Integration of biological kinetics and computational fluid dynamics to model the growth of Nannochloropsis salina in an open channel raceway
Abstract
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-ε 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 56 day 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 0.150 g L(-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.
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One can mainly distinguish between two approaches for light transfer modeling: one-dimensional model equations and the Radiative Transfer Equation (RTE).
“One can mainly distinguish between two approaches: firstly, one-dimensional model equations which enable quick and simple estimates of the light intensity with respect to the distance from the light source [23,24,31,36,39,41,43,125] and secondly, the Radiative Transfer Equation (RTE) [18,26-28,34], whose solution requires the application of numerical methods.”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [43]
A number of different turbulence models were employed by researchers: the k-ε model, the RNG k-ε model, the realizable k-ε model, and the k-ω models are the most commonly used ones.
“According to Table 1, a number of different turbulence models were employed by researcher: the k -# model [32,33,43], the RNG k -# model [22], the realizable k -# model [35], and the k -w models [22,33] are the most commonly used ones.”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [43]
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- Authors
- Park, S., & Li, Y.
- Affiliations
- The Ohio State University (US)
- Corresponding author
- Li, Yebo
- ORCID
- Li, Yebo
- Venue
- Biotechnology and Bioengineering
- Publisher
- Wiley
- Published
- 2015-03-13
- Volume
- 112
- Issue
- 5
- Pages
- 923-933
- ISSN
- 0006-3592 (ISSN-L)
- 1097-0290
- OpenAlex
- W2136252690
- Cited by
- 44
- References
- 35
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 5 · 2023: 4 · 2022: 2 · 2021: 3 · 2020: 7 · 2019: 4 · 2018: 4 · 2017: 5 · 2016: 4
- FWCI
- 0.99
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biotechnology and Bioengineering (publishedVersion)
- PubMed (publishedVersion)
- Funders
- US Department of Energy (DE-FE0002546)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
- Physical Sciences › Environmental Science › Environmental Chemistry › Aquatic Ecosystems and Phytoplankton Dynamics
- Keywords
- Nannochloropsis salina, microalgal growth kinetics, raceway ponds, computational fluid dynamics, self-shading, CO2 concentration, light attenuation, heat transfer, nutrient balance, microalgae productivity, sensitivity analysis, k-epsilon turbulence model
- MeSH terms
- Computer Simulation, Kinetics, Models, Biological, Temperature, Biomass, Hydrodynamics, Stramenopiles, Microalgae
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