Physics of Fluids (PoF) is a highly cited, well-known, and respectable journal in the field of fluid mechanics. It has a tough and meticulous peer-review process. MMelanie Ortiz 4 years ago Dear Raju,Thank you for contacting us. If the articles of a journal are highly cited, it means...
- 《Physical Review E Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics》 被引量: 0发表: 2002年 Eckhaus-like instability of large scale coherent structures in a fully turbulent von K\\\'arm\\\'an flow Physics of FluidsHERBERT, E., CORTET, P.-P., DAVIAUD, F. & DUBRU...
- 《Physical Review E Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics》 被引量: 0发表: 2001年 A study of time correlations in lattice Boltzmann-based large-eddy simulation of isotropic turbulence A study of time correlations in Lattice Boltzmann-based Large-Eddy Simulation of ...
Probabilistic forecasts of extreme heatwaves using convolutional neural networks in a regime of lack of data. Phys. Rev. Fluids 8, 040501 (2023). Article ADS Google Scholar Tagklis, F., Bracco, A., Ito, T. & Castelao, R. M. Submesoscale modulation of deep water formation in the ...
- 《Physical Review E Statistical Physics Plasmas Fluids & Related Interdisciplinary Topics》 被引量: 0发表: 2002年 Ultrafast x-ray sources[ATOTHER]@f|[/ATOTHER] Short x-ray pulses have been obtained by spectral selection or by plasma gradient scalelength control. Time-dependent calculations of...
摘要: Physical review. Third series. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics Published by the American Physical Society through the American Institute of Physics, c1993-2000 Vol. 47, no. 1 (Jan. 1993)-v. 62, no. 6 (Dec. 2000)...
SCIE期刊 学科领域:PHYSICS, FLUIDS & PLASMAS Physical Review Fluids is APS’s newest online-only journal dedicated to publishing innovative research that will significantly advance the fundamental understanding of fluid dynamics. Physical Review Fluids expands the scope of the APS journals to include ...
Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels. Phys. Fluids 33, 073603 (2021). Lu, L., Jin, P., Pang, G., Zhang, Z. & Karniadakis, G. E. Learning nonlinear operators via DeepONet based on the universal ...
This describes the motion of oscillating systems, such as pendulums and springs, where the restoring force is directly proportional to the displacement and acts in the opposite direction. 11. Fluid Dynamics: The study of fluids (liquids and gases) in motion. It encompasses concepts such as visco...
In this Review, we disentangle the respective roles of the arrow of time and the non-Boltzmann nature of steady-state fluctuations in this rich phenomenology. We show that effective, time-reversible descriptions of active systems may be found at all scales and discuss how interactions, either ...