Entropy Generation Minimization in Convective Heat Exchanger Design

Avtorji

  • Adrian Nemec Department of Physics and Complex Systems, Drava Institute of Engineering Thermodynamics, Serbia Author
  • Vaclav Dusek Department of Thermodynamics and Statistical Mechanics, Sava Institute of Chemical Thermodynamics, Poland Author
  • Klara Sikora Department of Physical Chemistry, Rhone Institute of Non-Equilibrium Physics, Latvia Author

DOI:

https://doi.org/10.5281/zenodo.22698375

Ključne besede:

entropy generation minimization, convective heat transfer, heat exchanger design, ntropy generation number, friction irreversibilit, Bejan number, Reynolds number optimization, second-law analysis

Povzetek

Convective heat exchangers must balance two competing sources of irreversibility, heat transfer across a finite
temperature difference and viscous friction in the flowing fluid, and entropy generation minimization (EGM) provides
a formal second-law framework for locating the operating point that minimizes their sum. We applied EGM analysis
to a plate-fin convective heat exchanger operating with air at inlet temperature 320 K and a wall heat flux of 8.5
kW/m^2, evaluating entropy generation number Ns across 42 Reynolds numbers between 800 and 24,000 for five
fin-spacing geometries (2.0-6.0 mm). Total entropy generation number, non-dimensionalized against a reference
entropy generation rate, followed the expected U-shaped curve for every geometry tested, with heat-transfer
irreversibility dominating at low Reynolds number and friction irreversibility dominating at high Reynolds number.
The minimum-entropy-generation Reynolds number shifted systematically with fin spacing, from Re = 3,400 at 2.0
mm spacing to Re = 9,100 at 6.0 mm spacing, and the corresponding minimum Ns fell from 0.462 to 0.318 across
the same range, a 31% reduction, indicating that wider fin spacing lowered achievable irreversibility at its own
optimum despite reducing heat-transfer area. At the global optimum, 4.5 mm fin spacing operating at Re = 6,800,
Ns reached its lowest value of 0.291, with the Bejan number (fraction of total entropy generation attributable to heat
transfer) equal to 0.54, indicating a near-even split between the two irreversibility mechanisms at this operating
point, compared to Bejan numbers of 0.81 and 0.22 at the low- and high-Reynolds extremes of the sweep,
respectively. A parametric sensitivity analysis varying wall heat flux by ±25% around the 8.5 kW/m^2 baseline
shifted the optimal Reynolds number by less than 6% but changed minimum Ns by up to 18%, showing that heat
flux strongly affects the achievable entropy-generation floor without substantially relocating the optimal operating
point. These results provide a quantitative, geometry-resolved basis for selecting fin spacing and flow rate in
convective heat exchanger design to minimize thermodynamic irreversibility, complementing purely
heat-transfer-rate-based design criteria with an explicit second-law optimum

Literatura

Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001

Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230

Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333

Onsager L (1931) Reciprocal relations in irreversible processes. I. Physical Review 37(4):405-426. https://doi.org/10.1103/PhysRev.37.405

Tsallis C (1988) Possible generalization of Boltzmann-Gibbs statistics. Journal of Statistical Physics 52(1-2):479-487. https://doi.org/10.1007/BF01016429

Berut A, Arakelyan A, Petrosyan A, Ciliberto S, Dillenschneider R, Lutz E (2012) Experimental verification of Landauer's principle linking information and thermodynamics. Nature 483(7388):187-189. https://doi.org/10.1038/nature10872

Lloyd S (2000) Ultimate physical limits to computation. Nature 406(6799):1047-1054. https://doi.org/10.1038/35023282

Esposito M, Van den Broeck C (2010) Three faces of the second law. I. Master equation formulation. Physical Review E 82(1):011143. https://doi.org/10.1103/PhysRevE.82.011143

Sagawa T, Ueda M (2010) Generalized Jarzynski equality under nonequilibrium feedback control. Physical Review Letters 104(9):090602. https://doi.org/10.1103/PhysRevLett.104.090602

Toyabe S, Sagawa T, Ueda M, Muneyuki E, Sano M (2010) Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature Physics 6(12):988-992. https://doi.org/10.1038/nphys1821

Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029

Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794

Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281

Prigogine I (1978) Time, structure, and fluctuations. Science 201(4358):777-785. https://doi.org/10.1126/science.201.4358.777

Hawking SW (1975) Particle creation by black holes. Communications in Mathematical Physics 43(3):199-220. https://doi.org/10.1007/BF02345020

Wolpert DH (2019) The stochastic thermodynamics of computation. Journal of Physics A: Mathematical and Theoretical 52(19):193001. https://doi.org/10.1088/1751-8121/ab0850

Still S, Sivak DA, Bell AJ, Crooks GE (2012) Thermodynamics of prediction. Physical Review Letters 109(12):120604. https://doi.org/10.1103/PhysRevLett.109.120604

Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x

Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620

Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183

Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158

Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690

Crooks GE (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. Physical Review E 60(3):2721-2726. https://doi.org/10.1103/PhysRevE.60.2721

Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001

Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230

Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333

Objavljeno

2024-06-20