Thermophysiological Model Research Articles

Resting energy expenditure differs among individuals with different levels of perceived thermal sensitivity: A cross-sectional study.

Metabolic rate has been used in thermophysiological models for predicting the thermal response of humans. However, only a few studies have investigated the association between an individual's trait-like thermal sensitivity and resting energy expenditure (REE), which resulted in inconsistent results. This study aimed to explore the association between REE and perceived thermal sensitivity. The REE of healthy adults was measured using an indirect calorimeter, and perceived thermal intolerance and sensation in the body were evaluated using a self-administered questionnaire. In total, 1567 individuals were included in the analysis (women = 68.9%, age = 41.1 ± 13.2 years, body mass index = 23.3 ± 3.3 kg/m2, REE = 1532.1 ± 362.4 kcal/d). More women had high cold intolerance (31.8%) than men (12.7%), and more men had high heat intolerance (23.6%) than women (16.1%). In contrast, more women experienced both cold (53.8%) and heat (40.6%) sensations in the body than men (cold, 29.1%; heat, 27.9%). After adjusting for age, fat-free mass, and fat mass, lower cold intolerance, higher heat intolerance, and heat sensation were associated with increased REE only in men (cold intolerance, P for trend = .001; heat intolerance, P for trend = .037; heat sensation, P = .046), whereas cold sensation was associated with decreased REE only in women (P = .023). These findings suggest a link between the perceived thermal sensitivity and REE levels in healthy individuals.

THERMODE 2023: Formulation and Validation of a new Thermo-physiological Model for Moderate Environments

Thermo-physiological models allow the evaluation of the human response to thermal environments, assessing thermal comfort and (or) thermal stress due to exposure to heat and cold, in clothing and automotive research, and building simulation. Fifty years after the final version of the model developed by Stolwijk over the period 1966–1973, this paper describes a novel multi-cylindrical model which integrates the most recent advances in the active and the passive components and a thermal sensation model. The model, named THERMODE (THERMoregulation MOdel for Disuniform Environments) 2023, will be presented in-depth to allow its independent implementation by researchers in the field and favour further developments. Consisting of 14 blocks, 48 segments, and 193 nodes, THERMODE has been validated based on climatic chamber measurements carried out on nine groups of twelve subjects in a range of thermal sensations close to comfort (e.g., from slightly cool (−1) to slightly warm (+1) according to the ASHRAE scale). THERMODE predicts with acceptable accuracy core and local skin temperature values with deviations that do not exceed 0.5 °C in moderate environments. The thermal sensation model was validated on a sample of more than 4000 subjects and predicts with high accuracy the thermal sensation in the range from −1.2 to 2.0. THERMODE seems to be also reliable in a broader range of microclimatic conditions with skin and core temperatures close to those predicted by other models (e.g., JOS-3 or 3-D).

Research on the Heating Effect of a Convection Radiator Based on a Human Thermophysiological Model

Forced convection is the most effective way to improve the thermal efficiency of a radiator under low-temperature conditions. This technical method differs significantly from the heating effects of general radiation and natural convection. Few studies have applied the objective evaluation method based on quantitative calculation to evaluate the effectiveness of indoor heating or optimize the technical parameters (air flow rate, air supply method, etc.) of heating systems. This article couples human metabolic factors with heating environmental factors and uses a 57-node human thermal physiological model to evaluate the effectiveness of forced convection radiator heating from the perspective of the local thermal comfort of the human body and demonstrates the feasibility of this scheme by comparing it with floor radiation heating. The research shows that the air supply speed of a radiator affects human thermal comfort. Continuing to increase the wind speed, at a speed of 3 m/s, the surface temperature of the human body reaches a high value and will then decrease, leading to a decrease in thermal comfort. Research on indoor air distribution shows that the use of bottom-side air supply provides better thermal comfort compared to top air supply. The local skin temperature distribution of the human body indicates that when the indoor average temperature is higher than 20 °C, the overall thermal comfort of convective radiator heating and floor radiant heating is comparable. The article provides a way of objectively calculating and directly quantifying the effect of heating equipment on human thermal physiological parameters.

A data-driven model on human thermophysiological and psychological responses under dynamic solar radiation

Excessive solar radiation can also cause thermophysiological and psychological discomfort in the human body. In real-world environments, solar radiation is highly variable. Moreover, the amount of solar radiation exposure that people receive due to their outdoor activities can have large fluctuation. The physiological and psychological responses of the human body under this dynamic solar radiation exposure are quite different from those under steady-state solar radiation exposure. Therefore, this paper studies the physiological and psychological responses of the human body under the condition of dynamic solar radiation through the method of field experimental research and explores the applicability of the existing indicators of PET and UTCI in the dynamic radiation environment. A novel recurrent neural network model was used to predict skin temperatures and thermal sensations, in which genetic algorithm was applied to tune hyper-parameters.It is noteworthy that both thermal sensations and skin temperatures at exposed body segments show a stronger correlation to solar radiation, while there exists a time lag between solar radiation and skin temperature when people are exposed to solar radiation. Compared with thermophysiological models (DTS), the GA-LSTM model has a better prediction accuracy in thermal sensations.

Novel Technological Advances to Protect People Who Exercise or Work in Thermally Stressful Conditions: A Transition to More Personalized Guidelines

Background: Prevention plays a key role in ensuring health and safety and is particularly important in scenarios when life is threatened. Adverse thermal conditions are experienced by billions of people daily, affecting the human capacity for thermoregulation and increasing the risks of life-threatening accidents, diseases, and fatalities. The aim of this study was to develop and validate a new, freely accessible method that will ultimately allow health, as well as exercise and labour organizations, to predict and potentially mitigate the physiological strain experienced by people who exercise or work in thermally stressful environmental conditions. Methods: First, we used concurrent technological advances and thermophysiological modelling to (i) develop a mobile phone application that predicts the physiological heat strain experienced by individuals conducting physical activity in adverse environmental conditions, and (ii) provide them with individualized heat mitigation strategies. Second, to examine the construct validity of the newly developed mobile phone application, core body temperature was recorded using gastrointestinal thermometry in 37 healthy soldiers during different activities. These data were used to examine the predictive capacity of our application in pre-classifying individuals with an increased risk of experiencing elevated physiological heat strain during work based on the guidelines (core body temperature ≥ 38 °C) of the World Health Organization. Results: The core body temperature predictions made by the mobile phone application were positively related (r = 0.57, p < 0.05) with the actual physiological measurements taken by our participants (mean absolute error: 0.28 °C). More importantly, our application correctly predicted 93% of occurrences of elevated physiological heat strain and 90% of those that were not (overall accuracy: 92%). Conclusions: Mobile phone applications integrating thermophysiological models can predict the physiological heat strain experienced by an individual, but it remains to be studied whether the suggested heat mitigation strategies can reduce or prevent adverse impacts.

Applicability of Human Thermophysiological Model for Prediction of Thermal Strain in PPE

The use of personal protective equipment (PPE) is essential to protect the human body in hazardous environments or where there is a risk of CBRN agents. However, PPE also poses a barrier to evaporative heat dissipation, therefore increasing heat accumulation in the body. In our research, we investigated the applicability of thermophysiological models for the prediction of thermal strain and the permissible working time in a contaminated environment when the usage of protective ensembles is required. We investigated the relationship between the thermal insulation characteristics of four types of PPE against CBRN agents and the induced thermal strain in a set of real physiological strain tests with human probands wearing the PPE in a climatic chamber. Based on the results, we compared the predictions using two thermophysiological models—Predicted Heat Strain Index (PHS) and FIALA-based model of thermal comfort (FMTK)—with the experimental data. In order to provide a user-friendly platform for the estimation of thermal stress in PPE, a user-friendly computational tool, Predictor of Thermal Stress (PTS), was developed. The PTS tool is based on an extensive database of simulated calculations using an FMTK model based on PPE characteristics, environmental conditions, individual parameters, and expected workload. The PTS tool was validated by means of the results from real tests in a climatic chamber. The PTS was shown to be an easy-to-use computational tool, which can be run on a regular PC, based on real data applicable for the estimation of the permissible work time limit with regard to thermal strain in PPE under various conditions.

Application of a thermo-physiological model to determine sweating thermo-active zone for a medical staff subject

Thermo-physiological models represent a valid approach for the study of person-environment energy interactions and constitute an alternative and promising methodology for the study of comfort in all those cases in which the Fanger’s statistical model is not applicable. By dividing the body into several segments, and these into several nodes, including physiological variables among the inputs and detailing the representation of clothing, these models are better suited to application in the healthcare sector, as they can take into account pathological states that alter physiological responses (patients) and specific types of clothing and activities (medical staff). In this work, the Tanabe 65 MN model, implemented in the ABICS opensource software, has been used to identify the thermo-active zones in which sweating occurs on at least one section of the body for a person of the medical staff. A parametric analysis was developed by varying the ambient temperature (20 - 36 °C), the relative humidity (40 - 60%), the metabolic rate (1.5 - 2.0 met) and considering a young subject (30 years) and an older one (60 years). These zones were identified on charts correlating the skin temperature to the ambient one. In both cases, a similar trend is observed: the average temperature of the skin, at which sweating occurs, increases as the ambient temperature grows and on average this mechanism is activated for lower skin temperatures in the case of the older individual.

Validation of upper thermal thresholds for outdoor sports using thermal physiology modelling

ABSTRACT Thermal safety guidelines with upper thresholds aim to protect athletes’ health, yet evidence-based sport-specific thresholds remain unestablished. Experimenting with athletes in severely hot conditions raises ethical concerns, so we used a thermo-physiological model to validate the thresholds of guidelines for outdoor sports. First, the reproducibility of the joint system thermoregulation model (JOS-3) of core temperature has been validated for 18 sports experiments (n = 213) and 11 general exercise experiments (n = 121) using the Bland – Altman analysis. Then, core temperatures were predicted using the JOS-3 in conditions corresponding to the upper thresholds, and if the 90th–99.7th percentile core temperature value (corresponding to 0.3%–10% of the participants) exceeded 40°C, the thresholds were judged as potentially hazardous. Finally, we proposed revisions for sports with potentially hazardous thresholds. As a result, the JOS-3 could simulate core temperature increases in most experiments (27/29) for six sports and general exercises with an accuracy of 0.5°C. The current upper thresholds for marathons, triathlons, and football are potentially hazardous. Suggested revisions, based on specified percentiles, include: Football: revise from wet bulb globe temperature (WBGT) 32°C to 29–31°C or not revise. Marathon: revise from WBGT 28°C to 24–27°C. Triathlon: revise from WBGT 32.2°C to 23–26°C. If conducting sports events under the revised upper thresholds proves difficult, taking measures for a possible high incidence of heat illness becomes crucial, such as placing additional medical resources, assisting heat acclimatization and cooling strategies for participants, and rule changes such as shorter match times and increased breaks.

A Database of Static Thermal Insulation and Evaporative Resistance Values of Dutch Firefighter Clothing Items and Ensembles.

The rescue operations' environment can impair firefighters' performance and increase the risk of injuries, e.g., burns and hyperthermia. The bulk and carried weight of heavy protection contributes to lower physical performance, higher metabolic load and internal body heat production. For recommending optimal protection for the tasks and incident scenarios, knowledge of clothing thermal properties is needed. However, detailed data on firefighter protective clothing systems are not available. The aim of the study was to provide scientific background and a dataset that would allow for validation of thermo-physiological models for task-specific conditions of rescue work. Thermal insulation of 37 single items and their variations and 25 realistic protective clothing ensembles were measured on a thermal manikin. Twelve (12) ensembles that evenly covered the whole insulation range were selected for evaporative resistance testing. The equations for summing up individual item's insulation to ensemble insulation and calculating clothing area factor were derived from the dataset. The database of a firefighter clothing system was created. In addition, the local and regional thermal properties of the clothing ensembles were provided for use in future validation of advanced thermo-physiological models for rescue worker exposure predictions and for designing decision aid tools.

Modelling and experimental study of thermo-physiological responses of human exercising in cold environments

A numerical human thermo-physiological model is developed with the consideration of characteristics of exercising people in cold environments. The developed model is characterized by: 1) the concept of net exercise efficiency which is used to correct the calculation of metabolic heat production by excluding mechanical energy; 2) the effects of low temperature on basal metabolic rate and basal blood flow rate; 3) the integration with a multi-layer clothing model to calculate the heat and moisture transfer through the clothing system, which takes into account the air gaps between the clothing layers to reflect the ventilation and air penetration effect from the ambient wind. Human subject experiment is conducted in a climate chamber to validate the proposed model. The human subject experiment is also carried out in a cold environment (−5 °C) combined with different air velocity conditions (still air, 2 m/s), taking into account the activities of different intensities (standing statically, 2 km/h walking and 7 km/h running). Thermo-physiological parameters including the core temperature, 8-point local skin temperatures and the clothing layer temperatures, are measured during the experiment. Comparison between the predicted and experimental results gives the root mean squared error (RMSE) of core temperature and mean skin temperature of 0.06–0.10 °C and 0.17–0.27 °C, respectively. RMSE values for local skin and clothing layer temperatures are no higher than 1.5 °C and most within 0.8 °C. The model is also validated with published data under various ambient temperature and activity intensity conditions. The proposed model is shown to be capable of predict the thermo-physiological responses of people exposed and exercising in cold environments.

Thermoregulatory clothing with temperature-adaptive multimodal body heat regulation

Thermoregulatory clothing plays an indispensable role in maintaining body thermal comfort and achieving building energy savings in response to fluctuating ambient. Existing temperature-adaptive clothing without external energy input has very limited thermoregulatory power because of the lack of simultaneous regulation of multiple heat-dissipation pathways. Here, we report thermoregulatory clothing with temperature-adaptive multimodal body-heat regulation (viz. convection, radiation, and sweat evaporation), which can automatically adapt to temperature change (15°C–35°C) within seconds by incorporating mechanically and infrared optically tailored metalized polyethylene actuators into textiles. Based on thermal manikin tests and thermo-physiological modeling, it demonstrates that the designed clothing can expand comfort zone by more than 2°C on both cold and hot sides, corresponding to about 30% building energy savings when used in indoor environment. The smart clothing can also significantly improve the comfort and performance of wearers when exposed to fluctuating or extreme environmental conditions. • A temperature-adaptive actuator is mechanically and infrared-optically tailored • The actuator is integrated into clothing for multimodal body-heat regulation • Thermal manikin tests and thermo-physiological modeling are conducted • Thermal comfort zone is expanded by more than 2°C on both cold and hot sides Chai et al. fabricate temperature-adaptive clothing, adopting metalized polyethylene film as actuator. The clothing can automatically adapt to ambient temperature change with multimodal body-heat regulation for improved thermal comfort and building energy savings.

A mathematical model for predicting cardiovascular responses at rest and during exercise in demanding environmental conditions.

The present research describes the development and validation of a cardiovascular model (CVR Model) for use in conjunction with advanced thermophysiological models, where usually only a total cardiac output is estimated. The CVR Model detailed herein estimates cardio-dynamic parameters (changes in cardiac output, stroke volume, and heart rate), regional blood flow, and muscle oxygen extraction, in response to rest and physical workloads, across a range of ages and aerobic fitness levels, as well as during exposure to heat, dehydration, and altitude. The model development strategy was to first establish basic resting and exercise predictions for cardio-dynamic parameters in an "ideal" environment (cool, sea level, and hydrated person). This basic model was then advanced for increasing levels of altitude, heat strain, and dehydration, using meta-analysis and reaggregation of published data. Using the estimated altitude- and heat-induced changes in maximum oxygen extraction and maximum cardiac output, the decline in maximum oxygen consumption at high altitude and in the heat was also modeled. A validation of predicted cardiovascular strain using heart rate was conducted using a dataset of 101 heterogeneous individuals (1,371 data points) during rest and exercise in the heat and at altitude, demonstrating that the CVR Model performs well (R2 = 0.82-0.84) in predicting cardiovascular strain, particularly at a group mean level (R2 = 0.97). The development of the CVR Model is aimed at providing the Fiala thermal Physiology & Comfort (FPC) Model and other complex thermophysiological models with improved estimations of cardiac strain and exercise tolerance, across a range of individuals during acute exposure to environmental stressors.NEW & NOTEWORTHY The present research promotes the adaption of thermophysiological modeling to the estimation of cardiovascular strain in individuals exercising under acute environmental stress. Integration with advanced models of human thermoregulation opens doors for detailed numerical analysis of athletes' performance and physiology during exercise, occupational safety, and individual work tolerability. The research provides a simple-to-validate metric of cardiovascular function (heart rate), as well as a method to evaluate key principles influencing exercise- and thermoregulation in humans.

An effective temperature derived from a mechanistic thermophysiological model for sows reared in hot climates

Increased metabolic heat production caused by breeding for higher productivity puts sows at a high risk of suffering from heat stress. To reasonably predict the actual thermal status of sows becomes essential for efficiently mitigating heat stress. However, the existing thermal indices for pigs neither have been verified by experimental data of sows nor consider the effect of the dynamic heat balance within sow's body. This study proposed an effective temperature for sows (ETS) in hot climates based on an existing 2-node mechanistic thermophysiological model. The ETS was verified to be able to reflect the thermal status of sows with desired level of confidence by using physiological parameters measured sow experiments. The relative humidity and airspeeds impact ETS and effective temperature (ET), which was predicted by other four ET models, at different levels. The impact of ambient temperature on ET could be well reflected by both ETS and the four ET models. In addition, the ETSs predicted under dynamic conditions with/without considering heat storage were comparable in temperate climate. However, the thermal status of sows in hot climate was predicted more precisely by ETS obtained from dynamic conditions considering heat accumulation in the body of the sow. Considering heat storage in dynamic simulations, ETS derived based on metabolic heat production predicted the thermal status of sows better than ETS derived based on total heat loss. • An effective temperature for sows (ETS) reared in hot climates derived. • Influences of relative humidity and airspeed on ETS investigated. • Impact of dynamic heat accumulation within sow's body on ETS revealed. • Dynamic ETS can better serve for the control of climatic conditions in pig houses.

The Metamatrix of Thermal Comfort: A compendious graphical methodology for appropriate selection of outdoor thermal comfort indices and thermo-physiological models for human-biometeorology research and urban planning

Ongoing climate crisis increase people's outdoor thermal stress, discouraging outside activities and intensifying indoor consumptions. Amelioration of urban microclimates is necessary to safeguard citizens from thermal strokes without energy-intensive strategies, ensuring future cities’ sustainable development. More than 200 calculation methods can be adopted with the purpose to design thermally comfortable public spaces, but existing literature lacks selection criteria to justifiably choose the appropriate ones. As resolution, the Metamatrix of Thermal Comfort has been developed. It's a graphical methodology, addressed to academicians and practitioners, that allows to rapidly comprehend and compare the specificities of 65 renowned thermal comfort indices and thermo-physiological models, explaining their mutual interactions. To promote practicality in thermal comfort studies, relying on calculation tools, an Operational version, including only 22 indices and models integrated in computer programs, is presented. A qualitative evaluation by approximately 30 criteria, such as climatic and physical factors, meteorological conditions, solar exposure and type of environment, allows to select thermal comfort calculation methods compatible to specific needs. To find appropriate computational tools, the Metamatrix of Software can be consulted. An application example is provided, proving the suitability of this graphical methodology as a powerful asset to apply outdoor thermal comfort-driven design to urban planning.

Study on a thermophysiological model for health assessment of showering environment in China

In China, the thermal environment of family showers in old communities is quite different from that of other living spaces, especially when the thermal environment changes drastically during showering, which can easily cause health problems. The human thermal physiological model is an effective tool to predict and evaluate the non-uniform and unstable shower thermal environment and human health risks. In this research, the showering experiment was carried out in a typical bathroom in an old community in China, during which environmental parameters such as air temperature, wall temperature and water temperature of the bathroom during the showering were recorded, and physiological parameters such as skin temperature, core temperature and blood pressure during the whole showering process were detected. Based on the multi-node numerical human body model of Stowljik and a cardiovascular control model with human body temperature as the driving force, a temperature-blood pressure coupling prediction model was established. The validity of the proposed model was examined for blood circulation. This predictive model can accurately reflect changes in physiological parameters and is verified as suitable for the health assessment of showering environment in residential buildings.

A two-node mechanistic thermophysiological model for pigs reared in hot climates – Part 2: Model performance assessments

The performance of the mechanistic two-node thermophysiological model was assessed using the experimental data with respect to gestating sows and fattening pigs. The relation between the convective heat transfer coefficient and local airspeed was derived from CFD simulation. The improvement brought by the newly proposed active module over the selected available models was analysed and discussed. Generally, the proposed two-node model with novel active modules for pulmonary ventilation rate (related to panting) and vasodilatation could predict rectal and skin temperatures for fattening pigs and gestating sows with an error of 0.88% and 3.96%, and 0.42% and 1.27% respectively. Employing existing relationships for pulmonary ventilation rate and vasodilatation resulted overestimations on the skin and rectal temperature. Additionally, the convective heat transfer coefficient should be developed based on the field conditions when the flow pattern is not similar to that under which the existing models were developed. The mean radiant temperature should be input with a decent level of accuracy when a high level of accuracy of prediction was necessary. The proposed model is reliable and robust when predicting the pig thermal status under various climate conditions and it is expected to be applied when operating the technical approaches to mitigate the heat stress. • Experimental measurements conducted under various test conditions. • Thermophysiological model for pigs validated using experimental data. • Influence of the active modules on the model performance investigated. • Convective heat transfer coefficient determined by CFD simulations.

A two-node mechanistic thermophysiological model for pigs reared in hot climates – Part 1: Physiological responses and model development

Due to the climate change and the increasing heat production of modern pigs (e.g. larger size sows having a larger number of piglets nowadays), pigs are more frequently suffering heat stress. In order to prevent the occurrence of heat stress, there is a need to develop a model which can effectively and efficiently predict the effect of ambient thermal environments on pigs. This study developed a two-node mechanistic model to simulate processes of pig thermoregulation and heat release to an ambient hot environment based on biophysical laws. The two-node model consists of a passive system, which can simulate the heat transfer processes occurring in the body core and at the skin surface, and an active system, which controls the thermoregulatory system based on a positive deviation of core temperature from its reference value under thermal neutral conditions. Vasodilatation and panting in relation to the ambient environment were specifically investigated and mathematically described based on the experimental data from previously published studies. The functions to predict vasodilatation and panting provided a relatively more detailed modelling of the thermo-physiological processes of the pigs compared to the available mechanistic models. The proposed two-node model was expected to effectively predict the thermal status of pigs under various combinations of environmental conditions without further tuning. • A mathematical model simulating pig thermoregulatory processes in hot climates. • Correlation between skin blood flow rate and ambient air temperature. • Correlation between pulmonary ventilation rate and ambient air temperature. • A novel active system developed with emphases on vasodilatation and panting.

A transient thermal sensation equation fit for the modified Stolwijk model

ABSTRACT There are different thermal perception models linked to a mathematical thermophysiological human model, with which the thermal sensation under stationary and/or dynamic conditions can be evaluated. Each of these perception and thermophysiological models have their own field of application. Stolwijk developed a thermophysiological human model without an associated thermal perception model, which today is still the basis for other mathematical thermophysiological models. Fiala developed the FPC model, also based on the Stolwijk model, and is one of the latest developments in the field of thermophysiological human models. In the FPC model, an equation is included with which the thermal sensation under stationary and dynamic conditions can be assessed; the so-called Dynamic Thermal Sensation (DTS). The DTS equation is, however, specifically developed for use in combination with the FPC model. In contrast to the Stolwijk model, the source code of the computer programs of the later developed thermophysiological human models is not freely available, which limits the use and applicability of the models in practice. It is precise because of the availability of the source code that the Stolwijk model is still used in industry and the research world. The question, therefore, arises: ‘To what extent can a human transient thermal sensation equation be derived, combined with the Stolwijk model, in a similar way to that used for the DTS equation in the FPC model?’.

Human thermophysiological models: Quantification of uncertainty in the output quantities of the passive system due to uncertainties in the control equations of the active system via the Monte Carlo method.

Uncertainty propagation analysis in the Fiala thermophysiological model is performed by the Monte Carlo Method. The uncertainties of the output quantities of the passive system, due to imported uncertainties in the coefficients of the control equations of the active system, caused by the variation of the experimental data, are computed. The developed and implemented in-house code is accordingly validated. The effect of the input uncertainties, in each of the four main responses (shivering, vasodilatation, vasoconstriction, sweating) of the active system, is separately examined by simulating the human exposure from neutral conditions to cold and hot environments. It is predicted that the maximum output uncertainties of the response mechanisms may be of the same order of magnitude as the imported ones, while the corresponding maximum uncertainties in core and skin temperatures always remain less than 2%. The maximum absolute deviations of the rectal (core) temperatures from their estimated mean values may be up to 0.72°C and 0.22°C, due to input uncertainties in shivering and sweating respectively, while the corresponding deviations due to uncertainties in vasomotion processes are negligible. The deviations, particularly the ones due to shivering, are significant, since differences of a few tenths of a degree may have large impact in human health. The maximum absolute deviations of the skin temperatures are 0.42°C in the hands due to uncertainties in shivering and 0.69°C in the feet due to uncertainties in vasodilatation. These deviations are less significant than the core ones, but they may still affect human thermal sensation and comfort. The present analysis provides a better insight in the dynamic response of the model and indicates which response mechanism needs to be further investigated by more accurate estimates in order to improve model reliability. It can be also applied in other human thermophysiological models.

Impact of wind turbulence on thermal perception in the urban microclimate

Ongoing urbanization has led to complexities in the urban terrain, increasing roughness length within the atmospheric surface layer, and introduced highly turbulent wind flow at pedestrian height. This research aims to explicitly examine the effect of wind flow turbulence on thermal perception under outdoor conditions. A wind tunnel with passive grid was used to introduce turbulence into simulated wind conditions. Thermal physiological (skin temperature) and perceptual (questionnaire) responses were collected from 20 college-age subjects during the exposures to various simulated urban wind conditions. Results confirm that increased turbulence intensity enhances perceived coolness by reducing the skin temperature. We updated the convective heat transfer coefficient in a numerical skin thermoreceptor model and also Gagge's two-node thermophysiological model so that they both reflect more accurately the effects of turbulence intensity on skin temperature. Skin temperatures simulated with the modified models were in good agreement with experimental observations, and corrected the un-modified model's 30% and 50% underestimation of mean skin temperature decrement for standing and cycling conditions respectively. These findings contribute to the broader goal of a thermal comfort model for application to urban microclimate.