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Entropy, Volume 6, Issue 4 (September 2004) – 2 articles , Pages 364-387

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Article
On The Use of Entropy to Predict Boundary Layer Stability
by Ed J. Walsh, Mark R.D. Davies and Donald M. McEligot
Entropy 2004, 6(4), 375-387; https://doi.org/10.3390/e6040375 - 26 Aug 2004
Cited by 5 | Viewed by 6631
Abstract
Boundary layer transition is a critical parameter in the design of fluid flow systems. This situation is due to the dramatic change in both entropy production and heat transfer that accompanies it. It is well recognized that many parameters affect the location of [...] Read more.
Boundary layer transition is a critical parameter in the design of fluid flow systems. This situation is due to the dramatic change in both entropy production and heat transfer that accompanies it. It is well recognized that many parameters affect the location of transition onset, however, no models exist which unify all these parameters. This paper presents a new hypothesis that the driving force of boundary layer transition onset is the entropy generation rate alone, with all other parameters being functions of this higher order quantity. At present this hypothesis is speculative, but encouraging since good compatibility is found with more established transition models. Full article
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Article
On a simple derivation of a family of nonextensive entropies from information content
by Takuya Yamano
Entropy 2004, 6(4), 364-374; https://doi.org/10.3390/e6040364 - 01 Aug 2004
Cited by 5 | Viewed by 4956
Abstract
The nonextensive entropy of Tsallis can be seen as a consequence of postulates on a self-information, i.e., the constant ratio of the first derivative of a self-information per unit probability to the curvature (second variation) of it. This constancy holds if we regard [...] Read more.
The nonextensive entropy of Tsallis can be seen as a consequence of postulates on a self-information, i.e., the constant ratio of the first derivative of a self-information per unit probability to the curvature (second variation) of it. This constancy holds if we regard the probability distribution as the gradient of a self-information. Considering the form of the nth derivative of a self-information with keeping this constant ratio, we arrive at the general class of nonextensive entropies. Some properties on the series of entropies constructed by this picture are investigated. Full article
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