The vacuum degassing (VD) process is one of the prominent processes in the secondary metallurgy thereby improving the quality of the produced steel. The combination of steam ejectors and liquid-ring pumps (LRPs) is a prevalent mechanism for creating a deep vacuum in industrial applications including the VD process. The objective of this study is to design the ejector system for the VD process of a 20-ton furnace with such a mechanism. Through computational fluid dynamics (CFD) with experimental data validation, the effects of geometrical parameters are investigated and reported for selecting the optimized values. Among the potential geometric parameters, the most influential ones are described including nozzle inlet radius, mixing chamber radius, and area ratio. Apart from satisfying the process requirements, the ejector system should elevate the pressure to the value at which LRPs can operate effectively. Given the mentioned demands, three ejectors are designed and simulated to operate serially.
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References
1.
GhoshA.Secondary steelmaking: principles and applications. CRC Press; 2000. View online.
2.
CapurroCCerruttiGCicuttiC.Influence of vacuum degassing on steel cleanliness. In: Conference: 9th International Conference on Clean Steel. View online.
3.
FruehanRJ.Foundation AISE steel. In: The making, shaping, and treating of steel: steelmaking and refining volume. AISE Steel Foundation; 1998. View online.
4.
SteneholmKAnderssonMTillianderAet al.Removal of hydrogen, nitrogen and sulphur from tool steel during vacuum degassing. Ironmak Steelmak. 2013;40:199–205. View online. doi: 10.1179/1743281212Y.0000000029
5.
KnightJ.The use of steam ejectors for the vacuum degassing of steel. Proc Inst Mech Eng. 1966;181:225–241. View online. doi: 10.1243/PIME_PROC_1966_181_024_02
6.
DeshpandeVSModakJP.Application of RCM for safety considerations in a steel plant. Reliab Eng Syst Safety. 2002;78:325–334. View online. doi: 10.1016/S0951-8320(02)00177-1
7.
HucknallDJ.Vacuum technology and applications. Elsevier; 2013. View online.
8.
PianthongKSeehanamWBehniaMet al.Investigation and improvement of ejector refrigeration system using computational fluid dynamics technique. Energy Convers Manage. 2007;48:2556–2564. View online. doi: 10.1016/j.enconman.2007.03.021
9.
AbadiSMANRKouhikamaliR.CFD-aided mathematical modeling of thermal vapor compressors in multiple effects distillation units. Appl Math Model. 2016;40:6850–6868. View online. doi: 10.1016/j.apm.2016.02.032
SriveerakulTAphornratanaSChunnanondK.Performance prediction of steam ejector using computational fluid dynamics: part 1. Validation of the CFD results. Int J Therm Sci. 2007;46:812–822. View online. doi: 10.1016/j.ijthermalsci.2006.10.014
12.
SriveerakulTAphornratanaSChunnanondK.Performance prediction of steam ejector using computational fluid dynamics: part 2. Flow structure of a steam ejector influenced by operating pressures and geometries. Int J Therm Sci. 2007;46:823–833. View online. doi: 10.1016/j.ijthermalsci.2006.10.012
13.
LinCCaiWLiYet al.Numerical investigation of geometry parameters for pressure recovery of an adjustable ejector in multi-evaporator refrigeration system. Appl Therm Eng. 2013;61:649–656. View online. doi: 10.1016/j.applthermaleng.2013.08.033
14.
YadavRLPatwardhanAW.Design aspects of ejectors: effects of suction chamber geometry. Chem Eng Sci. 2008;63:3886–3897. View online. doi: 10.1016/j.ces.2008.04.012
15.
YanJWenNWangLet al.Optimization on ejector key geometries of a two-stage ejector-based multi-evaporator refrigeration system. Energy Convers Manage. 2018;175:142–150. View online. doi: 10.1016/j.enconman.2018.08.110
16.
DingZWangLZhaoHet al.Numerical study and design of a two-stage ejector for subzero refrigeration. Appl Therm Eng. 2016;108:436–448. View online. doi: 10.1016/j.applthermaleng.2016.07.104
17.
ChattopadhyayKIsacMGuthrieRIL.Applications of computational fluid dynamics (CFD) in iron-and steelmaking: part 1. Ironmak Steelmak. 2010;37:554–561. View online. doi: 10.1179/030192310X12731438631804
18.
ChattopadhyayKIsacMGuthrieRIL.Applications of computational fluid dynamics (CFD) in iron-and steelmaking: part 2. Ironmak Steelmak. 2010;37:562–569. View online. doi: 10.1179/030192310X12731438631840
19.
BruceSimonCheethamVLeggeG.Recent operating experience with dry running vacuum pumps on vacuum degassing and vacuum oxygen decarburising systems. In: Iron & Steel Society International Technology Conference (ISS Tech); Citeseer. View online.
20.
BruceS.CheethamVLeggeG.Recent experience of mechanical vacuum pumps replacing steam ejectors in VOD and VD processes. In: 4th Asia Steel International Steel; 2009. View online.
21.
ESDU. Ejector and jet pump. London: ESDU International Ltd; 1985. View online.
22.
KouhikamaliRSharifiN.Experience of modification of thermo-compressors in multiple effects desalination plants in Assaluyeh in IRAN. Appl Therm Eng. 2012;40:174–180. View online. doi: 10.1016/j.applthermaleng.2012.02.002
23.
CroquerSPoncetSGalanisN.Comparison of ejector predicted performance by thermodynamic and CFD models. Int J Refrig. 2016;68:28–36. View online. doi: 10.1016/j.ijrefrig.2016.04.026
24.
MaghsoodiAAfshariEAhmadikiaH.Optimization of geometric parameters for design a high-performance ejector in the proton exchange membrane fuel cell system using artificial neural network and genetic algorithm. Appl Therm Eng. 2014;71:410–418. View online. doi: 10.1016/j.applthermaleng.2014.06.067
25.
HaghparastPSorinMVNesreddineH.The impact of internal ejector working characteristics and geometry on the performance of a refrigeration cycle. Energy. 2018;162:728–743. View online. doi: 10.1016/j.energy.2018.08.017
26.
YangXLongXYaoX.Numerical investigation on the mixing process in a steam ejector with different nozzle structures. Int J Therm Sci. 2012;56:95–106. View online. doi: 10.1016/j.ijthermalsci.2012.01.021
27.
LiuJWangLJiaL.A predictive model for the performance of the ejector in refrigeration system. Energy Convers Manage. 2017;150:269–276. View online. doi: 10.1016/j.enconman.2017.08.021
28.
BartosiewiczYAidounZMercadierY.Numerical assessment of ejector operation for refrigeration applications based on CFD. Appl Therm Eng. 2006;26:604–612. View online. doi: 10.1016/j.applthermaleng.2005.07.003
29.
BartosiewiczYAidounZDesevauxPet al.Numerical and experimental investigations on supersonic ejectors. Int J Heat Fluid Flow. 2005;26:56–70. View online. doi: 10.1016/j.ijheatfluidflow.2004.07.003
30.
LucasCRuscheHSchroederAet al.Numerical investigation of a two-phase CO2 ejector. Int J Refrig. 2014;43:154–166. View online. doi: 10.1016/j.ijrefrig.2014.03.003
31.
PetrovicASvorcanJPejcevAet al.Comparison of novel variable area convergent-divergent nozzle performances obtained by analytic, computational and experimental methods. Appl Math Model. 2018;57:206–225. View online. doi: 10.1016/j.apm.2018.01.016
32.
RuangtrakoonNThongtipTAphornratanaSet al.CFD simulation on the effect of primary nozzle geometries for a steam ejector in refrigeration cycle. Int J Therm Sci. 2013;63:133–145. View online. doi: 10.1016/j.ijthermalsci.2012.07.009
33.
BesagniGMereuRChiesaPet al.An integrated lumped parameter-CFD approach for off-design ejector performance evaluation. Energy Convers Manage. 2015;105:697–715. View online. doi: 10.1016/j.enconman.2015.08.029
34.
VersteegHKMalalasekeraW.An introduction to computational fluid dynamics: the finite volume method. Pearson Education Limited; 2007. View online.
35.
BerkeleyFD.Ejectors have a wide range of uses. Petroleum Refiner. Dec;37:95–100. View online.
36.
MohammadiA.An investigation of geometrical factors of multi-stage steam ejectors for air suction. Energy. 2019;186:115808. View online. doi: 10.1016/j.energy.2019.07.138
37.
WangX-DDongJ-L.Numerical study on the performances of steam-jet vacuum pump at different operating conditions. Vacuum. 2010;84:1341–1346. View online. doi: 10.1016/j.vacuum.2010.03.001
38.
SharifiN.Numerical study of non-equilibrium condensing supersonic steam flow in a jet-pump based on supersaturation theory. Int J Mech Sci. 2020;165:105221. View online. doi: 10.1016/j.ijmecsci.2019.105221
