Simulations of light intensity variation in photobioreactors
Abstract
In photobioreactors, turbulent flow conditions and light gradients frequently occur. Thus, algal cells cultivated in such reactors experience fluctuations in light intensity. This work presents a new method for the calculation of these light-dark patterns. The investigation is focused on temporal and spatial aspects of light patterns which may affect the photosynthetic reaction. The method combines computational fluid dynamics simulations of three-dimensional turbulent single-phase fluid flow with statistical particle tracking and signal analysis. In this way, light-dark phases are derived which affect singular (algal) cells. An example case is presented of a tubular photobioreactor in which static mixers are used for the efficient mixing of liquid and also of gases with liquid. Particle trajectories representing the path of algal cells were analysed to obtain light fluctuations on single cells. Particles were exposed to light-dark phases with frequencies between 3 and 25Hz in a helical mixer at a mean velocity of 0.5ms(-1), which contrasts to the case of a tube without static mixers, where only frequencies of 0.2-3.1Hz were obtained under the same conditions. The simulations show the potential of improving radial flow in a tubular photobioreactor by means of using a static mixer and the usefulness of CFD and trajectory analysis for scale-down/scale-up.
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The purpose of the listed models covers a variety of applications, including mechanistic understanding, investigations on flashing-light effect, design optimization, and optimization of operating conditions.
“The purpose of the listed models covers a variety of applications, including the mechanistic understanding of photobioreactors [17-21], investigations on the flashing-light effect [22-31], photobioreactor design optimization [21,22,29,32-42] and optimization of operating conditions [26,34-36,43-45].”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [24]
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 [24]
The situation is different for cells since their presence has a negligible effect on the liquid flow so that a manageable number of cells as representatives of the culture can be included in a simulation model.
“The situation is different for cells since their presence has an negligible effect on the liquid flow so that a manageable number of cells as representatives of the culture can be included in a simulation model [24,26].”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [24]
Microalgae cells are mostly modeled as discrete objects in photobioreactor CFD models.
“In contrast, microalgae cells are mostly modeled as discrete objects [23,24,26-29,31,34,36-38,136].”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [24]
As recent developments in photobioreactor technology include complex geometries with static mixers or internal light sources, employing the full RTE for light transfer calculations becomes increasingly important.
“As recent developments in photobioreactor technology include complex geometries with static mixers [24,36] or internal light sources [21,214], employing the full RTE for light transfer calculations becomes increasingly important.”
From Modeling and Simulation of Photobioreactors with Computational Fluid Dynamics—A Comprehensive Review (2022) · cites this paper as [24]
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- Authors
- Perner-Nochta, I., & Posten, C.
- Affiliations
- Karlsruhe Institute of Technology (DE)
- Corresponding author
- Perner-Nochta, Iris
- Venue
- Journal of Biotechnology
- Publisher
- Elsevier BV
- Published
- 2007-09
- Volume
- 131
- Issue
- 3
- Pages
- 276-285
- ISSN
- 0168-1656 (ISSN-L)
- OpenAlex
- W2072963788
- Cited by
- 202
- References
- 41
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 7 · 2023: 8 · 2022: 7 · 2021: 14 · 2020: 17 · 2019: 13 · 2018: 10 · 2017: 15 · 2016: 9 · 2015: 19 · 2014: 11 · 2013: 15 · 2012: 15
- FWCI
- 4.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Greenhouse Technology and Climate Control
- Keywords
- photobioreactors, fluctuating light, light-dark cycle, turbulent flow, algal cells, particle tracking, static mixer, tubular photobioreactor, radial flow, photosynthesis, scale-up, scale-down
- MeSH terms
- Computer Simulation, Equipment Design, Light, Lighting, Models, Theoretical, Nephelometry and Turbidimetry, Radiometry, Refractometry, Scattering, Radiation, Photobiology, Bioreactors, Equipment Failure Analysis, Microfluidics
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