2026-09-21T20:46:14Zhttps://api.mountainscholar.org/server/oai/requestoai:mountainscholar.org:10217/1856862025-12-30T03:20:12Zcom_10217_100532com_10217_100000com_10217_100470com_10217_100303col_10217_100538col_10217_100472
Compton, Samuel Lighthall, author
Quinn, Jason C., advisor
Marchese, Anthony, committee member
Peers, Graham, committee member
2018-01-17T16:45:45Z
2018-01-17T16:45:45Z
2017
Compton_colostate_0053N_14504.pdf
https://hdl.handle.net/10217/185686
https://doi.org/10.25675/3.018476
Proper assessment of the sustainability of algal products is constrained by the onerous process of pilot-scale experimental study. This study developed a bulk growth model that utilizes strain characterization, geospatial data, and cultivation platform geometry to predict productivity across different outdoor systems. The model interprets a minimum of measureable algal strain characteristics along with characteristics of the growth architecture to calculate a time-resolved algal concentration. Validation of the model illustrates an average accuracy of 7.33%+/5.65% for photobioreactors (PBR) and 6.7%+/5.33% for an open raceway pond (ORP) across five total species: Chlorella vulgaris, Desmodesmus intermedius, Galdieria sulphuraria, Galdieria sulphuraria Soos, and Nannochloropsis oceanica. The validated model assesses productivity at several locations in the United States with Chlorella vulgaris, grown in open raceway ponds and Galdieria sulphuraria grown in vertical flat panel photobioreactors. The model investigates seasonal variability through geospatially and temporally resolved extrapolation.
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masters theses
English
eng
Colorado State University. Libraries
2000-2019
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biofuel
dynamic
algae
model
biomass
A dynamic engineering model of algal cultivation systems
Text
Master of Science (M.S.)
Masters
Mechanical Engineering
Colorado State University
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open.access