2022
DOI: 10.1007/s00231-022-03197-z
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Numerical investigation of roughness effect on wet steam ejector performance in the refrigeration cycle

Abstract: 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… Show more

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Cited by 11 publications
(1 citation statement)
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“…Experimental and numerical studies from Zhang et al [31] on superheated steam through IWSEP nozzle further confirmed the feasibility of studying condensing steam flows with superheating using numerical models. Mehdi et al [32] investigated the relationship between a steam ejector's performance and cost criteria, where entrainment ratio and COP were used to reflect the performance, while the wall roughness is treated as cost. Similar concept was also adopted in the current study, where the cost is reflected by the increase in superheating, and exergy analysis is also included as a part of performance analysis.…”
Section: Introductionmentioning
confidence: 99%
“…Experimental and numerical studies from Zhang et al [31] on superheated steam through IWSEP nozzle further confirmed the feasibility of studying condensing steam flows with superheating using numerical models. Mehdi et al [32] investigated the relationship between a steam ejector's performance and cost criteria, where entrainment ratio and COP were used to reflect the performance, while the wall roughness is treated as cost. Similar concept was also adopted in the current study, where the cost is reflected by the increase in superheating, and exergy analysis is also included as a part of performance analysis.…”
Section: Introductionmentioning
confidence: 99%