[1]韩骏骋,贾鹤鸣*,李瑶,等.基于计算流体力学的微型植物工厂温湿度环境模拟及优化方案[J].林业工程学报,2019,4(06):136-142.[doi:10.13360/j.issn.2096-1359.2019.06.019]
 HAN Juncheng,JIA Heming*,LI Yao,et al.Temperature and humidity environment simulation and optimum scheme of micro plant factory based on computational fluid dynamics[J].Journal of Forestry Engineering,2019,4(06):136-142.[doi:10.13360/j.issn.2096-1359.2019.06.019]
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基于计算流体力学的微型植物工厂温湿度环境模拟及优化方案()
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《林业工程学报》[ISSN:1001-8081/CN:32-1160/S]

卷:
4
期数:
2019年06期
页码:
136-142
栏目:
装备与信息化
出版日期:
2019-11-20

文章信息/Info

Title:
Temperature and humidity environment simulation and optimum scheme of micro plant factory based on computational fluid dynamics
文章编号:
2096-1359(2019)06-0136-07
作者:
韩骏骋贾鹤鸣*李瑶孙康健康立飞李金夺
东北林业大学机电工程学院,哈尔滨 150040
Author(s):
HAN Juncheng JIA Heming* LI Yao SUN Kangjian KANG Lifei LI Jinduo
College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China
关键词:
微型植物工厂 湿度场 模拟计算 计算流体力学 均匀性 结构优化
Keywords:
micro plant factory humidity field simulation calculation computational fluid dynamics uniformity structure optimization
分类号:
S625
DOI:
10.13360/j.issn.2096-1359.2019.06.019
文献标志码:
A
摘要:
为研究微型植物工厂内温度场和湿度场的分布情况并对其进行优化,通过Gambit将建于东北林业大学内的微型植物工厂进行3D建模,采用计算流体力学软件,引入混合了空气和水蒸气的组分运输模型和替代植物的多孔介质模型对工厂内温湿度的分布情况进行数值模拟计算,同时设计2种拥有不同回风口和通风机的位置或数量的优化方案。模拟计算的结果与实际监测值进行对比发现,相对湿度的平均相对误差为0.385%,温度的平均相对误差为1.10%,温湿度的最大误差分别不超过0.9 ℃和1.5%,模拟情况与实际情况吻合度较好,使得模型的可行性和准确性得以验证。在对2种优化方案进行模拟并与初始方案比较后,得出如下结论:工厂内部气流流动对温湿度的分布有较为明显的影响,2种优化方案的温度分布均匀性均优于初始方案,其中,方案2的温湿度分布均匀性最好,相对湿度和温度的标准偏差分别为0.60%和0.08 ℃,相对湿度范围为76.4%~79.4%,最高温度和最低温度分别为25.4和25.0 ℃,平均温湿度分别为25.2 ℃和77.9%,温湿度的分布均匀性较好,没有抑制植物生长的因素存在,因此方案2,即将通风机分别置于工厂西墙离地0.3和1.0 m处,回风口分别离地0.6和1.3 m,为工程设计优化的最优方案。最后,对最优方案进行了试验验证,认定最优方案中温湿度的模拟情况可以真实反映温室中的实际环境。
Abstract:
To explore and optimize the distribution of temperature field and humidity field in the micro plant factory, the 3D modeling was developed by Gambit based on the micro plant factory in the Northeast Forestry University.The computational fluid dynamics software was utilized for the numerical simulation.When Fluent was used to simulate the environment in the micro plant factory, the component transport model with mixed air and water vapor was chosen, the porous medium model was used to simulate plants, and the distribution of temperature and humidity in the factory was investigated.Then two kinds of optimization schemes which had different position and numbers of windows and ventilation fans were designed.When compared the simulation results with the actual monitoring values, it was found that the average relative error of the relative humidity was 0.385%, the average relative error of temperature was 1.10%, and the maximum errors of temperature and humidity were less than 0.9 ℃ and 1.5%, respectively.Besides, the simulated situations obtained were in good agreement with the actual situations, which could verify the feasibility and accuracy of the model.After simulating the schemes of two kinds of optimization, the conclusions were drawn out by comparing with the initial plan: the air flow inside the factory had obvious influence on the distribution of temperature and humidity; two kinds of optimization schemes of the uniformity of the distribution of temperature and humidity were better than the initial solution, and the scheme two, which had the best distribution uniformity of temperature and humidity, had the standard deviation of relative humidity within 0.6% and the standard deviation of temperature within 0.08 ℃.As for the limitation of relative humidity, the maximum and minimum relative humidity in the scheme two were 79.4% and 76.4%, respectively, and the maximum and minimum temperatures were 25.4 ℃ and 25.0 ℃, respectively.According to the data, there were no factors which could inhibit the growth of plant in scheme two.In conclusion, compared with all schemes, the scheme two was chosen, in which the ventilation fans were placed 0.3 m and 1.0 m above the ground on the west wall of the factory and the windows were placed 0.6 m and 1.3 m above the ground, as the optimal scheme for engineering design.Finally, the optimum scheme was tested and verified.It could be concluded that the simulation of temperature and humidity in the optimum scheme could truly reflect the actual environment in greenhouse.

参考文献/References:

[1] CHOI J M, CHO S W.A study on the indoor airflow pattern by changing the location of mechanical terminal unit[J].Journal of Air-Conditioning and Refrigerating, 2009, 21(3):193-200.
[2] LIM T G, KIM Y H.Analysis of airflow pattern in plant factory with different inlet and outlet locations using computational fluid dynamics[J].Journal of Biosystems Engineering, 2014, 39(4): 310-317.DOI: 10.5307/jbe.2014.39.4.310.
[3] 何国敏, 汪小旵, 孙国祥.现代化温室自然通风时湿热环境CFD模拟研究[J].西南大学学报(自然科学版), 2011, 33(9): 136-141.DOI: 10.13718/j.cnki.xdzk.2011.09.031.
HE G M,WANG X C, SUN G X.CFD simulation of temperature and humidity distribution in naturally ventilated modern greenhouses[J].Journal of Southwest University(Natural Science Edition), 2011,33(9):136-141.
[4] 刘焕, 方慧, 程瑞锋, 等.基于CFD的人工光植物工厂气流场和温度场的模拟及优化[J].中国农业大学学报, 2018, 23(5): 108-116.DOI: 10.11841/j.issn.1007-4333.2018.05.13.
LIU H, FANG H, CHENG R F, et al.Simulation and optimization of the air flow and temperature in plant factory with artificial light based on CFD[J].Journal of China Agricultural University, 2018, 23(5): 108-116.
[5] 赵杰强, 赵云.机械通风连栋温室的温度场CFD模拟[J].中国农机化学报, 2014, 35(6): 76-79.DOI: 10.13733/j.jcam.issn.2095-5553.2014.06.020.
ZHAO J Q, ZHAO Y.Computational fluid dynamics simulation on temperature field of mechanical ventilation for multi-span greenhouse[J].Journal of Chinese Agricultural Mechanization, 2014, 35(6): 76-79.
[6] 贾鹤鸣, 张森, 宋文龙, 等.基于CFD的微型植物工厂湿热环境数值分析[J].林业工程学报, 2018, 3(6): 122-127.DOI: 10.13360/j.issn.2096-1359.2018.06.020.
JIA H M, ZHANG S, SONG W L, et al.Numerical analysis of humid and hot environment in micro plant factory based on CFD[J].Journal of Forestry Engineering, 2018, 3(6): 122-127.
[7] 陈教料,胥芳, 张立彬, 等.基于CFD技术的玻璃温室加热环境数值模拟[J].农业机械学报, 2008, 39(8): 114-118.
CHEN J L, XU F, ZHANG L B, et al.CFD-based simulation of the temperature distribution in glass greenhouse with forced-air heater[J].Transactions of the Chinese Society for Agricultural Machinery, 2008, 39(8): 114-118.
[8] 戴剑锋, 罗卫红, 李永秀, 等.基于小气候模型的温室能耗预测系统研究[J].中国农业科学, 2006, 39(11): 2313-2318.DOI: 10.3321/j.issn:0578-1752.2006.11.022.
DAI J F, LUO W H, LI Y X, et al.A microclimate model-based energy consumption prediction system for greenhouse heating[J].Scientia Agricultura Sinica, 2006, 39(11): 2313-2318.
[9] 张艳,杜震宇.日光温室内浅层土壤温湿度场的数值模拟[J/OL].太原理工大学学报:1-11[2019-06-25].http://kns.cnki.net/kcms/detail/14.1220.n.20181217.1040.002.html.
ZHANG Y, DU Z Y.Numerical simulation on the temperature and moisture fields of shallow soil in solar greenhouse[J/OL].Journal of Taiyuan University of Technology:1-11[2019-06-25].http://kns.cnki.net/kcms/detail/14.1220.n.20181217.1040.002.html.
[10] 方慧, 杨其长, 张义, 等.基于CFD的不同走向大跨度保温型温室温度场模拟[J].中国农业大学学报, 2017, 22(11): 133-139.DOI: 10.11841/j.issn.1007-4333.2017.11.15.
FANG H, YANG Q C, ZHANG Y, et al.Prediction model on air temperature in large-span greenhouse with different orientation based on CFD[J].Journal of China Agricultural University, 2017, 22(11): 133-139.
[11] 宿文,薛晓萍,熊宇,等.自然通风对日光温室气温影响的模拟分析[J].生态学杂志,2016,35(6):1635-1642.DOI: 10.13292/j.1000-4890.201606.030.
SU W, XUE X P, XIONG Y, et al.Modeling the effect of natural ventilation on temperature inside solar greenhouse[J].Chinese Journal of Ecology, 2016, 35(6):1635-1642.
[12] 程秀花, 毛罕平, 伍德林, 等.栽有番茄的玻璃温室内气流场分布CFD数值模拟[J].江苏大学学报(自然科学版), 2010, 31(5): 510-514.DOI: 10.3969/j.issn.1671-7775.2010.05.004.
CHENG X H, MAO H P, WU D L, et al.CFD simulations of airflow distributions inside glasshouse with tomato crops[J].Journal of Jiangsu University(Natural Science Edition), 2010, 31(5): 510-514.
[13] 贾鹤鸣,宋文龙.基于松弛序列法的温室传感器优化布置研究[J].森林工程,2015,31(5):82-85.DOI: 10.16270/j.cnki.slgc.2015.05.019.
JIA H M, SONG W L.Relaxation sequential algorithm for optimal placement of greenhouse sensors[J].Forest Engineering, 2015,31(5):82-85.
[14] 罗孟德, 贾鹤鸣, 赵文科, 等.微型植物工厂营养液循环控制系统设计[J].科技创新与生产力, 2017(5): 70-74.DOI: 10.3969/j.issn.1674-9146.2017.05.070.
LUO M D, JIA H M, ZHAO W K, et al.Design of nutrient solution circulation control system for miniature plant[J].Sci-Tech Innovation and Productivity, 2017(5): 70-74.
[15] 贾鹤鸣, 张森, 朱柏卓,等.变风速条件下微型植物工厂传感器优化布置[J].应用科技, 2018, 45(1): 7-13.DOI: 10.11991/yykj.201708002.
JIA H M, ZHANG S, ZHU B Z, et al.Optimal placement of sensors in a miniature plant under variable wind speed[J].Applied Science and Technology, 2018, 45(1): 7-13.

相似文献/References:

[1]贾鹤鸣,张森,宋文龙*,等.基于CFD的微型植物工厂湿热环境数值分析[J].林业工程学报,2018,3(06):122.[doi:10.13360/j.issn.2096-1359.2018.06.020]
 JIA Heming,ZHANG Sen,SONG Wenlong*,et al.Numerical analysis of humid and hot environment in micro plant factory based on CFD[J].Journal of Forestry Engineering,2018,3(06):122.[doi:10.13360/j.issn.2096-1359.2018.06.020]

备注/Memo

备注/Memo:
收稿日期:2019-03-20 修回日期:2019-05-13 基金项目:国家自然科学基金(31470714); 中央高校基本科研业务费专项资金(2572019BF04); 东北林业大学横向课题(43217002,43217005,43219002)。 作者简介:韩骏骋,女,研究方向为基于温室流体力学的仿真技术。通信作者:贾鹤鸣,男,副教授。E-mail:jiaheminglucky99@126.com
更新日期/Last Update: 2019-11-10