Spatial interpolation-based analysis method targeting visualization of the indoor thermal environment

A comprehensive understanding of the thermal environment of building spaces is essential to the improvement of building energy-saving design and human comfort. However, current measurements of the thermal environment are limited by testing instruments, measurement points, etc., and only the parameters of a given measurement point can be considered rather than those of a plane covering the entire space. Besides, there are few studies on the spatial visualization of indoor thermal environment. To solve these problems, this paper proposes a method that combines point measurement and spatial interpolation to generate a spatial temperature distribution map. The exhibition hall of an office building in Shanghai was selected as an example. Eleven spatial interpolation methods (SIMs) were applied by Surfer to obtain contour maps after inputting the coordinates and air temperature of every measurement point. By comparing the mot mean square errors (RMSEs) of 11 SIMs, it was found that the SIM with the smallest error was inverse distance to a power method, whose RMSE reached 0.87 degrees C on rainy days and 0.80 degrees C on sunny days. Therefore, the inverse distance to a power method was finally applied to generate a visual stacked temperature distribution map that serves as a basis for spatial design and retrofitting. The proposed method aims to improve the limitations in terms of accuracy and efficiency in the post-occupancy evaluation and make architects accurately analyse the indoor temperature distribution, which provides architects with data-based support for applying passive design strategies, thus facilitating reasonable energy-saving planning, designing, or retrofitting.