Estimation of Heat Production Rate using Thermal Data During Exercise in Indoor Environments: A Study of Heat Storage Rate in Male Athletes.

The increasing preference for indoor exercise spaces highlights the relationship between indoor thermal environments and physiological responses, particularly concerning thermal comfort during physical activity. Determining the metabolic heat production rate during exercise is essential for optimizing the thermal comfort, well-being, and performance of individuals engaged in physical activities. This value can be determined during the activity using several methods, including direct calorimetry measurement, indirect calorimetry that uses analysis of respiratory gases, or approximations using collected data such as speed, body mass, and heart rate. The study aimed to calculate the metabolic heat production rate by infrared thermal evaluation (ITE) based on the body's thermal balance approach and compare it with the values determined by indirect calorimetry (IC). Fourteen participants volunteered for the study, using a cycling ergometer in a controlled climatic chamber. After the familiarization sessions, maximal O2 intake levels (VO2max) were determined through maximal graded exercise tests. Subsequently, constant work rate exercise tests were performed at 60% of VO2max for 20 min. The metabolic heat production rates were calculated by IC and ITE for each athlete individually. Respiratory gases were used to determine IC, while body skin and core temperatures, along with physical environmental data, were applied to calculate ITE using the human body thermal balance approximation of ASHRAE. According to the results, heat storage rates were misleading among the body's heat transfer modes, particularly during the first 8 min of the exercise. ITE showed a moderate level of correlation with IC (r: 0.03-0.86) with a higher level of dispersion relative to the mean (CV%: 12-84%). Therefore, a new equation (ITEnew) for the heat storage rates was proposed using the experimental data from this study. The results showed that ITEnew provided more precise estimations for the entire exercise period (p > 0.05). Correlations between ITEnew and IC values were consistently strong throughout the exercise period (r: 0.62-0.85). It can be suggested that ITEnew values can predict IC during the constant work rate steady-state exercise.

Associations between Thermal and Physiological Responses of Human Body during Exercise.

In this study, thermal behaviours of the athletes were investigated with respect to thermal comfort and exercise intensity. The relationship between an index for analysing thermal comfort (Predicted Mean Vote: PMV) and Rating of Perceived Exertion (RPE) which shows exercise intensity and exhaustion level was evaluated. Eleven moderately trained male athletes ( V ˙ O2max 54 ± 9.9 mL∙min-1∙kg-1) had volunteered for the study (age: 22.2 ± 3.7 years; body mass: 73.8 ± 6.9 kg; height: 181 ± 6.3 cm; Body surface area (BSA): 1.93 ± 0.1 m²; body fat: 12.6% ± 4.2%; V ˙ O2max: 54 ± 9.9 mL∙min-1∙kg-1). Experiments were carried out by using a cycle ergometer in an air-conditioned test chamber which provided fresh air and had the ability to control the temperature and relative humidity. The study cohort was divided into two groups according to maximal oxygen consumption levels of the participants. Statistical analyses were conducted with the whole study cohort as well as the two separated groups. There was a moderate correlation between PMV and RPE for whole cohort (r: -0.51). When the whole cohort divided as low and high aerobic power groups, an average correlation coefficient at high oxygen consumption cohort decreased to r: -0.21, while the average correlation coefficient at low oxygen consumption cohort increased to r: -0.77. In conclusion, PMV and RPE have a high correlation in less trained participants, but not in the more trained ones. The case may bring to mind that thermal distribution may be better in high aerobic power group in spite of high RPE and thus the relation between PMV and RPE is affected by exercise performance status.

Experimental data showing the thermal behavior of a flat roof with phase change material.

The selection and configuration of building materials for optimal energy efficiency in a building require some assumptions and models for the thermal behavior of the utilized materials. Although the models for many materials can be considered acceptable for simulation and calculation purposes, the work for modeling the real time behavior of phase change materials is still under development. The data given in this article shows the thermal behavior of a flat roof element with a phase change material (PCM) layer. The temperature and energy given to and taken from the building element are reported. In addition the solid-liquid behavior of the PCM is tracked through images. The resulting thermal behavior of the phase change material is discussed and simulated in [1] A. Tokuç, T. Basaran, S.C. Yesügey, An experimental and numerical investigation on the use of phase change materials in building elements: the case of a flat roof in Istanbul, Build. Energy, vol. 102, 2015, pp. 91-104.