Results 11 to 20 of about 6,048,558 (383)
Machine learning–accelerated computational fluid dynamics [PDF]
Proceedings of the National Academy of Sciences of the United States of America, 2021 Significance Accurate simulation of fluids is important for many science and engineering problems but is very computationally demanding. In contrast, machine-learning models can approximate physics very quickly but at the cost of accuracy.
Dmitrii Kochkov +5 more
semanticscholar +1 more source
Potential quantum advantage for simulation of fluid dynamics [PDF]
Physical Review Research, 2023 Numerical simulation of turbulent fluid dynamics needs to either parametrize turbulence—which introduces large uncertainties—or explicitly resolve the smallest scales—which is prohibitively expensive. Here, we provide evidence through analytic bounds and
Xiangyu Li +6 more
semanticscholar +1 more source
Theories of Relativistic Dissipative Fluid Dynamics [PDF]
Entropy, 2023 Relativistic dissipative fluid dynamics finds widespread applications in high-energy nuclear physics and astrophysics. However, formulating a causal and stable theory of relativistic dissipative fluid dynamics is far from trivial; efforts to accomplish ...
G. Rocha +4 more
semanticscholar +1 more source
Radial Flow Turbocompressors, 2021 Contents: Finite-Element method and aspects for computer implementation, computa-tion of mechanical problems, coupled field problems (magnetic, mechanical and acoustic), optimization of modern mechatronic systems.
Prof. Manoj Kumar +5 more
semanticscholar +1 more source
Introduction to Computational Fluid Dynamics
essentials, 2023 A projected frontal area or planform area of an object b span or depth of a flat plate (into the page when viewed from the edge) CD drag coefficient: CD = 2FD /VA D height (2-dimensional) or diameter (axisymmetric) of a block or other object in the flow
Karim Ghaib
semanticscholar +1 more source
DualSPHysics: from fluid dynamics to multiphysics problems [PDF]
Computational Particle Mechanics, 2021 DualSPHysics is a weakly compressible smoothed particle hydrodynamics (SPH) Navier–Stokes solver initially conceived to deal with coastal engineering problems, especially those related to wave impact with coastal structures.
J. Dominguez +12 more
semanticscholar +1 more source
Current and emerging deep-learning methods for the simulation of fluid dynamics
Proceedings of the Royal Society A, 2023 Over the last decade, deep learning (DL), a branch of machine learning, has experienced rapid progress. Powerful tools for tasks that have been traditionally complex to automate have been developed, such as image synthesis and natural language processing.
Mario Lino +3 more
semanticscholar +1 more source
The Fluid Dynamics of Disease Transmission
Annual Review of Fluid Mechanics, 2021 For an infectious disease such as the coronavirus disease 2019 (COVID-19) to spread, contact needs to be established between an infected host and a susceptible one.
L. Bourouiba
semanticscholar +1 more source
Journal of Advances in Modeling Earth Systems, 2021 A two‐moment Morrison‐Gettelman bulk cloud microphysics with prognostic precipitation (MG2), together with a mineral dust and temperature‐dependent ice nucleation scheme, have been implemented into the Geophysical Fluid Dynamics Laboratory's Atmosphere ...
Huan Guo +5 more
doaj +1 more source
GFDL SHiELD: A Unified System for Weather‐to‐Seasonal Prediction
Journal of Advances in Modeling Earth Systems, 2020 We present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken ...
Lucas Harris +22 more
doaj +1 more source