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Expanded psychrometric landscapes for radiant cooling and natural ventilation system design and optimization

Authors:

Abstract

Maintaining the thermal comfort of building occupants is a challenge typically negotiated by air based heating and cooling systems that rigidly maintain supply air temperatures and humidity levels. Such a practice overlooks several other design variables, including the mean radiant temperature, TMRT , which is responsible for a significant portion of an occupant’s thermal comfort, or air velocity, v(air). The increased deployment of low exergy cooling strategies such as evaporative cooling and radiant cooling allows temperature potentials to be efficiently and effectively leveraged. However, the precise execution and subsequent control of these potentials in air based or radiant systems is driven by incomplete empirically based standards, removing heuristic guiding. Deciding where system setpoints should be for systems that go beyond simple air based cooling is difficult to arrive at through intuition and current metrics, as the inclusion and modulation of other thermal comfort variables such as air velocity, skin temperature, skin wettedness and metabolic rate are not entirely independent variables. The focus of this research is to approach thermal comfort with an occupant-centered stance, comparing heat loss through primary modes of heat transfer generated by an occupant’s metabolic rate. In doing so, the holistic integration of all comfort variables currently missing from the literature opens a window into an integrated design landscape including air temperature, T(MRT) , and relative humidity as the relevant independent variables for thermal comfort. Building on the array of low exergy building systems with integrated evaporative and radiative cooling systems in the literature, this new landscape will be presented as a tool for assessing a new radiant cooling system.
Available online at www.sciencedirect.com
Energy Procedia 00 (2016) 000–000
www.elsevier.com/locate/procedia
CISBAT 2017 International Conference Future Buildings & Districts Energy Eciency from
Nano to Urban Scale, CISBAT 2017 6-8 September 2017, Lausanne, Switzerland
Expanded psychrometric landscapes for radiant cooling and natural
ventilation system design and optimization
Eric Teitelbauma,, Forrest Meggersb,c
aCivil and Environmental Engineering, Princeton University, Princeton, NJ, 08544, USA
bSchool of Architecture, Princeton University, Princeton, NJ, 08544, USA
cAndlinger Center for Energy and the Environment, Princeton University, Princeton, NJ, 08544, USA
Abstract
Maintaining the thermal comfort of building occupants is a challenge typically negotiated by air based heating and cooling sys-
tems that rigidly maintain supply air temperatures and humidity levels. Such a practice overlooks several other design variables,
including the mean radiant temperature, TMRT , which is responsible for a significant portion of an occupant’s thermal comfort,
or air velocity, vair. The increased deployment of low exergy cooling strategies such as evaporative cooling and radiant cooling
allows temperature potentials to be eciently and eectively leveraged. However, the precise execution and subsequent control of
these potentials in air based or radiant systems is driven by incomplete empirically based standards, removing heuristic guiding.
Deciding where system setpoints should be for systems that go beyond simple air based cooling is dicult to arrive at through
intuition and current metrics, as the inclusion and modulation of other thermal comfort variables such as air velocity, skin temper-
ature, skin wettedness and metabolic rate are not entirely independent variables. The focus of this research is to approach thermal
comfort with an occupant-centered stance, comparing heat loss through primary modes of heat transfer generated by an occupant’s
metabolic rate. In doing so, the holistic integration of all comfort variables currently missing from the literature opens a window
into an integrated design landscape including air temperature, TMRT , and relative humidity as the relevant independent variables for
thermal comfort. Building on the array of low exergy building systems with integrated evaporative and radiative cooling systems
in the literature, this new landscape will be presented as a tool for assessing a new radiant cooling system.
c
2016 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of the scientific committee of the CISBAT 2017 International Conference Future Buildings &
Districts Energy Eciency from Nano to Urban Scale.
Keywords: Thermal comfort; Psychrometrics; Radiant Cooling; Mean Radiant Temperature
1. Introduction
In a broad sense, buildings act as barriers between biological thermal engines and ambient environmental condi-
tions, providing protection from undesirable conditions that would otherwise direct heat and coupled mass transfer
to the engine at rates incongruent with engine output. In this analogy, a building is abstracted as a heat and mass
Corresponding author. Tel.: +1-609-408-7786.
E-mail address: eteitelb@princeton.edu
1876-6102 c
2016 The Authors. Published by Elsevier Ltd.
Peer-review under responsibility of the scientific committee of the CISBAT 2017 International Conference Future Buildings & Districts Energy
Eciency from Nano to Urban Scale.
2Author name /Energy Procedia 00 (2016) 000–000
exchanger for a human body, with dynamically linked conductive, convective, and radiative modes available to tune
the rate of heat loss or gain. Yet despite the depth of our understanding regarding thermoregulation and radiant heat
transfer, the majority of HVAC systems control for comfort using air based metrics. And when radiant systems are
installed, they rarely are controlled adequately with TMRT values. Even if such controls existed, our familiarity with
air based systems has led to an intuition for air temperature set points, however the same could not be said for radiant
systems or air velocities. As such, the overarching goal of this research is to reimagine comfort criteria with intuitive
visualizations for design and control of more complex systems.
Nomenclature
A area
MR metabolic rate
P partial pressure
Q heat
T temperature
h heat transfer coecient
v air velocity
w skin wettedness
emissivity
σStefan-Boltzmann constant
wb wet bulb
dp dew point
eevaporative
cconvective
rradiative
skin skin property
air air property
MRT mean radiant temperature
Heat transfer in buildings occurs through radiative and convective exchanges, convection linked explicitly to evap-
orative mass transfer, and conductive exchanges. However, standard practice attempts to maintain historically-dictated
stringent guidelines, referred to as the “comfort zone”, which uses operative temperature and moisture content in air
as the two tunable parameters through which comfort is achieved. Academically, thermal comfort is well researched,
and empirical and analytical relationships exist between thermal comfort and a full set of climatic conditions for a
building space [1,2]. A full framework for human comfort has been proposed through the frame of exergy destruction
[3,4].
Using the heat transfer analogy, it becomes clear that a static comfort zone is true for a subset of conditions only.
Such a dimensional reduction, however, excludes many facets of heat transfer that could more eciently maintain
comfort. Still, a conventional comfort zone dictated by air temperature and relative humidity only. This approach
neglects the influence of mean radiant temperature, air velocity, skin wettedness, and an individual’s metabolic rate.
A phenomenal tool was created by the Berkeley Center for the Built Environment that takes inputs for each of these
parameters, however variables are still fixed and trends are not easily discerned with precision [5].
2. Methods
Applying a reductionist approach to thermal comfort yields seven key variables acting within 3 interconnected
modes of heat and mass transfer (radiative, convective, and evaporative, neglecting conduction for this analysis). The
7 variables are air temperature, Tair, mean radiant temperature, TM RT , relative humidity, %RH, skin temperature, Tskin ,
air velocity, vair , skin wettedness, w, and metabolic rate, MR. Clothing level is also an important factor to consider,
however this is a variable parameter that can easily be added later to calibrate a specific model.
For this abstracted model of human comfort, the comfort condition is defined as equality between heat removed
and metabolic rate. Metabolic rates are well defined and independent of size, and are therefore a robust metric to serve
as the basis of this analysis [2]. Specifically 1.2 met (69.8 W/m2) is the metabolic rate of an individual performing
light oce work such as typing, and 2 met (116.3 W/m2) is one’s metabolic rate when walking briskly. These values
of metabolic rate were chosen to serve as the boundary of the oce space comfort zone, or in other words this range
describes the range a building system must be able to operate within to remove heat between 69.8 and 116. 3 W/m2
from an individual.
Author name /Energy Procedia 00 (2016) 000–000 3
Heat transfer between a building and an occupant can occur through radiative and convective exchanges, as well
as convection linked explicitly to evaporative mass transfer, and conductive exchanges. Conduction was neglected for
this paper, since conduction tends to be situational and therefore dicult to quantify, rather than the other three modes
which are always present and empirically calculable. The following equation demonstrates the objective function for
analysis.
Qevap +Qconv +Qrad =MR (1)
In equation 1, Qrepresents heat transfer in W/m2with subscripts for the particular mode of heat transfer. Parametriz-
ing this model in equation set 2 reveals interconnectedness between the relevant modes of heat transfer.
Qevap =f(w,%RH,Tskin,vair)Qconv =f(vair,Tair ,Tskin)Qrad =f(TM RT ,Tskin) (2)
Each mode is coupled by a dependence on skin temperature, and evaporative and convective modes have a dependence
on vair.
In models presented by Arens and deDear [2,6], the three modes are simply portrayed as potential-driven transfer
mechanisms as depicted in equation sets 3 through 5. Equation set 3 shows Qconv divided into a two regimes, forced
and free convection. Free convection occurs for vair 0.1m/sand forced convection occurs for vair >0.1m/s. For
this paper, free convection assumes an individual is sitting, and forced convection assumes an individual is standing
(walking) thereby changing the form of hc[2].
Qconv =hc(Tskin Tair)hc,fr ee =0.78(Tskin Tair)0.56 hc,f orced =10.4v0.56
air (3)
Equation set 4 shows the dependence of evaporatively generated heat transfer on convective heat transfer as shown
in the heterm, in addition to partial pressure dierences, P. In this model, Pskin,sat is the partial pressure of water at
the skin’s surface and therefore at Tskin, and Pair is the partial pressure of water in the air at Tair. For an individual that
is not sweating but transporting moisture at a background rate, it is assumed that w=0.06. At the onset of sweating,
this number increases to a maximum practical threshold of 0.80 [2].
Qevap =whe(Pskin,sat Pair )he=16.5hc(4)
Equation set 5 is an empirical simplification of radiant heat transfer that is possible due to relatively small temper-
ature dierences at building scales. AR
ADrepresents the eective area through which radiative heat transfer can occur,
chosen for a seated, clothed occupant.
Qrad =hr(Tskin TMRT )hr=4 σ AR
AD
[273.15 +Tskin +TMRT
2]3AR
AD
=0.70 (5)
The challenge is presenting these empirical models as a comprehensive, holistic, and intuitive model, rather than a
disparate set of equations.
Additionally, a significant amount of research has been conducted measuring skin temperature as a function of air
temperature [7], a useful equation to begin reducing parameters among the modes of heat transfer. While there is a
nonuniform relaxation period during which the skin temperature approaches the equilibrium value, a simple linear
expression can be defined to more accurately model Tskin as a function of Tair as follows in equation 6, which fits data
with R2=0.99.
Tskin =0.3182Tair +22.406 (6)
Using these fundamental relationships, a model was developed using Python scripting that allowed for the funda-
mental parameters to be varied and the resulting topology change plotted. Similar to the models created by Shukuya
[3] and Fanger [1], these topologies were created with the intent of defining a comfort zone and performing a gener-
alized system optimization. However unlike other work in the field, the intended goal of this analysis is to provide a
user with an intuitive picture of his or her surroundings, adding more complexity than just air temperature and relative
humidity.
4Author name /Energy Procedia 00 (2016) 000–000
3. Results
The generalized heat transfer models have the flexibility to incorporate any set of the 7 fundamental parameters.
Since heat flux via radiative, evaporative, and convective modes are treated equally, comfort is defined as when the
sum of these three equals an individual’s metabolic rate. For using radiant systems to address thermal comfort, the
design space was able to be dimensionally reduced parametrizing %RH and eliminating forced convection entirely.
This allowed for TMRT to be solved implicitly for a given MR,w, and Tskin . Figure 1 demonstrates this result for
MR =2 met, w=0.6, and Tskin =f(Tair ). This assumes that air is entering a room with a known Tair and %RH, and
these values are used to solve implicitly for the required TMRT for the given metabolic rate. In figure 1, the standard
psychrometric chart is superimposed on the calculated TMRT at each (Tair ) and %RH, for a fixed MR and w. Equation
6 was used to make Tskin a dependent variable in this model.
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
MRT C
18.8
19.2
19.6
20.0
20.4
20.8
21.2
21.6
22.0
22.4
22.8
23.2
23.6
24.0
24.4
24.8
25.2
25.6
26.0
18.5
19.7
20.9
22.1
23.3
24.5
25.7
26.9
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
MRT C
20.8
21.6
22.4
23.2
24.0
24.8
25.6
26.4
27.2
28.0
28.8
29.6
30.4
31.2
32.0
32.8
33.6
34.4
35.2
20.2
22.4
24.6
26.8
29.0
31.2
33.4
35.6
Fig. 1. (a) Expanded comfort zone for free convection at MR =1.2 met and w=0.06 when TMRT , shown by the gradient, is solved for, expanding
the comfort zone to encompass many air temperature and humidity regimes. (b) Expanded comfort zone for forced convection at MR =1.2 met for
forced convection at vair =0.5 m/s. The nearly vertical white line corresponds to TMRT =Tair , the middle white line as TMRT =Twb, and the top
white line corresponds to TMRT =Td p.
In figure 1 the comfort zone has been greatly expanded with the inclusion of radiant cooling and heating. For any
Tair and %RH on the x,yplane, there is now a corresponding TMRT which must be achieved to satisfy the comfort
condition, indicated by the color gradient. Practicalities associated with deriving particularly low values for TMRT set
aside for this study, this assessment of thermal comfort provides visual confirmation of the narrow approach associated
with air-based design only.
Figure 1 also includes white lines for dierent TMRT scenarios. Namely The nearly vertical white line corresponds
to TMRT =Tair , the middle white line as TMRT =Twb, and the top white line corresponds to TM RT =Tdp . Therefore,
any point that lies above the top white line could expect condensation on surfaces providing the required TMRT . While
typically a design constraint, there are commercially available radiant cooling panels that allow cooling below the dew
point [8,9].
Interpretation of the figure would require knowing the mean radiant temperature perceived by an occupant, some-
thing not typically available but certainly obtainable [10]. For a given Tair, %RH, and TMRT , the plotted point would
have an (x,y) coordinate, and a color determined by the mean radiant temperature. A mismatch between the tempera-
ture of the datapoint and the background TMRT would imply the occupant could be more comfortable, and either Tair
or TMRT should be adjusted accordingly.
The same approach can be used to visualize the eects of a forced convection based system, i.e. fans, by solving
for a required air velocity. Here, the function used to reduce the dimensionality of the problem is TM RT =Tair, a
standard HVAC assumption. For cooling demand, air velocities can be determined.
Figure 2 demonstrates some nonlinearities experienced with air based comfort, as moving from 2a to 2b demon-
strates sweat’s ability to shed heat. 2 met and 20% skin wettedness is not a likely steady state oce environment
scenario, and likely implies a transitional period such as arriving to work from a bike ride or climbing many flights of
stairs. Therefore an oce maintained at conditions presented in figure 2b would not be desirable.
Author name /Energy Procedia 00 (2016) 000–000 5
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
m/s
0.1
0.3
0.5
0.7
0.9
1.1
1.2
1.4
1.6
1.8
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
m/s
0.1
0.3
0.5
0.7
0.9
1.1
1.2
1.4
1.6
1.8
Fig. 2. (a) Expanded comfort zone for forced convection at MR =1.2 met and w=0.06 when TM RT =Tair, and vair shown by the gradient is
solved for. (b) Expanded comfort zone for forced convection at MR =2 met and w=0.2.
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
MRT C
18.8
19.2
19.6
20.0
20.4
20.8
21.2
21.6
22.0
22.4
22.8
23.2
23.6
24.0
24.4
24.8
25.2
25.6
26.0
18.5
19.7
20.9
22.1
23.3
24.5
25.7
26.9
5 10 15 20 25 30 35 40
Air Temperature C
0
5
10
15
20
25
Humidity Ratio (g water/kg dry air)
10%
20%
30%
40%
50%
60%
70%
80%90%
100%
m/s
0.1
0.3
0.5
0.7
0.9
1.1
1.2
1.4
1.6
1.8
Fig. 3. (a) Cooling in San Francisco’s Federal Building modeled with a radiant system operating under Tair =TMRT , and (b) more aggressive
natural ventilation system. Singapore climate data is also shown.
4. Discussion
This work provides a new set of visualizations for thermal comfort, and familiarity with radiant and air velocity
setpoints for system control and design can be achieved. To put the model into perspective, San Francisco’s moder-
ate climate was compared to climate conditions in tropical Singapore. Figure 3b uses TMY3 weather data for San
Francisco and Singapore, plotting air temperature and humidity ratio on the xand yaxes, with the color assignment
determined by the prevailing wind speed. A mismatch between the color of a point and the background implies an
uncomfortable condition. If the wind speed is too great, the occupant would likely feel cold, or too blue for slow
wind, and the occupant would feel hot. Figure 3b shows that passive cooling through natural ventilation should be
sucient, implying solutions should be built in so occupants can reduce the air volume, rather than restrict the air into
the building. Free cooling could also be accomplished with a wet-bulb hydronic radiant cooling system, as shown in
figure 3a. This figure was generated similar to figure 3b, but instead with the assumption that TMRT =Tair for some
type of hydronic radiant system maintaining a TMRT as dictated by Tair . Only a small subset of points are mismatched
as being too warm, which could be addressed with a wet bulb evaporative cooling system for the radiant system.
However this still some form of active system incurring parasitic power costs, unlike the completely passive natural
ventilation system, making radiant cooling in San Francisco less desirable.
Singapore is a good contrasting example, as maintaining occupant thermal comfort is a more challenging endeavor.
Conditions are always hot and humid, and figures 3a and b shows that wind alone and evaporatively driven wet-bulb
cooling cannot always generate comfort. High humidity makes evaporative cooling dicult, and often radiant systems
6Author name /Energy Procedia 00 (2016) 000–000
are avoided as the risk of condensation is believed to be too high. However, a new class of radiant cooling panels [8]
that allow supply temperatures to go below the dew point while avoiding condensation could be used to cool surfaces,
rather than incoming air. And when combined with a desiccant dehumidification system rather than a conventional
sub dew point driven system, power consumption is considerably lower than with conventional systems [11].
However, visualizing the climate conditions in terms of required setpoints for unconventional systems, i.e. radiant
cooling or natural ventilation, helps engineers and architects achieve realistic design opportunities truly based on local
climate. Using the expanded psychrometric chart as a tool, one easily identifies methods other than standard vapor
compression air conditioning approaches that could be used to maintain occupant thermal comfort. Since Singapore
and San Francisco have such dierent climatic conditions, it makes sense that radiant cooling and natural ventilation,
respectively, may be the most sensible alternative choices. But most importantly, it is also clear that prescribing the
same standard air conditioning systems to the two extraordinarily dierent design opportunities is also a mistake, and
using such a tool can remedy such situation in the future.
Going one step further in the context of actual buildings, the Federal Building in San Francisco uses passive ven-
tilation where air velocities cannot be set. Unfortunately, the design narrative was not translated in to a comfortable
space with only 32% of occupants reporting feeling comfortable due the lack of freedom with the air velocity. In
Singapore, the 3for2 [11] installation was used as pilot program for desiccant dehumidification with radiant panels,
however radiant temperature cannot be modulated. (The 3for2 post occupancy comfort studies are currently under-
way.) Using a more holistic approach such as the proposed expanded psychrometrics to system design should help
elucidate the methods for better control and design of sustainable building systems.
5. Conclusions
This work was particularly successful at designing a new radiant cooling and natural ventilation framework allow-
ing HVAC engineers and architects design for systems that do not change the air temperature or humidity to provide
comfortable living or working conditions. The theoretical governing equations for controlling such systems were syn-
thesized, and a thermal comfort reference framework within which both air and radiant systems may be adjusted was
developed, intuitively and quickly allowing occupants and operators to visualize which parameters could be modified
to become more comfortable. Future work could look more closely at materials for sub-Td p radiant cooling panels. A
rigorous thermal comfort study should be performed in the high humidity, high temperature, low radiant temperature
region of the expanded thermal comfort zone to fully verify the model.
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... The result is a space that uses radiation to activate a shift of the occupant's perception of temperature while minimizing any actual convective cooling of the outside air. The mean radiant temperature (MRT) is depressed by the wet bulb surface temperature 25 of the indirect evaporative cooling system, creating a unique experience of feeling cooled without any actual air conditioning in the space. ...
... We analyze this difference by considering the convective heat transfer in equation set 1, and compare that to the radiant heat transfer in equation set 2. These can be combined to generate 210 a ratio of radiant to convective heat transfer making some assumptions about airflow in a simple free convection regime. This ratio can be calculated from the experimental data taken for the Thermoheliodome and illustrates its ability to maintain occupant cooling via radiation as convective cooling becomes limited as the air temperature approaches an occupant's skin temperature [25,24]. ...
... Our ongoing and future work considers the broader implications of designing systems to leverage radiant heat transfer for comfort delivery [25], and considering the potential for using optimal 360 human body exergy analysis to control heating and cooling thereby moving away from conditioning rooms and toward conditioning people [33]. In the vein, the SMART sensor that was developed for scanning the MRT in the Thermoheliodome has the potential to define the MRT in rooms with radiant cooling panels or heated floors that are poorly controlled by thermostats that only measure air temperature, and can also detect the presence and surface temperature of occupants for better 365 comfort control [18]. ...
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The Thermoheliodome is an experimental pavilion that explores cooling without air conditioning. The two research aims were to explore the use of indirect evaporative cooling and the geometric reflection of radiant cooling. For evaporative cooling we utilize a cooling tower outside of the pavilion to indirectly supply water chilled near the wet-bulb temperature. The radiant cooling system is made up of 55 coaxial chilled pipes each located in the central axis of cones with reflective surfaces that spectrally reflect the surface of the pipes and expand their radiant view factor to the occupants inside the pavilion. The specific geometry was digitally fabricated using an industrial robot and hot-wire foam cutter. The mean radiant temperature (MRT) was shown to be significantly decreased using thermal imaging cameras and with a novel scanning MRT sensor. The radiant cooling delivered from the fluid is maximized by reflection and concentration of heat emitted by occupants on the pipes, while the convective cooling of the air is minimized because only the small pipes are cooled and the reflecting surfaces are not, so the convective heat transfer surface area is small. Under typical indoor conditions the ratio of radiant to convective cooling is slightly greater than one, and for warm daytime conditions it was greater than 10 inside the pavilion. Occupant surveys found that although the air temperature was not modified, they felt that inside the space there is a cooling sensation (p ≤0.01). The day of the survey they felt on average 3 ° C cooler.
... Line C is which shows the upper limit of M-Cycle evaporative cooling, but also the risk of condensation with conventional radiant cooling panels. Reproduced with permission from [23]. ...
... Additionally, it is assumed that . Reproduced from [23]. ...
... Additionally, it is assumed that . Reproduced from[23]. ...
... To show the condition of the air at any time needed a system that is integrated between the data acquisition device and data display. This research designs and develops applications that are ready to display data and psychrometric charts that can later be integrated with hardware equipped with sensors through an interface [10][11][12][13]. Psychrometric applications are designed using the JavaScript programming language, so they can be opened using any web browser. ...
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This paper first introduces the concept of "exergy", which quantifies what is consumed by any working systems from man-made systems such as heat engines to biological systems including human body. "Exergy" balance equation for a system can be derived by combining both mass/energy and entropy balance equations based upon the two thermodynamic laws together with the concept of "environmental temperature" for the system to be described. The unique feature of the exergy balance equation, distinct from the energy balance equation, is that a term quantifying "consumption" appears explicitly. Exergetic view leads us to deepening our understanding of the built environment and thereby to the development of various low-exergy systems for future buildings. The rest of the paper outlines some of the findings obtained from the recent exergy research focusing on the built environment. What follows are that 1) exergy contained by a volume of indoor air consists of "warm" or "cool" exergy and "wet" or "dry" exergy; 2) a heat pump is basically an equipment to separate exergy supplied by electricity into warm, cool and dry exergies; 3) there is the lowest human-body exergy consumption rate in winter season; 4) availability of cool radiant exergy seems very important for a naturally-ventilated room in summer season; 5) "cool" radiant exergy available from the sky is not marginal even in the hot and humid regions so that its exploitation for cooling is to be pursued.
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Human thermal physiological and comfort models will soon be able to simulate both transient and spatial inhomogeneities in the thermal environment. With this increasing detail comes the need for anatomically specific convective and radiative heat transfer coefficients for the human body. The present study used an articulated thermal manikin with 16 body segments (head, chest, back, upper arms, forearms, hands, pelvis, upper legs, lower legs, feet) to generate radiative heat transfer coefficients as well as natural- and forced-mode convective coefficients. The tests were conducted across a range of wind speeds from still air to 5.0 m/s, representing atmospheric conditions typical of both indoors and outdoors. Both standing and seated postures were investigated, as were eight different wind azimuth angles. The radiative heat transfer coefficient measured for the whole-body was 4.5 W/m2 per K for both the seated and standing cases, closely matching the generally accepted whole-body value of 4.7 W/m2 per K. Similarly, the whole-body natural convection coefficient for the manikin fell within the mid-range of previously published values at 3.4 and 3.3 W/m2 per K when standing and seated respectively. In the forced convective regime, heat transfer coefficients were higher for hands, feet and peripheral limbs compared to the central torso region. Wind direction had little effect on convective heat transfers from individual body segments. A general-purpose forced convection equation suitable for application to both seated and standing postures indoors was h c=10.3v 0.6 for the whole-body. Similar equations were generated for individual body segments in both seated and standing postures.
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This paper briefly describes the human-body exergy balance equation developed so far applying a variety of formulae derived from the fundamentals of thermodynamics, namely the concepts of wet/dry exergy associated with moist air and liquid water, warm/cool exergy transferred by radiation and convection. A couple of numerical examples of the whole human-body exergy balance are given and discussed in relations to mean radiant temperature, room air temperature, air velocity, and outdoor environmental temperature. We have found so far that it is very important to control the amount of thermal radiant exergy in room space both in winter and in summer.
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