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#dynamics

3 posts2 participants0 posts today
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💧🌏 Greg Cocks

Interpretable Physics-Informed Graph Neural Networks For Flood Forecasting
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doi.org/10.1111/mice.13484 <-- shared paper
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github.com/MehdiTaghizadehUVa/ <-- shared GitHub repository
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#GIS #spatial #mapping #FloodForecasting #GraphNeuralNetworks #PhysicsInformedAI #Hydrology #ClimateResilience #ScientificMachineLearning #CivilEngineering #HydroGraphNet #PhyiscsNeMo #hydrology #water #flood #flooding #spatialanalysis #spatiotemporal #climatechange #model #modeling #machinelearning #AI #extremeweather #prediction #forecasting #planning #humanimpacts #loss #lossoflife #publicsafety #cost #economics #infrastructure #risk #hazard #disaster #mitigation #preparedness #naturaldisaster #HydroGraphNet #floodforecasting #dynamics #remotesensing #earthobservation

Public
Rxiv mechanobio

📰 "A Navier-Stokes-Peridynamics hybrid algorithm for the coupling of compressible flows and fracturing materials"
arxiv.org/abs/2504.11006 #Physics.Comp-Ph #Dynamics #Cell

arXiv logo
arXiv.orgA Navier-Stokes-Peridynamics hybrid algorithm for the coupling of compressible flows and fracturing materialsModeling and simulation of fluid-structure interactions are crucial to the success of aerospace engineering. This work addresses a novel hybrid algorithm that models the close coupling between compressible flows and deformable materials using a mesoscopic approach. Specifically, the high-speed flows are described by the gas-kinetic scheme, which is a robust Navier-Stokes alternative solver built on the molecular kinetic theory. The deformation, damage, and fracture of materials are depicted using the bond-based peridynamics, which serves as coarse-grained molecular dynamics to construct non-local extensions of classical continuum mechanics. The evolution of fluids and materials are closely coupled using the ghost-cell immersed boundary method. Within each time step, the solutions of flow and solid fields are updated simultaneously, and physics-driven boundary conditions are exchanged for each other via ghost cells. Extensive numerical experiments, including crack propagation in a pre-cracked plate, subsonic flow around the NACA0012 airfoil, supersonic flow around the circular cylinder, and shock wave impacting on the elastic panel, are performed to validate the algorithm. The simulation results demonstrate the unique advantages of current hybrid algorithm in solving fracture propagation induced by high-speed flows.
Public
Charo del Genio

New paper, just out.

Often, in real-world situations, one does not know the full structure of a network. However, at the same time, one can often observe some interactions that take place on it, and may be interested in knowing its full structure. For example, one may be detecting some partial criminal activity and may want to determine the whole organization. We consider higher-order networks, which are structures with many-body interactions, and specifically simplicial complexes, and show that one can reconstruct a whole network almost perfectly simply by observing the transient of the dynamics that takes place on it. In fact, we give 3 different algorithms to do it, with different complexities and accuracies, so you can choose which one suits you best.

Nine plots, arranged in a 3-by-3 grid. The columns, left to right, correspond to three real-world data sets, marked "Malawi", "SFHH" and "LH10", left to right. The rows, from top to bottom, correspond to the three algorithms introduced in the article, namely PBP, GLO and GLOC. Each plot show how the F1 score, on the y axis, very quickly approaches almost 100% for 1-simplices and 2-simplices as the size of the observation set, on the x axis, increases. In general, GLO and GLOC perform better than PBP.
#physics#mathematics#networks
Public *
Pustam | पुस्तम | পুস্তম🇳🇵

An Article in the Annual Review of Condensed Matter Physics on Turbulence by KR Sreenivasan and J Schumacher
annualreviews.org/content/jour

What is the turbulence problem, and when can we say it’s solved? 🌪️ This deep dive by Sreenivasan & Schumacher explores the math, physics, and engineering challenges of turbulence—from Navier-Stokes equations to intermittency and beyond. A must-read for anyone fascinated by chaos, complexity, and the unsolved mysteries of fluid dynamics! 🌀

A summary of the talk presented by KR Sreenivasan in December 2023 at the International Center for Theoretical Sciences (ICTS-TIFR) in Bengaluru, as part of a program on field theory and turbulence.
youtube.com/watch?v=fwVSBYh-KC

"Field Theory and Turbulence" program link: icts.res.in/discussion-meeting

#FluidDynamics #Physics #NavierStokes #UnsolvedMystery #Mechanics #Dynamics #FluidMechanics #Science #Chaos #TurbulentMotion #Randomness #Chaotic #Fluid #ClassicalMechanics
#Turbulence

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