scholarly journals Interface learning of multiphysics and multiscale systems

2020 ◽  
Vol 102 (5) ◽  
Author(s):  
Shady E. Ahmed ◽  
Omer San ◽  
Kursat Kara ◽  
Rami Younis ◽  
Adil Rasheed
Keyword(s):  
2007 ◽  
Vol 62 (13) ◽  
pp. 3419-3428 ◽  
Author(s):  
T.W. Martin ◽  
J.P.K. Seville ◽  
D.J. Parker

2018 ◽  
Vol 75 (3) ◽  
pp. 907-925 ◽  
Author(s):  
Shen-Ming Fu ◽  
Rui-Xin Liu ◽  
Jian-Hua Sun

Abstract Persistent heavy rainfall events (PHREs) are the product of the combined effects of multiscale systems. A PHRE that occurred during the 2016 mei-yu season was selected to further the understanding of the scale interactions accounting for the persistence of this type of event. The scale interactions were analyzed quantitatively using a piecewise energy budget based on temporal scale separation. Results show that the strongest interactions between the precipitation-related eddy flow and its background circulation (BC) occur in the mid- to lower troposphere, where a significant downscale kinetic energy (KE) cascade alone dominates eddy flow persistence. An obvious upscale KE cascade (i.e., a feedback effect) appears in the mid- to upper troposphere but has a negligible effect on the BC. Overall, within the precipitation region, the downscale KE cascade is primarily dependent on BC signals with shorter periods, whereas the upscale KE cascade is more dependent on BC signals with longer periods. Thus, the BC has asymmetric effects on the KE cascades. The most significant BC signal as determined via wavelet analysis [i.e., quasi-biweekly (10–18 days) oscillations in this event] does not play the leading role in the downscale KE cascade. Instead, the quasi-weekly oscillations provide the maximum amount of energy for eddy flow maintenance. Semi-idealized simulations of various BC signals show similar results: precipitation and the intensities of lower-level shear lines and transversal troughs (both of which are closely related to the precipitation-related eddy flow) are more sensitive to the quasi-weekly oscillation than to the quasi-biweekly oscillation.


Automatika ◽  
2011 ◽  
Vol 52 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Ronald Summers ◽  
Tariq Abdulla ◽  
Lucile Houyel ◽  
Jean Marc Schleich

Information ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 272
Author(s):  
Harald Atmanspacher ◽  
Mike Martin

Correlations between observed data are at the heart of all empirical research that strives for establishing lawful regularities. However, there are numerous ways to assess these correlations, and there are numerous ways to make sense of them. This essay presents a bird’s eye perspective on different interpretive schemes to understand correlations. It is designed as a comparative survey of the basic concepts. Many important details to back it up can be found in the relevant technical literature. Correlations can (1) extend over time (diachronic correlations) or they can (2) relate data in an atemporal way (synchronic correlations). Within class (1), the standard interpretive accounts are based on causal models or on predictive models that are not necessarily causal. Examples within class (2) are (mainly unsupervised) data mining approaches, relations between domains (multiscale systems), nonlocal quantum correlations, and eventually correlations between the mental and the physical.


1996 ◽  
Vol 44 (8) ◽  
pp. 1893-1911 ◽  
Author(s):  
E. Fabre
Keyword(s):  

2006 ◽  
Vol 412 (2-3) ◽  
pp. 326-347 ◽  
Author(s):  
Daniel Alpay ◽  
Haim Attia ◽  
Dan Volok
Keyword(s):  

AIChE Journal ◽  
2017 ◽  
Vol 63 (8) ◽  
pp. 3361-3373 ◽  
Author(s):  
Grigoriy Kimaev ◽  
Luis A. Ricardez-Sandoval

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