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Validation of an adaptive temperature model for closed microalgae cultivation systems
Accurate temperature prediction plays a crucial role in optimizing microalgae growth conditions. For that, we recently developed a generic adaptive temperature prediction model, called the Simplified Auto Tuning Heat Exchange (SATHE) model, which was initially tailored to open raceway ponds. In this...
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Published in: | Algal research (Amsterdam) 2025-01, p.103838, Article 103838 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Accurate temperature prediction plays a crucial role in optimizing microalgae growth conditions. For that, we recently developed a generic adaptive temperature prediction model, called the Simplified Auto Tuning Heat Exchange (SATHE) model, which was initially tailored to open raceway ponds. In this study, we adapt and validate the SATHE model specifically for the case of closed reactors. We assess two distinct closed reactor types across different geographical locations: a tubular photobioreactor situated in a greenhouse in Wageningen (Netherlands) and a flat panel reactor on Bonaire, a Caribbean island in the Lesser Antilles. Finally, we discuss the practical applications of our model. We test the reactors' performance in different geographical settings and assess energy consumption under varied meteorological conditions. This paper highlights the versatile model's potential for optimizing closed-reactor operation and thermal management in various geographical locations.
•Achieve precise microalgae system temperature predictions inside closed reactors with an adaptable reduced-model.•Validating the SATHE-model's on predicting the temperature on closed systems.•Demonstrating the model's adaptability and improved accuracy through seasonal recalibration across different reactor configurations and sizes.•Showcasing the model's utility for simulating scenarios under different weather conditions and energy consumptions. |
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ISSN: | 2211-9264 2211-9264 |
DOI: | 10.1016/j.algal.2024.103838 |