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Spatial interpolation-based analysis method targeting visualization of the indoor thermal environment
Abstract 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 root 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 °C on rainy days and 0.80 °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.
Highlights Spatial visualization of indoor thermal environment is realized by Surfer. Spatial interpolation methods combined with measured data generate contour maps. Inverse distance to a power method is extracted through error analysis. 3D temperature map facilitates post-occupancy evaluation and building retrofitting.
Spatial interpolation-based analysis method targeting visualization of the indoor thermal environment
Abstract 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 root 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 °C on rainy days and 0.80 °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.
Highlights Spatial visualization of indoor thermal environment is realized by Surfer. Spatial interpolation methods combined with measured data generate contour maps. Inverse distance to a power method is extracted through error analysis. 3D temperature map facilitates post-occupancy evaluation and building retrofitting.
Spatial interpolation-based analysis method targeting visualization of the indoor thermal environment
Yu, Zhuoyu (author) / Song, Yifan (author) / Song, Dexuan (author) / Liu, Yi (author)
Building and Environment ; 188
2020-11-23
Article (Journal)
Electronic Resource
English
Spatial interpolation , Visualization , Fieldwork measurement , Indoor thermal environment , SIMs , spatial interpolation methods , RMSEs , root mean square errors , HVAC , heating, ventilation, and air-conditioning , CFD , computational fluid dynamics , CAUP , College of Architecture and Urban Planning
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