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Air supply parameter optimization of a custom nonuniform temperature field based on the POD method

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Abstract In a traditional indoor environment, when a single environmental parameter is changed, the entire room is taken as the object of adjustment. Different locations in the same space may… Click to show full abstract

Abstract In a traditional indoor environment, when a single environmental parameter is changed, the entire room is taken as the object of adjustment. Different locations in the same space may have different needs. In this study, the temperature field in a building is simulated with the computational fluid dynamics (CFD) method. A small number of data samples are obtained by examining the error between the adjacent sample results and the CFD simulation results. Then, the proper orthogonal decomposition method is used to extract the characteristics of the sample data, and the causal relationship between the air supply parameters and the indoor environmental field is established. An optimization scheme is proposed to meet the different requirements of different spatial coordinates. In the optimal scheme, optimization calculations are performed on multiple design variables simultaneously, and the optimization calculation results are used as CFD simulation input conditions for a numerical simulation verification, which proves the reliability of the converse design method for creating a non-uniform environment. This study is different from previous ones because the controlled area in the room is no longer the entire room, a work area, or a certain local area, but an arbitrary position in the room. Starting from the demand side of the target point, an ideal air supply scheme is designed to meet the different needs of different positions in the room simultaneously. The results of this study are helpful for establishing or improving terminal control systems and reverse design methods in practical engineering.

Keywords: room; field; air supply; method

Journal Title: Building and Environment
Year Published: 2021

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