Experimental and Numerical Investigations on the Flow Characteristics within Hydrodynamic Entrance Regions in Microchannels.

Clicks: 153
ID: 22735
2019
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Flow characteristics within entrance regions in microchannels are important due to their effect on heat and mass transfer. However, relevant research is limited and some conclusions are controversial. In order to reveal flow characteristics within entrance regions and to provide empiric correlation estimating hydrodynamic entrance length, experimental and numerical investigations were conducted in microchannels with square cross-sections. The inlet configuration was elaborately designed in a more common pattern for microdevices to diminish errors caused by separation flow near the inlet and fabrication faults so that conclusions which were more applicable to microchannels could be drawn. Three different microchannels with hydraulic diameters of 100 μm, 150 μm, and 200 μm were investigated with Reynolds (Re) number ranging from 0.5 to 50. For the experiment, deionized water was chosen as the working fluid and microscopic particle image velocimetry (micro-PIV) was adopted to record and analyze velocity profiles. For numerical simulation, the test-sections were modeled and incompressible laminar Navier-Stokes equations were solved with commercial software. Strong agreement was achieved between the experimental data and the simulated data. According to the results of both the experiments and the simulations, new correlations were proposed to estimate entrance length. Re numbers ranging from 12.5 to 15 was considered as the transition region where the relationship between entrance length and Re number converted. For the microchannels and the Reynolds number range investigated compared with correlations for conventional channels, noticeable deviation was observed for lower Re numbers ( < 12.5) and strong agreement was found for higher Re numbers ( > 15).
Reference Key
li2019experimentalmicromachines Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Li, Haiwang;Huang, Binghuan;Wu, Min;
Journal micromachines
Year 2019
DOI
E317
URL
Keywords
genotyping rapd aflp daktulosphaira vitifoliae mtdna sequencing induced resistance wgcna nematode–rice interactions rice cell suspension cultures Machine learning feature selection sensor svm accelerometer gyroscope human activity recognition (har) thoroughbred racehorses biomolecular changes immunological adaptations long-term training metabolic modifications sprint exercise medicinal plant rehmannia glutinosa (gaertn.) dc drug equivalence validation field productivity

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.