Evaluation of a photobioreactor performance grafting microalgal growth model and particle tracking technique using CFD

Biodiesel production from microalgae is a novel green technology designed to cope with fossil fuel depletion and climate change. Photobioreactors (PBRs) have been used to maintain optimum culture conditions for microalgae, including light, temperature, CO2, and nutrients, to produce a stable year-round biomass yield. To design a good PBR, the techniques of computational fluid dynamics (CFD) have been actively used to overcome limitations related to measurements and field experiments. In this study, a biomass production prediction grafting mixing and growth (BPMG) model was developed and used for quantitative comparison of the biomass productivity between different PBR designs by combining statistical analysis of hydrological particle movement using CFD and a microalgal growth model related to light intensity. A CFD model of a 20 L PBR was designed and validated using particle image velocimetry (PIV) under the same operating conditions. The vector fields showed applicable similarities between the measured PIV and the CFD-computed flow pattern, with 0.044 m s-1 average error. The biomass productivity was calculated using the BPMG model with various PBR designs to consider practical improvements, such as bubble injection and internal baffles to guide fluid circulation. In the CFD computation, the maximum improvement was 88.0% for a plate PBR with eight uniform bubble injections and an internal baffle. Culture experiments with Chlorella vulgaris were conducted to compare the performance of four cylinder and plate type PBRs before and after improvements. After modifying the PBR design, the cell concentration was improved by a maximum of 88.7% (59.4% to 144% during five successive culture experiments) using a modified plate PBR in comparison to a basic cylindrical PBR.