The building parameters of Chinese solar greenhouse(CSG)directly affect the front roof lighting and indoor thermal environment.In order to obtain the optimal parameter combination,a building parameter optimization met...The building parameters of Chinese solar greenhouse(CSG)directly affect the front roof lighting and indoor thermal environment.In order to obtain the optimal parameter combination,a building parameter optimization method based on computational fluid dynamics(CFD)simulation and entropy weight method was proposed.Firstly,a three-dimensional thermal and humidity environment model of CSG was constructed considering the coupling effect of soil,crop,and back wall based on CFD.The reliability of the model was validated through experiments in a CSG of Yongqing County,Hebei Province of China.Then,the indoor air temperature rise rate,air temperature and humidity uneven coefficient,and average air temperature and humidity were selected as the evaluation indicators of CSG thermal and humidity environment.The ridge height,back wall height and the horizontal projection of back roof of CSG were selected as the three factors of the orthogonal test plan,and a three-factor and four-level plan was designed,resulting in 16 different parameter combinations.By use of CFD simulation,the thermal and humidity environment evaluation indicators under different parameter combinations were calculated.The entropy weight method was used to assign weights to the evaluation indicators,and the comprehensive evaluation indicators of CSG thermal and humidity environment were obtained based on the linear weighting principle.By comparing comprehensive evaluation indicators,the optimal combination of building parameters was obtained with a ridge height of 5.72 m,a back wall height of 3.2 m,and a horizontal projection of 2.1 m on the back roof.The research results can provide a practical and feasible method for optimizing the building parameters of CSG,and provided theoretical guidance for the structural design and optimization of CSG.展开更多
基金support provided by Hebei Province Key Research and Development Program (Grant No.22327214D)Independent Research and Development Plan of Academy of Agricultural Planning and Engineering,Ministry of Agriculture and Rural Affairs (Grant No.SP202101).
文摘The building parameters of Chinese solar greenhouse(CSG)directly affect the front roof lighting and indoor thermal environment.In order to obtain the optimal parameter combination,a building parameter optimization method based on computational fluid dynamics(CFD)simulation and entropy weight method was proposed.Firstly,a three-dimensional thermal and humidity environment model of CSG was constructed considering the coupling effect of soil,crop,and back wall based on CFD.The reliability of the model was validated through experiments in a CSG of Yongqing County,Hebei Province of China.Then,the indoor air temperature rise rate,air temperature and humidity uneven coefficient,and average air temperature and humidity were selected as the evaluation indicators of CSG thermal and humidity environment.The ridge height,back wall height and the horizontal projection of back roof of CSG were selected as the three factors of the orthogonal test plan,and a three-factor and four-level plan was designed,resulting in 16 different parameter combinations.By use of CFD simulation,the thermal and humidity environment evaluation indicators under different parameter combinations were calculated.The entropy weight method was used to assign weights to the evaluation indicators,and the comprehensive evaluation indicators of CSG thermal and humidity environment were obtained based on the linear weighting principle.By comparing comprehensive evaluation indicators,the optimal combination of building parameters was obtained with a ridge height of 5.72 m,a back wall height of 3.2 m,and a horizontal projection of 2.1 m on the back roof.The research results can provide a practical and feasible method for optimizing the building parameters of CSG,and provided theoretical guidance for the structural design and optimization of CSG.