Research on a visual thermal landscape model of underground space based on the spatial interpolation method—A case study in Shanghai

Abstract

It is very significant to comprehensively understand the variation and distribution of the underground thermal environment, which will help to increase the building energy efficiency and improve the users’ thermal comfort. Because of these requirements, spatial interpolation technology provided by Surfer software is used to visualize the physical data of the spatial thermal environment and diagram the spatio-temporal thermal landscape model of underground space. According to the thermal landscape model, a new environmental control scheme is proposed. An​ underground shopping mall in Shanghai is taken as an example, in which 1512 data points were measured for interpolation. By comparison, it is found that the inverse distance to a power interpolation has the highest accuracy among the four commonly used interpolation methods, with an error of 0.57 °C. Therefore, the inverse distance to a power was used to build the spatio-temporal thermal landscape model of underground space based on measured data. This model can reduce the energy consumption of public space heating from 17885.75 kWh to 11536.18 kWh in December, saving 35.5% of energy consumption. In addition, the optimizing strategy was given from 3 aspects: seating arrangement, shading system and entrance design. The thermal landscape model provides practical solutions for research and design practice, which are recommended with direct implications on user comfort and energy consumption.

Keywords

• Underground space
• Thermal landscape model
• Visualization of thermal environment
• Inverse distance to a power method