Modeling and optimization of algae growth

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Thornton, Anthony and Weinhart, Thomas and Bokhove, Onno and Zhang, Bowen and Sar, Dick M. van der and Kumar, Kundan and Pisarenco, Maxim and Rudnaya, Maria and Savcenco, Valeriu and Rademacher, Jens and Zijlstra, Julia and Szabelska, Alicja and Zyprych, Joanna and Schans, Martin van der and Timperio, Vincent and Veerman, Frits (2010) Modeling and optimization of algae growth. [Report]

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Abstract:The wastewater from greenhouses has a high amount of mineral contamination
and an environmentally-friendly method of removal is to use algae
to clean this runoff water. The algae consume the minerals as part of their
growth process. In addition to cleaning the water, the created algal bio-mass
has a variety of applications including production of bio-diesel, animal feed,
products for pharmaceutical and cosmetic purposes, or it can even be used as
a source of heating or electricity .
The aim of this paper is to develop a model of algae production and use
this model to investigate how best to optimize algae farms to satisfy the dual
goals of maximizing growth and removing mineral contaminants.
With this aim in mind the paper is split into five main sections. In the
first a review of the biological literature is undertaken with the aim of determining
what factors effect the growth of algae. The second section contains
a review of exciting mathematical models from the literature, and for
each model a steady-state analysis is performed. Moreover, for each model
the strengths and weaknesses are discussed in detail. In the third section,a new two-stage model for algae production is proposed, careful estimation
of parameters is undertaken and numerical solutions are presented. In the
next section, a new one-dimensional spatial-temporal model is presented,
numerically solved and optimization strategies are discussed. Finally, these
elements are brought together and recommendations of how to continue are
drawn.
Item Type:Report
Additional information:
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/73345
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