Loading…

Experimental and modelling of Arthrospira platensis cultivation in open raceway ponds

•Arthrospira platensis cultivation in the open raceway pond was studied by both experimental and modelling methods.•Dynamic modelling of algae growth was developed and validated.•CFD modelling of raceway ponds for hydrodynamics and residence time distribution was investigated.•Modelling tools can be...

Full description

Saved in:
Bibliographic Details
Published in:Bioresource technology 2017-10, Vol.242, p.197-205
Main Authors: Ranganathan, Panneerselvam, Amal, J.C., Savithri, S., Haridas, Ajith
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Arthrospira platensis cultivation in the open raceway pond was studied by both experimental and modelling methods.•Dynamic modelling of algae growth was developed and validated.•CFD modelling of raceway ponds for hydrodynamics and residence time distribution was investigated.•Modelling tools can be applied to design and scale-up of large scale cultivation. In this study, the growth of Arthrospira platensis was studied in an open raceway pond. Furthermore, dynamic model for algae growth and CFD modelling of hydrodynamics in open raceway pond were developed. The dynamic behaviour of the algal system was developed by solving mass balance equations of various components, considering light intensity and gas-liquid mass transfer. A CFD modelling of the hydrodynamics of open raceway pond was developed by solving mass and momentum balance equations of the liquid medium. The prediction of algae concentration from the dynamic model was compared with the experimental data. The hydrodynamic behaviour of the open raceway pond was compared with the literature data for model validation. The model predictions match the experimental findings. Furthermore, the hydrodynamic behaviour and residence time distribution in our small raceway pond were predicted. These models can serve as a tool to assess the pond performance criteria.
ISSN:0960-8524
1873-2976
DOI:10.1016/j.biortech.2017.03.150