https://doi.org/10.4081/jae.2023.1384
Design and experiment of Internet-of-Things cooling system in glass greenhouse based on computational fluid dynamics simulation
Published: 25 July 2022
Abstract Views: 1870
PDF: 653
HTML: 29
HTML: 29
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
In the summer heat season, the performance of the greenhouse cooling system is the key factor in greenhouse crop pollination and fruit formation. Scientific design of greenhouse cooling systems and intelligent control of cooling equipment can ensure the normal growth of greenhouse crops and save energy. In this paper, the thermal equilibrium theory of the greenhouse is analysed, and the glass greenhouse thermal environment model is established based on the theory of engineering thermophysics combined with greenhouse environmental regulation. This study uses computational fluid dynamics simulation technology to simulate the change of the greenhouse temperature field, perform experimental analysis, and scientifically design an intelligent greenhouse temperature control cooling system. It provides a reference for designing an internet of things cooling system in a glass greenhouse in theoretical analysis and engineering practice.
Benni S., Tassinari P., Bonora F., Barbaresi A., Torreggiani D. 2016. Efficacy of greenhouse natural ventilation: Environmental monitoring and CFD simulations of a study case. Energy. Build. 125:276-286.
DOI: https://doi.org/10.1016/j.enbuild.2016.05.014
Boulard T., Roy J. C., Fatnassi H., Kichah A., Lee I. B. 2010. Computer fluid dynamics prediction of climate and fungal spore transfer in a rose greenhouse. Comput. Electron. Agric. 74:280-292.
DOI: https://doi.org/10.1016/j.compag.2010.09.003
Boulard T., Roy J. C., Pouillard J. B., Fatnassi H., Grisey A. 2017. Modelling of micrometeorology, canopy transpiration and photosynthesis in a closed greenhouse using computational fluid dynamics. Biosyst. Eng. 158:110-133.
DOI: https://doi.org/10.1016/j.biosystemseng.2017.04.001
Bournet P. E., Boulard T. 2010. Effect of ventilator configuration on the distributed climate of greenhouses: A review of experimental and CFD studies. Comput. Electron. Agric. 74:195-217.
DOI: https://doi.org/10.1016/j.compag.2010.08.007
Cheng X. H., Mao H. P., Ni J. 2011. Numerical prediction and CFD modeling of relative humidity and temperature for greenhouse-crops system. Trans. Chin. Soc. Agric. Mach. 42:173-179+157.
Chen Y. W. 2018. Study on optimization of CFD simulation of energy-saving cooling by South China-Styled Multi-Span Greenhouse. South China Agricultural University.
Dong X. Y. 2019. Characteristic analysis and CFD model establishment of different external thermal insulation cover materials in solar greenhouse. Shenyang Agricultural University.
Enrica S., Beatrice P., Paolo G., Marco B., Daniele T., Patrizia T. 2022. Analysis of the effects of shading screens on the microclimate of greenhouses and glass facade buildings. Build. Environ. 211.
DOI: https://doi.org/10.1016/j.buildenv.2021.108691
Franco A., Valera D. L., Pena A., Perez A. M. 2011. Aerodynamic analysis and CFD simulation of several cellulose evaporative cooling pads used in Mediterranean greenhouses. Comput. Electron. Agric. 76:218-230.
DOI: https://doi.org/10.1016/j.compag.2011.01.019
Ghoulem M., Moueddeb K. E., Nehdi E., Boukhanouf R., Calautit J. K. 2019. Greenhouse design and cooling technologies for sustainable food cultivation in hot climates: Review of current practice and future status. Biosyst. Eng. 183:121-150.
DOI: https://doi.org/10.1016/j.biosystemseng.2019.04.016
Ghoulem M., Moueddeb K. E., Nehdi E., Zhong F. L., Calautit J. 2020. Analysis of passive downdraught evaporative cooling windcatcher for greenhouses in hot climatic conditions: Parametric study and impact of neighbouring structures. Biosyst. Eng. 197:105-121.
DOI: https://doi.org/10.1016/j.biosystemseng.2020.06.016
Huang Q. F., Zhao Y. 2013. A simulation on temperature field and dynamic characters of a forced ventilated greenhouse in summer. Journal of Agricultural Mechanization Research. 35:30-33.
Hu J. 2020. Application of CFD numerical simulation technology in greenhouse environmental factor regulation. Agr. Eng. 10:43-48.
Jia H. M., Han J. C., Zhang S., Sun K. J., Li Y. 2019. Numerical analysis simulation and optimization of the environment in glass greenhouse based on CFD. Appl. Sci. Technol. 46:28-33.
Li L. L., Wang X. Z., Hong Y. J., Lu Q., Chen J. 2019. Analysis of canopy radiation and temperature field in greenhouse under different shading conditions based on CFD. Journal of Agricultural Mechanization Research. 41:192-197.
Liu J., Cui T., Wang C. D., Li X., Ma C. W., Zhang T. Z. 2018. Cooling technology of multi-span greenhouse in summer. Journal of Agricultural Mechanization Research. 40:262-268.
Liu Y. J., Xu J. T., Pang S. R., Sun Z. P., Li T. L. 2019. Design of positive-pressure wet curtain fan system for solar greenhouse and its cooling effects. J. China Agric. Univ. 24:130-139.
Ma L. 2020. Research on CFD temperature simulation model of solar greenhouse based on tomato group effect. Shenyang Agricultural University.
Ren S. G., Yang W., Wang H. Y., Xue W., Xu H. L., Xiong Y. J. 2015. Prediction model on temporal and spatial variation of air temperature in greenhouse and ventilation control measures based on CFD. Trans. Chin. Soc. Agric. Eng. 31:207-214.
Sun W. T., Zhou B., Xu F., Shang C., Lu C. G., Gou W. Z. 2019. Performance of positive pressure fan-pad cooling system and cooling load model for Chinese solar greenhouse. Trans. Chin. Soc. Agric. Eng. 35:214-224.
Wu C. R., Cheng R. F., Fang H., Yang Q. C., Zhang C. 2021. Simulation and optimization of air tube ventilation in plant factory based on CFD. J. China Agric. Univ. 26:78-87.
Xu D. 2017. Application of dutch large glass greenhouse technology in China. Agricultural Engineering Technology. 37:28-30.
Xu F., Cai Y. W., Chen J. L., Zhang L. B. 2015. Temperature/flow field simulation and parameter optimal design for greenhouses with fan-pad evaporative cooling system. Trans. Chin. Soc. Agric. Eng. 31:201-208.
Xu J., Li Y., Wang R. Z., Liu W., Zhou P. 2015. Experimental performance of evaporative cooling pad systems in greenhouses in humid subtropical climates. Appl. Energy. 138: 291-301.
DOI: https://doi.org/10.1016/j.apenergy.2014.10.061
Yan L. L. 2020. Effects of different natural ventilation methods on Solar Greenhouse environment and tomato growth. Northwest A＆F University.
Zhao C., Tan H. W., Shi H. F. 2011. Cooling performance of evaporative cooling pad-fan unit in greenhouse in hot and humid environment. Heating Ventilating & Air Conditioning. 41:108-112.
Zhou Z. C., Zhao J., Li X. G., Wang W. S. Dong W., Lan L. B. 2018. Experimental study of summer cooling in semi-closed greenhouse. Agr. Eng. 8:46-49.
How to Cite
Zhu, Z., Li, Y. and Gong, S. (2022) “Design and experiment of Internet-of-Things cooling system in glass greenhouse based on computational fluid dynamics simulation”, Journal of Agricultural Engineering, 54(3). doi: 10.4081/jae.2023.1384.
Copyright (c) 2023 the Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
Similar Articles
- Alina Evelyn Badillo-Márquez, Jonathan J. Cid-Galiot, Rubén Posada-Gómez, Alberto Alfonso Aguilar-Lasserre, Automated system for the detection of risk in agricultural sugarcane harvesting using digital image processing and deep learning , Journal of Agricultural Engineering: Vol. 55 No. 3 (2024)
- Pier Riccardo Porceddu, Laura Rosati, Marco Dionigi, EVALUATION OF TEMPORALVARIATIONS IN MOISTURE AND CALORIFIC VALUE OF VINE AND OLIVE PRUNING , Journal of Agricultural Engineering: Vol. 41 No. 4 (2010)
- Salvatore Margiotta, TECHNICAL CHARACTERIZATION OF ECO-COMPATIBLE PLASTIC FILMS FOR SOIL SOLARIZATION: FOUR YEARS OF EXPERIMENTS , Journal of Agricultural Engineering: Vol. 38 No. 4 (2007)
- Silvio Kosutic, Daniele De Wrachien, Report on the 42nd International Symposium: Actual Tasks on Agricultural Engineering, 25-28 February 2014, Opatija, Croatia , Journal of Agricultural Engineering: Vol. 45 No. 1 (2014)
- Vincenzo Bagarello, Giuseppe Basile, Gaetano Caltabellotta, Giuseppe Giordano, Massimo Iovino, Testing soil water repellency in a Sicilian area two years after a fire , Journal of Agricultural Engineering: Vol. 51 No. 2 (2020)
- Changjian Zhou, Zhenyuan Zhao, Wenzhuo Chen, Yuquan Feng, Jia Song, Wensheng Xiang, Residual attention based multi-label learning for apple leaf disease identification , Journal of Agricultural Engineering: Vol. 55 No. 4 (2024)
- Daniele de Wrachien, David Proverbs, Report on the 3rd International Conference on Flood Recovery, Innovation and Response (FRIAR) 2012 , Journal of Agricultural Engineering: Vol. 43 No. 3 (2012)
- Ernest Ekow Abano, Robert Sarpong Amoah, Catherine Mbabazi, Microwave and steam blanching as pre-treatments before air drying of Moringa oleifera leaves , Journal of Agricultural Engineering: Vol. 51 No. 4 (2020)
- Fabrizio Mazzetto, Aldo Calcante, Aira Mena, COMPARING COMMERCIAL OPTICAL SENSORS FOR CROP MONITORING TASKS IN PRECISION VITICULTURE , Journal of Agricultural Engineering: Vol. 40 No. 1 (2009)
- Raffaele Cavalli, Stefano Grigolato, GEOGRAPHICALANALYSIS WITH GIS METHODOLOGY FOR A SUSTAINABLE USE OF LOGGING RESIDUES IN MOUNTAINOUS AREA , Journal of Agricultural Engineering: Vol. 38 No. 3 (2007)
<< < 45 46 47 48 49 50 51 > >>
You may also start an advanced similarity search for this article.
