The entropy generation rate minimization for a proposed air ejector for the carpet industry

Lakzian, Esmail; Hajian, Masoud; Farahmand, Ali

doi:10.1007/s11012-017-0706-1

Cited by 18 publications

(12 citation statements)

References 38 publications

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“…Nevertheless, in a large body of literature, entropy generation in the presence of turbulent flows is calculated considering only the contribution of the mean flow. This simplification has been adopted for Wells turbines [66,67,68,69,71], pipe flows [61,44], and turbine blades [51]. Herwig et al [34] demonstrated how neglecting the entropy produced by turbulent fluctuation may lead to errors in the global entropy production, as well as to misleading conclusions.…”

Section: Introductionmentioning

confidence: 99%

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

et al. 2018

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In recent years, a number of authors have studied entropy generation in Wells turbines. This is potentially a very interesting topic, as it can provide important insights into the irreversibilities of the system, as well as a methodology for identifying, and possibly minimizing, the main sources of loss. Unfortunately, the approach used in these studies contains some crude simplifications that lead to a severe underestimation of entropy generation and, more importantly, to misleading conclusions. This paper contains a re-examination of the mechanisms for entropy generation in fluid flow, with a particular emphasis on RANS equations. An appropriate methodology for estimating entropy generation in isolated airfoils and Wells turbines is presented. Results are verified for different flow conditions, and a comparison with theoretical values is presented. 1Wells turbines have been studied extensively, both experimentally [15,31,24,63,74,53,57,48] and numerically [40,62,17,76,30,72,32,27], but mainly from a first-law perspective. More recently, a number of authors [66,67,68,69,71] have focused on the irreversibilities in this component, trying to link the amount of available work (exergy) and the entropy produced.The application of second-law analyses is not novel, as such analyses have been done by many authors, but mainly from a system perspective: Bejan [8,9] presents an extensive review of the application to different thermodynamic systems. Similar approaches have been used in the analysis of thermal power plants [39], wind turbines [56,6,7,60,52], and vortex generators [33].Computational Fluid Dynamics (CFD), aside from making possible a more rapid and economic evaluation of many systems (compared to experimental testing), can provide a better and more detailed understanding of many phenomena, by capturing a level of detail that would be extremely difficult in an experimental study. It allows a very fine decomposition of the overall problem that can be used to locate the sources of irreversibility within the system. Entropy generation by thermal and viscous sources can be calculated directly by post-processing the fields of thermo-and fluid-dynamic variables available from the numerical solution [8]. However, particular attention needs to be paid to the nature of the flow and to the solution approach. While in laminar flows all entropy generation is directly found in the CFD solution [18,2,70,33,79,59], this is not true for turbulent flows, unless a Direct Numerical Simulation (or DNS) is used. However, with current computational resources, the use of DNS is still impractical even for moderately large Reynolds numbers. To make high-Reynolds-number flows treatable, the governing equations are either averaged (leading to the Reynolds Averaged Navier Stokes equations, or RANS) or filtered (leading to the Large Eddy Simulation approach, or LES).Moore and Moore [49, 50] present a methodology for calculating entropy production in viscous flows, using RANS equations. They divide the mean entropy production into the contr...

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Section: Introductionmentioning

confidence: 99%

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

et al. 2018

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“…The working fluid was air, and it was considered as ideal and compressible. Some recent papers in which the fluid was considered as ideal and compressible and working under similar pressure differentials are Reference [17,18]. In the present paper, the simulations were performed under dynamic conditions, therefore matching the experimental test conditions.…”

Section: Dynamic Computational Fluid Dynamic Simulationsmentioning

confidence: 99%

“…The maximum Courant number was kept below 0.8, being the time step around 5 × 10 −8 s.Turbulence intensity was set to 0.05% in all cases. The realizable k − turbulent model, along with a wall function, as previously used by Lakzian et al [18], were employed in all the simulations. The maximum y + on the wall of the nozzle was about 90.…”

Section: Dynamic Computational Fluid Dynamic Simulationsmentioning

confidence: 99%

“…CFD simulations on compressible flow through valves, whether purging or relief ones, have recently been performed in Reference [15,16]. The modeling of flow ejectors under sonic flow conditions was considered in Reference [17][18][19][20][21]. Some of the recent papers simulating compressible flow conditions at high Mach numbers inside nozzles are Reference [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, they stated that the main differences between the numerical and experimental results appeared when comparing 2D and 3D models. Lakzian et al [18] performed a compressible 2D RANS simulation on an air ejector pump. In their analysis, they assumed the working fluid as ideal gas and the walls were treated as adiabatic.…”

Section: Introductionmentioning

confidence: 99%

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Discharge Coefficients of a Heavy Suspension Nozzle

et al. 2021

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The suspensions used in heavy vehicles often consist of several oil and two gas chambers. In order to perform an analytical study of the mass flow transferred between two gas chambers separated by a nozzle, and when considering the gas as compressible and real, it is usually needed to determine the discharge coefficient of the nozzle. The nozzle configuration analyzed in the present study consists of a T shape, and it is used to separate two nitrogen chambers employed in heavy vehicle suspensions. In the present study, under compressible dynamic real flow conditions and at operating pressures, discharge coefficients were determined based on experimental data. A test rig was constructed for this purpose, and air was used as working fluid. The study clarifies that discharge coefficients for the T shape nozzle studied not only depend on the pressure gradient between chambers but also on the flow direction. Computational Fluid Dynamic (CFD) simulations, using air as working fluid and when flowing in both nozzle directions, were undertaken, as well, and the fluid was considered as compressible and ideal. The CFD results deeply helped in understanding why the dynamic discharge coefficients were dependent on both the pressure ratio and flow direction, clarifying at which nozzle location, and for how long, chocked flow was to be expected. Experimentally-based results were compared with the CFD ones, validating both the experimental procedure and numerical methodologies presented. The information gathered in the present study is aimed to be used to mathematically characterize the dynamic performance of a real suspension.

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Numerical investigation of roughness effect on wet steam ejector performance in the refrigeration cycle

2022

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Machining operation and presence of water droplet cause increasing the surface roughness of wet steam ejector walls and changing its performance in the refrigeration cycle. The purpose of this work is to investigate the influences of the primary nozzle surface roughness on wet steam ejectors in the refrigeration cycle with steam water as a working flow. The flow is modeled by solving governed equations based on the Eulerian-Eulerian approach. The proposed model is validated by comparison numerical results with experimental data of the ejector and nozzle. Moreover, different surface roughness has been successfully applied to the primary nozzle and its effect on the entire flow is shown. Six properties of wet steam are selected, including pressure, temperature, Mach number, droplet average radius, droplet growth rate, and liquid mass fraction. The result shows, increase in the surface roughness resulted in a shift of the shock chain to the primary nozzle, damping shock strength, and increasing temperature in the diffuser. In addition, increment of the primary nozzle surface roughness decreases ER and COP of the refrigeration cycle by 3.67% and 3.8%, respectively. According to the important impact of the roughness on the liquid mass fraction, droplet average radius, droplet growth rate, ER, and COP, designers and operators should be considered the roughness effects in the design and operation of wet steam ejectors.

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The entropy generation rate minimization for a proposed air ejector for the carpet industry

Cited by 18 publications

References 38 publications

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

Numerical evaluation of entropy generation in isolated airfoils and Wells turbines

Discharge Coefficients of a Heavy Suspension Nozzle

Numerical investigation of roughness effect on wet steam ejector performance in the refrigeration cycle

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