Thermal Sensation Of Occupants Research Articles

Exploring the correlation and synchronicity between environmental factors and occupant thermal response in dynamic outdoor cabin environments

To improve the cabin thermal environment and explore advanced automotive air-conditioning control methods, it is essential to understand the key factors affecting occupant thermal response as well as the synchronicity of the thermal response to environmental changes in outdoor conditions. Given the current gaps in research, this study conducted outdoor experiments in summer to analyze the correlation and synchronicity between the cabin thermal environment and occupant thermal sensation as well as facial skin temperature. Results showed that, during the cooling phases of experiments with high initial cabin air temperatures, occupant thermal sensation improved significantly within 7 min. After 15 min, facial skin temperature and thermal sensation reached quasi-steady states. Thermal sensation was primarily influenced by air temperature, followed by solar radiation, and exhibited significant synchronicity with changes in these factors. When the air temperature stabilized at around 26 °C, every 200 W/m2 of solar radiation exposure increased the thermal sensation unit during the 40-min experiment period. Cheek and nose skin temperatures were significantly correlated with air temperature and solar radiation, and were sensitive to environmental changes, synchronizing with changes in air temperature and relative humidity. Further analysis showed the feasibility of using cheek and nose skin temperatures to characterize the occupant thermal sensation in a cabin. Additionally, this study found sex differences in the occupant thermal response in a cabin. The results provide insight into the key optimization parameters for comfort-oriented cabin thermal environment design and offer support for future air conditioning control in cabins based on thermal imaging.

Hot, cold, or just right? An infrared biometric sensor to improve occupant comfort and reduce overcooling in buildings via closed-loop control

To improve occupant comfort and save energy in buildings, we have developed a closed-loop air conditioning (AC) sensor-controller that predicts occupant thermal sensation from the thermographic measurement of skin temperature distribution, then uses this information to reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating AC output. Taking measures to protect privacy, it combines thermal-infrared (TIR) and color (visible spectrum) cameras with machine vision to measure the skin-surface temperature profile. Since the human thermoregulation system uses skin blood flow to maintain thermoneutrality, the distribution of skin temperature can be used to predict warm, neutral, and cool thermal states. We conducted a series of human-subject thermal-sensation trials in cold-to-hot environments, measuring skin temperatures and recording thermal sensation votes. We then trained random-forest classification machine-learning models (classifiers) to estimate thermal sensation from skin temperatures or skin-temperature differences. The estimated thermal sensation was input to a proportional integral (PI) control algorithm for the AC, targeting a sensation level between neutral and warm. Our sensor-controller includes a sensor assembly, server software, and client software. The server software orients the cameras and transmits images to the client software, which in turn assesses occupant skin temperature distribution, estimates occupant thermal sensation, and controls AC operation. A demonstration conducted in a conference room in an office building near Houston, TX showed that our system reduced overcooling, decreasing AC load by 42% when the room was occupied while improving occupant comfort (fraction of “comfortable” votes) by 15 percentage points.

The impact of socio-demographic factors on occupants’ thermal comfort and sensation: An integrated approach using statistical analysis and agent-based modeling

The thermal comfort and thermal sensation of occupants can significantly impact the overall performance of the building. However, very little is known about how occupants perceive or thermally respond to their building interior layouts or what factors affect their thermal comfort and sensation, particularly in low-income residential homes. Through a post-occupancy evaluation of 394 occupants from 190 households in Chittagong, Bangladesh, this study examines the socio-demographic factors (i.e., gender, age, and home ownership) that influence occupants' thermal comfort and sensation. The chi-square, Cramer's V, and Lambda tests were used to statistically analyze the impact of selected socio-demographic factors. The results showed that female occupants were significantly less satisfied than male occupants with their existing thermal environment. However, the study did not find any influence of age or home ownership on occupant thermal comfort. Furthermore, comprehensive agent-based modeling (ABM) was implemented to support the results of the statistical analysis of the influence of gender on occupants' thermal comfort levels. The ABM was designed based on the theory of planned behavior. As a simulation output, the ABM model stochastically estimated occupants' thermal comfort and sensation level in terms of the predicted mean vote. Similar to the statistical analyses, the results of the ABM also indicated better thermal comfort and thermal sensation for male occupants than for female occupants. The results of the study can serve as a guideline for better understanding the socio-demographic factors involved in the modeling or remodeling of occupant thermal comfort in developing economies.

Human response to the bed thermal environment generated by a ventilated mattress combined with local heating

A ventilated mattress (VM) was designed to withdraw the polluted air of the bed micro-environment through an opening located near the feet, moving the air inside the mattress to where it was cleaned and could be discharged back to the room or ducted out of the room. Thermal manikin experiments indicated a risk of uncomfortable local cooling of user's feet. The design of the VM was therefore improved by incorporating local heating (LH). The response of 30 subjects to the bed thermal environment (BTE) generated by the improved design was studied while they lay awake on the VM at room temperatures: 19 °C, 23 °C and 28 °C. Based on the subjects' responses the flow rate through the VM and the LH were adjusted to provide acceptable whole body and local thermal sensation. The surface temperature of the mattress, the air temperature and relative humidity in the BTE and the temperature and flow rate of the air exhausted through the VM were measured. The results show that the VM if used alone may cause unacceptable local body cooling at 19 °C and 23 °C, so some LH was required. At 28 °C the VM improved subjects' thermal comfort. Continuous control of the VM and the LH improved the acceptability of the BTE and decreased the risk of local discomfort. The surface temperature of the mattress measured near the feet correlated well with occupant's thermal sensation and could be used to control the operation of the VM fan speed and the LH.

Quantification of visual thermal perception changes in a wooden interior environment using physiological responses and immersive virtual environment

Wood can be used for various applications, such as for carbon storage, to enhance structural strength, and to promote biophilia; additionally, wooden building can positively affect the carbon footprint and well-being of occupants through changes in the thermal sensation by hue-heat hypothesis-based visual effects. However, previous studies focusing on the visual effect of indoor wood have limitations in terms of physical model implementation and subjective evaluation. In this study, an indoor wood application model is implemented using Virtual reality, and the subjective thermal sensation is quantitatively measured through physiological response measurement. The occupant's subjective thermal sensation is higher in the wood condition than in the nonwood condition and the occupant feels warmer as the level of wood application is increased. Physiological response, skin temperature, electrodermal activity, and electroencephalogram exhibit significant differences according to the level of wood application and similar tendencies to the data measured for the prediction of thermal sensation in previous studies. Using VR, the increase in the thermal sensation of occupants through the visual effect of wood without temperature control is confirmed through objective physiological parameters.

Where should the thermal image sensor of a smart A/C look?-Occupant thermal sensation model based on thermal imaging data

Applying thermal imaging sensor to air conditioner for monitoring human thermal sensation and achieving dynamic settings may satisfy occupants' thermal needs while saving energy. The existing studies are mostly based on single-view imaging to build the model and ignore the possible differences in body surface temperature on thermal sensation response by gender, etc., which may have many limitations. Subject experiments were conducted in an artificial climate chamber to obtain subjective questionnaires and thermal images of the exposed frontal face, lateral face, top of the head, forearm, and hand dorsum of 27 subjects in this study. By applying machine learning classification algorithms and global optimal regression algorithms, the temperature collection zones that can accurately reflect the thermal sensation of both genders in each view were analyzed, and a two-stage thermal sensation assessment model applicable to multiple views was developed. Of the various imaging views, the frontal view of the face is the best, followed by the lateral view of the face, the top view of the head, and the forearm/hand dorsum view. For male and female, the mean absolute errors of the thermal sensation assessment model established were 0.41–0.49 and 0.50–0.53 thermal sensation units. In addition, gender differences were found in the response of head surface temperatures to thermal sensation. The results obtained can provide a reference for the application of thermal image sensor to smart air conditioners.

Influencing assessment of different heating modes on thermal comfort in electric vehicle cabin

Electric vehicle (EV) is more environmental-friendly than gasoline vehicle because the main power is not petrol. For the heating system, the waste heat generated by engines is recycled to heat the cabin of gasoline ones, while the EV need extra electric energy consumption for heating the cabin which decreases the driving range. Personal comfort system (PCS) has been reported that it is an alternative technique to improve occupant thermal comfort and indirectly save building heating energy. This study aims to investigate the occupants’ thermal sensation under four heating modes in the EV cabin in winter, including no heating, only PCS, only air conditioning, and both air conditioning and PCS. The field survey is conducted in a parked EV with 12 subjects. Three thermal comfort indexes (PMV, SET*, and operative temperature Top) are used and assessed for their applicability in the thermal environment of the EV. Results show that the thermal environment in the cabin is non-uniform and dynamic with the air conditioning mode, while the PCS mode just slightly affects the temperature differences inside. Meanwhile, the subjects’ thermal sensations cannot maintain neutral or warmer under the PCS mode only. The results of PMV are lower than the subjects’ actual thermal sensation votes (TSV), while the results of SET* and Top show significant linear relationships with the TSV for the correlation coefficients above 0.80. Compare to the air conditioning mode, the neutral SET* and neutral Top are decreased by 2.7 °C and 1.6 °C under the mode with PCS and air conditioning, respectively. The findings indicate that PCS not only has a positive effect on improving the cabin environment and occupant's thermal sensation but also has the potential to lower the setting temperature of air conditioner of EVs in winter.

Analysis of the long-term effects of solar radiation on the indoor thermal comfort in office buildings

Windows play a critical role in building energy consumption and thermal comfort. Although many different models have been adopted for developing standards for indoor thermal comfort evaluation, the impact of solar radiation on occupant thermal sensation is still overlooked. In this study, the SMRT-Air temperature deviation method, in which the impact of solar radiation can be assessed based on the deviation of the solar-adjusted mean radiant temperature from air temperature, was developed to help the designer conveniently evaluate the impact of solar radiation on indoor thermal comfort in initial design stage. This method was applied to evaluate the effect of solar radiation on occupants in office buildings under different orientation and climate zones in China. The results show that the effect of solar radiation on thermal comfort is more severe in cold climate zones. Controlling the amount of solar radiation transmitted by windows facing east and west is more critical than for windows oriented in other directions. An appropriate decrease SHGC of windows from the current standard requirements can reduce over 86% discomfort times when SHGC decrease to 0.3 in all climate zones. The outcomes of this study can help designers implement appropriate measures for improving indoor thermal comfort.

A Bayesian Deep Neural Network Approach to Seven-Point Thermal Sensation Perception

To create and maintain comfortable indoor environments, predicting occupant thermal sensation is an important goal for architects, engineers, and facility managers. The link between thermal comfort, productivity, and health is common knowledge, and researchers have developed many state-of-the-art thermal-sensation models from dozens of research projects over the last 50 years. In addition to these, the use of intelligent data-analysis techniques, such as black-box artificial neural networks (ANNs), is receiving research attention with the aim of designing building thermal-behavior models from collected data. With the convergence of the internet of things (IoT), cloud computing, and artificial intelligence (AI), smart buildings now protect us and keep us comfortable while saving energy and cutting emissions. These types of smart buildings play a vital role in building smart cities of the future. The aim of this study is to help facility managers predict the thermal sensation of the occupants under the given circumstances. To achieve this, we applied a data-driven approach to predict the thermal sensation of occupants of an indoor environment using previously collected data. Our main contribution is to design and evaluate a deep neural network (DNN) for predicting thermal sensations with a high degree of accuracy regardless of building type, climate zone, or a building’s heating and/or ventilation methods. We used the second version of the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database to train our model. The hyperparameter-tuning process of the proposed model is optimized using the Bayesian strategy and predicts the thermal sensation of occupants with 78% accuracy, which is much higher than the traditional predicted mean vote (PMV) model and the other shallow and deep networks compared.

Feasibility study to detect occupant thermal sensation using a low-cost thermal camera for indoor environments in Indonesia

This paper concerns the feasibility study of 7 classes of thermal sensation detection in Indonesia's indoor environment using a low-cost thermal camera through face skin temperature. This study is required as an initial step to build a thermal comfort sensor system of HVAC control systems to produce a comfortable indoor environment with minimum and efficient energy use. The feasibility study was started by studying the thermoregulation system of respondents in Indonesia through measuring their body and facial skin temperatures under heating and cooling conditions, including their relationship with thermal sensations. The facial skin temperature variable, which is covered by four measurement points, namely forehead, nose, cheeks, and chin, represents the MST variable by the coefficient of determination of 0.54. The thermal sensation detection algorithm based on Artificial Neural Network (ANN) is 35.7% of accuracy. The thermal sensation questionnaire with 7 class categories is unsuitable for Indonesian respondents, and the number of the category classes predicted too much compared to the number of inputs. The detection algorithm has better accuracy with a smaller number of classes, namely 52.2% and 68.70% for the 5 and 3 classes of thermal sensation. Practical application: The air conditioning buildings system is possible to influence a thermal environmental control system to meet the occupants' thermal comfort level requirement in an indoor environment if the system is equipped with a sensor that can detect the occupants' thermal sensations. The thermal camera can be used as a non-contact sensor, detecting the occupant’s thermal sensation by reading the occupant's face skin temperature in an indoor environment.

Evaluation of a Coupled Model to Predict the Impact of Adaptive Behaviour in the Thermal Sensation of Occupants of Naturally Ventilated Buildings in Warm-Humid Regions

Improving indoor environment quality and making urban centres in tropical regions more sustainable has become a challenge for which computational models for the prediction of thermal sensation for naturally ventilated buildings (NVBs) have major role to play. This work performed analysis on thermal sensation for non-residential NVBs located in Brazilian tropical warm-humid climate and tested the effectiveness of suggested adaptive behaviours to mitigate warm thermal sensation. The research method utilized transient computational fluid dynamics models coupled with a dynamic model for human thermophysiology to predict thermal sensation. The calculated results were validated with comparison with benchmark values from questionnaires and from field measurements. The calculated results for dynamic thermal sensation (DTS) seven-point scale showed higher agreement with the thermal sensation vote than with the predicted mean vote. The test for the suggested adaptive behaviours considered reducing clothing insulation values from 0.18 to 0.32 clo (reducing DTS from 0.1 to 0.9), increasing the air speed in 0.9 m/s (reducing DTS from 0.1 to 0.9), and applying both suggestions together (reducing DTS from 0.1 to 1.3) for five scenarios with operative temperatures spanning 34.5–24.0 °C. Results quantified the tested adaptive behaviours’ efficiency showing applicability to improve thermal sensation from slightly-warm to neutral.

Occupant behaviour in mixed-mode office buildings in a subtropical climate: Beyond typical models of adaptive actions

Recent years have seen considerable interest amongst building professionals and researchers in describing occupant behaviour. This has led to the development of models of adaptive behaviour to improve the accuracy and realism of building energy and indoor environment simulations. The objective of this study was to go beyond the typical behaviour models for building simulation and suggest models for other adaptive actions, such as changing clothes or ingestion of hot or cold beverages. The scope of the study is mixed-mode buildings, which alternate the air-conditioning operation and the opening of windows according to outdoor conditions and occupant preferences. A field study on occupant thermal comfort and behaviour in office buildings was performed in a subtropical climate in Brazil. Simple and multiple logistic models and mixed effects logistic models of adaptive actions were used to analyse key variables based on the results of the field campaign. Occupant clothing behaviour was affected by thermal sensation, clothing insulation and indoor operative temperature. The action of drinking a hot beverage was affected by occupant thermal sensation and the indoor operative temperature, while the cold drink intake was linked to both indoor and outdoor thermal conditions. Our analysis of windows and air-conditioning operation may be used by researchers and practitioners as input for simulations of mixed-mode offices, which can improve energy use predictions.

Outdoor Thermal Comfort at a University Campus: Studies from Personal and Long-Term Thermal History Perspectives

Thermally comfortable outdoor spaces have contributed to high-quality urban living. In order to provide a further understanding of the influences of gender and long-term thermal history on outdoor thermal comfort, this study conducted field surveys at a university campus in Shanghai, China by carrying out microclimatic monitoring and subjective questionnaires from May to October, 2019. The analysis of collected data found that, during our survey, 57% of the occupants felt comfortable overall and 40–60% of them perceived the microclimate variables (air temperature, humidity, solar radiation, and wind speed) as “neutral”. The universal thermal climate index (UTCI) provided a better correlation with occupant thermal sensation than the physiologically equivalent temperature (PET). Females were more sensitive to the outdoor thermal environment than males. Older age led to lower thermal sensation, but the thermal sensitivities for age groups of <20, 20–50, and >50 were similar. Occupants who had resided in Shanghai for a longer period showed higher overall comfort rating and lower thermal sensation. Interviewees who came from hot summer and cold winter climate regions were less effected by the change of UTCI than those from severe cold or cold climate regions.

A simulation framework for predicting occupant thermal sensation in perimeter zones of buildings considering direct solar radiation and ankle draft

Buildings with highly glazed envelopes have gained popularity in recent decades. Though it is well understood that these modern buildings can be less energy efficient, only a few attempts have been made to examine the impact of certain building design decisions, such as window characteristics, on indoor thermal sensation and thermal comfort. While conventional assessment of thermal sensation and comfort primarily considers zone-level environmental conditions (e.g. air temperature and relative humidity), localized effects including direct solar radiation exposure and ankle draft may also exist and can impact indoor thermal sensation especially in highly glazed perimeter zones. In this work, a simulation framework is introduced to incorporate the solar radiation effect and ankle draft effect, which are shown to increase warm and cold thermal sensation levels, respectively. The novel proposed ankle draft model adapts local draft conditions to determine the impact on overall thermal sensation for the first time. This simulation framework is demonstrated using a single-zone model using the climate of Toronto, Canada to illustrate the effect of three primary window design parameters on thermal sensation using a visualization approach: window size, U-factor, and solar heat gain coefficient. All observations are aligned with anecdotal evidence: warm thermal sensation level is positively correlated with window size and solar heat gain coefficient, whereas cold thermal sensation level is positively correlated with window size and window U-factor. This simulation framework can be used to analyze indoor thermal sensation and comfort for perimeter zones in existing buildings or fenestration alternatives during building design phases.

Quantification of thermal environments and comfort expectations of residents in hostel dormitories during hot and humid days in Indian composite climate

ABSTRACT Improved quality of the thermal environment in hostel buildings will have a constructive role in the health, learning and overall productivity of student’s activities. We, therefore, conducted a thermal comfort field study in two mid-rise naturally ventilated (NV) hostel buildings during rainy days (August–September, 2018). The field study conducted for three consecutive weeks collecting 642 valid subjective responses (out of 679 sample) with objective information of thermal environments in 253 rooms at different floor levels. Statistical analysis of measured thermal variables was performed for assessing the effects on student’s thermal perception considering inter buildings effects, different weather conditions and different daytime duration, respectively. The study reported higher comfort bandwidth of 25.2–33.3°C for the studied group. Results of present study are compared with Predicted Mean Vote (PMV), Predicted Mean Vote with expectancy factor (PMVe) and adaptive Predicted Mean Vote (aPMV). aPMV is observed to be more reliable than PMV and PMVe to estimate the actual thermal sensation of occupants. Further, field study results are showing good agreement with the adaptive comfort models for NV buildings in India. Highlights Study quantifies thermal environments of two multi-storey NV hostel buildings. About 76% responses voted comfortable (±1 TS scale). Comfort bandwidth for occupant's ranges between 25.2–33.3°C for the study period. aPMV model of thermal comfort predicts TS more closely than PMV or PMVe model. Indian composite climate-specific adaptive models fit better with present data base.

Evaluation of Thermal Comfort in the Traditional Bourgeoisie Houses in Beirut

The increasing of energy demands has considerably increased the requirements for new and traditional buildings in different climate zones. Unprecedented heat waves have increased climate temperature, in particular, in moderate climate zones such as Lebanon. In Beirut, only the residential sector consumes 50% of total electricity consumption. HVAC (Heating, Ventilation and Air conditioning) systems are used to reach acceptable thermal comfort levels in the new residential buildings. In case of the traditional bourgeoisie houses in Beirut, there are no discussions about the use of HVAC systems to achieve the required thermal comfort level. Thus, to reach an acceptable thermal comfort level, these houses which already contain natural ventilation system shall adapt the modern thermal comfort requirements and thermal comfort strategies and technologies where their architectural features and existing materials condition the available solutions. In order to identify the best options within the possible intervention lines (envelopes, passive strategies, equipment, renewable energy systems), it is necessary to perceive the real performance of this type of houses. In this context, the article presents the results of the study of thermal performance and comfort in a three case studies located in Beirut. Detailed field data records collected are analyzed, with a view to identify the indoor thermal environment with respect to outdoor thermal environment in different seasons. Monitoring also included measurement of hygrothermal parameters and surveys of occupant thermal sensation.

The impact of courtyard geometry on its mean radiant temperature

For hot regions, studies have been advocating re-adopting the courtyard pattern for its thermal advantages. Aiming at developing thermally comfortable courtyards, studies have been exploring the impact of courtyards geometry on their shading and natural ventilation, which are the two environmental principles of courtyards. However, there is a lack of studies on the impact of manipulating courtyards geometry on the thermal sensation of occupants. This research investigates the impact of changing the courtyard geometry and the resulted shading on Mean Radiant Temperature (MRT) and Globe temperature (Tg). The latter represents the thermal perception of occupants and the former is the main effective factor on the thermal sensation of people in outdoor and semi-outdoor spaces. The research carried out simulation experiments to test 360 different courtyard configurations. The simulation experiments included using Envi-met and IES-VE simulation tools. The former was used to determine MRT and Tg, and the latter to determine shading levels. Baghdad was selected to represent an example of a hot city in which summer air temperature reaches around 50 °C. The results show that the difference in shading that results from changing the courtyard geometry can lead to a difference in MRT and Tg of up to 15°C.

Numerical evaluation of the effects of different types of shading devices on interior occupant thermal comfort using wind tunnel experimental data

In this study, it is aimed to determine the effects of shading device alternatives on the thermal sensations of occupants in a cross-ventilated office zone by considering changing indoor airflow velocities in summer conditions. Interior airflow velocities on 3 vertical profile heights were measured for 5 cases in a wind tunnel. The effects of alternatives on simulated occupant thermal comfort conditions in a modelled environment at different time intervals were investigated by comparing the results of mean radiant temperature, predicted mean vote, predicted percentage of dissatisfied calculations, conducted by EnergyPlus, considering the measured airflow velocity values, calculated angle factors defining the location of the occupants and their interaction with interior surfaces. The results show that the effect of shading devices on thermal comfort changes due to geometry and the location of the element on the facade. Shading devices lower dissatisfaction ratios at all measurement points. The most satisfaction is obtained near the backward window in the morning hours changing among D and B Category defined in ISO 7730. Dissatisfaction ratios are much higher in the morning hours than afternoon hours. The alternatives having lower cavity area for airflow intake and stimulating lower airflow velocity while also enabling the access of solar radiation throughout the open windows provide more satisfaction when the outside temperature is low. The optimum shading device among the alternatives derived for the study, providing the lowest MRT, PPD is “3.1-CDE-CPK-90” (Perpendicular to facade, slat angle: 90°) at all occupant locations, especially in the middle of the zone.

Investigation of Thermal Comfort Responses with Fuzzy Logic

In order to reduce the energy consumption of buildings a series of new heating, ventilation and air conditioning strategies, methods, and equipment are developed. The architectural trends show that office and educational buildings have large glazed areas, so the thermal comfort is influenced both by internal and external factors and discomfort parameters may affect the overall thermal sensation of occupants. Different studies have shown that the predictive mean vote (PMV)—predictive percentage of dissatisfied (PPD) model poorly evaluates the thermal comfort in real buildings. At the University of Debrecen a new personalized ventilation system (ALTAIR) was developed. A series of measurements were carried out in order to test ALTAIR involving 40 subjects, out of which 20 female (10 young and 10 elderly) and 20 male (10 young and 10 elderly) persons. Based on the responses of subjects related to indoor environment quality, a new comfort index was determined using fuzzy logic. Taking into consideration the responses related to thermal comfort sensation and perception of odor intensity a new the fuzzy comfort index was 5.85 on a scale from 1–10.

The effect of front pattern perforation shape on thermal sensations of occupants in personalized ventilation systems

The aim of this study was to find the most favourable shape of the front panel perforation shape, which would allow us to obtain the greatest cooling effect and – at the same time – be positively perceived by the people. The capacity of the personalized ventilation (PV) system to affect human thermal sensation, with different shapes of front panel perforation used, was analyzed.Once the pilot study was conducted, it used a rectangular nozzle of front pattern size 320 mm × 125 mm and six different front patterns perforation shapes with round holes were tested. Operational parameters such as: airflow 20 l/s, supply air temperature at 24 °C or ambient temperature at 28 °C were invariable. The experiment consisted of a two-stage analysis of air jets characteristics and of tests in which people participated. Twenty-five male volunteers, at the age of 22–23 were engaged. They their assessed thermal sensation and completed relevant questionnaires.On the basis of the results of the above study, differences in jet characteristics depending on the pattern shapes and their different impact on thermal sensation of the volunteers were demonstrated. The biggest cooling effect was obtained using front panels with small hole size (d = 5 mm). These perforations allowed us to obtain a more even air outflow from the entire panel. This ensured a broader airflow of lower velocity, reaching and affecting a larger area. With holes of larger size (d = 15 mm), air outflow occurred mainly through the central part, which produced narrow jets of higher velocity.