Optimization of optical properties of greenhouse particle-based spray coating configuration
Using Non-Dominated Sorting Genetic Algorithm-II in combination with Monte Carlo ray tracing
B.J.M. Slotboom (TU Delft - Applied Sciences)
E. van der Kolk – Mentor (TU Delft - Applied Sciences)
P. Dorenbos – Graduation committee member (TU Delft - Applied Sciences)
D. Lathouwers – Graduation committee member (TU Delft - Applied Sciences)
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Abstract
This study introduces a theoretical framework for assessing the impact of particle-based greenhouse spray coatings on crop yield. Greenhouses are pivotal for optimizing crop growth efficiency, and these coatings can enhance their performance. The research employs Monte Carlo ray tracing to model transmission, scattering, and luminescence processes within a coating-glass system. It investigates coatings with scattering particles (SiO2), luminescent scattering particles (SiAlO:Eu2+), and a combination of both. Key performance metrics, including hemispherical transmittance and hortiscatter, are calculated. The primary challenge is to effectively scatter incoming light while maintaining high transmission rates. Additionally, the luminescent coatings should efficiently absorb ultraviolet light without affecting photosynthetically active radiation. By utilizing the Non-dominated Sorting Algorithm II alongside Mie theory, this investigation explores the effects of varying particle size, volume mixing percentage, and coating thickness. Notably, the study identifies an optimal coating configuration that combines micrometer-sized SiO2 and nanometer-sized SiAlO:Eu2+ particles, resulting in a significant increase in crop yield (Y+ = 10.1 %). Further research is recommended to validate the crop yield formula and gain a deeper understanding of the impact of greenhouse coatings on agricultural productivity.