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Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture

Bejan, Adrian·2002·International Journal of Energy Research

Abstract

This paper outlines the fundamentals of the methods of exergy analysis and entropy generation minimization (or thermodynamic optimization—the minimization of exergy destruction). The paper begins with a review of the concept of irreversibility, entropy generation, or exergy destruction. Examples illustrate the accounting for exergy flows and accumulation in closed systems, open systems, heat transfer processes, and power and refrigeration plants. The proportionality between exergy destruction and entropy generation sends the designer in search of improved thermodynamic performance subject to finite-size constraints and specified environmental conditions. Examples are drawn from energy storage systems for sensible heat and latent heat, solar energy, and the generation of maximum power in a power plant model with finite heat transfer surface inventory. It is shown that the physical structure (geometric configuration, topology) of the system springs out of the process of global thermodynamic optimization subject to global constraints. This principle generates structure not only in engineering but also in physics and biology (constructal theory). Copyright © 2002 John Wiley & Sons, Ltd.

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Metadata

Authors
Bejan, A.
Venue
International Journal of Energy Research
Published
2002
Volume
26
Issue
7
Pages
0-43
ISSN
  • 0363-907X (ISSN-L)
  • 1099-114X
OpenAlex
W2032399386
Cited by
603
References
0
FWCI
14.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture. https://app.cochat.ai/papers/10.1002/er.804
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Bejan, A. (2002). Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture. International Journal of Energy Research. https://doi.org/10.1002/er.804

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.