Dirac Structures in Open Thermodynamics

Hiroaki Yoshimura, François Gay-Balmaz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Dirac structures are geometric objects that generalize Poisson structures and presymplectic structures on manifolds. They naturally appear in the formulation of constrained mechanical systems and play an essential role in the understanding of the interrelations between system elements in implicit dynamical systems. In this paper, we show how nonequilibrium thermodynamic systems can be naturally understood in the context of Dirac structures, by mainly focusing on the case of open systems, i.e., thermodynamic systems exchanging heat and matter with the exterior.

Original languageEnglish
Title of host publicationGeometric Science of Information - 4th International Conference, GSI 2019, Proceedings
EditorsFrank Nielsen, Frédéric Barbaresco
PublisherSpringer
Pages199-208
Number of pages10
ISBN (Print)9783030269791
DOIs
Publication statusPublished - 2019
Event4th International Conference on Geometric Science of Information, GSI 2019 - Toulouse, France
Duration: 2019 Aug 272019 Aug 29

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11712 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Geometric Science of Information, GSI 2019
CountryFrance
CityToulouse
Period19/8/2719/8/29

Keywords

  • Dirac dynamical systems
  • Dirac structures
  • Nonequilibrium thermodynamics
  • Open systems

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Yoshimura, H., & Gay-Balmaz, F. (2019). Dirac Structures in Open Thermodynamics. In F. Nielsen, & F. Barbaresco (Eds.), Geometric Science of Information - 4th International Conference, GSI 2019, Proceedings (pp. 199-208). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11712 LNCS). Springer. https://doi.org/10.1007/978-3-030-26980-7_21