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Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture
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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Cited by
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Low grade thermal energy sources and uses from the process industry in the UK
Ammar, Y., Joyce, S., Norman, R., Wang, Y., & Roskilly, A. P. (2012) · Applied Energy · doi:10.1016/j.apenergy.2011.06.003 · Cited by 323
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Metadata
- Authors
- Bejan, A.
- Venue
- International Journal of Energy Research
- Publisher
- Hindawi Limited
- 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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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.