A Paradox of Decreasing Entropy in Multiscale Monte Carlo Grain Growth Simulations

Entropy

Michael Nosonovsky¹ 

关键词: grain growth;    Monte Carlo simulation;    Cellular Automata;    multiscale modeling;   

DOI  :  10.3390/entropy-e10020049

来源: mdpi

【 摘 要 】

Grain growth in metals is driven by random thermal fluctuations and increases the orderliness of the system. This random process is usually simulated by the Monte Carlo (MC) method and Cellular Automata (CA). The increasing orderliness results in an entropy decrease, thus leading to a paradoxical apparent violation of the second law of thermodynamics. In this paper, it is shown that treating the system as a multiscale system resolves this paradox. MC/CA simulations usually take into consideration only the mesoscale entropy. Therefore, the information entropy of the system decreases, leading to an apparent paradox. However, in the physical system, the entropy is produced at the nanoscale while it is consumed at the mesoscale, so that the net entropy is growing.

【 授权许可】

CC BY   
© 2008 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.