|
|
Role of entropy generation minimization in thermal optimization |
Xue-Tao Cheng(程雪涛)1,2, Xin-Gang Liang(梁新刚)1 |
1. Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, School of Aerospace, Tsinghua University, Beijing 100084, China; 2. The Administrative Committee of the Modern Industrial Park, New District of Zhengpu Port, Maanshan 238261, China |
|
|
Abstract Thermal optimization is very important for improving the performances of thermal systems. In engineering, the entropy generation minimization (EGM) has been widely used to optimize and evaluate the performances of thermal systems. However, the consistency between the EGM and the optimization objective should be specified when the EGM is used. In this paper, we discuss the view angle of irreversibility of entropy generation, and show that entropy generation directly reflects the exergy destruction or the ability loss of doing work. As the design objective in a thermal system is not often consistent with the view angle of irreversibility of entropy generation, the EGM may not lead to the optimal value of the design objective. In heat transfer and heat-work conversion, the inconsistence between the design objectives and the EGM is shown with some examples, and the applicability of the EGM is found to be conditional. The “entropy generation paradox” in heat exchanger analyses is also discussed, and it is shown that there is no direct monotonic relation between the minimum entropy generation rate and the best heat transfer performance of heat exchangers.
|
Received: 03 August 2017
Revised: 31 August 2017
Accepted manuscript online:
|
PACS:
|
05.70.Ln
|
(Nonequilibrium and irreversible thermodynamics)
|
|
44.05.+e
|
(Analytical and numerical techniques)
|
|
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 51376101) and the National Natural Science Fund for Creative Research Groups, China (Grant No. 51621062). |
Corresponding Authors:
Xue-Tao Cheng
E-mail: chengxt02@gmail.com
|
Cite this article:
Xue-Tao Cheng(程雪涛), Xin-Gang Liang(梁新刚) Role of entropy generation minimization in thermal optimization 2017 Chin. Phys. B 26 120505
|
[1] |
Bergles A E 1981 Application of heat transfer augmentation (Washington DC:Hemisphere)
|
[2] |
Chen L G 2012 Chin. Sci. Bull. 57 4404
|
[3] |
Wei S H, Chen L G and Sun F R 2011 Int. J. Therm. Sci. 50 1285
|
[4] |
Cheng X T, Xu X H and Liang X G 2009 Sci. China Ser. E:Tech. Sci. 52 2937
|
[5] |
Sun C, Cheng X T and Liang X G 2014 Chin. Phys. B 23 050513
|
[6] |
Li M and Lai A C K 2013 Energy Convers. Maneg. 65 133
|
[7] |
Abbassi H 2007 Energy 32 1932
|
[8] |
Baytaș A C 2000 Int. J. Heat Mass Transfer 43 2089
|
[9] |
Bejan A 1997 Advanced engineering thermodynamics (NewYork:John Wiley & Sons)
|
[10] |
Klein S A and Reindl D T 1998 J. Energy Res. 120 172
|
[11] |
Cheng X T and Liang X G 2013 Energy Buildings 67 387
|
[12] |
Salamon P, Hoffmann K H, Schubert S, Berry R S and Andresen B 2001 J. Non-Equilib. Thermodyn. 26 73
|
[13] |
Shah R K and Skiepko T 2004 J. Heat Transfer 126 994
|
[14] |
Chen Q, Zhu H Y, Pan N and Guo Z Y 2011 P. Roy. Soc. A-Math. Phys. 467 1012
|
[15] |
Prigogine I 2007 From being to becoming (Beijing:Peking University Press) (in Chinese)
|
[16] |
Zhao K H and Luo W Y 2002 Thermotics (Beijing:Higher Education Press) (in Chinese)
|
[17] |
Cheng X T and Liang X G 2013 Energy Convers. Manag. 73 121
|
[18] |
Cheng X T, Zhang Q Z, Xu X H and Liang X G 2013 Chin. Phys. B 22 020503
|
[19] |
Guo Z Y, Zhu H Y and Liang X G 2007 Int. J. Heat Mass Transfer 50 2545
|
[20] |
Cheng X T and Liang X G 2012 Energy 44 964
|
[21] |
Cheng X T and Liang X G 2013 Chin. Sci. Bull. 58 4696
|
[22] |
Xu Y C and Chen Q 2012 Int. J. Heat Mass Transfer 55 5148
|
[23] |
Cheng X T and Liang X G 2013 Int. J. Heat Mass Transfer 64 903
|
[24] |
Cheng X T and Liang X G 2012 Energy 46 386
|
[25] |
Bejan A 2016 Renew. Sustain. Energy Rev. 53 1636
|
[26] |
Cheng X T and Liang X G 2012 Energy Convers. Manag. 58 163
|
[27] |
Guo Z Y, Liu X B, Tao W Q and Shah R K 2010 Int. J. Heat Mass Transfer 53 2877
|
[28] |
Hesselgreaves J E 2000 Int. J. Heat Mass Transfer 43 4189
|
[29] |
Xu Z M, Yang S R and Chen Z Q 1996 J. Thermal Sci. 5 257
|
[30] |
Sahiti N, Krasniqi F, Fejzullahu X, Bunjaku J and Muriqi A 2008 Appl. Thermal Eng. 28 2337
|
[31] |
Ogiso K 2003 ASME J. Heat Transfer 125 530
|
[32] |
Cheng X T and Liang X G 2012 Energy 47 421
|
[33] |
Cheng X T and Liang X G 2015 Chin. Phys. B 24 060510
|
[34] |
Wu Y Q 2015 Chin. Phys. B 24 070506
|
[35] |
Cheng X T and Liang X G 2013 Chin. Phys. B 22 010508
|
[36] |
Chen Q, Wu J, Wang M R, Pan N and Guo Z Y 2010 Chin. Sci. Bull. 56 449
|
[37] |
Wang W H, Cheng X T and Liang X G 2013 Chin. Phys. B 22 110506
|
[38] |
Wu Y Q, Cai L and Wu H J 2016 Chin. Phys. B 25 060506
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|