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Development of a bioheat model for older people under hot and cold exposures

  • Research Article
  • Architecture and Human Behavior
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Abstract

Physiological modeling is important to evaluate the effects of heat and cold conditions on people’s thermal comfort and health. Experimental studies have found that older people (above 65 year old) undergo age-related weakening changes in their physiology and thermoregulatory activities, which makes them more vulnerable to heat or cold exposure than average aged young adults. However, addressing the age-related changes by modeling has been challenging due to their wide variability among the older population. This study develops a two-node physiological model to predict the thermal response of older people. The model is built on a newly developed two-node model for average-age young adults by accounting for the age-related attenuation of thermoregulation and sensory delays in triggering thermoregulatory actions. A numerical optimization method is developed to compute the model parameter values based on selected benchmark data from the literature. The proposed model is further validated with published measurement data covering large input ranges. The model predictions are in good agreement with the measurements in hot and cold exposure conditions with a discrepancy 0.60 °C for the mean skin temperature and of 0.30 °C for the core temperature. The proposed model can be integrated into building simulation tools to predict heat and cold stress levels and the associated thermal comfort for older people in built environments.

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Abbreviations

A b :

dubois body surface area (m2)

c cr :

specific thermal capacity of the core node (W/(kg·°C))

c sk :

specific thermal capacity of the skin node (W/(kg·°C))

CCE:

attenuation coefficients of vasoconstriction for older people

CDE:

attenuation coefficient of vasodilation for older people

CSWE:

sweat attenuation coefficient for older people

Dry:

skin sensible heat exchange (W/m2)

dτ :

time step (1 minute)

E dif :

evaporative heat by skin water vapour diffusion (W/m2)

E max :

maximum evaporative heat (W/m2)

E vap :

skin evaporative heat exchange (W/m2)

h c :

convective heat transfer coefficient (W/(m2·°C))

h r :

radiative heat transfer coefficient (W/(m2·°C))

h sk :

thermal conductance of skin accounting for blood flow perfusion (W/(m2·°C))

M :

metabolic rate of activity (W/m2)

m cr :

mass of the core node (kg)

m sk :

mass of the skin node (kg)

Q res :

respiration heat loss (W/m2)

R d,air :

air layer thermal resistances (m2·°C/W)

R d,clo :

clothing layer thermal resistances (m2·°C/W)

RMSE:

root mean square error

RMSEcr :

RMSE values for the core temperature

RMSEsk :

RMSE values for the skin temperature

SBF:

skin blood flow rate (L/(m2·h))

SBFbasal :

basal skin blood flow rate (L/(m2·h))

SHIV:

shivering metabolic rate (W/m2)

SWR:

sweating rate (g/(m2·h))

T a :

ambient air temperature (°C)

T b0,sw :

body temperature threshold for sweating (°C)

T cl :

clothing surface temperature (°C)

T cr :

core temperature (°C)

T cr0,sh :

core temperature threshold for shivering (°C)

T cr0,sw :

core temperature threshold for sweating (°C)

T sk :

mean skin temperature (°C)

T sk0,sw :

skin temperature threshold for sweating (°C)

ΔT b,sw :

body temperature control signal for sweating (°C)

ΔT cr,dil :

core temperature control signal for vasodilation (°C)

ΔT cr,sh :

core temperature control signal for shivering (°C)

ΔT sk,cons :

skin temperature control signal for vasoconstriction (°C)

ΔT sk,sw :

skin temperature control signals for sweating (°C)

W :

body mechanical work (W/m2)

w :

skin wettedness

w′:

ratio of sweat secretion to the maximum evaporative heat

η evap :

sweat evaporation efficiency

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Acknowledgements

This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery Grants Program [#RGPIN-2018-06734] and the Advancing Climate Change Science in Canada Program [#ACCPJ 535986-18], and the Construction Research Centre of the National Research Council of Canada through funding from Infrastructure Canada in support of the Pan Canadian Framework on Clean Growth and Climate Change. The authors were very thankful for their supports.

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Authors and Affiliations

  1. Construction Research Centre, National Research Council Canada, 1200 Montréal Road, Ottawa, ON, K1A 0R6, Canada

    Lili Ji, Abdelaziz Laouadi & Michael A. Lacasse

  2. Department of Building, Civil and Environmental Engineering, Concordia University, 1455 De Maisonneuve Blvd. W., Montreal, QC, H3G 1M8, Canada

    Lili Ji & Liangzhu Wang

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  1. Lili Ji
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  2. Abdelaziz Laouadi
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Correspondence to Abdelaziz Laouadi.

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Ji, L., Laouadi, A., Wang, L. et al. Development of a bioheat model for older people under hot and cold exposures. Build. Simul. 15, 1815–1829 (2022). https://doi.org/10.1007/s12273-022-0890-3

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  • DOI: https://doi.org/10.1007/s12273-022-0890-3

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