scales–like those of tiny eddies moving around a wind-turbine blade. Capturing all of these scales for a problem like four wind turbines in a wind farm requires using the full computing power of every processor in a large supercomputer. That’s the level of power behind the simulation visualized in this video. The results, however, are stunning. (Video and image credit: M. da Frahan et al.)

Oceans Could “Burp” Out Absorbed Heat

Earth’s atmosphere and oceans form a complicated and interconnected system. Water, carbon, nutrients, and heat move back and forth between them. As humanity pumps more carbon and heat into the atmosphere, the oceans–and particularly the Southern Ocean–have been absorbing both. A new study looks ahead at what the long-term consequences of that could be.

The team modeled a scenario where, after decades of carbon emissions, the world instead sees a net decrease in carbon–which could be achieved by combining green energy production with carbon uptake technologies. They found that, after centuries of carbon reduction and gradual cooling, the Southern Ocean could release some of its pent-up heat in a “burp” that would raise global temperatures by tenths of a degree for decades to a century. The burp would not raise carbon levels, though.

The research suggests that we should continue working to understand the complex balance between the atmosphere and oceans–and how our changes will affect that balance not only now but in the future. (Image credit: J. Owens; research credit: I. Frenger et al.; via Eos)

#CFD #climateChange #computationalFluidDynamics #fluidDynamics #geophysics #heatTransfer #numericalSimulation #ocean #physics #science

Tracing the Origins of Ocean Waters

The Sub-Antarctic Mode Waters (SAMW) lie in the southern Indian Ocean and the east and central Pacific Ocean, where they serve as an important sink for both heat and carbon dioxide. Scientists have long debated the origins of the SAMW’s waters, and a new study may have an answer.

Researchers combined data from ocean observations with a model of the Southern Ocean to essentially trace the SAMW’s ingredients back to their respective origins. The results showed that about 70% of the Indian Ocean’s SAMWs came from subtropical waters, but those waters contributed to only about 40% of the Pacific’s SAMWs. Pacific SAMWs had their largest contributions from upwelling circumpolar waters.

Understanding where a SAMW’s waters came from helps scientists predict how those waters will mix and how much heat and carbon they can absorb. (Image credit: NASA; research credit: B. Fernández Castro et al.; via Eos)

#fluidDynamics #mixing #numericalSimulation #oceanography #physics #planetaryScience #science

Roll Waves in Debris Flows

When a fluid flows downslope, small disturbances in the underlying surface can trigger roll waves, seen above. Rather than moving downstream at the normal wave speed, roll waves surge forward — much like a shock wave — and gobble up every wave in their way.

Such roll waves are fairly innocuous when flowing down a drainage ditch but far more problematic in the muddy debris flows of a landslide. Debris flows are harder to predict, too, thanks to their combined ingredients of water, small grains, and large debris.

A new numerical model has shed some light on such debris flows, after showing good agreement with a documented landslide in Switzerland. The model suggests that roll waves get triggered in muddy flows at a higher flow speed than in a dry granular flow but a lower flow speed than is needed in pure water.

For a great overview of roll waves, complete with videos, check out this post by Mirjam Glessner. (Image credit: M. Malaska; research credit: X. Meng et al.; see also M. Glessmer; via APS)

#channelFlow #fluidDynamics #freeSurfaceDynamics #FroudeNumber #geophysics #landslide #numericalSimulation #physics #science

Bow Shock Instability

There are few flows more violent than planetary re-entry. Crossing a shock wave is always violent; it forces a sudden jump in density, temperature, and pressure. But at re-entry speeds this shock wave is so strong the density can jump by a factor of 13 or more, and the temperature increase is high enough that it literally rips air molecules apart into plasma.

Here, researchers show a numerical simulation of flow around a space capsule moving at Mach 28. The transition through the capsule’s bow shock is so violent that within a few milliseconds, all of the flow behind the shock wave is turbulent. Because turbulence is so good at mixing, this carries hot plasma closer to the capsule’s surface, causing the high temperatures visible in reds and yellows in the image. Also shown — in shades of gray — is the vorticity magnitude of flow around the capsule. (Image credit: A. Álvarez and A. Lozano-Duran)

#2024gofm #CFD #computationalFluidDynamics #flowVisualization #fluidDynamics #hypersonic #instability #numericalSimulation #physics #science #shockWave #turbulence

Stunning Interstellar Turbulence

The space between stars, known as the interstellar medium, may be sparse, but it is far from empty. Gas, dust, and plasma in this region forms compressible magnetized turbulence, with some pockets moving supersonically and others moving slower than sound. The flows here influence how stars form, how cosmic rays spread, and where metals and other planetary building blocks wind up. To better understand the physics of this region, researchers built a numerical simulation with over 1,000 billion grid points, creating an unprecedentedly detailed picture of this turbulence.

The images above are two-dimensional slices from the full 3D simulation. The upper image shows the current density while the lower one shows mass density. On the right side of the images, magnetic field lines are superimposed in white. The results are gorgeous. Can you imagine a fly-through video? (Image and research credit: J. Beattie et al.; via Gizmodo)

#astrophysics #compressibility #flowVisualization #fluidDynamics #fluidsAsArt #magnetohydrodynamics #numericalSimulation #physics #science #turbulence

Escape From Yavin 4

In an ongoing tradition, let’s take another look at some Star Wars-inspired aerodynamics. This year it’s the TIE fighter’s turn. Here, researchers simulate the spacecraft trying to escape Yavin 4’s atmosphere at Mach 1.15. The research poster’s blue contours show pressure contours, with darker colors connoting higher pressures. The bright low pressure region immediately behind the craft suggests a difficult, high-drag ascent and a turbulent, subsonic wake despite the craft’s supersonic velocity. (Image credit: A. Martinez-Sanchez et al.)

#flowVisualization #fluidDynamics #numericalSimulation #physics #science #starWars #supersonic #turbulence

Kolmogorov Turbulence

Turbulent flows are ubiquitous, but they’re also mindbogglingly complex: ever-changing in both time and space across length scales both large and small. To try to unravel this complexity, scientists use simplified model problems. One such simplification is Kolmogorov flow: an imaginary flow where the fluid is forced back and forth sinusoidally. This large-scale forcing puts energy into the flow that cascades down to smaller length scales through the turbulent energy cascade. Here, researchers depict a numerical simulation of a turbulent Kolmogorov flow. The colors represent the flow’s vorticity field. Notice how your eye can pick out both tiny eddies and larger clusters in the flow; those patterns reflect the multi-scale nature of turbulence. (Image credit: C. Amores and M. Graham)

#2024gofm #flowVisualization #fluidDynamics #Kolmogorov #numericalSimulation #physics #science #turbulence #turbulentEnergyCascade

As a #physics researcher doing a lot of #NumericalSimulation , I learned code mostly on my own with educated people around to answer my questions. Some that were not so easily answered were about how the F #git works. Mostly because many people learned other systems like SVN, but also because Git is not so easy to wrap your head around on your own when going on sophisticated stuff.

So I learned how to do the basics and that was roughly it until I finished (just now) Anna Skoulikari''s book "Learning Git" at O'Reilly. While it does not go into technical details, it is very simple in its examples and has diagrams that are helps to intuit what is going on for visual people (like me).

I'll put this into my future students hands without restriction. You should do the same. It will help them clutching how git works and starting good practice as software developers.

https://www.oreilly.com/library/view/learning-git/9781098133900/

Pro tip: It is regularly sold for low prices in #HumbleBundle coding book collections. I got it for like 5 euros.

Galloping Bubbles

A buoyant bubble rises until it’s stopped by a wall. What happens, this video asks, if that wall vibrates up and down? If the vibration is large enough, the bubble loses its symmetry and starts to gallop along the wall. Using numerical simulations, the team determined the flow around the bubble. They also demonstrate several possible applications for this behavior: sorting bubbles by size, traversing mazes, and cleaning a surface. (Video and image credit: J. Guan et al.)

#2024gofm #bubbles #experimentalFluidDynamics #fluidDynamics #numericalSimulation #physics #science #vibration

How CO2 Gets Into the Ocean

Our oceans absorb large amounts of atmospheric carbon dioxide. Liquid water is quite good at dissolving carbon dioxide gas, which is why we have seltzer, beer, sodas, and other carbonated drinks. The larger the surface area between the atmosphere and the ocean, the more quickly carbon dioxide gets dissolved. So breaking waves — which trap lots of bubbles — are a major factor in this carbon exchange.

This video shows off numerical simulations exploring how breaking waves and bubbly turbulence affect carbon getting into the ocean. The visualizations are gorgeous, and you can follow the problem from the large-scale (breaking waves) all the way down to the smallest scales (bubbles coalescing). (Video and image credit: S. Pirozzoli et al.)

#2024gfm #breakingWave #bubbles #carbonCycle #carbonDioxide #CFD #climateChange #computationalFluidDynamics #dissolution #flowVisualization #fluidDynamics #numericalSimulation #physics #science #turbulence

Why Icy Giants Have Strange Magnetic Fields

When Voyager 2 visited Uranus and Neptune, scientists were puzzled by the icy giants’ disorderly magnetic fields. Contrary to expectations, neither planet had a well-defined north and south magnetic pole, indicating that the planets’ thick, icy interiors must not convect the way Earth’s mantle does. Years later, other researchers suggested that the icy giants’ magnetic fields could come from a single thin, convecting layer in the planet, but how that would look remained unclear. Now a scientist thinks he has an answer.

When simulating a mixture of water, methane, and ammonia under icy giant temperature and pressure conditions, he saw the chemicals split themselves into two layers — a water-hydrogen mix capable of convection and a hydrocarbon-rich, stagnant lower layer. Such phase separation, he argues, matches both the icy giants’ gravitational fields and their odd magnetic fields. To test whether the model holds up, we’ll need another spacecraft — one equipped with a Doppler imager — to visit Uranus and/or Neptune to measure the predicted layers firsthand. (Image credit: NASA; research credit: B. Militzer; via Physics World)

#convection #fluidDynamics #Neptune #numericalSimulation #phaseSeparation #physics #planetaryScience #science #Uranus

Holding Steady

Before a mammalian cell divides, the spindle — a protein structure — divides the cell’s genetic material in two. As it does, the cytoplasm inside the cell forms a toroidal flow (below, left). Researchers wondered how the spindle manages to stay in place with this flow; the spindle sits just where the flow diverges, a spot that seems ripe for unstable shifts in position. But, contrary to expectations, their analysis showed that — although a smaller spindle would be unstable in that spot — the protein spindle is large enough that its size distorts the cell’s flow and creates a pressure that moves it back into place if it shifts. (Image credit: top – ColiN00B, illustration – W. Liao and E. Lauga; research credit: W. Liao and E. Lauga; via APS Physics)

#biology #cellDivision #fluidDynamics #numericalSimulation #physics #science

If you had to do a lot of dense linear algebra (QR eigenvalues, SVD, linear least squares, etc.) on modern AMD *CPUs*, which library would you choose for maximum performance? #HPC #BLAS #LAPACK #linearalgebra #NumericalSimulation #amd

Why Death Valley Is Full Of Polygons [salt flats, deserts, and dry lakes]
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https://physics.aps.org/articles/v16/31 <-- shared article
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https://doi.org/10.1103/PhysRevX.13.011025 <-- shared paper
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#GIS #spatial #mapping #spatialanalysis #model #modeling #salt #polygons #tiling #saltflats #saltdeserts #convection #research #chemistry #water #hydrology #soil #evaporation #evapotranspiration #precipitation #solution #salinity #DeathValley #numericalanalysis #numericalmodeling #numericalsimulation #simulation #groundwater

I've talked a lot as a member of the scientific community at #ScienceMastodon, now my #introduction as a researcher... with a separate account for that.

My aim is to understand how living #cells and #tissues can actively change shape through the generation of internal #prestress within the #cytoskeleton.

For this, I devise #mechanical #models of the #actomyosin (a component of the cell's skeleton which can bear forces and generate #prestress) and then solve them, mostly by #numericalsimulation

We have job opening for a Research Software Engineer for Coastal & Fluvial System Modelling at the Department of Physical Geography at Utrecht University, the Netherlands.

https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs/research-software-engineer-for-coastal-fluvial-system-modelling-08-10-fte

#Hiring #ResearchSoftwareEngineer #RSE #NumericalSimulation #PhysicalGeography #CoastalFluvialResearch