基于CFD的日光温室墙体蓄热层厚度的确定

    Determination of thickness of thermal storage layer of solar greenhouse wall based on CFD

    • 摘要: 日光温室墙体蓄放热能力的优劣取决于墙体蓄放热特性与蓄热层厚度,确定日光温室蓄热层厚度,对于推进日光温室墙体改进意义重大。该研究以温室内太阳辐射与室外气温作为输入条件,按照试验温室实际尺寸和相关关系进行参数化建模并模拟计算不同月份墙体蓄热层厚度。选择乌鲁木齐地区2018年1月-4月典型晴天进行测试,以温室地面、墙体表面的太阳辐射为输入条件,室外空气温度为边界条件,利用Autodesk CFD软件对晴天9:00至次日9:00的温室砖墙内部温度场进行了模拟,并通过对比墙体内部0、10、20、30、40、50 cm处温度测点的实测值与模拟值验证模拟结果的准确性。结果表明,温室墙体模拟结果与测试结果吻合度较高,1月9日、2月9日、3月6日各层平均误差均在1.5 ℃以下,4月6日实际值与模拟值误差较大,模拟值较实际值滞后,趋势随着深度与墙体温度的升高而更加明显。在温室墙体材料、结构、室内外的光温环境的共同影响下,温室墙体传热是一个复杂的非稳态过程。砖墙温室与土墙温室类似,墙体可划分为"保温层、稳定层、蓄热层",各层的厚度与墙体蓄热材料、保温材料的热物性有关。对墙体温度场、各层的温度衰减因子以及延迟时间分析可知,墙体厚度在0~30 cm范围内,墙体温度波动较为明显,墙体厚度大于30 cm时,温室墙体一天内温度波动较为平缓,波幅较小。随着气温回升,温室墙体内部温度整体提高,各层温度波动相差不大。在温室结构、保温性能不变的情况下,温室蓄热层厚度及波动情况受外界光温环境的综合影响较小。综上所述,采用CFD模拟温室墙体温度场的变化,并根据温室墙体温度场变化确定温室墙体蓄热层厚度是可行的,可靠性较高。该研究可为其他区域优选温室墙体结构,推进日光温室墙体改进提供依据和参考。

       

      Abstract: The performance of greenhouse wall thermal storage and release capacity depends on the characteristics of the wall material and the thickness of the thermal storage layer. Determining the thickness of the solar greenhouse thermal storage layer is of great significance for promoting the improvement of the solar greenhouse wall. Parametric model according to the actual size and correlation of the test greenhouse was created based on the solar radiation and air temperature. Thickness of the wall thermal storage layer in different months was simulated in this study. In this paper, January 9th, February 9th, March 6th, and April 6th, 2018 in Urumqi was selected as typical sunny days. The solar radiation on the greenhouse floor and wall surface were used as the input condition, and the outdoor air temperature was the boundary conditions. The internal temperature field including each depth of 0, 10, 20, 30, 40, 50 cm of the greenhouse wall from 9:00 to next day 9:00 were simulated by using Autodesk CFD software. In order to ensure the consistency of CFD geometric models within one day and full release of heat from the greenhouse wall at night, no covering insulation quilt was carried out during the greenhouse test. The accuracy of simulated values was verified by comparing with the measured values. The results showed that the simulation results of the greenhouse wall were agreed well with the test results. The average error of each layer on January 9th, February 9th and March 6th was below 1.5 °C. The error and simulated results lags between the test results and the simulated results on April 6th is large. The trend becomes more pronounced as the depth and wall temperature increased. Under the combined influence of greenhouse wall materials, structures, and light and temperature environments, greenhouse wall heat transfer is a complex unsteady process. The brick wall greenhouse was similar to the soil wall greenhouse. The wall could be divided into "insulation layer, stable layer and heat storage layer". The thickness of each layer was related to the thermal properties of the wall heat storage material and insulation material. The wall temperature fluctuation was more obvious in the depth range of 0-30 cm according to the temperature field of the wall, the temperature attenuation factor of each layer and the delay time. When the wall depth was more than 30 cm, the greenhouse wall temperature fluctuations was relatively flat and the amplitude is small. As the temperature rose, the internal temperature of the greenhouse wall increased overall, and the temperature fluctuations of the various layers were small. The thickness and fluctuation of the greenhouse heat storage layer were less affected by the external light and temperature environment in the case of the greenhouse structure and insulation performance unchanged. In summary, it was feasible to simulate the change of greenhouse wall temperature field. It was reliable that the thickness of greenhouse wall thermal storage layer determined according to the temperature field variation of greenhouse wall. Solar greenhouse temperature environment dynamic simulation model based on greenhouse structure parameters and environmental parameters also could be established in other regions through the methods provided in this paper. It can provide basis and reference for the improvement and optimization of greenhouse wall structure.

       

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