Structural fragility and principle of maximum entropy

1985 ◽  
Vol 3 (1) ◽  
pp. 37-46 ◽  
Author(s):  
J. Goodman
Keyword(s):  
Maximum Entropy ◽  
Principle Of Maximum Entropy ◽  
Structural Fragility ◽  
Principle Of Maximum

scholarly journals To Be or to Have Been Lucky, That Is the Question

Philosophies ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 57
Author(s):  
Antony Lesage ◽  
Jean-Marc Victor
Keyword(s):  
High Risk ◽  
Maximum Entropy ◽  
Chronic Diseases ◽  
Statistical Test ◽  
Low Risk ◽  
Principle Of Maximum Entropy ◽  
Ex Ante ◽  
Social Opportunities ◽  
Global Population ◽  
Principle Of Maximum

Is it possible to measure the dispersion of ex ante chances (i.e., chances “before the event”) among people, be it gambling, health, or social opportunities? We explore this question and provide some tools, including a statistical test, to evidence the actual dispersion of ex ante chances in various areas, with a focus on chronic diseases. Using the principle of maximum entropy, we derive the distribution of the risk of becoming ill in the global population as well as in the population of affected people. We find that affected people are either at very low risk, like the overwhelming majority of the population, but still were unlucky to become ill, or are at extremely high risk and were bound to become ill.

scholarly journals An Expression for Velocity Lag in Sediment-Laden Open-Channel Flows Based on Tsallis Entropy Together with the Principle of Maximum Entropy

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 522 ◽  
Author(s):  
Zhongfan Zhu ◽  
Jingshan Yu ◽  
Jie Dou ◽  
Dingzhi Peng
Keyword(s):  
Maximum Entropy ◽  
Shannon Entropy ◽  
Open Channel ◽  
Tsallis Entropy ◽  
Channel Flows ◽  
Test Cases ◽  
Deterministic Models ◽  
Open Channel Flows ◽  
Principle Of Maximum Entropy ◽  
Principle Of Maximum

In the context of river dynamics, some experimental results have shown that particle velocity is different from fluid velocity along the stream-wise direction for uniform sediment-laden open-channel flows; this velocity difference has been termed velocity lag in the literature. In this study, an analytical expression for estimating the velocity lag in open-channel flows was derived based on the Tsallis entropy theory together with the principle of maximum entropy. The derived expression represents the velocity lag as a function of a non-dimensional entropy parameter depending on the average and maximum values of velocity lag from experimental measurements. The derived expression was tested against twenty-two experimental datasets collected from the literature with three deterministic models and the developed Shannon entropy-based model. The Tsallis entropy-based model agreed better with the experimental datasets than the deterministic models for eighteen out of the twenty-two total real cases, and the prediction accuracy for the eighteen experimental datasets was comparable to that of the developed Shannon entropy-based model (the Tsallis entropy-based expression agreed slightly better than the Shannon entropy-based model for twelve out of eighteen test cases, whereas for the other six test cases, the Shannon entropy-based model had a slightly higher prediction accuracy). Finally, the effects of the friction velocity of the flow, the particle diameter, and the particles’ specific gravity on the velocity lag were analyzed based on the Tsallis entropy-based model. This study shows the potential of the Tsallis entropy theory together with the principle of maximum entropy to predict the stream-wise velocity lag between a particle and the surrounding fluid in sediment-laden open-channel flows.

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