Study of the flow mixing in a novel ARID raceway for algae production

Xu, Ben; Li, Peiwen; Waller, P.

doi:10.1016/j.renene.2013.06.049

Title: Study of the flow mixing in a novel ARID raceway for algae production

Journal Article · Thu Jul 31 00:00:00 EDT 2014 · Renewable Energy

DOI:https://doi.org/10.1016/j.renene.2013.06.049· OSTI ID:1093709

Xu, Ben ^[1]; Li, Peiwen ^[1]; Waller, P. ^[1]

Univ. of Arizona, Tucson, AZ (United States)

A novel flow field for algae raceways has been proposed, which is fundamentally different from traditional paddlewheel-driven raceways. To reduce freezing and heat loss in the raceway during cold time, the water is drained to a deep storage canal. The ground bed of the new raceway has a low slope so that water, lifted by propeller pump, can flow down in laterally-laid serpentine channels, relying on gravitational force. The flow rate of water is controlled so that it can overflow the lateral channel walls and mix with the main flow in the next lower channel, which thus creates a better mixing. In order to optimize the design parameters of the new flow field, methods including flow visualization, local point velocity measurement, and CFD analysis were employed to investigate the flow mixing features. Different combinations of channel geometries and water velocities were evaluated. An optimized flow field design and details of flow mixing are presented. The study offers an innovative design for large scale algae growth raceways which is of significance to the algae and biofuel industry.

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Research Organization:: Univ. of Arizona, Tucson, AZ (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Technology Development (EE-20); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office

Grant/Contract Number:: EE0003046; ee0006269

OSTI ID:: 1093709

Alternate ID(s):: OSTI ID: 1592769

Report Number(s):: DOE-DANF-0003046-Q7; 28302-Q

Journal Information:: Renewable Energy, Vol. 62; ISSN 0960-1481

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 20 works

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Cited By (4)

Numerical prediction of algae cell mixing feature in raceway ponds using particle tracing methods: Numerical Prediction of Algae Cell Mixing Feature in Raceway Ali, Haider; Cheema, Taqi A.; Yoon, Ho-Sung Biotechnology and Bioengineering, Vol. 112, Issue 2 https://doi.org/10.1002/bit.25443	journal	October 2014
Evaluation of microalgae-based biorefinery alternatives Fozer, Daniel; Valentinyi, Nora; Racz, Laszlo Clean Technologies and Environmental Policy, Vol. 19, Issue 2 https://doi.org/10.1007/s10098-016-1242-8	journal	June 2016
Simulation of algal photobioreactors: recent developments and challenges Gao, Xi; Kong, Bo; Vigil, R. Dennis Biotechnology Letters, Vol. 40, Issue 9-10 https://doi.org/10.1007/s10529-018-2595-3	journal	July 2018
Quantitative Evaluation of Passive Scalar Flow Mixing - A Review of Recent Developments Xu, Ben; Li, Yuchun; Xu, Xiankun ChemBioEng Reviews, Vol. 4, Issue 2 https://doi.org/10.1002/cben.201600019	journal	March 2017

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