Statistical thermodynamic foundation for mesoscale aggregation in ternary mixtures

This paper presents a novel method of pattern identification in complex systems using the tools derived from statistical thermodynamics. Complexity issues arise in natural or human-engineered systems due to behavioral uncertainties and nonlinearities involved in the process dynamics. The paper introduces a novel concept of behavioral pattern identification and anomaly detection in mechanical systems from macroscopically observed time series of the available sensor data. The theme is built upon the principles of Statistical Thermodynamics and Information Theory. The efficacy of this method is experimentally validated on a laboratory apparatus where the behavioral changes accrue from the evolving fatigue damage in polycrystalline alloy structures.

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Reality in a few thermodynamic reference frames: Statistical thermodynamics from Boltzmann via Gibbs to Einstein

10.31235/osf.io/e4qt7 ◽

2020 ◽

Author(s):

Vasil Dinev Penchev

Keyword(s):

Reference Frame ◽

Reference Frames ◽

Statistical Thermodynamics ◽

Statistical Thermodynamic ◽

Scientific Theories ◽

Common Space ◽

Starting Point ◽

The Subject ◽

The Many ◽

Selection Of

The success of a few theories in statistical thermodynamics can be correlated with their selectivity to reality. These are the theories of Boltzmann, Gibbs, end Einstein.The starting point is Carnot’s theory, which defines implicitly the general selection of reality relevant to thermodynamics. The three other theories share this selection, but specify it further in detail. Each of them separates a few main aspects within the scope of the implicit thermodynamic reality. Their success grounds on that selection. Those aspects can be represented by corresponding oppositions. These are: macroscopic – microscopic; elements – states; relational – non-relational; and observable – theoretical. They can be interpreted as axes of independent qualities constituting a common qualitative reference frame shared by those theories. Each of them can be situated in this reference frame occupying a different place. This reference frame can be interpreted as an additional selection of reality within Carnot’s initial selection describable as macroscopic and both observable and theoretical. The deduced reference frame refers implicitly to many scientific theories independent of their subject therefore defining a general and common space or subspace for scientific theories (not for all).The immediate conclusion is: The examples of a few statistical thermodynamic theories demonstrate that the concept of “reality” is changed or generalized, or even exemplified (i.e. “de-generalized”) from a theory to another.Still a few more general suggestions referring the scientific realism debate can be added: One can admit that reality in scientific theories is some partially shared common qualitative space or subspace describable by relevant oppositions and rather independent of their subject quite different in general. Many or maybe all theories can be situated in that space of reality, which should develop adding new dimensions in it for still newer and newer theories. Its division of independent subspaces can represent the many-realities conception. The subject of a theory determines some relevant subspace of reality. This represents a selection within reality, relevant to the theory in question. The success of that theory correlates essentially with the selection within reality, relevant to its subject.

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Characterizing Atomic Interactions in Interstitial Non-Stoichiometric Compounds by Statistical Thermodynamics: Engineering Usage of Estimated Values of Statistical Thermodynamic Parameters

Journal of Modern Physics ◽

10.4236/jmp.2017.83025 ◽

2017 ◽

Vol 08 (03) ◽

pp. 365-381 ◽

Cited By ~ 1

Author(s):

Nobumitsu Shohoji

Keyword(s):

Thermodynamic Parameters ◽

Statistical Thermodynamics ◽

Statistical Thermodynamic ◽

Atomic Interactions

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Statistical thermodynamics unveils the dissolution mechanism of cellobiose

Physical Chemistry Chemical Physics ◽

10.1039/c7cp04647b ◽

2017 ◽

Vol 19 (34) ◽

pp. 23106-23112 ◽

Cited By ~ 6

Author(s):

Thomas W. J. Nicol ◽

Noriyuki Isobe ◽

James H. Clark ◽

Seishi Shimizu

Keyword(s):

Thermodynamic Analysis ◽

Statistical Thermodynamics ◽

Statistical Thermodynamic ◽

Dissolution Mechanism ◽

Molecular Scale

Statistical thermodynamic analysis of cellobiose solubility in aqueous salts sheds light on the mechanism of cellulose solubilization on a molecular scale.

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