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![Static and dynamic responses of warm and cold cutaneous thermoreceptors as elicited during two constant levels of skin temperature and during sudden changes in skin temperature. Redrawn from [11].](profile/Dusan-Fiala/publication/281899653/figure/fig1/AS:669533782159374@1536640701619/Static-and-dynamic-responses-of-warm-and-cold-cutaneous-thermoreceptors-as-elicited.png)
Static and dynamic responses of warm and cold cutaneous thermoreceptors as elicited during two constant levels of skin temperature and during sudden changes in skin temperature. Redrawn from [11].
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During their daily lives, human beings respond to, and interact with, their immediate environment by thermoregulatory and behavioural reactions. Comfort standards such as ISO 7730 tend to neglect these responses, although they can substantially affect the acceptability of thermal environments. A multi-segmental, dynamic thermal comfort model has be...
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... functions of ghy and gsk are plotted in Fig. 4. Even though dynamically predicted skin and body core temperatures account to some extent for the effects of time on thermal sensation, additional, specifically transient, phenomena are dominant in rapid environmental transients (see also Fig. 1). This is illustrated in Fig. 5 which shows the response of subjects undergoing step changes in ambient temperature from Ta=28°C to 18°C and back again ...
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... temperature as a punitive signal in the physiologically based thermal comfort model is of particular relevance when modelling the effect of personal circumstances and adaptive responses on the sensation of thermal comfort. The impact of temporally changing internal temperature (due to transient exercise) on the thermal sensation is evident from Fig. 10. The subjects exercised for 60 min on an ergometer at a rate of 2.6 met and then sat quietly on the bicycle for a further hour whilst exposed to a steady environment of Ta=10°C ...
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... 'short-term adaptation'-effect has frequently been observed in comfort experiments, e.g. [16,18]. This effect causes subjects to feel warmer during the initial phases of an exposure and to 'adapt' to the steady state climatic conditions as the exposure prolongs, Fig. 11. The dynamic comfort model confirms this effect to be a transient event involving the human body's inertia and recent thermal history. It arises from a slightly elevated activity level (1.6met) during the first five or ten minutes of the ...
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... warm environments building occupants may mitigate warm discomfort by taking cold drinks. The effect of (i) a 0.5 l drink at 5°C taken over a period of 15 minutes and (ii) continuous intake of a 10°C-drink at a rate of 1 l/h is quantified for a subject involved in office-type activity and exposed to a room temperature of 27°C in Fig. 12. Here, the thermal effect of a drink as it flows through upper digestive system and cools the core of the neck, thorax and abdomen element was ...
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... Thermal Comfort Standards into the 21 th Century, Windsor, UK, 2001, Conference Proc., p. 154 2 abdomen core in the model Fig. 11 The 'short-term-adaptation' effect as observed, and as predicted, for an exposure to a steady temperature of Ta=25.6°C ...
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... recovery. Individuals working near windows may be exposed to solar radiation (Qs=50W/m 2 ) which would exacerbate any feeling of warm discomfort. They may opt to improve their situation by opening windows to generate more air movement. The impact of increasing room air speed from 0.1 m/s to 0.5 m/s (at 27°C) after one hour of exposure is shown in Fig. 13. The figure also shows the additional benefit which would result from closing window blinds (Qs=0W/m 2 ...
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... cooler conditions, office workers might compensate for increased body cooling by behavioural elevation of their metabolic rate. An increase in activity level of just 0.2 met was predicted to provide comfort in a 19°C-environment which otherwise would be an uncomfortable space, Fig. 14 ...
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Citations
... The extension of the Fiala model with passive and active parts [92,147] predicts TS from moderate to stressful cases, from low activity to high activity levels. Standard human manikins are used in [148], where a Computational Fluid Dynamics (CFD) code is coupled with the Fanger model to compute the impact of the human body on the environment, and in [149] to integrate the Fiala model with a realistic 3D figure. ...
The assessment of thermal sensation is the first stage of many studies aimed at addressing thermal comfort and at establishing the related criteria used in indoor and outdoor environments. The study of thermal sensation requires suitable modelling of the human body, taking into account the factors that affect the physiological and psychological reactions that occur under different environmental conditions. These aspects are becoming more and more relevant in the present context in which thermal sensation and thermal comfort are represented as objectives or constraints in a wider range of problems referring to the living environment. This paper first considers the models of the human body used in steady-state and transient conditions. Starting from the conceptual formulations of the heat balance equations, this paper follows the evolution occurred during the years to refine the models. This evolution is also marked by the availability of increasingly higher computational capability that enabled the researchers developing transient models with a growing level of detail and accuracy, and by the validation of the models through experimental studies that exploit advanced technologies. The paper then provides an overview of the indicators used to characterise the local and overall thermal sensation, indicating the relations with local and overall thermal comfort.
... Ioannour and Itard (2015) explain the three forms of adaptation: psychological adaptation, i.e. a person's thermal expectations based on his past experiences and habits (Humphreys and Hancock, 2007;Shove, 2004;Holmes and Hacker, 2007) physiological adaptation to a thermal environment over a period of time; and behavioral adaptation, i.e. modifications or actions of an individual that changes in the heat and mass fluxes governing the body's thermal balance (Brager and de Dear, 1998). Adaptations are interrelated and affect one another, besides modifications are grouped as personal (Holmes and Hacker, 2007;Fiala and Lomas, 2001;Baker and Standeven, 1996), technological or environmental adjustments (ASHRAE, 2004). ...
... Most work on the performance gap is based on deterministic predictions and measurements. Work at Plymouth University has piloted a probabilistic approach, contrary to several other works which follow more deterministic methods (Field, 2005; de Wilde, et al. 2013). De Wilde makes a summary of the current concerns and future work regarding energy performance gap, as follows: There are different types of energy performance gap that vary over time and with context. ...
Chapter 2 provides an overview of a literature study of the existing knowledge on energy consumption from the urban to the user scale, energy performance modelling methods, the energy performance gap, and insights to determinants of heating energy and electricity consumption. This review first helped to set up a reference point for the reasons to actual occupant behavior, how perception, lifestyle, norms, rules lead to various actions at home (Figure 1). Secondly, through this study, a framework for the relationship between occupant behavior and energy consumption was created (Figure 2), based on the determinants of behavior, i.e. occupant characteristics (educational, economic, social), dwelling characteristics (envelope, systems, lighting and appliances…). This literature study set the context and also the first steps of this research. The determinants found through this review (Table 2) gave input to the content and structure of the questions of the survey designed for the OTB dataset.
... There are three different forms of adaptation, which are all interrelated and affect one another [20]: psychological adaptation relates to a person's thermal expectations based on his past experiences and habits [21][22][23]; physiological adaptation (acclimatization), relates to how an individual adapts to a thermal environment over a period of some days or weeks, behavioural adaptation relates to all the modifications or actions that an individual might make, consciously or unconsciously; and changes in the heat and mass fluxes governing the body's thermal balance [20]. These modifications may be personal adjustments [24][25][26], technological or environmental adjustment [27]. ...
... As one experiences thermal stress, for example, shading does not alleviate the stress immediately. The nature of our human experience of thermal environments is spatiotemporal, as exhibited by the Dynamic Thermal Sensation (DTS) model (Fiala & Lomas, 2001), as shown in Figure 43. Interpreting the effect walking and cycling has on thermal comfort sensation through space and time is critical. ...
Outdoor thermal comfort can influence human powered mobility choices, namely walking and biking. As more people are living in cities than ever before in human history, the urban environments we erect and populate are unfortunately contributing to phenomena such as climate change, which is negatively affecting urban life. Our understanding and creation of comfortable environments that are conducive to human powered transport can significantly influence carbon emissions, energy efficiency, and human health, as well as have considerable economic and time saving impacts. With the continuous integration of computer-based decision support systems in design processes, there is a need for developing simulation frameworks that aid architects, urban designers and planners in making informed sustainable design decisions. The focus of this work, therefore, is the development of computer tools and workflows that promote the design of walkable and bikeable cities through comfortable outdoor spaces. This dissertation presents firstly, a simulation methodology, verified through a validation experiment conducted on the MIT campus, for spatially and temporally resolved Mean Radiant Temperature (MRT) simulation and consequent outdoor thermal comfort assessment. Secondly, Building Performance Simulation (BPS) occupancy and trip schedules generation through data clustering techniques applied to activity-based travel surveys. An office modeling case study is presented through extracted occupancy scenarios, to compare simulation accuracy against current practice standards. Finally, an assimilation of both workflows is presented to generate "Trip Comfort" metrics for human powered mobility assessment, in the context of existing or newly designed urban structures.
... Behavioural thermoregulation, or adjustment, includes all modifications a person might consciously or unconsciously make, which in turn modify heat and mass fluxes governing the body"s thermal balance [12]: personal adjustment ( [11], [17], [18]), technological or environmental adjustment [4] and cultural adjustment. ...
Building Energy Simulation (BES) programmes often use conventional thermal comfort theories to make decisions, whilst recent research in the field of thermal comfort clearly shows that important effects are not incorporated. The conventional theories of thermal comfort were set up based on steady state laboratory experiments. This, however, is not representing the real situation in buildings, especially not when focusing on residential buildings. Therefore, in present analysis, recent reviews and adaptations are considered to extract acceptable temperature ranges and comfort scales. They will be defined in an algorithm, easily implementable in any BES code. The focus is on comfortable temperature levels in the room, more than on the detailed temperature distribution within that room.
Energy performance simulation is a generally used method for assessing the energy consumption of buildings. Simulation tools, though, have shortcomings due to false assumptions made during the design phase of buildings, limited information on the building’s envelope and installations and misunderstandings over the role of the occupant’s behavior. This paper presents the results of a Monte Carlo sensitivity analysis on the factors (relating to both the building and occupant behavior) that affect the annual heating energy consumption and the PMV comfort index. The PMV results are presented only for the winter (heating) period, which is important for energy consumption in Northern Europe. The reference building (TU Delft Concept House) was simulated as both a Class-A and Class F dwelling and with three different heating systems. If behavioral parameters are not taken into account, the most critical parameters affecting heating consumption are the window U value, window g value and wall conductivity. When the uncertainty of the building-related parameters increases, the impact of the wall conductivity on heating consumption increases considerably. The most important finding was that when behavioral parameters like thermostat use and ventilation flow rate are added to the analysis, they dwarf the importance of the building parameters. For the PMV comfort index the most influential parameters were found to be metabolic activity and clothing, while the thermostat had a secondary impact.
Rich, rapid, and simultaneous variations in wind and solar radiation produced by complex urban continuums are supposed to have positive effects on thermal comfort during walking. However, the identification of these influences is still challenging. In view of this, this study observed the mixed thermal perceptions and skin temperature of 70 healthy young college students when strolling in two complex urban continuums and experiencing rapid variations in sun and wind conditions. An index was proposed to categorize the varying wind and solar radiation in both numerical and geometrical respects. The results showed that, the intensities of varying wind, varying solar radiation, and air temperature simultaneously influenced the mixed thermal perceptions. Meanwhile, the intensity of simultaneously varied wind and solar radiation can be quantified by the mean skin temperature variability in a multiple linear model. An increase in the intensity of simultaneously varied wind and solar radiation led to a two-degree rise in the acceptable air temperature and a 1.2-degree increase in the mean skin temperature threshold for irritation. The study revealed the effects of simultaneously varied wind and solar radiation on pedestrian thermal comfort, motivating urban planners to take advantage of the dynamic nature created by urban morphologies to generate wind and solar radiation variations for comfort.
Local thermal comfort plays a growing role in terms of occupant satisfaction and in the
energy performance of a building. To improve thermal comfort of occupants,
decentralized heating and cooling systems are getting more interest in the research
community but also in the market. Some studies have also shown that they can reduce
the heating and cooling demand of buildings. These systems can be for example, an office chair with heating and cooling function, a thermoelectric heating and cooling wall or even a table fan.
Building simulation software is used to optimize the energy performance of buildings
during the planning process, but just a few programs enable detailed comfort calculations. Programs which allow the usage of decentralized heating and cooling
systems are totally missing.
This dissertation presents a newly developed adaptive building controller for combined,
central and decentralized systems inside the building simulation software ESP‐r. The
building controller adapts the setpoint‐temperatures of the central heating and cooling
system and regulates the usage of decentralized systems, based on the thermal sensation and comfort values of a virtual thermal manikin in the considered building zone.
This work shall contribute to the application of detailed comfort values within building
simulation, which is also necessary to consider decentralized heating and cooling
systems like the thermoelectric movable partition or the office chair with heating and
cooling function.
The first step by the development of the adaptive controller, was the coupling of PhySCo,
a "Physiology, Sensation and Comfort" model with the building simulation software
Esp-r. The physiology model within PhySCo uses the values of room temperature, mean
radiant temperature, air velocity, relative humidity, solar radiation as well as personal
parameters such as clothing and activity level. The model calculates skin and core
temperatures for 16 individual body parts under consideration of thermophysiological
control mechanisms such as sweating, shivering, vasodilatation and vasoconstriction of
the blood vessels. These values are used to calculate local and overall sensation and
comfort values. Within the adaptive building controller, the local and overall sensation
and comfort values are used to control the setpoint‐temperatures of the central heating
and cooling system, as well as to regulate the decentralized heating and cooling systems.
The adaptive building controller with a wide deadband, with setpoints of 18 to 26 °C was
in simulation studies compared with a basic controller with a fixed and narrow setpoint
range of 21 to 24 °C. The evaluation focused on the overall comfort values and on a
possible reduction of the heating and cooling energy demand of the central system.
The results showed, that the adaptive controller could keep the comfort values at the
same level as the basic controller and reduced the heating demand at the same time
noticeably. The cooling load could also be reduced compared to the basic controller, but
the reduction was much smaller compared to the heating load.In the next step, the decentralized heating and cooling systems were added to the
adaptive building controller. First the thermoelectric heating and cooling wall, followed
by the office chair with heating and cooling function, then both systems were added to
the adaptive controller and tested together.
The results show clearly that by adding the decentralized heating and cooling systems,
the comfort could get further improved and at the same time, the heating and cooling
energy demand could get reduced.
It was noticeable that during the summer simulation period, comfort was increased,
though the increase was rather small. As an additional support, a fan was simulated,
which increased the air velocity for the heat‐sensitive head. Thereby, the comfort could
be further increased, thus the cooling of the central system was also reduced. In addition,
an increase of the upper set point to 30 °C was possible without reducing the comfort
level.
The adaptive building controller enables a detailed comfort analysis within the building
simulation software. It can also be used for the planning of decentralized heating and
cooling systems and their effect on thermal comfort.
During their daily lives, humans are frequently exposed to conditions which differ from homo-geneous moderate steady states. A widely validated multi-segmental, dynamic model of human temperature regulation was used to simulate thermal comfort experiments and to develop a phys-iologically based model for predicting the overall Dynamic Thermal Sensation (defined using the seven point ASHRAE scale). Regression analysis of measured and predicted data revealed that punitive signals associated with the mean skin temperature, the head core temperature, and the rate of the change of skin temperature are the responsible thermophysiological variables which govern the human Thermal Sensation. The new comfort model was verified and validated against exposures to steady state and various types of transient conditions and showed good general agreement with experimental observations within the range of ambient temperatures between 13°C (55.4°F) and 48°C (118.4°F) and activity levels between 1 and 10 met. The model value for analyzing the adaptive behavior of humans is illustrated.
