“…The location of zero axial velocity was almost identical for all the four models. at z/L = 0.5 [10] In case of profiles of static temperature, all the four turbulence models predicted the same qualitative nature; however the magnitude obtained differed considerably. The resulting temperature differential was attributed to difference in predicted pressure differential by various models (Fig.…”
Section: Numerical Studies On Rhvtmentioning
confidence: 74%
“…Dutta et al [10] used Four Reynolds Average NavierStokes (RANS) based turbulence models, namely the standard k-ε, RNG k-ε, Standard k-ω and Shear Stress Transport (SST) k-ω to model the turbulence present in the flow field of RHVT. Their results indicated that difference of pressure between wall and axis are maximum with RNG k-ε while it was least for Standard k-ε model (Fig.…”
Section: Numerical Studies On Rhvtmentioning
confidence: 99%
“…20). at z/L = 0.5 [10] IV. CONCLUSION AND FUTURE ENHANCEMENT Due to small size, RHVT presents difficulties associated with accurate determination of profiles of temperature and flow field using experimental arrangement.…”
“…The location of zero axial velocity was almost identical for all the four models. at z/L = 0.5 [10] In case of profiles of static temperature, all the four turbulence models predicted the same qualitative nature; however the magnitude obtained differed considerably. The resulting temperature differential was attributed to difference in predicted pressure differential by various models (Fig.…”
Section: Numerical Studies On Rhvtmentioning
confidence: 74%
“…Dutta et al [10] used Four Reynolds Average NavierStokes (RANS) based turbulence models, namely the standard k-ε, RNG k-ε, Standard k-ω and Shear Stress Transport (SST) k-ω to model the turbulence present in the flow field of RHVT. Their results indicated that difference of pressure between wall and axis are maximum with RNG k-ε while it was least for Standard k-ε model (Fig.…”
Section: Numerical Studies On Rhvtmentioning
confidence: 99%
“…20). at z/L = 0.5 [10] IV. CONCLUSION AND FUTURE ENHANCEMENT Due to small size, RHVT presents difficulties associated with accurate determination of profiles of temperature and flow field using experimental arrangement.…”
“…Along with this, the location of stagnation point was marked with reference to the highest wall temperature. Then the comparison of numerical turbulent models (Dutta, Sinhamahapatra, & Bandyopdhyay, 2010) demonstrates results to identify the best model getting close to experimental results. The numerical analysis of curved tubes (Bovand M. , Valipour, Dincer, & Tamayol Heat and Mass Transfer (2017) Vol.…”
Section: Fig 15 Turbulence Models Used For Vortex Tube Analysismentioning
confidence: 85%
“…Numerical results for varieties of different models (Dutta, Sinhamahapatra, & Bandyopdhyay, 2010;Shamsoddini & Nezhad, 2010;Baghdad, Ouadha, & Addad, 2012;Khazaei, Teymourtash, & Jafarian, 2012;Pourmahmoud, Hassanzadeh, & Moutaby, 2012;Pourmahmoud, Jahangiramini, & Izadi, 2013;Rafiee & Rahimi, 2013;Rafiee & Masoud, 2014;Rafiee & Sadeghiazad, 2014) are available for their efficiency and closeness to realistic situation inside the vortex phenomenon. Few models were successfully captured flow phenomenon and occurrence of secondary flow, stagnation point, hot and cold separation etc.…”
Section: Fig 15 Turbulence Models Used For Vortex Tube Analysismentioning
Vortex tube is the device that separates pressurized fluid into hot and cold fluid streams simultaneously. The scientific community has done extensive experimental and theoretical studies since invention of vortex tube to augment the performance of the tube by varying geometrical and operational parameters; the paper deals with parametric review of all such work. The review takes into account effect of almost 14 parameters on performance of vortex tube. It includes developments in tube geometry like L/D ratio, number of nozzles; hot end valve angle and cold orifice diameter etc. are discussed along with different fluids and operational parameters like CMF and stagnation point etc. The focus of most of the theoretical and experimental studies was to investigate mechanism of thermal separation and geometry optimization. The main objective of this review is to discuss efforts made in order to enhance the refrigeration effect so that, missing links could help for future research.
Mixing a small amount of magnetic beads and regents with large volume samples evenly in microcavities of a microfluidic chip is always the key step for the application of microfluidic technology in the field of magnetophoresis analysis. This article proposes a microfluidic chip for DNA extraction by magnetophoresis, which relies on bubble rising to generate turbulence and microvortices of various sizes to mix magnetic beads with samples uniformly. The construction and working principle of the microfluidic chip are introduced. CFD simulations are conducted when magnetic beads and samples are irritated by the generation of gas bubbles with the variation of supply pressures. The whole mixing process in the microfluidic chip is observed through a high-speed camera and a microfluidic system when the gas bubbles are generated continuously. The influence of supply pressure on the mixing characteristics of the microfluidic chip is investigated and discussed with both simulation and experiments. Compared with magnetic mixing, bubble mixing can avoid the magnetic beads gather phenomenon caused by magnetic forces and provide a rapid and high efficient solution to realize mixing small amount of regents in large volume samples in a certain order without complex moving structures and operations in a chip. Two applications of mixing with the proposed microfluidic chip are also carried out and discussed.
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