1、4765 (RP-1162) Window Performance for Human Thermal Comfort Jeet Sengupta Kirby S. Chapman, PhD Ali Keshavarz, PhD ABSTRACT This paper discusses the development of a methodology to quantib windowperformance on human thermal comfort with eight case studies of different window systems. The methodol- o
2、gy is based on the Building Comfort Analysis Program that was developedduringASHRAEresearchprojects 657and907. Human thermal comfort is achieved by maintaining a heat balance between the human body and the environment. This is accomplished by convection and radiation. In a room there are other assoc
3、iated issues, such as conduction through the walls, convection past the walls, and radiation between the various surfaces, that will influence comfort. Thepresence of a window system adds complexity to the problem as they have different optical and thermal properties. This paper expands on the exist
4、ing three-dimensional mathematical model by incorpo- rating a method to read in a user-de$ned window and also read in the properties obtained from the widely available Window 5. I TMprogram. A representative case study is analyzed to illus- trate the means of quantifying the results. Results have be
5、en quantjed as percentage of comfortable floor area. INTRODUCTION Human thermal comfort, defined as a state of mind that expresses satisfaction with the thermal environment (ASHRAE 1992), is a function of convective and radiative heat transfer between the human body and the surroundings. In a built
6、environment, such as an office space or residential homes, rooms usually have windows on one or more walls. Since a window, which is composed of frame, muntins, and glass, has different thermal and optical properties than walls, energy exchange between the human body and the window is significantly
7、different from the exchange between the body and the walls. Thus, the presence of a window in a room impacts thermal comfort quite differently. The simplest way to ensure that everyone is comfortable is to ask each person in a room and then regulate the heating or cooling system to satis every indiv
8、idual. Since there are large variations, physiologi- cal and psychological, from person to person, it is difficult to satisfi everybody in the space. Hence, this method may result in numerous thermostat adjustments and, as a worse case, rein- stallation of the entire heating or cooling system. Since
9、 the environmental conditions required for comfort are not the same for everyone, the study of thermal comfort is complex and intriguing and the presence of a window in a room further adds to this complexity. Thus, the type and size of a window system will dictate the localized comfort. If building
10、enve- lopes with enhanced window areas have to be adopted and heating and cooling systems designed to incorporate the effects of the same, it is vital to understand how the presence of a window impacts localized human thermal comfort. Thermal Comfort Variables and Quantifying Parameters Human therma
11、l comfort has been traditionally quantified by six variables: activity level, clothing insulation value, air velocity, humidity, air temperature, and mean radiant temper- ature (Fanger 1967). The dry-bulb air temperature measures the temperature of air in the room, while Tmrr is a measure of the rad
12、iant energy exchange between the room surfaces and the occupant. Since convective and radiative heat transfer both play a role in the occupants perceived temperature (Chapman and DeGreef 1997), neither mean radiant temperature nor the dry-bulb temperature alone is a good thermal comfort indica- tor.
13、 Instead, Fanger (1 967) suggested using the operative Jeet Sengupta is a graduate student, Kirby S. Chapman is a professor and director of the KSU National Gas Machinery Laboratory, and Ali Keshavarz is a research associate professor in the Department of Mechanical and Nuclear Engineering, Kansas S
14、tate University, Manhattan, Kansas. 254 02005 ASHRAE. temperature (To a review of them appears in Brager and deDear ASHRAE Transactions: Research 255 (1998) and Watson and Chapman (2001) in general, but they do not focus specifically on quantifying the impact of windows, A joint study done by the Wi
15、ndows and Daylighting Group at Lawrence Berkeley National Laboratory (LBNL) and the Center for Environmental Design Research (CEDR) at the University of California at Berkeley used a parametric approach to study windows and their effect on indoor comfort. Ten generic glazing systems, ranging from a
16、single-pane window to high-performance windows were examined for their thermal comfort impacts. The PMV was calculated for each combination of occupantiwindow geometry, window surface temperature, and clothing insulation. Results in terms of net PPD for each case were plotted to help visualize the t
17、rends for the dependence of thermal comfort on clothing and window type (Lyons et al. 1999). THERMAL COMFORT SIMULATION AND MODELING THE EFFECT OF WINDOWS It is understood from the above discussion that the impact ofwindows on human thermal comfort can be quantified if, for a room with windows, the
18、air and mean radiant temperatures can be accurately calculated, since other quantifying comfort parameters depend on these two variables. The dry-bulb temperature is easily measured, while the mean radiant temperature can be calculated either by the classical method using surface temperatures and vi
19、ew factors, as described in ASHRAE Fundamentals (ASHRAE 2001), or the radiant intensity method presented by Chapman and DeGreef (1 997). The classical method assumes the surfaces to be isothermal. Unfortunately, such is not the case for walls bearing windows. Because of different thermal and optical
20、 properties of the glaz- ing, the glazing surface temperatures are distinctly different from the wall surface temperatures. In such cases the surface is subdivided into smaller surfaces until the assumption of uniform temperatures is valid. This necessitates calculating a large number of view factor
21、s beween the point under analysis and the surfaces as the number of surfaces increases. Further, since the glass is opaque in the infrared region, the radiant energy in that region is reflected back into the room and this effect is not accounted for in the classical method. Also, in the case where s
22、olar radiation, which is short-wavelength radia- tion, shines through a window, the method fails, as it does not consider window transmission and only considers the wall surface temperatures as boundary conditions. On the other hand, in the radiant intensity method, the mean radiant temper- ature is
23、 calculated by (Chapman and DeGreeC1997): (4) Since this equation provides a more generalized approach to calculating T, than using the surrounding surface temper- atures given in the classical method and was extensively vali- dated by DeGreef and Chapman (1 998), this method is used here to calcula
24、te the mean radiant temperature. However, this necessitates an accurate determination of the radiant intensity field. The easiest way to do so would be to solve the radiative transfer equation (RTE) (zisik 1977; Siegel and Howell 1981; Viskanta and Mengc 1987): For the case of a typical occupied roo
25、m, the absorption and scattering coefficients can be assumed to be zero and the equation reduces to ar, ar, ai, ax ay aZ p-+k-+q- =o The associated boundary condition in the x, y, and z direc- tions are given by (7) where Each of the equations in equation set 7 has two terms. The first term represen
26、ts the spectral emission from the surface, while the second term represents the reflected radiant inten- sity. Several models that engineers have developed to acquire the techniques of the RTE solution are documented in Siegel and Howell (1 98 i) and Modest (1 993). A review of the solu- tion techni
27、ques can be found in Chapman and Sengupta (2004) and DeGreef (1998). The technique adopted here is the discrete ordinates model first developed by Carlson and Lath- rop (1968) in the neutron transport analysis. Jones and Chap- man (1994) used this model in ASHRAE Research Project 657 to develop an i
28、mproved methodology, known as the BCAP methodology, to determine radiant exchange in an enclosure and incorporate the same in human comfort calculations. The model, also used by Chapman and Zhang (1995, 1996) and Chapman et al. (1997), considers discrete directions and nodes (Figure lc) and calculat
29、es the radiant intensity at each point and direction within the enclosure. The enclosure space is divided into a three-dimensional space of finite control volumes, and Equation 6 is integrated over each three-dimen- sional control volume. The resulting equation in a discrete directionj is given by 2
30、56 ASHRAE Transactions: Research 4 c a .T Fgure IC Discrete ordinates model. Direction Ordinate x+Ax y+Ay z+Az I I I Pz ap+-+q- ay dz dxdydz = O. (9) “I pj 8, rll wj The control volume intensity on one side is assumed to be independent of the other two directions. For example, the intensity on the x
31、 interface is not affected by the y and z direc- tions (Patankar 1980). The consequence of this procedure is that the intensity I$, is uniform over the left surface of the control volume (Figure lc). Similarly, the intensity 4 is uniform over the bottom surface of the control volume. The equation th
32、en becomes Table 1. First Quadrant Values for Direction Cosines and Weighting Factors 1 I 1 -0.2959 1 -0.9082 1 :.:21: 1 0.5239 o.5236 1 0.2959 -0.9082 0.2959 -0.9082 -0.9082 0.5236 -0.2959 -0.2959 0.9082 0.5236 C(AzAy4 + AzAx$ + qAxAy4 JAzAy + eAzAx + qJAxAy . Ip= (12) . Equation 12 is written for
33、all the discrete directions for each control volume. For the fourth-order discrete approxima- tion (S,) each control volume has 24 discrete directions. The values for $, tJ, and must satisfi the integral of the solid angle over all the directions, the half-range flux, and the di Jamaluddin and Smith
34、, 1988). The values for Ax, Ay, and Az are determined by the size of the control volume. The solution for Equation 12 is essen- tially an iterative solution solved in conjunction with appro- priate boundary conditions. The discretized form of the boundary conditions given by Equation 7 is: love 1988
35、; Fiveland 1988): The interpolation factor a is set equal to 1 to avoid nega- (13) tive intensities (Fiveland 1987, 1988), which are physically impossible and will yield unstable solutions. Substituting Equation 11 into Equation 10 yields Equation 12 is solved iteratively in association with boundar
36、y conditions given by Equation 13 to obtain the inten- sity in each ofthe j directions at pointp. These can be then used ASHRAE Transactions: Research 257 in Equation 4 to determine the mean radiant temperature. Note that for a room with a glazing system, the boundary conditions need to be modified
37、to incorporate the transmission through the window. The x direction boundary condition can then be written as: where It was seen earlier that apart from the mean radiant temperature, the air temperature was the other quantity required to calculate the operative temperature and the PME Though the air
38、 temperature can be easily measured using a dry-bulb thermometer, since a numerical technique was employed to calculate the mean radiant temperature, a numer- ical scheme can be easily adopted to calculate the air temper- ature as well. Such a numerical scheme would need a room air energy balance an
39、d a wall surface energy balance for each wall. For steady-state calculations the equations are: r 1 The first term of Equation 16 represents convective losses to the bounding surfaces, and the second term represents the air infiltration rate, where To is the temperature of the infiltrat- ing air. Th
40、e first term of Equation 17 represents conduction through the wall where R, is the thermal resistance of the wall and the outer convective boundary layer. The second term is the convective heat flux between the inner surface and room air. The third term represents the incident radiant heat flux abso
41、rbed by the wall surface, while the fourth term is the radi- ant emission from the wall. Together these two terms equal the net radiant heat flux at the bounding surface. Equations 16 and 17 can be solved iteratively in association with relevant bound- ary conditions. A finite difference method as d
42、escribed by Patankar (1 980) was used for the numerical solution. Interest- ingly the value of Z(Q) needed in Equation 17 can be obtained by solving the RTE using the discrete ordinates model delin- eated earlier. Furthermore, solving Equations 16 and 17 will also give the surface temperature 1;: fo
43、r each wall surface element. BCAP Modified The Building Comfort Analysis Program (BCAP) meth- odology (Jones and Chapman 1994), briefly reviewed earlier, Figure Id Modjed BCAP methodology (Chapman and Sengupta 2004). has been used with necessary modifications to suit the work presented here. Figure
44、Id gives the modified methodology. The boundary condition has been modified to include trans- mission through the glazing system, and they have been math- ematically described in Equation14. The other enhancement has been to incorporate the surface properties directly from the Window 5.1TM program a
45、nd the ability to describe a frame around the glazing system. The last modification to the exist- ing BCAP has been the addition of PMV to quanti the ther- mal comfort along with the operative temperature. The PMV corresponding to a PPD of 10% is calculated at each node point in the calculation doma
46、in, and the PMV distribution at a height of 1.25 m from the floor is plotted. 258 ASHRAE Transactions: Research Figure 2 Room geometry, fenestration configuration, and numerical mesh. CASE STUDIES 2. ASHRAE summer daytime (32C) outside temperature while the room is maintained at 24C with a solar bou
47、ndary condition of 780 W/m2 on the lefi wall for cases 1,2,5, and A test room 4 m x 4 m x 2.5 m high (Figure 2a) was analyzed for eight different window configurations, as / o. detajled in Table 2. Table 3 furnishes the geometric details, Table 4 provides the optical properties of glazing systems, a
48、nd Table 5 gives the thermal properties for each case. BoundaV conditions imposed were: 1. ASHRAE winter nighttime (-18C) outside temperature while the room is maintained at 21 “C for cases 3,4,7, and 8. A thermostat located on the right wall controlled the temperature inside the room. For cases 1 t
49、hrough 4 the ther- mostat is located 1.25 m from the floor and 2 m from the back wall (Figure 2c), while for cases 5 through 8 it is located 1 m from the back wall (Figure 2d). In the simulation, the exterior ASHRAE Transactions: Research 259 Table 2. Characteristic Features of the Demonstration Cases Spectrally selective, e-0.04, argon, aluminum spacer Surface 2 Spectrally selective, e-0.04, argon, aluminum spacer Surface 3 .60 .60 .60 .60 .o0 .o0 .o0 .o0 nh Y- EE fg s 2.50 2.50 2.50 2.50 1.00 1.00 1.00 1.00 0.740 0.538 0.202 0.260 0.065 0.051 Weather Glass Room Configurati
