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Developing thermal prediction models for the elderly under temperature step changes

  • Shan Zhou
  • , Baizhan Li
  • , Chenqiu Du
  • , Runming Yao
  • , Linyuan Ouyang
  • , Haixia Zhou
  • , Risto Kosonen
  • , Arsen Krikor Melikov
  • , Liangyue Shang
  • , Hong Liu*
  • *Corresponding author for this work
  • Chongqing University
  • Aalto University

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Daily transitions between indoor and outdoor environments involving temperature step changes have been extensively studied in young people, but little attention has been given to age-related differences and the development of thermal prediction models specifically for the elderly. To address this knowledge gap, a study was conducted in a climate chamber using warm-neutral-warm experimental sessions. Twenty-four elderly participants were selected from volunteers who met the health and body shape requirements. Thermal sensation vote (TSV) and mean skin temperature (MST) responses of the elderly were collected and analyzed. The results demonstrate that temperature step changes (3–9 °C) and neutral thermal experiences significantly influence the thermal responses of the elderly. Compared to the young, the elderly exhibit lower TSV, lower MST, lower skin heat loss, and different associations between TSV and skin heat loss. Leveraging these age-related differences, an MST prediction model was established for the elderly. The predicted MST can also serve as an input for the TSV prediction model established in this study. The TSV prediction model is based on skin heat loss and applicable to both transient and steady-state conditions. This study introduces a new approach for predicting the thermal responses of the elderly and enhances understanding of age-related differences in thermal responses.
Original languageEnglish
Article number110902
JournalBuilding and Environment
Volume245
Number of pages14
ISSN0360-1323
DOIs
Publication statusPublished - 2023

Keywords

  • Elderly
  • Skin temperature
  • Temperature step change
  • Thermal comfort
  • Thermal environments
  • Thermal sensation prediction model

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