Integration of Biological Kinetics and Computational Fluid Dynamics to Model the Growth of Nannochloropsis salina in an Open Channel Raceway

Microalgal growth and systemic productivity is not only affected by environmental conditions such as temperature, irradiance, and nutrient concentrations, but also by physical processes such as fluid flow and particulate sedimentation. Modeling and simulating the system is a cost-effective way to predict the growth behavior under various environmental and physical conditions while determining effective engineering approaches to maximize productivity. Many mathematical models have been proposed to describe microalgal growth, while computational fluid dynamics (CFD) have been used to model the behavior of many fluid systems. Integrating the growth kinetics into a CFD model can help researchers understand the impact of a variety of parameters and determine what measures can be taken to overcome some obstacles in the aquaculture industry - self-shading, biomass sedimentation, and contamination - which prevent the production of high biomass yields. The aim of this study was to integrate physical and environmental effects to predict space- and time-dependent algal growth in industrial scale raceways. A commercial CFD software, ANSYS-Fluent 14.5, was used to solve the proposed models in regards to fluid flow, heat transfer, and nutrient balance. User-defined functions written in C language were used to incorporate the kinetic equations into a three-dimensional standard k-epsilon turbulence model of an open channel raceway system driven by a single paddlewheel. Simulated results were compared with light intensity, temperature, nutrient concentration, and algal biomass data acquired for 56day from an industrial scale raceway pond constructed for the growth of Nannochloropsis salina and were observed to be in good agreement with one another. There was up to a 17.6% increase in simulated productivity when the incoming CO2 concentration was increased from 0.0006 to 0.150gL(-1), while the effect of paddlewheel velocity was not significant. Sensitivity analysis showed that the model was particularly sensitive to the species-specific maximum growth rate, light attenuation coefficient, optimal growth temperature, half-saturation constant for growth based on irradiance, and death coefficient. Biotechnol. Bioeng. 2015;112: 923-933. (c) 2014 Wiley Periodicals, Inc.