Visualization analysis and optimization strategy of thermal landscape in retrofitted elderly care buildings: A case study in Shanghai
Due to the increasing ageing population, numerous public buildings in major cities have been retrofitted into elderly care buildings. However, these retrofitted buildings often fail to meet the thermal needs of the elderly, particularly indoor thermal comfort. Unfortunately, existing measurement methods do not effectively capture the spatial and temporal distribution of the thermal environment. This study introduced a three-dimensional visualization method that combines measurements with spatial interpolation techniques to address these issues. A case study of a retrofitted nursing home in Shanghai, China, was considered, where four space interpolation methods provided by the Surfer software were used to establish visualization models of the indoor thermal landscape. The inverse distance to a power interpolation method was found to have the highest accuracy with an error of 0.27°C. Furthermore, the visualization model revealed temperature fluctuation exceeding 3°C in the activity space during the summer and identified energy waste. Consequently, thermal landscape optimization strategies were proposed, including an external shading system that can reduce cooling energy consumption by 26.8%. This study provides a visual tool for architects to accurately analyse indoor thermal environments’ distribution and variation trends whilst providing reliable data support for post-occupancy evaluation of indoor thermal environments in elderly care buildings.
Authors
- Pengfei Zhou (ORCID: https://orcid.org/0009-0006-3872-3863)
- Dexuan Song
- Chi Zhang (ORCID: https://orcid.org/0000-0002-9188-6307)
Institutions
- Tongji University (CN)
- Shanghai Tongji Urban Planning and Design Institute (CN)
Publication Details
- Journal
- Indoor and Built Environment
- Published
- 2024-11-25
- DOI
- https://doi.org/10.1177/1420326x241302448
- Citations
- 1
- Primary Topic
- Building Energy and Comfort Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.27
Funders
- National Natural Science Foundation of China