4.7 Article

Irreversibility evaluation for transport processes revisited

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijheatmasstransfer.2022.122699

Keywords

Transport process; Irreversibility; Entropy generation analysis; Least action principle; Lyapunov function; Entransy theory

Funding

  1. National Natural Science Founda-tion of China [52106096, 51906121]
  2. ShuimuTs-inghua Scholar Program of Tsinghua University [2020SM028]

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This work revisits the evaluation of irreversibility in typical transport processes and proposes a new irreversibility indicator that can better recover the constitutive relation, characterize the evolution direction of the process, and optimize the performance of transport processes. The new indicator, compared to the traditional entropy generation rate, exhibits better performance in measuring the irreversibility of heat, mass, and momentum diffusion processes.
The entropy generation has been widely used for evaluating irreversibility of transport processes and optimize their performance. However, there still exist challenges against this methodology. This work revisits the irreversibility evaluation in typical transport processes. The irreversibility indicator of transport processes is proposed combining aspects of physical essence and practical application. It is expected to be able to recover the constitutive relation, characterize the evolution direction of process, and optimize standalone transport processes. The entropy generation rate is examined against these conditions, and results show that it fails to meet them. These failures challenge the legitimacy of entropy generation rate in characterizing transport processes' irreversibility. In contrast, the irreversibility of heat, mass, and momentum diffusion processes can be measured by the entransy dissipation, mass entransy dissipation, and momentum entransy dissipation, respectively. A one-dimensional volume-to-point heat conduction and a mass diffusion optimization problem are numerically studied, respectively. Results show that the entransy dissipation-based optimization reduces the average temperature by 3-5 K, giving a better performance than entropy generation optimization, which increases the average temperature up to 17.55 K. In the mass diffusion problem, the mass entransy dissipation-based optimization reduces the average concentration by 3.67%, showing a much better performance than the entropy generation optimization, which yields a 26% increase. Finally, these irreversibility indicators are found to be equivalent to their corresponding energy dissipations. (c) 2022 Elsevier Ltd. All rights reserved.

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