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湿帘-风机降温下的温室热/流场模拟及降温系统参数优化 被引量:30

Temperature/flow field simulation and parameter optimal design for greenhouses with fan-pad evaporative cooling system
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摘要 为提高温室夏季降温环境性能,提出了一种基于计算流体力学(computational fluid dynamics,CFD)的温室湿帘-风机系统的降温环境优化设计方法。采用太阳射线追踪法来模拟太阳辐射对夏季温室内流场环境的影响,并结合温室内作物的多孔介质模型,构建并求解温室三维非稳态模型,模拟了湿帘-风机降温下的温室内部温度场与速度场分布情况。模拟结果与试验测量的温度值和风速值进行了对比,其平均误差分别在4%和6%以内,验证了建立的温室CFD模型的准确性。结合正交试验方法,基于CFD模型对不同温室长度、湿帘面积和风机速度参数条件下的室内降温环境进行了优化设计。根据模拟优化获得的不同配置方案结果,建立了温室长度、湿帘面积和风机速度参数的拟合结果,为夏季华东沿海地区Venlo型温室湿帘-分机降温系统的设计提供了可靠的理论依据。 As one of the most effective cooling method, the fan-pad evaporative cooling system has been widely used to provide a suitable growth environment for greenhouse crops. An optimization method of the fan-pad cooling system based on computational fluid dynamics (CFD) was proposed to improve the cooling performance inside the greenhouse in summer. The Reynolds-averaged Navier-Stokes equations were solved using finite volume method (FVM). Due to the remarkable effect of gravitation on the microclimate distribution inside the greenhouse, the Boussinesq hypothesis was taken into account. The standardk-εturbulent model was selected to predict the distribution of air flow. Solar ray tracing was applied to load the solar radiation model, while the discrete ordinate model was selected for considering the effect of thermal radiation. Crops in the greenhouse were regarded as the porous medium, which was governed by the Darcy-Forcheimier equation in the CFD model. A three-dimension greenhouse model was developed to simulate the microclimate distribution and air circulation inside the greenhouse adopting fan-pad cooling system. The verification experiment was conducted in a Venlo-type greenhouse in the campus of Zhejiang University of Technology (30°14′N, 120°09′E) from 12:30 to 13:30 on July 23, 2012. Thirteen observation points of T1-T10 and TH1-TH3 were set up in the experimental greenhouse to validate the simulated air temperature and velocity. The errors between simulated and measured air temperature at the observation points varied from 0.7 to 2℃, and the errors of air velocity were less than 0.13 m/s. Compared with the measured values, the absolute mean errors of simulated temperature and air velocity were less than 4% and 6% respectively. It proved that the CFD method is reliable to estimate the distribution of air velocity and temperature in the greenhouse. The validated CFD model was then used to further analyze the cooling performance of different greenhouse cases in terms of the greenhouse lengths, the evaporative pad areas and the greenhouse ventilation rates. The indoor environment with the temperature of below 30℃ and the velocity of below 1 m/s was suitable for crop growth, and this condition was used as a criterion for optimal design. Based on the orthogonal test method, greenhouse cases with different greenhouse lengths, evaporative pad areas and air velocities of fans were classified and simulated to analyze their relations. The simulations illustrated that the greenhouse ventilation rate of 153.1 m3/(m2·h) and the minimum pad area of 6 m2can meet the cooling requirement in a Venlo-type greenhouse with 24 m length and 9.6 m width. In contrast with greenhouse of 70 m length, the maximum pad area of 13.5 m2had to be configured, because the greenhouse with smaller evaporative pad need combine with the fan’s velocity of more than 105 m3/(m2·h). According to the relations among greenhouse length, evaporative pad area and fan’s velocity resulted from CFD analysis; the fitted results could be achieved to design the fan-pad evaporative cooling system in the greenhouse in eastern China. The fitting optimization showed good agreement with the previous corresponding research results, which demonstrated that CFD technique was rational and reliable to design the fan-pad evaporative cooling system in the greenhouse.
出处 《农业工程学报》 EI CAS CSCD 北大核心 2015年第9期201-208,共8页 Transactions of the Chinese Society of Agricultural Engineering
基金 国家高技术研究发展计划(863计划)(2013AA050405) 国家国际科技合作专项(2014DFE60020)
关键词 温室 计算流体力学 降温 优化 湿帘-风机 数值仿真 greenhouses computational fluid dynamics cooling optimization fan-pad numerical simulation
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参考文献22

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