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Article Dans Une Revue Algal Research - Biomass, Biofuels and Bioproducts Année : 2021

A numerical framework to predict the performances of a tubular photobioreactor from operating and sunlight conditions

Résumé

A framework model is proposed to evaluate the actual overall growth rate of microalgae in an outdoor tubular photobioreactor. A Monte Carlo-based radiative transfer modeling approach describes the local distribution of light energy inside the broth as a function of static (reactor geometry, location) and dynamic solar radiation parameters (angle of incidence, direct and diffuse solar contribution, incident radiation intensity). The light fields are coupled to a Lagrangian discrete random walk tracking of the cells to give the light variations experienced by each microalga for different broth flow rates. The cell light experiments are combined with a dynamic biological model to statistically calculate the actual overall growth rate. Using this model, 380 numerical experiments were performed for a wide range of geographic, light, biomass concentration, and broth flow turbulence conditions. Correlations for a normalized growth rate, Gamma, relating the actual overall growth rate to its asymptotic behaviors (i.e., the instantaneous response and the full integration response), are proposed. The results clearly show that, for a fixed broth flowrate, Gamma does not change with cell concentration variation. Under given light conditions, the level of turbulence linearly manages Gamma, and thus the efficiency of sunlight utilization by the photobioreactor biomass can be tuned by the broth flow rate in the tubular photobioreactor. Gamma also increases linearly with the diffuse fraction of solar radiation. A simple correlation is proposed for fast calculation of the actual overall growth rate.
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hal-03494613 , version 1 (05-01-2024)

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Ryma Laifa, Jérôme Morchain, L. Tiruta-Barna, Pascal Guiraud. A numerical framework to predict the performances of a tubular photobioreactor from operating and sunlight conditions. Algal Research - Biomass, Biofuels and Bioproducts, 2021, 60, ⟨10.1016/j.algal.2021.102550⟩. ⟨hal-03494613⟩
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