FIFA World Cup ball comparison
Trionda (2026) vs Al Rihla (2022)

This CFD comparison is showing two different FIFA World Cup ball designs spinning at the same rate (600 rpm) in the same airflow (30 m/s).

The colours and wake structure reveal how the surface geometry affects the air around the ball.

* Trionda (2026): Much more intricate surface pattern with many grooves, ridges and dimples.

* Al Rihla (2022): Simpler panel layout with fewer aerodynamic features.

players might notice the Trionda:

* Grips the air more strongly
* Curves more readily when spun
* Feel slightly more stable aerodynamically

The 2026 Trionda appears designed to give the airflow more to “hold onto”, creating stronger vortex structures and slightly larger aerodynamic forces than the smoother 2022 Al Rihla, which may translate into more pronounced curl and control for skilled players.

#FIFAWorldCup #WorldCup2026 #WorldCupBall #Trionda #AlRihla #FootballScience #SoccerScience #SportsEngineering #Aerodynamics #CFD #ComputationalFluidDynamics #FluidDynamics #SportsTech #FootballTechnology #BallDesign #FootballEngineering #SportsInnovation #EngineeringVisualization #FlowSimulation #WakeStructure #VortexDynamics #AerodynamicForces #FootballAnalysis #SoccerBall #SportsResearch #EngineeringInsights #DataVisualization #FootballPerformance #SportsPhysics #FootballAerodynamics

The Faculty Development Program on CFD using OpenFOAM, organized by FOSSEE, IIT Bombay, concluded successfully.

We thank the speakers, trainers, faculty partners, and participants for their enthusiastic involvement. We look forward to continuing our efforts to promote open-source tools for CFD education and research.

#FOSSEE #IITBombay #OpenFOAM #CFD #OpenSource #EngineeringEducation #FOSS #EngineeringEducation #ComputationalFluidDynamics

#FluidMechanics #FluidDynamics #AskFedi #DuckDuckFedi hey, I'm wondering which is better for cooling ? The desk isn't a perfect seal if you're wondering, air can vent, but slowly.

This computer is in a pull-push configuration, the GPU at the back is pulling fresh air in and the radiator is pushing hot air out as drawn by arrows. The radiator "pushing" fans are stronger than the GPU's "pulling" fans, so there is negative pressure, which means some air gets sucked in from surrounding case intakes (above, below etc).

#ComputationalFluidDynamics #FluidSimulation

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)

AI-Based Weather Forecasting Has Blind Spots

Traditional weather forecasting models are physics-based and rely on supercomputers. Practically speaking, this means that they start from the basic governing equations (like the Navier-Stokes equations) and use approximations to model aspects of the problem in order to make the physics solvable, given constraints on time, computational power, spatial resolution, and so on.

So-called AI models approach the problem differently, training a model on past weather conditions in order to predict future weather. In some respects, this approach is very successful; AI-based models require less computational infrastructure to run and, in recent years, have greatly improved their predictions of everyday weather.

However, these AI models do poorly when predicting extreme weather events, because their training data contain relatively few examples of these events. They show limited ability to extrapolate their predictions to more extreme events. But these events–like the unprecedented 2021 heatwave in the Pacific Northwest or many of the Category 5 hurricanes we’ve seen in the last decade–are happening increasingly often due to climate change. Those events will keep happening, more frequently, as warming continues. Physics-based models can predict and forecast these events in ways that AI-based models fail to because they are limited by their trained experiences.

Researchers are working to find ways to better equip AI-based models with more physical sense, but, as these models proliferate, it’s important for their users (and those of us using their forecasts) to know what their current weaknesses are. (Image credit: B. McGowan; research credit: Y. Sun et al.; see also S. Nath and T. Palmer; via Gizmodo)

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)

📣 Registration is open for the Faculty Development Program on CFD using OpenFOAM by FOSSEE, IIT Bombay.

This free online program is specially designed for faculty members using CFD in research and teaching.

📅 2–5 June 2026
💻 Online | Free of cost

🔗 Register: shorturl.at/CYUzi

📲 Scan QR code in poster for registration.

#CFD #OpenFOAM #ComputationalFluidDynamics #EngineeringFaculty #FDP #FOSSEE #IITBombay #OpenSource #Research #EngineeringEducation #Simulation #OpenSource

37x Speedup in Lattice Boltzmann Cylinder Flow

https://github.com/alikamp/Parks-KPBM-Scaling

#HackerNews #LatticeBoltzmann #Speedup #ComputationalFluidDynamics #Research #Innovation

📣 Faculty members working in CFD and simulation are invited to join the Faculty Development Program on CFD using OpenFOAM by FOSSEE, IIT Bombay.

🗓 2–5 June 2026
💻 Online Mode

Learn OpenFOAM from basic to intermediate level with interactive sessions and receive a certificate upon fulfilling attendance criteria.

🔗 Register: https://shorturl.at/CYUzi

#CFD #OpenFOAM #FDP #FOSSEE #IITBombay #OpenSource #EngineeringEducation #Simulation #ComputationalFluidDynamics

Petite vidéo de l'énergétique d'une expérience de Kelvin-Helmholtz que je trouvais sympa

#CFD #ComputationalFluidDynamics #fluidDynamics #physics