This month, CTCS (IIT Madras) & @PIK_climate present a webinar:
📢: The asymptotic state of decaying turbulence
🎙️: Prof. K. R. Sreenivasan, New York University
📅: March 30 |⏰ 19:30 IST | 16:00 CEST | 10:00 EDT
🔗: https://us06web.zoom.us/webinar/register/WN_0BicRp5MTFqu8Yf3I2jCcQ

#Complexsystems #phd #computationalfluiddynamics #Turbulence #NonlinearDynamics #Bifurcations #NYU #ITCP #PIK #webinarinvite #Zoomcodes #ComplexNetworks #MachineLearning #fluidmechanics

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.)

Funded PhD - multiscale electrochemical modeling
University College Dublin

See the full job description on jobRxiv: https://jobrxiv.org/job/university-college-dublin-27778-funded-phd-multiscale-electrochemical-modeling/

#battery #computationalfluiddynamics #electrochemistry #moleculardynamics #quantumchemistry #ScienceJobs #hiring #research
https://jobrxiv.org/job/university-college-dublin-27778-funded-phd-multiscale-electrochemical-modeling/?fsp_sid=10273

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)

Transport and settling of suspended particles in a simulated estuary: particle-laden freshwater enters a basin filled with seawater. The white iso-surface indicates 50% of the original particle density. Kelvin-Helmholtz instabilities evolve in the shear flow and drive the turbulent mixing. Rayleigh–Taylor instabilities can be observed in the initial settling phase. Based on Direct #Numerical #Simulation.

#sedimentation #estuary #fluiddynamics #turbulence #CFD #computationalfluiddynamics

Snapshot of the turbulent mixing of sediment-laden freshwater (black) and seawater (white / grey) in a modelled estuary. The scene is seen from the top. The freshwater enters from the bottom of the picture.

The results were obtained from a Direct #Numerical #Simulation. Only half of the domain is simulated (the other half is mirrored). Only the interesting part is shown (the simulated domain is actually a lot bigger).

#sedimentation #estuary #fluiddynamics #CFD #computationalfluiddynamics

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)

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.)

Having Just Realized™ that I can use Sphere Glyphs to render my particles in #ParaView, I am now Very Happy™ because my low-resolution #SPH simulations can be made to appear so much nicer.

#SmoothedParticleHydrodynamics #CFD #ComputationalFluidDynamics #rendering #visualization