Transient Human Thermal Comfort Response in Convective and Radiative Environments

2008 ◽  
Author(s):  
Mohamad Al-Othmani ◽  
Nesreen Ghaddar ◽  
Kamel Ghali
Keyword(s):  
Thermal Comfort ◽  
Thermal Conditions ◽  
Activity Level ◽  
Convective Heating ◽  
Convective System ◽  
Clothing Insulation ◽  
Indoor Space ◽  
Human Thermal Comfort ◽  
Walking Activity ◽  
Local Thermal Comfort

In this work, human transient thermal responses and comfort are studied in non-uniform radiant heating and convective heating environments. The focus was on a change from walking activity of human in outdoor cold environment at high clothing insulation to warm indoor environment at sedentary activity level associated with lower clothing insulation. A transient multi-segmented bioheat model sensitive to radiant asymmetry is used to compare how fast the human body approaches steady state thermal conditions in both radiative and convective warm environments. A space thermal model is integrated with the bioheat model to predict the transient changes in skin and core temperature of a person subject to change in metabolic rate and clothing insulation when entering conditioned indoor space. It was found that overall thermal comfort and neutrality were reached in 6.2 minutes in the radiative environment compared to 9.24 minutes in convective environment. The local thermal comfort of various body segments differed in their response to the convective system where it took more than 19 minutes for extremities to reach local comfort unlike the radiative system where thermal comfort was attained within 7 minutes.

Evaluation of Human Thermal Comfort in Offices in Kuwait and Assessment of the Applicability of the Standard PMV Model

Volume 1 ◽  
2004 ◽  
Author(s):  
Nawaf Al-Mutawa ◽  
Walid Chakroun ◽  
Mohammad H. Hosni
Keyword(s):  
Thermal Comfort ◽  
Psychological Impact ◽  
Activity Level ◽  
Office Buildings ◽  
Clothing Insulation ◽  
Comfort Index ◽  
Human Thermal Comfort ◽  
The State Of Kuwait ◽  
Radiant Temperature ◽  
Velocity Turbulence

It has been known that the human thermal comfort is not exclusively a function of air temperature but also a function of six additional parameters, namely, mean radiant temperature, air velocity, turbulence intensity, humidity, activity level, and clothing insulation. The combined physical and psychological impact of these parameters on thermal comfort is mathematically described in various comfort models. The current comfort models, while use extensive human comfort data, may not be applicable in all world regions due to environmental conditions and people’s expectations. The State of Kuwait has a population of 2.5 million inhabitants with majority of people living in a few populated cities with heavy vehicle traffic, office buildings, factories, petroleum operations, and shopping centers. During the summer months (especially in July and August) the temperature reaches 48 °C in the afternoon, and can sometimes exceed 55 °C requiring extensive use of air conditioning. The traditional clothing (Disdasha) is made of lightweight, white, fabric material to provide some level of comfort. To better understand the regional preferences and assess the applicability of the standard comfort models in Kuwait, important parameters influencing human thermal comfort were measured in ten different government offices and the corresponding PMV indices were calculated. The results were compared with other comfort indices to obtain the most viable comfort index and the appropriate temperature range for local comfort for Kuwait offices. This study is not only important for comfort evaluations but also for evaluation of energy consumption in office buildings.

scholarly journals Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 619
Author(s):  
Jinsong Liu ◽  
Isak Worre Foged ◽  
Thomas B. Moeslund
Keyword(s):  
Metabolic Rate ◽  
Thermal Comfort ◽  
Real Life ◽  
Activity Level ◽  
Tracking Accuracy ◽  
Classification Rate ◽  
Clothing Insulation ◽  
Activity Intensity ◽  
Bounding Box ◽  
Tracking By Detection

Satisfactory indoor thermal environments can improve working efficiencies of office staff. To build such satisfactory indoor microclimates, individual thermal comfort assessment is important, for which personal clothing insulation rate (Icl) and metabolic rate (M) need to be estimated dynamically. Therefore, this paper proposes a vision-based method. Specifically, a human tracking-by-detection framework is implemented to acquire each person’s clothing status (short-sleeved, long-sleeved), key posture (sitting, standing), and bounding box information simultaneously. The clothing status together with a key body points detector locate the person’s skin region and clothes region, allowing the measurement of skin temperature (Ts) and clothes temperature (Tc), and realizing the calculation of Icl from Ts and Tc. The key posture and the bounding box change across time can category the person’s activity intensity into a corresponding level, from which the M value is estimated. Moreover, we have collected a multi-person thermal dataset to evaluate the method. The tracking-by-detection framework achieves a mAP50 (Mean Average Precision) rate of 89.1% and a MOTA (Multiple Object Tracking Accuracy) rate of 99.5%. The Icl estimation module gets an accuracy of 96.2% in locating skin and clothes. The M estimation module obtains a classification rate of 95.6% in categorizing activity level. All of these prove the usefulness of the proposed method in a multi-person scenario of real-life applications.

scholarly journals Application of wearable EEG sensors for indoor thermal comfort measurements

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 214
Author(s):  
Silvia Angela Mansi ◽  
Ilaria Pigliautile ◽  
Camillo Porcaro ◽  
Anna Laura Pisello ◽  
Marco Arnesano
Keyword(s):  
Thermal Comfort ◽  
Brain Activity ◽  
Low Cost ◽  
Wearable Sensors ◽  
Real Life ◽  
Thermal Conditions ◽  
Ambient Temperatures ◽  
Human Thermal Comfort ◽  
Power Spectral ◽  
Wearable Eeg

Multidomain comfort theories have been demonstrated to interpret human thermal comfort in buildings by employing human-centered physiological measurements coupled with environmental sensing techniques. Thermal comfort has been correlated with brain activity through electroencephalographic (EEG) measurements. However, the application of low-cost wearable EEG sensors for measuring thermal comfort has not been thoroughly investigated. Wearable EEG devices provide several advantages in terms of reduced intrusiveness and application in real-life contexts. However, they are prone to measurement uncertainties. This study presents results from the application of an EEG wearable device to investigate changes in the EEG frequency domain at different indoor temperatures. Twenty-three participants were enrolled, and the EEG signals were recorded at three ambient temperatures: cold (16 °C), neutral (24 °C), and warm (31 °C). Then, the analysis of brain Power Spectral Densities (PSDs) was performed, to investigate features correlated with thermal sensations. Statistically significant differences of several EEG features, measured on both frontal and temporal electrodes, were found between the three thermal conditions. Results bring to the conclusion that wearable sensors could be used for EEG acquisition applied to thermal comfort measurement, but only after a dedicated signal processing to remove the uncertainty due to artifacts.

scholarly journals Experimental and statistical survey on local thermal comfort impact on working productivity loss in university classrooms

2019 ◽  
Vol 23 (1) ◽  
pp. 379-392 ◽  
Author(s):  
Tamara Bajc ◽  
Milos Banjac ◽  
Maja Todorovic ◽  
Zana Stevanovic
Keyword(s):  
Thermal Comfort ◽  
Productivity Loss ◽  
Thermal Conditions ◽  
Co2 Concentration ◽  
Heating System ◽  
Indoor Environmental Quality ◽  
Personal Factor ◽  
Predicted Mean Vote ◽  
Local Thermal Comfort ◽  
The Impact

The paper presents an experimental analysis of the relationship between local thermal comfort and productivity loss in classrooms. The experimental investigation was performed in a real university classroom during the winter semester in city of Belgrade. Measurements were taken for four scenarios, with different indoor comfort conditions. Variations were made by setting the central heating system on/off, adding an additional heat source to provoke higher indoor temperatures, and measuring the radiant asymmetry impact. Innovative questionnaires were developed especially for the research, in order to investigate students? subjective feelings about local thermal comfort and indoor environmental quality. Local predicted mean vote and predicted percentage dissatisfied indices were calculated using data measured in situ. The results were compared to existing models recommended in literature and European and ASHRAE standards. Student productivity was evaluated using novel tests, designed to fit the purposes of the research. Surveys were conducted for 19 days under different thermal conditions, during lectures in a real classroom, using a sample of 240 productivity test results in total. Using the measured data, new correlations between the predicted mean vote, CO2, personal factor and productivity loss were developed. The research findings imply that local thermal comfort is an important factor that can impact productivity, but the impact of the personal factor is of tremendous importance, together with CO2 concentration in the classroom.

scholarly journals Calculating human thermal comfort and thermal stress in the PALM model system 6.0

2019 ◽  
Author(s):  
Dominik Fröhlich ◽  
Andreas Matzarakis
Keyword(s):  
Thermal Comfort ◽  
City Planning ◽  
Model System ◽  
Climate Index ◽  
Mean Radiant Temperature ◽  
Clothing Insulation ◽  
Human Thermal Comfort ◽  
Model Based ◽  
Perceived Temperature ◽  
Radiant Temperature

Abstract. In the frame of the project MOSAIK – Model–based city planning and application in climate change, a German-wide research project within the call Urban Climate Under Change ([UC]2) funded by the German Federal Ministry of Education and Research (BMBF), a biometeorology module was implemented into the PALM model system. The new biometeorology module comprises of methods for the calculation of uv-exposure quantities, a human–biometeorologically weighted mean radiant temperature (Tmrt), as well as for the estimation of human thermal comfort or stress. The latter is achieved through the implementation of the three widely–used thermal indices Perceived Temperature (PT), Universal Thermal Climate Index (UTCI), as well as Physiologically Equivalent Temperature (PET) together with a newly developed instationary index instationary Perceived Temperature (iPT) based on PT for use with the multi–agent model. Comparison calculations were performed for the indices PT, UTCI and PET based on the SkyHelios model and showing PALM calculates higher values in general. This is mostly due to a higher radiational gain leading to higher values of mean radiant temperature. For a more direct comparison, the indices PT, PET and UTCI were calculated by the biometeorology module, as well as the programs provided by the attachment to the VDI guideline 3787, as well as by the RayMan model based on the very same input dataset. Results show deviations below rounding precision (less than 0.1 K) for PET and UTCI and some deviations of up to 2.683 K for PT caused by rounding leading to the selection of a different clothing insulation step in very rare cases (0.027 %).

scholarly journals Investigating the Behaviour of Human Thermal Indices under Divergent Atmospheric Conditions: A Sensitivity Analysis Approach

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 580 ◽  
Author(s):  
Ioannis Charalampopoulos ◽  
Andre Santos Nouri
Keyword(s):  
Energy Balance ◽  
Thermal Comfort ◽  
Thermal Conditions ◽  
Radiation Condition ◽  
Additive Models ◽  
Balance Model ◽  
Climate Index ◽  
Atmospheric Conditions ◽  
Thermal Indices ◽  
Human Thermal Comfort

This paper aims to analyse and conclude about the behaviour of the most commonly used human thermal comfort indices under a variety of atmospheric conditions in order to provide further information about their appropriateness. Utilising Generalized Additive Models (GAMs), this article examines the indices’ sensitivity when exposed to diverse classified atmospheric conditions. Concentrated upon analysing commonly used human thermal indices, two Statistical/Algebraic indices (Thermohygrometric Index (THI) and HUMIDEX (HUM)), and four Energy Balance Model indices (Physiologically Equivalent Temperature (PET), modified PET (mPET), Universal Thermal Climate Index (UTCI), and Perceived Temperature (PT)) were selected. The results of the study are twofold, the identification of (1) index sensitivity to parameters’ variation, and change rates, resultant of different atmospheric conditions; and, (2) the overall pertinence of each of the indices for local thermal comfort evaluation. The results indicate that the thermohygrometric indices cannot follow and present the thermal conditions’ variations. On the other hand, UTCI is very sensitive under low radiation condition, and PET/mPET present higher sensitivity when the weather is dominated by high radiation and air temperature. PT index provides the lower sensitive among the human energy balance indices, but this is adequately sensitive to describe the thermal comfort environment.

scholarly journals Thermal Equations for Predicting Foot Skin Temperatur

2019 ◽  
Vol 14 (1) ◽  
pp. 31
Author(s):  
Pui-Ling Li ◽  
Kit-lun Yick ◽  
Joanne Yip ◽  
Sun-pui Ng
Keyword(s):  
Thermal Comfort ◽  
Skin Temperature ◽  
Thermal Conditions ◽  
The Elderly ◽  
Activity Level ◽  
Elderly Subjects ◽  
Regression Equations ◽  
Foot Diseases ◽  
Level Of Activity ◽  
Footwear Design

Purpose: Studying the foot skin temperature of both the young and elderly is important for preventing foot diseases and improving thermal comfort and variability during gait. However, few studies have predicted the thermal conditions in footwear under different variables. The aim of this study is to therefore formulate thermal equations for both the young and elderly to predict their foot skin temperature under the variables of age, gender, activity level and various properties of different types of footwear. Methodology: A total of 80 participants between 20 and 85 years old are recruited in this study, including 40 younger subjects (mean: 23.0; SD: 4.05) and 40 elderly subjects (mean: 69.8; SD: 4.59). They are tasked to sit, walk and run in a conditioning chamber. Findings: Regression equations for predicting the foot skin temperature of the young and elderly people are formulated, with R squares of 0.513 and 0.350 respectively. The level of activity is the most important factor when predicting the foot skin temperature. The material properties of the footwear also show a significant impact on the foot skin temperature of the elderly. Value: The findings of this study provide the basis for better thermal comfort and help to facilitate the footwear design process.

scholarly journals The potential for domestic thermal insulation retrofits on the South African Highveld

2019 ◽  
Vol 29 (1) ◽  
Author(s):  
Newton R Matandirotya ◽  
Dirk P Cilliers ◽  
Roelof P Burger ◽  
Brigitte Language ◽  
Christian Pauw ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
South African ◽  
Thermal Insulation ◽  
Low Income ◽  
Prolonged Exposure ◽  
Winter Season ◽  
Thermal Conditions ◽  
The South ◽  
Ambient Temperatures ◽  
Human Thermal Comfort

The South African Highveld is a portion on the inland plateau characterized by low winter ambient temperatures. Studies done in several climatic regions around the world have found a positive relationship between inadequate housing and low indoor temperatures during the winter season. Prolonged exposure to low indoor temperature is a threat to human physical health. This study characterizes indoor human thermal comfort conditions in typical low-income residential dwellings during the winter season. Mapping indoor human thermal comfort can assist in exploring the potential for domestic thermal insulation retrofits interventions. In-situ temperature measurements were done in 2014, 2016 and 2017 across three Highveld settlements of kwaZamokuhle, kwaDela, and Jouberton. The sample included a mixture of old (pre-1994), post 1994 Reconstruction and Development Programme (RDP) as well as non-RDP structures. Findings were that 88% of sampled dwellings in Jouberton 2016, 86% in Jouberton 2017, 62% in kwaDela and 58% in kwaZamokuhle had daily mean temperatures below the WHO guideline of 18°C. These low indoor temperatures indicate poor insulation in these sampled dwellings. Across all settlements, insulated dwellings had higher daily mean indoor temperatures than non-insulated dwellings. These findings indicate the potential to use thermal insulation retrofits in improving indoor thermal conditions as the majority of dwellings are non-insulated thereby exposing occupants to low indoor temperatures.

scholarly journals Artificial Neural Network for the Thermal Comfort Index Prediction: Development of a New Simplified Algorithm

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4500
Author(s):  
Domenico Palladino ◽  
Iole Nardi ◽  
Cinzia Buratti
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Relative Humidity ◽  
Thermal Comfort ◽  
Air Temperature ◽  
Thermal Conditions ◽  
Feed Forward Neural Network ◽  
Clothing Insulation ◽  
Artificial Neural ◽  
Simplified Algorithm

A simplified algorithm using an artificial neural network (ANN, a feed-forward neural network) for the assessment of the predicted mean vote (PMV) index in summertime was developed, using solely three input variables (namely the indoor air temperature, relative humidity, and clothing insulation), whilst low air speed (<0.1 m/s), a minimal variation of radiant temperature (25.1 °C ± 2 °C) and steady metabolism (1.2 Met) were considered. Sensitivity analysis to the number of variables and to the number of neurons were performed. The developed ANN was then compared with three proven methods used for thermal comfort prediction: (i) the International Standard; (ii) the Rohles model; (iii) the modified Rohles model. Finally, another network able to predict the indoor thermal conditions was considered: the combined calculation of the two networks was tested for the PMV prediction. The proposed algorithm allows one to better approximate the PMV index than the other models (mean error of ANN predominantly in ±0.10–±0.20 range). The accuracy of the network in PMV prediction increases when air temperature and relative humidity values fall into 21–28 °C and 30–75% ranges. When the PMV is predicted by using the combined calculation (i.e., by using the two networks), the same order of magnitude of error was found, confirming the reliability of the networks. The developed ANN could be considered as an alternative method for the simplified prediction of PMV; moreover, the new simplified algorithm can be useful in buildings’ design phase, i.e., in those cases where experimental data are not available.

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