Thermoregulation Model Research Articles

Prediction on Chinese elderly's thermo-physiological and cardiovascular responses to non-uniform and transient thermal environment during getting-up process

Getting-up process after sleep would typically involve the non-uniform transition with temperature reduction, increased activity level, and change in clothing insulation, which is rarely explored in existing research. Due to the decline of physiological adaptability of the elderly, they may have sudden changes in physiology under transient environment. It is necessary to develop prediction models for the elderly to prevent or reduce health risks. The aim of this research is to predict the thermo-physiology and cardiovascular responses to non-uniform and transient thermal environments during getting-up process, a 4-node thermoregulatory-cardiovascular predicted model was established based on Gagge's thermoregulatory and heart rate model in International Organization for Standardization. Experimental data of twenty-six Chinese elderly subjects aged over 60 at a caring home in Chongqing both in winter and summer conditions was collected for validating. The results showed that the non-uniformity and dynamic states were 5.0–15.0 °C temperature differences between cover and bedroom. Core and overall skin temperatures decreased by 0.1–0.3 °C, while the heart rate increased by 5–10 %. Bare skin temperature decreased significantly by 0.2–1.0 °C. It implied that the process posed a potential risk to body cooling, local thermal discomfort, and cardiovascular health in the elderly, which was more severe in winter. The prediction result's error was below 6.0 %, which was more accurate by 6.0 %–18.0 % than that of typical models. This research can provide a reference for creating comfortable and healthy bedroom temperatures after sleeping for the elderly by intelligent air conditioning at residences and care homes.

A modified multi-node human thermoregulation model with improved sweating response to simulate human physiological behaviours in warm and hot environments

The present research developed a modified multi-node thermoregulation model derived from the renowned Tanabe and JOS series models (JOS-2 and JOS-3). The JOS-3 model's predictions showed an abrupt spike in mean skin temperature, contradicting the findings from experiments. The JOS-3 model's sweating mechanism exhibits an inconsistency, and the sweating mechanism is not triggered promptly and accurately, leading to a sudden rise in skin temperature. This disparity significantly impacts the ability of the model to precisely replicate thermoregulatory responses under various climatic conditions and levels of physical activity. The proposed modified thermoregulation model extends the JOS-3 model by modifying the set-point temperature and sweating signals. The performance of the developed modified thermoregulation model is thoroughly analyzed under various conditions involving different environmental conditions, activity levels, and clothing types. The proposed model eliminates abrupt rise in the mean skin temperature and improves its prediction accuracy, notably reducing mean skin temperature RMSE in hot-humid conditions (0.66 °C vs. 0.85 °C) compared to the JOS-3 model. In hot-dry settings, improvements are significant, reducing the mean skin temperature and core temperature RMSE (0.48 °C vs. 0.06 °C and 0.05 °C vs. 0.02 °C, respectively). Overall, the modified thermoregulation model offers a reliable and accurate solution to analyze human physiological conditions for a wide range of practical problems.

Research on The local clothing thermal insulation prediction model with different dress state of indoor occupants

In a dynamic and non-uniform thermal environment, adjusting personal dress states is an effective method for achieving thermal comfort. During this process, clothing thermal insulation, as a key parameter in human thermoregulation models, is not uniformly distributed across the body. However, current thermal comfort standards do not provide a direct method for obtaining local clothing thermal insulation. Based on field surveys, this study summarized typical year-round clothing ensembles and common dress states, and tested the local thermal insulation of 40 clothing ensembles and 60 individual garments using a thermal manikin. Subsequently, a prediction model for the local thermal insulation of clothing ensembles was developed based on the overall thermal insulation of individual garments. Meanwhile, it was found that changes in dress state significantly alter the thermal insulation of body parts such as the arms and chest. Simulations conducted using the JOS-3 and UCB models revealed that the lower the ambient temperature, the greater the impact of changes in local clothing thermal insulation on human skin temperature and thermal sensation. Finally, a correction model for different dress states was developed, and comparison with existing models showed the lower root mean square error (RMSE) between the predicted and measured values. This study provides a more accurate and convenient method for determining local thermal insulation, offering a data foundation for improving indoor environmental control and enhancing energy efficiency.

Evaluating thermal sensation in outdoor environments - Different methods of coupling CFD and radiation modelling with a human body thermoregulation model

Thermal comfort is vital in outdoor spaces for social interaction and recreation. With increases in heat wave events and global warming, it becomes more essential to be able to assess heat stresses. Outdoor spaces have asymmetrical and transient environmental factors such as solar radiation, long-wave radiation and natural wind, which makes the thermal perception outdoors largely different from indoors. Traditional thermal comfort models have some limitations and less accuracy when applied to outdoor spaces. The current study focuses on developing a method to assess the human thermal interaction with the complex outdoor environment and the consequent thermal sensation. Computational Fluid Dynamics (CFD) and radiation modelling are coupled to the Joint System Thermoregulation (JOS-3) model to assess the skin temperature, based on which thermal sensation is predicted using the updated thermal comfort model developed by UC Berkeley. The proposed methodology is applied to assess the thermal sensation of human subjects standing in front of an outdoor radiant cooling hub. The important finding is that the one-way coupling, i.e., no skin temperature feedback to the CFD simulation, works reasonably well in the outdoor environment, and that convective heat transfer coefficients available from experimental studies can be coupled with CFD simulated environmental parameters to obtain more reliable convective heat exchange to avoid meshing the geometry of a human body in CFD and further reduce the computing cost.

Human thermal comfort in kitchen with different ventilation modes based on a coupled CFD and thermoregulation model

Kitchen ventilation is crucial in effective removal of pollutants and heat in the enclosed kitchens to ensure occupants' thermal comfort and health. However, mechanical ventilation systems, such as range hoods and make-up air systems, often create non-uniform and dynamic thermal conditions, posing challenges for traditional comfort metrics. In response, this study utilizes Computational Fluid Dynamics (CFD) coupled with a human thermoregulation model to evaluate the thermal comfort across various kitchen ventilation modes. Our findings reveal significant non-uniformity in indoor thermal environments surrounding the occupant, with differences in ambient temperature reaching 14.2 °C and air velocity up to 0.64 m/s, directly impacting occupants' comfort. Notably, mechanical ventilation employing air curtains for make-up air surpasses natural methods, enhancing overall thermal sensation by 42 % and reducing mean drought rates by 70 % during winter. Additionally, ceiling supply systems improve upper body comfort in summer, offering personalized thermal comfort solutions, and achieves optimal thermal comfort conditions at a make-up air temperature of 25 °C. This research contributes valuable insights into selecting appropriate ventilation strategies for residential kitchens, thereby promoting occupants' well-being and health.

Numerical simulation and experimental validation of human head thermoregulation under motorbike helmet

Headgear including helmets are essential and law-enforced in many countries. However, one of the most main reasons drivers give for not wearing helmets is the discomfort and excessive heat that helmets create. More comfortable helmets can potentially increase helmet use among population, thus play a major role in people safety. In this study, a thermoregulation model of the human helmeted head was created using Finite Element Analysis (FEM) and based on an anatomically correct medical image-based CT-scan model. The model investigated three cases with different wind speeds namely; 1km/h, 20km/h, and 50km/h. In addition, the combined FEM Head-helmet model results is verified by an experimental trail. The compared results shown the ability of the model to predict the head temperature profile and results were in good agreement with experiment. The established model is to predict the thermal distribution of the head parts under helmet conditions. Results reflect the thermoregulatory responses of the rider parts, thus providing grounds for suggestions and recommendations for the helmet design and processing.

Effectiveness of cooling interventions on heat-stressed dairy cows based on a mechanistic thermoregulatory model

Addressing heat stress in dairy farming is a substantial challenge, and there is an increasing need for efficient cooling systems, even in regions with moderate climates. Accurately predicting the efficacy of diverse cooling options under different climatic conditions is crucial for reducing heat stress in modern high-producing dairy cows, aligning with sustainability goals. This study assessed the effectiveness and feasibility of different cooling measures, including fans, sprinklers with fans, and evaporative air cooling, using a dynamic thermoregulatory model. This 3-node dynamic model was developed based on recent animal data simulating the processes of dairy cows' physiological regulation and heat dissipation under various environmental conditions. The cooling methods were based on two principles: enhancing heat loss from cows using fans with/without sprinklers; lowering the ambient temperature by evaporative air cooling. The predicted results were discussed and partly validated using the experimental data from the literature. The predictions indicated that fan cooling alone was effective in ambient temperatures below 26 °C, while higher temperatures required a combination of fans and sprinklers for effective heat stress alleviation. Consideration of individual cow characteristics and environmental factors, including fan speed and wetting area, is crucial for optimal cooling. In regions with high relative humidity, evaporative air cooling could be counterproductive to some extent. The model's predictions largely aligned with experimental data, demonstrating its capability to forecast cooling effects under various climatic conditions. Future model improvements included refining calculations for water holding capacity, wetted skin area, and dry time, depending on the influence of spraying time and rate.

The thermoneutral zone in women takes an “arctic” shift compared to men

Conventionally, women are perceived to feel colder than men, but controlled comparisons are sparse. We measured the response of healthy, lean, young women and men to a range of ambient temperatures typical of the daily environment (17 to 31 °C). The Scholander model of thermoregulation defines the lower critical temperature as threshold of the thermoneutral zone, below which additional heat production is required to defend core body temperature. This parameter can be used to characterize the thermoregulatory phenotypes of endotherms on a spectrum from "arctic" to "tropical." We found that women had a cooler lower critical temperature (mean ± SD: 21.9 ± 1.3 °C vs. 22.9 ± 1.2 °C, P = 0.047), resembling an "arctic" shift compared to men. The more arctic profile of women was predominantly driven by higher insulation associated with more body fat compared to men, countering the lower basal metabolic rate associated with their smaller body size, which typically favors a "tropical" shift. We did not detect sex-based differences in secondary measures of thermoregulation including brown adipose tissue glucose uptake, muscle electrical activity, skin temperatures, cold-induced thermogenesis, or self-reported thermal comfort. In conclusion, the principal contributors to individual differences in human thermoregulation are physical attributes, including body size and composition, which may be partly mediated by sex.

Thermoregulation enhances survival but not reproduction in a plant‐feeding insect

Abstract Temperature influences nearly all aspects of fitness. However, reproduction is often more thermally sensitive than survival. Thermoregulation must maintain performance in both components of fitness to buffer populations from environmental change. We assessed the fitness benefits of thermoregulation in Enchenopa binotata treehoppers. Under realistic mesocosm conditions, we quantified fine‐scale microclimates using 3D‐printed operative temperature models. We then compared operative temperatures to treehopper body temperatures and translated patterns of thermoregulation into variation in survival and reproduction. We also assessed two thermoregulatory mechanisms: precise microclimate choice and heat‐escape behaviours. Finally, we applied our results to evaluate if arthropod thermoregulation is accurately characterized by two theoretical models commonly used to simulate responses to environmental change. We found substantial thermal variation at fine spatial scales relevant to insects: at a single point in time, temperatures within 30‐cm‐tall plants spanned ranges up to 19°C (23–42°C). Lethal operative temperatures were common when air temperatures were high. However, heat escapes allowed treehoppers to almost entirely avoid lethal temperatures. By contrast, individuals thermoconformed in the absence of lethal operative temperatures. This finding suggests that precise microclimate choice imposes high costs due to thermal uncertainty at fine spatial scales. Furthermore, given the narrow range of temperatures in which reproduction occurs, thermoregulation is unlikely to maintain reproduction. Thermoregulation was most effective in the lowest‐quality and most spatially variable thermal habitats. Treehopper thermoregulation therefore more closely follows cost–benefit models of thermoregulation compared to models that account for inhibited movement at extreme temperatures. Overall, even if thermoregulation can prevent lethal heat stress, it may have limited capacity to buffer arthropods and other small ectotherms from environmental change if it cannot maintain reproductive performance. Read the free Plain Language Summary for this article on the Journal blog.

A thermoregulation model based on the physical and physiological characteristics of Chinese elderly

Given the increasing aging population and rising living standards in China, developing an accurate and straightforward thermoregulation model for the elderly has become increasingly essential. To address this need, an existing one-segment four-node thermoregulation model for the young was selected as the base model. This study developed the base model considering age-related physical and physiological changes to predict mean skin temperatures of the elderly. Measured data for model optimization were collected from 24 representative healthy Chinese elderly individuals (average age: 67 years). The subjects underwent temperature step changes between neutral and warm conditions with a temperature range of 25–34 °C. The model's demographic representation was first validated by comparing the subjects' physical characteristics with Chinese census data. Secondly, sensitivity analysis was performed to investigate the influences of passive system parameters on skin and core temperatures, and adjustments were implemented using measurement or literature data specific to the Chinese elderly. Thirdly, the active system was modified by resetting the body temperature set points. The active parameters to control thermoregulation activities were further optimized using the TPE (Tree-structured Parzen Estimator) hyperparameter tuning method. The model's accuracy was further verified using independent experimental data for a temperature range of 18–34 °C for Chinese elderly. By comprehensively considering age-induced thermal response changes, the proposed model has potential applications in designing and optimizing thermal management systems in buildings, as well as informing energy-efficient strategies tailored to the specific needs of the Chinese elderly population.

Modeling thermoregulatory responses during high-intensity exercise in warm environments.

The six cylinder thermoregulatory model (SCTM) has been validated thoroughly for resting humans. This type of modeling is helpful to predict and develop guidance for safe performance of work and recreational activities. In the context of a warming global climate, updating the accuracy of the model for intense exercise in warm environments will help a wide range of individuals in athletic, recreational, and military settings. Three sets of previously collected data were used to determine SCTM accuracy. Dataset 1: two groups [large (LG) 91.5 kg and small (SM) 67.7 kg] of individuals performed 60 min of semirecumbent cycling in temperate conditions (25.1°C) at metabolic rates of 570-700 W. Dataset 2: two LG (100 kg) and SM (65.8 kg) groups performed 60 min of semirecumbent cycling in warm/hot environmental conditions (36.2°C) at metabolic rates of 590-680 W. Dataset 3: seven volunteers completed 8-km track trials (∼30 min) in cool (17°C) and warm (30°C) environments. The volunteers' metabolic rates were estimated to be 1,268 W and 1,166 W, respectively. For all datasets, SCTM-predicted core temperatures were found to be similar to the observed core temperatures. The root mean square deviations (RMSDs) ranged from 0.06 to 0.46°C with an average of 0.2°C deviation, which is less than the acceptance threshold of 0.5°C. Thus, the present validation shows that SCTM predicts core temperatures with acceptable accuracy during intense exercise in warm environments and successfully captures core temperature differences between large and small individuals.NEW & NOTEWORTHY The SCTM has been validated thoroughly for resting humans in warm and cold environments and during water immersion. The present study further demonstrated that SCTM predicts core temperatures with acceptable accuracy during intense exercise up to 1,300 W in temperate and warm environments and captures core temperature differences between large and small individuals. SCTM is potentially useful to develop guidance for safe operation in athletic, military, and occupational settings during exposure to warm or hot environments.

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).

Predicting survival time for cold exposure by thermoregulation modeling

BackgroundExtreme temperatures are becoming increasingly common due to global warming. Extreme cold and heat events lead to an increase in mortality rates. More deaths occur in cold weather as a result of hypothermia. However, the change progress of body core temperature and the survival time during cold exposure has yet to be extensively studied. ObjectivesTo establish a mathematical thermoregulatory model for prolonged cold air exposure and to propose a method for predicting survival time under sedentary conditions. MethodsWe extended the classical multi-segment multi-node human thermoregulatory model by considering the effects of thermoregulatory fatigue on shivering and vasoconstriction based on the variable setpoint theory. The core threshold temperatures and the sensitivity of the responses decreased with the degree of fatigue (fa). The model was then used to systematically examine the effects of environmental parameters on the time course of body core temperature in the development of fatal hypothermia. A new wind chill index was constructed based on the simulated data of our thermoregulatory model to estimate the survival time. ResultsOur extended thermoregulatory model predicted that during prolonged cold air exposures, body core temperature would decrease in three distinct stages: an initial decrease due to uncompensated cooling load, an equilibrium plateau due to shivering, and a final rapid drop due to thermoregulatory fatigue. Fatal hypothermia occurred at the third stage due to impaired shivering and vasoconstriction caused by fatigue. Lower air temperature and higher air speed can accelerate the occurrence of hypothermia. We proposed a predictive equation for survival time, i.e., the maximum endurance time before fatal hypothermia occurs, which is an exponential function of the wind chill index, and the newly defined wind chill index considers the contribution from both air temperature and air speed. ConclusionsWe suggest a new thermoregulatory model to predict the fatal hypothermia due to thermoregulatory fatigue during cold air exposure. We proposed a survival time chart based on a new wind chill index, which can be used to alert the early risk of fatal hypothermia during extreme cold events.

An adaptive cabin air recirculation strategy for an electric truck using a coupled CFD-thermoregulation approach

Cabin climatization is one of the largest auxiliary loads in an electric vehicle, and its performance significantly affects the driving range. Recirculating climatized air from the cabin has been shown to reduce energy consumption, but at the risk of fogging the windows and deteriorating the air quality. Therefore, many automobile manufacturers refrain from adopting it at low ambient temperatures. In this paper, an adaptive recirculation strategy that takes these issues into account is proposed and studied on an electric truck cabin while heating. Numerical simulations were performed using a coupled CFD-thermoregulation model, with the consideration of humidity and CO2. The JOS-3 thermoregulation model was employed for estimations of skin temperatures and evaporation of vapor from the skin, and the Berkeley comfort model was used to evaluate the comfort metrics. Ten scenarios were considered at various vehicle speeds, temperatures, and relative humidity levels while evaluating them with and without the proposed return-air strategy. The controller adapted between humidity and CO2-critical conditions during run-time. The fresh-air mass flow requirements reduced with increasing difference between the setpoint and ambient vapor mass fractions under humidity critical conditions, and plateaued at 10 g/s where CO2 was more critical. The proposed strategy provided energy savings ranging from 9% to 34% depending on the operating condition.

Analysis of glove local microclimate properties for various glove types and fits using 3D scanning method

Due to their geometry and thermal physiology, hands are most vulnerable to cold weather injuries and loss of dexterity. Gloves are the most common for hand protection during exposure to extreme thermal and hazardous environments. Although glove microclimate properties such as area factor, air gap thickness, and contact area play a significant role in thermal protection, identifying local (at individual hand segments) glove microclimate properties is still a research gap. For the first time, the glove-microclimate properties for 16 hand segments at high spatial resolution were analyzed by employing state-of-the-art hand-held 3D scanner and post-processing techniques for different glove types. Our results clearly indicate that the glove area factor for distal phalanges is significantly higher (by 49.8 %) than that for other hand segments, which increases the heat transfer from distal phalanges. In contrast, average air gap thickness was relatively uniform across all hand segments. The glove type had a pronounced effect on glove microclimate properties, e.g., bulky and heavy cold weather protective gloves had a larger average air gap thickness and glove area factor. Regression models are also developed to estimate the glove microclimate properties from simple measurement (i.e., ease allowance). Overall, this study provides essential information for the design and development of protective gloves that can help improve safety, comfort, and dexterity. Methods and mathematical models developed in this study also contribute to facilitating extremity (e.g., hand) focused thermoregulation modeling, hazard simulation, injury prediction, ergonomic design, optimum performance (dexterity and tactility) along with thermal protection.

Integration of computer-simulated persons with multi-node thermoregulation model that considers the effect of clothing for skin surface temperature distribution analysis

There is a growing demand for more advanced and diverse computer-simulated persons (CSPs) to accurately evaluate the indoor environmental quality and analyze the human body interactions with environmental factors. This study aimed to develop a CSP targeting the ANDI thermal manikin, which regulates skin temperature and thermal functions through a multi-node thermoregulation model, that is, the development of a digital twin for the ANDI thermal manikin. Additionally, to ensure the prediction reliability of the numerical thermoregulation model applied to the CSP using computational fluid dynamics (CFD) analysis, the CFD results were compared with those from the chamber experiment using an ANDI thermal manikin. We conducted integrated analyses of the CSP using the Fiala thermoregulation model to calculate the metabolic heat production, at transfer between different layers and sections, and skin surface temperature. The CFD analysis was performed using the CSP under the same environmental conditions as those used in the experiment. The CSP analysis results reproduced the experimental results obtained using the thermal manikin in the thermal comfort evaluation with acceptable accuracy, and the root mean square deviation of the predicted mean skin temperature was approximately 0.195. Furthermore, the importance of detailed clothing geometry was highlighted by confirming that the thickness of the ventilation layer between the skin and clothing has a significant effect on the thermal performance. The comprehensive prediction method for indoor environments based on the advanced CSP developed in this study can contribute to human-centered indoor environmental planning through parametric analyses under various environmental scenarios.

Thermoregulation of human hands in cold environments and its modeling approach: A comprehensive review

Cold environments pose significant risks to human health, well-being, and productivity, with hands being particularly vulnerable to cold stress and injuries. Mathematical models of hand thermoregulation have emerged as valuable tools for understanding and predicting hand performance and injuries, especially in extremely cold environments. While significant progress has been made in mathematical modeling, a systematic review of these models is currently lacking. This paper aims to fill this knowledge gap by conducting a comprehensive review of the existing literature on hand thermoregulation models in cold environments. It begins with an introduction to the unique thermophysical and thermophysiological characteristics of the hand. It then summarizes the historical evolution of hand thermoregulation models. The essential principles for developing hand-specific thermoregulation models are outlined, encompassing modeling of hand anatomy and geometry, thermophysiological responses, and heat transfer between the hand and its surroundings. This review presents prediction methods for cold injuries and hand performance. The need for future advancements in hand thermoregulation modeling is emphasized. Specifically, achieving a more realistic representation of hand anatomy and geometry, as well as incorporating location-dependent thermophysical properties and physiological behaviors of the hand, are identified as crucial areas for improvement to enhance prediction accuracy. This review will contribute to a deeper understanding of hand thermoregulation mechanisms and their interaction with cold environments, as well as the development of more reliable and applicable models.

Myotendinous Thermoregulation in National Level Sprinters after a Unilateral Fatigue Acute Bout—A Descriptive Study

In the last decade there has been a growing interest in infrared thermography in the field of sports medicine in order to elucidate the mechanisms of thermoregulation. The aim of this study was to describe bilateral variations in skin temperature of the anterior thigh and patellar tendon in healthy athletes and to provide a model of baseline tendon and muscle thermoregulation in healthy sprinters following a unilateral isokinetic fatigue protocol. Fifteen healthy national-level sprinters (eleven men and four women), with at least 3 years of athletic training experience of 10–12 h/week and competing in national-level competitions, underwent unilateral isokinetic force testing and electrostimulation in which their body temperature was measured before, during, and after the protocol using an infrared thermographic camera. ANOVA detected a significant difference in the time × side interaction for patellar temperature changes (p ≤ 0.001) and a significant difference in the time/side interaction for quadriceps temperature changes (p ≤ 0.001). The thermal challenge produces homogeneous changes evident in quadriceps areas, but not homogeneous in tendon areas. These data show that metabolic and blood flow changes may depend on the physical and mechanical properties of each tissue. Future research could be conducted to evaluate the predictive value of neuromuscular fatigue in the patellar tendon and quadriceps after exercise in order to optimize post-exercise recovery strategies.

Enhancing energy efficiency and comfort with a multi-domain approach: Development of a novel human thermoregulatory model for occupant-centric control

Occupant Centric Control (OCC) strategies aims to achieve a more personalized and comfortable indoor environment, translating occupants' comfort requirements into real environmental conditions. This strategy relies on a multilevel non-linear programming optimization procedure to determine optimal thermo-hygrometric setpoints. The objective is to minimize space heating and cooling requirements while addressing multi-domain comfort concerns related to individual thermal sensations and perceived air quality. To facilitate this process, this study adopts a novel Personal Comfort Model (PCM), incorporating physiological factors to predict occupants' thermal sensations and CO2 intakes. The PCM's reliable predictive capabilities are confirmed through validation with real experimental data from a test room at the University of Perugia. For detailed energy analyses, considering occupants' subjective comfort preferences, the PCM is seamlessly integrated into DETECt, an in-house building energy performance simulation tool developed by the University of Naples Federico II, for the design of advanced control algorithms and energy efficiency strategies. To effectively manage the HVAC system, a model predictive control is implemented, using the determined setpoints to ensure mechanical ventilation and maximize cost savings. The proof of concept for the developed methodology involves simulating experimental tests using the thermal model of the human body and the new facility management system, to be simulated and optimized by means of the enhanced building energy performance simulation tool, exploited for the design and operation of more occupant-centric and sustainable buildings. The proposed study demonstrates that through the developed OCC strategy enables a significant reduction in thermal discomfort (40 % and 60 % less than the occupation time for test 1 and test 2, respectively) compared to reference scenarios. Additionally, energy analysis reveals high efficiency, achieving savings of 12.8 % and 7.8 % of electricity consumed for HVAC system operation.

Evaluation of thermal properties and thermoregulatory impacts of lower back exosuit using thermal manikin

As exoskeletons and exosuits rapidly transition from laboratory to practice, the thermal discomfort posed by wearing the devices is emerging as a significant challenge towards their widespread adoption. We use a thermal manikin coupled with a thermoregulation model to evaluate the thermal properties and thermophysiological impacts of such devices. We measure thermal and evaporative resistances of summer and full clothing coupled with a legacy low-back supporting exosuit and its successor that features two design alterations to improve the user's thermal comfort. We quantify the decrease in evaporative resistance provided by substantial perforation of the back portion of the updated exosuit. The thermal manikin can replicate local skin temperature decrease associated with a release of a dual-mode thigh body attachment measured during a prior human trial. Using the thermal manikin coupled with a thermoregulation model, we simulate how the updated exosuit with several levels of assumed metabolic rate reduction impacts sweat rate, skin and core temperature changes during multiple work-rest cycles in a hot and humid climate. While a large metabolic rate reduction (>15%) is required to significantly slow the core temperature increase, even a minor metabolic rate reduction (5%) could provide a substantial reduction (20%) in the sweat rate (i.e. could reduce dehydration). Results suggest that thermal manikins with a thermoregulation model are an effective and efficient platform for comparing exosuit design features and for improving their thermal aspects. Our study highlights the comprehensive method and importance of considering thermal aspects when designing exosuits for occupational use.