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Numerical prediction of algae cell mixing feature in raceway ponds using particle tracing methods

doi: 10.1002/bit.25443
pmid: 25163842
ABSTRACTIn the present study, a novel technique, which involves numerical computation of the mixing length of algae particles in raceway ponds, was used to evaluate the mixing process. A value of mixing length that is higher than the maximum streamwise distance (MSD) of algae cells indicates that the cells experienced an adequate turbulent mixing in the pond. A coupling methodology was adapted to map the pulsating effects of a 2D paddle wheel on a 3D raceway pond in this study. The turbulent mixing was examined based on the computations of mixing length, residence time, and algae cell distribution in the pond. The results revealed that the use of particle tracing methodology is an improved approach to define the mixing phenomenon more effectively. Moreover, the algae cell distribution aided in identifying the degree of mixing in terms of mixing length and residence time. Biotechnol. Bioeng. 2015;112: 297–307. © 2014 Wiley Periodicals, Inc.
- Kyungpook National University Korea (Republic of)
- Kyungpook National University Korea (Republic of)
Cell Culture Techniques, Microalgae, Computer Simulation
Cell Culture Techniques, Microalgae, Computer Simulation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
