RE: https://mast.hpc.social/@msleigh/116562490685026434

Are you dealing with large #legacy code bases, #numerical models with strict validation requirements, or operational #workflows? Are you maintaining #Fortran code?

Please consider submitting an abstract, we are genuinely interested in how you're approaching #software #sustainability and evolution! Especially if you come from outside the #weather and #climate domain!

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

#numerical : belonging to number

- French: numérique

- German: zahlenmäßig

- Italian: numerico

- Portuguese: numérico

- Spanish: numérico

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Fill in missing or incorrect translations @ https://wordofthehour.org/r/translations

Exploration of evidence for #numerical thinking in the #Palaeolithic

#archaeology #cognition

https://www.sciencedirect.com/science/article/abs/pii/S0003552125000317

🔄 Power transforms help reshape data toward a Gaussian distribution
💥 Overflow errors are common when implemented naively
🛠️ This post dives into the cause and shows practical solutions

https://xuefeng-xu.github.io/blog/power-transform.html

#Numerical #Statistics #Python

After quite some weeks of work I have quantified the #numerical error of several #FFT implementations compared to my own.

This was done by implementing an arbitrary precision FFT to compute the true value.

For each implementation we compare the L1, L2 and Linfinity norms as well as #rms

The theoretical l2 bound is derived by Nicholas J.Higham in his famous book 'accuracy and stability of numerical algorithms'

The Linf bound from P. Henrici 'Applied and Computational Complex Analysis'