Estudio CFD de la obstrucción del cultivo en la uniformidad térmica de un invernadero cenital
DOI:
https://doi.org/10.65093/aci.v17.n3.2026.61Palabras clave:
simulación de invernaderos, modelado de turbulencia, obstrucción, flujo internoResumen
Este estudio aplica la técnica de CFD para evaluar la uniformidad térmica en un invernadero considerando la obstrucción espacial por el cultivo. El sistema es un invernadero cenital con cuatro escenarios de cargas de cultivo usando una geometría realista del cultivo. Las condiciones de frontera provinieron de las condiciones externas bajo la vecindad de otros invernaderos. Un análisis de independencia aplicó al escenario de carga completa y el Índice de Convergencia de Malla obtuvo para la velocidad valores de 0.01% y 1.658% en las mallas fina y gruesa, respectivamente. El análisis involucró cuatro modelos de turbulencia para describir la uniformidad térmica. Los valores de temperatura del caso de mayor cantidad de plantas fueron validados con datos experimentales (raíz cuadrada de la diferencia cuadrática media de 5.2) y alcanzaron la mayor uniformidad térmica (1.4762). El modelo de turbulencia k-ω predijo la menor uniformidad térmica en todos los escenarios. Los escenarios de carga incompleta presentan una uniformidad térmica baja con valores superiores a 1.55. Esto demuestra la importancia de operar invernaderos con cargas homogéneas de cultivo. Así, la técnica de CFD es viable para predecir una homogeneidad térmica alta usando la geometría real de los cultivos en invernaderos.
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Ali, Z., Tucker, P.G. & Shahpar, S. (2017). Optimal mesh topology generation for CFD. Computer Methods in Applied Mechanics and Engineering, 317, 431-457. https://doi.org/10.1016/j.cma.2016.12.001
Allali, F.E., Fatnassi, H., Demrati, H., Amarraque, A., Bouharroud, R., Elame, F., et al. (2026). Design and evaluation of climate-adaptive greenhouses for semi-arid regions using CFD model. Case Studies in Thermal Engineering, 78, 107648. https://doi.org/10.1016/j.csite.2026.107648
Amara, H.B., Bouadila, S., Fatnassi, H., Arici, M. & Guizani, A.A. (2021). Climate assessment of greenhouse equipped with south-oriented PV roofs: An experimental and computational fluid dynamics study. Sustainable Energy Technologies and Assessments, 45, 101100. https://doi.org/10.1016/j.seta.2021.101100
Badji, A., Benseddik, A., Bensaha, H., Boukhelifa, A. & Hasrane, I. (2022). Design, technology, and management of greenhouse: A review. Journal of Cleaner Production, 373, 133753. https://doi.org/10.1016/j.jclepro.2022.133753
Barth, T.J. & Jesperson, D.C. (1989). The design and application of upwind schemes on unstructured meshes, 27th Aerospace Sciences Meeting, AIAA, 366. https://doi.org/10.2514/6.1989-366
Bournet, P.-E. & Boulard, T. (2010). Effect of ventilator configuration on the distributed climate of greenhouses: A review of experimental and CFD studies. Computers and Electronics in Agriculture, 74 (2), 195-217. https://doi.org/10.1016/j.compag.2010.08.007
Bournet, P.-E. & Rojano, F. (2022). Advances of Computational Fluid Dynamics (CFD) applications in agricultural building modelling: Research, applications and challenges. Computers and Electronics in Agriculture, 201, 107277. https://doi.org/10.1016/j.compag.2022.107277
Celik, I., Ghia, U., Roache, P.J., Freitas, C. J., Coleman, H. & Raad, P.A. (2008). Procedure for Estimation and Reporting of Uncertainty Due to Discretization in CFD Applications. Journal of Fluids Engineering, 130 (7). https://doi.org/10.1115/1.2960953
Chalill, S.M., Chowdhury, S. & Karthikeyan, R. (2021). Prediction of key crop growth parameters in a commercial greenhouse using cfd simulation and experimental verification in a pilot study. Agriculture, 11, 658. https://doi.org/10.3390/agriculture11070658
Cheng, P. (1964). Two-dimensional radiating gas flow by a moment method. AIAA Journal, 2 (9), 1662-1664. https://doi.org/10.2514/3.2645
Dehbi, A., Bouaza, A., Hamou, A., Youssef, B. & Saiter, J.M. (2010). Artificial ageing of tri-layer polyethylene film used as greenhouse cover under the effect of the temperature and the UV-A simultaneously. Materials & Design, 31 (2), 864-869. https://doi.org/10.1016/j.matdes.2009.07.047
Emekli, N.Y., Büyüktaş, K. & Başçetinçelik, A. (2016). Changes of the light transmittance of the LDPE films during the service life for greenhouse application. Journal of Building Engineering, 6, 126-132. https://doi.org/10.1016/j.jobe.2016.02.013
Fatnassi, H., Bournet, P.E., Boulard, T., Roy, J.C., Molina-Aiz, F.D. & Zaaboul, R. (2023). Use of computational fluid dynamic tools to model the coupling of plant canopy activity and climate in greenhouses and closed plant growth systems: A review. Biosystems Engineering, 230, 388-408. https://doi.org/10.1016/j.biosystemseng.2023.04.016
Gibson, M.M. & Launder, B.E. (1978). Ground effects on pressure fluctuations in the atmospheric boundary layer. Journal of Fluid Mechanics, 86 (3), 491-511. https://doi.org/10.1017/S0022112078001251
Jin, W., Hong, X., Yang, J., Liu, Q., Li, Z., Dingm Q., et al. (2025). Development of a high-accuracy temperature sensor for meteorological observations based on computational fluid dynamics and neural networks. International Communications in Heat and Mass Transfer, 164, 108801. https://doi.org/10.1016/j.icheatmasstransfer.2025.108801
Kalbasinia, A., Jafari, M., Kouhikamali, R., Sadeghi, M., Nikbakht, A. & Tayefi, A. (2025). Application of computational fluid dynamics (CFD) for optimal temperature sensor placement in a greenhouse equipped with a pad-fan cooling (PFC) system. Smart Agricultural Technology, 12, 101109. https://doi.org/10.1016/j.atech.2025.101109
Kang, L., Zhang, Y., Kacira, M. & van Hooff, T. (2024). CFD simulation of air distributions in a small multi-layer vertical farm: Impact of computational and physical parameters. Biosystems Engineering, 243, 148-174. https://doi.org/10.1016/j.biosystemseng.2024.05.004
Kichah, A., Bournet, P.-E., Migeon, C. & Boulard, T. (2012). Measurement and CFD simulation of microclimate characteristics and transpiration of an Impatiens pot plant crop in a greenhouse. Biosystems Engineering, 112 (1), 22-34. https://doi.org/10.1016/j.biosystemseng.2012.01.012
Launder, B.E., Reece, G.J. & Rodi, W. (1975). Progress in the development of a Reynolds-stress turbulence closure. J. Fluid Mechanics, 68 (3), 537-566. https://doi.org/10.1017/S0022112075001814
Launder, B.E. & Spalding, D.B. (1974). The numerical computation of turbulent flows. Computer Methods in Applied mechanics and Engineering, 3, 269-289. https://doi.org/10.1016/0045-7825(74)90029-2
Lee, S.-h., Kim, R.-w., Shin, H. & Lee, T.-s. (2026). Dynamic energy modeling of a naturally ventilated greenhouse using TRNSYS–TRNFlow: Part II. Impact of ventilation opening ratios on energy load and uncertainty quantification. Applied Thermal Engineering, 129818. https://doi.org/10.1016/j.applthermaleng.2026.129818
Lin, Y., Patel, R., Cao, J., Tu, W., Zhang, H., et al. (2019). Glass-like transparent high strength polyethylene films by tuning drawing temperature. Polymer, 171, 180-191. https://doi.org/10.1016/j.polymer.2019.03.036
Liu, R., Bournet, P.-E., Guzmán, J. L., Tingting, Q., Li, M. & Yang, X. (2026). Variation analysis of natural ventilation and air temperature within a greenhouse cluster using a large-scale 3D CFD modelling. Computers and Electronics in Agriculture, 240, 111220. https://doi.org/10.1016/j.compag.2025.111220
Lu, J., Li, H., Wang, C., Tian, X., Song, W., Zhao, S., et al. (2025). CFD based airflow uniformity optimization of Chinese solar greenhouses with long-row cultivation: Impact of unit layout design. Case Studies in Thermal Engineering, 71, 106192. https://doi.org/10.1016/j.csite.2025.106192
Ma, J., Chai, A., Shi, F., Liu, M., Li, B. & Fan, T. (2026). CFD-guided ventilation design to suppress pathogen spread in a cucumber greenhouse. Smart Agricultural Technology, 13, 101859. https://doi.org/10.1016/j.atech.2026.101859
Mao, C. & Su, Y. (2024). CFD based heat transfer parameter identification of greenhouse and greenhouse climate prediction method. Thermal Science and Engineering Progress, 49, 102462. https://doi.org/10.1016/j.tsep.2024.102462
Menter, F.R. (1994). Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal, 32 (8), 1598-1605. https://doi.org/10.2514/3.12149
Mistriotis, A., de Jong, T., Wagemans, M. & Bot, G.P.A. (1997). The analysis of ventilation and indoor microclimate in agricultural buildings by Computational Fluid Dynamics (CFD). IFAC Proceedings Volumes, 30 (5), 289-295. https://doi.org/10.1016/S1474-6670(17)44447-8
Modest, M.F. (2013). Radiative Heat Transfer, 3rd Ed., Academic Press, Boston, MA.
Norton, T., Sun, D.-W., Grant, J., Fallon, R. & Dodd, V. (2007). Applications of computational fluid dynamics (CFD) in the modelling and design of ventilation systems in the agricultural industry: A review. Bioresource technology, 98 (12), 2386-2414. https://doi.org/10.1016/j.biortech.2006.11.025
Qi, D., Wang, H., Zhao, C., Xu, L., Song, B. & Li, A. (2026). Airflow and pressure characteristics of naturally ventilated greenhouses with roof openings. Applied Thermal Engineering, 290, 129888. https://doi.org/10.1016/j.applthermaleng.2026.129888
Richards, P.J. & Hoxey, R.P. (1993). Appropriate boundary conditions for computational wind engineering models using the k-ϵ turbulence model. Journal of Wind Engineering and Industrial Aerodynamics, 46-47, 145-153. https://doi.org/10.1016/0167-6105(93)90124-7
Rodriguez, S. (2019). Applied Computational Fluid Dynamics and turbulence modeling, Springer-Verlag.
Roy, J.C., Bourland, T., Kittas, C. & Wang, S. (2002). Convective and ventilation transfers in greenhouses, Part 1: the greenhouse considered as a perfectly stirred tank. Biosystems Engineering, 83 (1), 1. https://doi.org/10.1006/bioc.2002.0107
Shih, T.-H., Liou, W.W., Shabbir, A., Yang, Z. & Zhu, J. (1995). A new eddy-viscosity model for high Reynolds number turbulent flows- Model development and validation. Computers Fluids, 24 (3), 227-238. https://doi.org/10.1016/0045-7930(94)00032-T
Smolka, J. (2013). Genetic algorithm shape optimisation of a natural air circulation heating oven based on an experimentally validated 3-D CFD model. International Journal of Thermal Sciences, 71, 128-139. http:// doi.org/10.1016/j.ijthermalsci.2013.04.014
Song, M., Li, C., Guo, X. & Liu, J. (2025). An adaptive gradient correction method based on mesh skewness for finite volume fluid dynamics simulations. Physics of Fluids, 37 (1). https://doi.org/10.1063/5.0246823
Speziale, C.G., Sarkar, S. & Gatski, T.B. (1991). Modelling the pressure–strain correlation of turbulence: an invariant dynamical systems approach. Journal of Fluid Mechanics, 227, 245-272. https://doi.org/10.1017/S0022112091000101
Sun, H., Qi, Z., Zhang, Q., Xu, Z., Zheng, W., Wei, M., et al. (2026). Thermal and ventilation performance of the innovative asymmetrical flexible wall greenhouse for annual usage. Applied Thermal Engineering, 289, 129969. https://doi.org/10.1016/j.applthermaleng.2026.129969
Wilcox, D.C. (1988). Multiscale model for turbulent flows. AIAA Journal, 26 (11), 1311-1320 https://doi.org/10.2514/3.10042
Wilcox, D.C. (2006). Turbulence Modeling for CFD, DCW Industries Inc.
Xu, D., Zhu, J. & Ma, Y. (2026). Advances in 3D simulation technology for solar greenhouse systems: A review. Renewable and Sustainable Energy Reviews, 226, 116387. https://doi.org/10.1016/j.rser.2025.116387
Xu, F.-y., Lu, H.-f., Chen, Z., Guan, Z.-c., Chen, Y.-w., Shen, G-w., et al. (2021). Selection of a computational fluid dynamics (CFD) model and its application to greenhouse pad-fan cooling (PFC) systems. Journal of Cleaner Production, 302, 127013. https://doi.org/10.1016/j.jclepro.2021.127013
Yeoh, G.-H. & Tu, J. (2010). Computational techniques for multi-phase flows, Butterworth-Heinemann.
Zghal, O., Ketata, A., Abid, H., Zouari, S., Gugliuzza, G., Mejri, M., et al. (2025). Numerical investigation of CFD parameters: Evaluating height variations on microclimate and crop performance in large-scale soilless greenhouses in northern Tunisia. Journal of Engineering Research. https://doi.org/10.1016/j.jer.2025.02.006
Zhang, C., Liu, R., Yang, J., Díaz, F.R. & Li, M. (2025). Assessing the impact of tomato crop row orientation on the microclimate in Chinese solar greenhouses: CFD simulation and numerical analysis. Biosystems Engineering, 258, 104247. https://doi.org/10.1016/j.biosystemseng.2025.104247
Zhang, C., Liu, R., Liu, K., Yang, X., Liu, H., et al. (2022a). A CFD transient model of leaf wetness duration on greenhouse cucumber leaves. Computers and Electronics in Agriculture, 200, 107257. https://doi.org/10.1016/j.compag.2022.107257
Zhang, Y., Yasutake, D., Hidaka, K., Okayasu, T., Kitano, M., et al. (2022b). Crop-localised CO2 enrichment improves the microclimate, photosynthetic distribution and energy utilisation efficiency in a greenhouse. Journal of Cleaner Production, 371, 133465. https://doi.org/10.1016/j.jclepro.2022.133465
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