Entropy Assessment on Direct Contact Condensation of Subsonic Steam Jets in a Water Tank through Numerical Investigation

Ji, Yu; Zhang, Haochun; Tong, Jianfei; Wang, Xuwei; Han, Wang; Zhang, Yining

doi:10.3390/e18010021

Cited by 14 publications

(9 citation statements)

References 32 publications

(43 reference statements)

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“…In the simulation, the Semi-Implicit Method for Pressure-Linked Equations-Consistent (SIMPLEC) algorithm is adopted for pressure-velocity coupling, and the second upwind scheme is used for spatial discretization of equations with regards to continuity, momentum, energy, turbulent kinetic energy and specific dissipation. During the simulation, the calculation will not be terminated unless the two criteria below are attained [22]: (1) The scaled residuals for all solutions except energy should be less than 10 −6 , while the term for energy is set to 10 −9 ; (2) The entropy generation rate integrated to whole domain hardly changes with iterations.…”

Section: Solution Methodsmentioning

confidence: 99%

Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids

Zhang

Xie

et al. 2017

Entropy

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Abstract:The entropy generation analysis of fully turbulent convective heat transfer to nanofluids in a circular tube is investigated numerically using the Reynolds Averaged Navier-Stokes (RANS) model. The nanofluids with particle concentration of 0%, 1%, 2%, 4% and 6% are treated as single phases of effective properties. The uniform heat flux is enforced at the tube wall. To confirm the validity of the numerical approach, the results have been compared with empirical correlations and analytical formula. The self-similarity profiles of local entropy generation are also studied, in which the peak values of entropy generation by direct dissipation, turbulent dissipation, mean temperature gradients and fluctuating temperature gradients for different Reynolds number as well as different particle concentration are observed. In addition, the effects of Reynolds number, volume fraction of nanoparticles and heat flux on total entropy generation and Bejan number are discussed. In the results, the intersection points of total entropy generation for water and four nanofluids are observed, when the entropy generation decrease before the intersection and increase after the intersection as the particle concentration increases. Finally, by definition of E p , which combines the first law and second law of thermodynamics and attributed to evaluate the real performance of heat transfer processes, the optimal Reynolds number Re op corresponding to the best performance and the advisable Reynolds number Re ad providing the appropriate Reynolds number range for nanofluids in convective heat transfer can be determined.

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Section: Solution Methodsmentioning

confidence: 99%

Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids

Zhang

Xie

et al. 2017

Entropy

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“…The entropy generation can be divided into two terms 37 : Frictional volumetric entropy generation

S_{vf} = \frac{μ}{\bar{T}} ()(, \frac{\partial \overset{U_{i}}{true}}{\partial x_{j}} + \frac{\partial \overset{U_{j}}{true}}{\partial x_{i}}) \frac{\partial \overset{U_{i}}{true}}{\partial x_{j}} + C_{μ} \frac{ρ k ω}{\bar{T}}

Thermal volumetric entropy generation

S_{vt} = \frac{λ}{\overset{T}{true} normal²} {(\frac{\partial \overset{T}{true}}{\partial x_{i}})}^{2} + \frac{α^{⁎} k}{{ω \Pr}_{t}} \frac{ρ c_{p}}{\overset{T}{true} normal²} {(\frac{\partial \overset{T}{true}}{\partial x_{i}})}^{2}

…”

Section: Governing Equations and Mathematical Formulationmentioning

confidence: 99%

Turbulent forced convection and entropy analysis of a nanofluid through a 3D 90° elbow using a two‐phase approach

Korei

Benissaad

2021

Heat Trans

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In a scenario characterized by a secondary flow called Dean's vortices, thermal and flow behavior analysis is examined. Forced convection of an Al2O3–water nanofluid through a three‐dimensional (3D) 90° elbow was analyzed numerically using a multiphase mixture model. Turbulence is taken into account by using the shear‐stress transport k–ω model. Also, entropy production is presented to obtain the optimized conditions. Simulation parameters consist of different Reynolds numbers (10,000 ≤ italicRe ≤ 100,000), nanoparticle volume fraction false( 2 % ≤ ϕ ≤ 6 % false), nanoparticle diameter ( 10 ≤ d p ≤ 40 ). The findings reveal that the increase in the ϕ and the Re along with a smaller dp discourages the appearance of Dean vortices in the flow. The pressure drop increases with the increase in the volume fraction and the decrease in the nanoparticles' diameter. The highest NuM is observed at ϕ = 6 % for d p = 10 nm. Significant heat transfer rates are observed near the outer wall. The minimum total entropy production is obtained at Re = 100,000 for ϕ = 2 % and d p = 40 nm.

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“…Hesselgreaves proposed the idea of dimensionless irreversibility number and employed it in optimizing heat exchangers [33]. Jiyu et al studied the entropy generation in the spray atomization process, analyzing the irreversibility of heat and mass transfer during the phase transition [34]. Thus, based on its outstanding performance, the entropy generation analysis will be employed to analyze the performance of the second law of thermodynamics of He-Xe in the heat transfer process inside different flow channels.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Thermodynamic Analysis of He–Xe in Microchannels with Different Structures

et al. 2023

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He–Xe, with a 40 g/mol molar mass, is considered one of the most promising working media in a space-confined Brayton cycle. The thermodynamic performance of He–Xe in different configuration channels is investigated in this paper to provide a basis for the optimal design of printed circuit board plate heat exchanger (PCHE). In this paper, the factors affecting the temperature distribution of the He–Xe flow field are analyzed based on the flow heat transfer mechanism. It is found that the flow patterns in the logarithmic and outer zones determine the temperature distribution pattern of the flow field. A series of numerical simulations verify the above conclusions, and it is found that reasonable channel structure and operating conditions can significantly improve the thermodynamic performance of the He–Xe flow. Based on the above findings, the Zig channel is optimized, obtaining Sine and Serpentine channels with different structural characteristics. Comprehensive thermodynamic comparisons of the helium–xenon flow domains inside channels are performed, and the Serpentine channel with a shape factor of tan 52.5° is found with the best performance. This work aims to improve the understanding of the thermodynamic performance of He–Xe in microchannels and provide theoretical support for further optimization of PCHE employing He–Xe.

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Entropy Assessment on Direct Contact Condensation of Subsonic Steam Jets in a Water Tank through Numerical Investigation

Cited by 14 publications

References 32 publications

Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids

Entropy Generation Analysis and Performance Evaluation of Turbulent Forced Convective Heat Transfer to Nanofluids

Turbulent forced convection and entropy analysis of a nanofluid through a 3D 90° elbow using a two‐phase approach

Comprehensive Thermodynamic Analysis of He–Xe in Microchannels with Different Structures

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