Transport processes in low turbulence flows associated with enclosing hoods

Karaismail, Ertan

doi:10.33915/etd.3035

Cited by 1 publication

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As can be seen in Figure B analysis to address this discrepancy is not undertaken owing to being beyond the scope of the current study. Nevertheless, interested readers are encouraged to consider sources [23], [24], and [25].…”

Section: Using the Dream ® Codementioning

confidence: 99%

“…The DREAM ® code has been verified; see sources [24] and [23]. The Implicit Turbulence Model (ITM) method allows for DREAM ® to perform very wellin being able to simulate flow for varying geometries; see source [25]. The code was written in FORTRAN ® with precise, accurate descriptions regarding the subroutines included in the implementation; a short summary is presented here for the reader's conveniencesee Table B-1.…”

Section: Appendix a : Solving Diffusion Equation Numericallymentioning

confidence: 99%

“…The current author is not yet up-to-par with all the intricacies involved in the code and is only familiar with manipulating basic functionalities to suite the relevant geometric boundaries. For further information the reader may refer to sources [24], [25] and [26].…”

Section: Appendix a : Solving Diffusion Equation Numericallymentioning

confidence: 99%

See 2 more Smart Citations

Quantification of Mixing in Microchannels

Manickam¹

View full text Add to dashboard Cite

Microchannels are used for delivery of two-or more fluids for multiple purposes, such as drug delivery, where good mixing is desired in a very short time (or distance). For this purpose, many design options are being proposed in the literature. For example herringbone baffles at the bottom of a rectangular channel are commonly proposed to enhance mixing in a drug delivery device. To assess the effectiveness of such devices many experiments need to be performed thus increasing the design cycle time and the cost involved. Computational fluid dynamics (CFD) can and is being used to shorten this design cycle by performing parametric analysis; however, due to numerical errors it is also necessary to verify and then validate the numerical models to ensure that the predictions are indeed accurate. In this study a recently developed microchannel is analyzed using CFD to determine its mixing effectiveness. There are two common ways of assessing the degree of mixing: (a) via calculation of a passive scalar transport equation, (b) by following fluid particle trajectories and calculating the statistics. The first approach suffers from presence of numerical diffusion. The second approach is usually used to only obtain qualitative information rather than quantitative assessment. In this study we explore both approaches and reconcile both of these in terms of extracting quantitative information. Furthermore we assess the results of simulations using both approaches to determine a mixing index that provides directly a measure of mixing quality.

show abstract

Section: Using the Dream ® Codementioning

confidence: 99%

Section: Appendix a : Solving Diffusion Equation Numericallymentioning

confidence: 99%