A computational fluid dynamics model of algal growth: Development and validation

Biofuels derived from algae are becoming an increasingly viable alternative to petroleum-based fuels; however, research and development in the field must continue to advance the technology before biofuels can be produced in an economical and environmentally friendly manner. Unlike with photobioreactors, there is no generally accepted model for evaluating the growth of algae in open raceways because algal growth involves a large number of variables. For this reason, computational fluid dynamics (CFD) could prove to be a valuable and effective tool for the design, optimization, and operation of large-scale raceway ponds under local environmental conditions. CFD can elucidate and quantify the complex sets of variables that govern heat, mass, and flow patterns within the pond and provide spatiotemporal data concerning algal concentration and other water quality variables, such as light and temperature. The corresponding outcomes will enable designers to create more efficient ponds and more accurately predict growth under a variety of scenarios, as well as optimize the pond's operation in order to produce the maximum amount of biomass possible within a given locality. The present study focuses on developing user-defined functions capable of capturing key parameters, verifying the CFD outcomes against existing experimental data, providing computational solutions, and assessing the sensitivity of the model.