A framework for an adaptive thermal heat balance model (ATHB)

Schweiker, Marcel; Wagner, Andreas

doi:10.1016/j.buildenv.2015.08.018

Cited by 93 publications

(84 citation statements)

References 18 publications

(25 reference statements)

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“…In total 65 healthy adults (31 females, age: 25.5y±4.5, height: 175cm±8.8, weight: 72kg±15.5) participated in three experimental campaigns all conducted at warm outdoor conditions . The participants were clothed according to the season (0.57clo±0.2) and performing light office work.…”

Section: Methodsmentioning

confidence: 99%

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Evaluating the performance of thermal sensation prediction with a biophysical model

2017

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Neutral thermal sensation is expected for a human body in heat balance in nearsteady-state thermal environments. The physiological thermoneutral zone (TNZ) is defined as the range of operative temperatures where the body can maintain such heat balance by actively adjusting body tissue insulation, but without regulatory increases in metabolic rate or sweating. These basic principles led to the hypothesis that thermal sensation relates to the operative temperature distance from the thermoneutral centroid (dTNZ op ). This hypothesis was confirmed by data from respiratory climate chamber experiments. This paper explores the potential of such biophysical model for the prediction of thermal sensation under increased contextual variance. Data (798 votes, 47 participants) from a controlled office environment were used to analyze the predictive performance of the dTNZ op model. The results showed a similar relationship between dTNZ op and thermal sensation between the dataset used here and the previously used dataset. The predictive performance had the same magnitude as that of the PMV model; however, potential benefits of using a biophysical model are discussed. In conclusion, these findings confirm the potential of the biophysical model with regard to the understanding and prediction of human thermal sensation. Further work remains to make benefit of its full potential. K E Y W O R D Sbiophysical model, indoor temperature, performance evaluation, prediction, thermal comfort, thermal sensation

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Section: Methodsmentioning

confidence: 99%

“…Fourth, the true positive rate, which is the proportion of the true positive cases (TP), ie, those cases where ASV is equal to PSV cat or PMV cat , respectively, is given by…”

Section: Methodsmentioning

confidence: 99%

Evaluating the performance of thermal sensation prediction with a biophysical model

2017

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“…so-called adaptive approach). The framework for an adaptive thermal heat balance model (ATHB) 1 combines these 2 approaches, improves the predictive performance and offers further potentials to explain variations in human thermal sensation as discussed below.…”

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confidence: 99%

“…1A), we derived the corresponding coefficients for these equations through mixed effect regression analyses. Thereby, the magnitude of increase and decrease of the metabolic rate was inferred from measurements of the heart rate and corresponding regression analyses 1 . Differences in the metabolic rate or the degree of its adaptation between individuals or groups of individuals were neglected so far.…”

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Adaptive processes explain variations in human thermal sensation

Schweiker

2016

Temperature

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Effects of Indoor Thermal Environment on Human Food Intake, Productivity, and Comfort: Pilot, Randomized, Crossover Trial

Richardson

Gohlke

Allison

2018

Obesity

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Objective: We hypothesized that exposure to mild temperatures above the human thermoneutral zone would decrease caloric intake in a sedentary office environment. Methods: Women (n = 25) were randomized in a crossover design to perform seated office work for 7 hours in a thermoneutral condition (control; 19–20°C) and a condition above the thermoneutral zone (warm; 26–27°C). Food intake was estimated by weight and bomb calorimetry, peripheral temperature by thermal imaging, and thermal comfort and productivity by questionnaires. Mixed effects models were used to examine the effects of thermal condition on caloric intake. Results: Participants ate on average 357 kcal less in the warm condition, adjusting for body mass index and peripheral temperature (p=0.0219). According to the survey results at midday (after 3.5 hours of exposure), 96% of the participants in the warm condition reported being comfortable (n=24) compared with 32% in the control condition (n=8). More participants reported being as productive or more productive than usual in the warm condition (n=22, 88%) than in the control condition (n=12, 48%). Conclusions: This line of research is worthy of further exploration. Untightening climate control towards warmer conditions during summer to increase comfort and productivity while decreasing caloric intake may prove both effective and comfortable.

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A framework for an adaptive thermal heat balance model (ATHB)

Cited by 93 publications

References 18 publications

Evaluating the performance of thermal sensation prediction with a biophysical model

Evaluating the performance of thermal sensation prediction with a biophysical model

Adaptive processes explain variations in human thermal sensation

Effects of Indoor Thermal Environment on Human Food Intake, Productivity, and Comfort: Pilot, Randomized, Crossover Trial

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