Thermodynamic optimization equalities in weakly driven processes

Fuente: arXiv
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Main Author: Nazé, Pierre
Format: Preprint
Published: 2023
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author Nazé, Pierre
author_facet Nazé, Pierre
contents Equalities are generally more suitable for experimental verification than inequalities. In this work, I derive valid equalities from the Euler-Lagrange equation for the optimization of macroscopic thermodynamic averages in weakly driven classical open systems. These equalities show that optimization occurs when work and heat become path-independent. I illustrate their applicability by employing them as a convergence criterion in the global optimization technique of genetic programming. Moreover, due to fluctuation-dissipation relations for internal energy, work, and heat, analogous results hold for their variances.
format Preprint
id arxiv_https___arxiv_org_abs_2309_00076
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Thermodynamic optimization equalities in weakly driven processes
Nazé, Pierre
Statistical Mechanics
Equalities are generally more suitable for experimental verification than inequalities. In this work, I derive valid equalities from the Euler-Lagrange equation for the optimization of macroscopic thermodynamic averages in weakly driven classical open systems. These equalities show that optimization occurs when work and heat become path-independent. I illustrate their applicability by employing them as a convergence criterion in the global optimization technique of genetic programming. Moreover, due to fluctuation-dissipation relations for internal energy, work, and heat, analogous results hold for their variances.
title Thermodynamic optimization equalities in weakly driven processes
topic Statistical Mechanics
url https://arxiv.org/abs/2309.00076