Temperature field simulation using CFD in the plant factory

Zhou, Shenghan; Liu, Huan; Fan, Ruiqi; He, Zhongqun; Zhang, Yao; Chen, Yufei; Sun, Xiaoyu; Zhou, Xiaoting; Yang, Qichang; Zheng, Youliang; Lu, Wen-Hsiang

doi:10.1088/1755-1315/560/1/012036

Cited by 5 publications

(3 citation statements)

References 2 publications

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“…Their research explored the comprehensive effects of the sun’s position, wind direction, and intensity on the microclimate within the greenhouse. Shenghan Zhou and colleagues [ 6 ] conducted a study using FLUENT software to simulate the temperature field in a plant factory. Their research focused on the detailed three-dimensional modeling of temperature distribution influenced by LED light heat dissipation and boundary conditions, emphasizing the significance of accurate modeling in such environments.…”

Section: Introductionmentioning

confidence: 99%

Optimizing heat pump unit selection for recirculating aquaculture workshops through computational fluid dynamics

Ziyun,

Ping,

Jiacheng

et al. 2024

PLoS ONE

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The selection of water temperature regulation equipment plays a crucial role in the design of workshops. At present, the choice of water temperature control equipment is usually based on the volume of the fish pond and thermal parameter calculation, combined with aquaculture experience. Empirical formulas only work in specific conditions due to factors like the environment, climate, and fish types,resulting in inaccurate equipment selection outcomes. Recognizing this limitation, this paper proposes to apply CFD simulation of the temperature field to accurately calculate the heat exchange value between indoor air and water, thereby predicting the heat exchange values during aquaculture activities in the aquaculture workshop. providing a new approach for equipment selection. This paper selects a puffer fish breeding workshop in Dalian as the simulation object, establishing a 3D unsteady-state Computational Fluid Dynamics model. The model considers outdoor temperature, solar radiation, and phase-change heat transfer in water. Comparison with experimental data reveals a root mean square error of 0.46°C for the simulated results. During summer, the highest cooling load occurs at 16:00, reaching 94.6 kW. It is recommended to employ the Daikin GCHP-40MAH ground source heat pump as the water temperature control equipment. CFD simulation validates its effectiveness in shaping the indoor temperature field post-installation. the investment in water temperature control equipment can be reduced to a certain degree. This provides a reference value for the selection of water temperature equipment in aquaculture workshops.

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Section: Introductionmentioning

confidence: 99%

Optimizing heat pump unit selection for recirculating aquaculture workshops through computational fluid dynamics

Ziyun,

Ping,

Jiacheng

et al. 2024

PLoS ONE

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“…Using CFD models to perform aerodynamic analyses based on various structures and monitoring points can help to identify issues within the internal environment and develop solutions to improve environmental uniformity [18,[21][22][23]. Incorporating CFD into the analysis of plant factory environments enhances our ability to optimize efficiency and achieve a more uniform atmospheric environment [24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics

Lee,

Seo,

et al. 2023

Horticulturae

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A seedling plant factory requires precise environmental control to ensure uniform growth within a limited cultivation period. A porous panel exhaust system was installed to maintain a stable and uniform internal environment. To provide optimal temperature, humidity, and airflow, it is necessary to interpret the internal aerodynamics. However, field monitoring has limitations in analyzing the invisible flow patterns. To overcome this limitation, CFD simulations can be utilized to understand internal environmental conditions and uniformity. The objective of this paper is to develop and validate a CFD model of a seedling plant factory with a porous panel for improving the uniformity of the internal environment. Multiple data loggers were evenly installed at various locations inside the seedling plant factory, and 24 h field monitoring was conducted. The average temperature and humidity during the 16 h light period and 8 h dark period were maintained within 1% of the set values, while the regional temperature deviation had an average of 1.65 °C and a maximum of 2.63 °C. The regional humidity deviation had an average of 14.1% and a maximum of 23.8%. The CFD model was designed to analyze the internal environmental uniformity after validation by comparing it with the field monitoring data. The Realizable k-ε turbulence model, which exhibited an error of 4.0% in comparison with the field data, was selected through a validation test among four different turbulence models with the same configuration of the seedling plant factory. The CFD simulation results were interpreted quantitatively and qualitatively, focusing on the airflow, temperature, and humidity distributions caused by the air conditioner and humidifier. Variations in the average temperature of up to 0.5 degrees and velocity differences of 0.28 m/s were observed depending on the location of the cultivation shelves. The locations and causes of stagnant regions resulting from the airflow patterns were identified through the simulations.

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“…In indoor plant factories, controlling room temperature is an extremely important part as it contributes a huge influence on plant cultivation [5]. To provide suitable temperature conditions and effective airflow movement around crops, the plant factory must be designed with proper air conditioning and ventilation system [6,7].…”

Section: Introductionmentioning

confidence: 99%

Numerical Investigation of Temperature Distribution in a Container-type Plant Factory

Sabudin

Zulkarnaen

Mohammed

et al. 2022

ARASET

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A container-type plant factory is a closed facility for crop production with artificial lighting and a controlled environment allowing year-round crop production. In a plant factory, a poor ventilation system can result in physiological problems and unequal post-harvest quality which will lower the crops' commercial value. This study was conducted to investigate the temperature distribution in a container-type plant factory via computational fluid dynamics (CFD), followed by experimental studies for validation. A three-dimensional computational fluid dynamics (CFD) model was developed to simulate the container-type plant factory with air conditioning and an exhaust fan providing cooling air and ventilation across the plant factory. The predicted airflow distribution on the upper shelves accommodating crops shows that the average temperature is about 23.74 ℃ while for lower shelves is 23.59℃. This shows the temperature distribution is rather uniformly distributed across the plant factory. A validation between experimental data and simulated values indicated that the temperature distribution had a deviation smaller than 2%, suggesting the validity of the CFD studies. Hence, the CFD model was used to simulate several operational conditions towards optimizing the indoor condition of the plant factory.

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Temperature field simulation using CFD in the plant factory

Cited by 5 publications

References 2 publications

Optimizing heat pump unit selection for recirculating aquaculture workshops through computational fluid dynamics

Optimizing heat pump unit selection for recirculating aquaculture workshops through computational fluid dynamics

Improvement of Environmental Uniformity in a Seedling Plant Factory with Porous Panels Using Computational Fluid Dynamics

Numerical Investigation of Temperature Distribution in a Container-type Plant Factory

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