- Page 4 and 5: Advanced Building Simulation Edited
- Page 6 and 7: Contents List of figures vii List o
- Page 8 and 9: Figures 1.1 Simulation viewed as a
- Page 10 and 11: Figures ix 5.9 Velocity and tempera
- Page 12 and 13: Tables 2.1 Categories of uncertain
- Page 14: Acknowledgement “Advanced Buildin
- Page 17 and 18: 2 Malkawi and Augenbroe users’ pr
- Page 19 and 20: Chapter 1 Trends in building simula
- Page 21 and 22: 6 Augenbroe Environment Exp. condit
- Page 23 and 24: 8 Augenbroe list of desired tool ch
- Page 25 and 26: 10 Augenbroe increasing pace, mostl
- Page 27 and 28: 12 Augenbroe allocations for mainte
- Page 29 and 30: 14 Augenbroe B Domain experts A Dom
- Page 31 and 32: 16 Augenbroe their performance in a
- Page 33 and 34: 18 Augenbroe for commercial offerin
- Page 35 and 36: 20 Augenbroe unstructured dialogue,
- Page 37 and 38: 22 Augenbroe References Augenbroe,
- Page 39 and 40: 24 Augenbroe Sahlin, P. (1996b). NM
- Page 41 and 42: 26 de Wit model parameters, which a
- Page 43 and 44: 28 de Wit otherwise urban environme
- Page 45 and 46: 30 de Wit Now that we have discusse
- Page 47 and 48: 32 de Wit result. In fact, economy
- Page 49 and 50: 34 de Wit Hence, an overview of the
- Page 51 and 52: 36 de Wit ASHRAE (1997), ISSO (1994
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38 de Wit AIR TEMPERATURE STRATIFIC
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40 de Wit Frequency 50 40 30 20 10
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42 de Wit studies on thermal buildi
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44 de Wit Cooke and Goossens (2000)
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46 de Wit a statistical comparison
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48 de Wit Unfortunately this proces
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50 de Wit 2.5 Decision-making under
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52 de Wit in de Wit (2001)): U(x,y)
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54 de Wit a TO-performance indicato
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56 de Wit information in decision-m
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58 de Wit Jensen, S.Ø. (ed.) (1994
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Chapter 3 Simulation and uncertaint
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62 Degelman Simulation of a buildin
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64 Degelman 3.4 Model for temperatu
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66 Degelman Mean: Prob = 0.9584 72
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68 Degelman therefore be 310. Then,
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70 Degelman Dry-bulb temperature (
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72 Degelman The procedure to simula
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74 Degelman atmosphere is dependent
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76 Degelman Direct fraction, K D=(H
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78 Degelman 3.8 Correlations betwee
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80 Degelman H = Total daily horizon
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82 Degelman Generally, the monthly
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84 Degelman compared to the simulat
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86 Degelman TRY (1976). “Tape ref
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88 Hensen Application Basic buildin
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90 Hensen Window conduction Transmi
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92 Hensen Table 4.1 Summary of pred
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94 Hensen Table 4.2 Typical fluid f
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96 Hensen As can be seen, the diffe
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98 Hensen Computed pressure c(0) c(
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100 Hensen Ping-pong Onion Flow The
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102 Hensen While, in principle, it
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104 Hensen Air flow (kg/s) 25.0 20.
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106 Hensen Table 4.3 Statistical su
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108 Hensen In some occasions, such
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Establish initial level of complexi
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112 Hensen A second step is to chec
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114 Hensen ● indicates whether (d
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116 Hensen References Allard, F. (e
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118 Hensen Kafetzopoulos, M.G. and
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120 Chen and Zhai combined indoor a
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122 Chen and Zhai 5.2.1 Large-eddy
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124 Chen and Zhai and � k�1.0,
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126 Chen and Zhai Most CFD programs
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128 Chen and Zhai (a) 0.6 (b) U (m/
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60 60 60 60 60 60 50 50 50 x = 4.0
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132 Chen and Zhai Surface heat flux
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134 Chen and Zhai Y/H Y/H 1 0.8 0.6
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136 Chen and Zhai Y/H Y/H 1 0.8 0.6
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138 Chen and Zhai � dissipation r
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140 Chen and Zhai Topp, C., Nielsen
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142 Addington Unlike many other com
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144 Addington yield a satisfactory
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146 Addington building’s electric
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148 Addington Boundary layer thickn
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150 Addington Gr/Re 2 �� 1, the
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152 Addington and application of CF
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154 Addington emerge, particularly
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156 Addington Figure 6.4 Velocity p
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158 Addington Roache, P.J. (2002).
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160 Mahdavi Mahdavi et al. 2001a,b)
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162 Mahdavi 7.3 Self-organizing mod
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164 Mahdavi Table 7.1 Terms, defini
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166 Mahdavi practice, however, cont
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168 Mahdavi Exterior light redirect
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170 Mahdavi MC BL_EL_ Lo_1 MC BL_EL
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172 Mahdavi 7.4.2 Approach Modern b
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174 Mahdavi irradiance sensors that
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176 Mahdavi appropriate correction
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178 Mahdavi 7.4.5.3 Efficient asses
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180 Mahdavi Preference index Prefer
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182 Mahdavi Table 7.5 Initial state
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184 Mahdavi Illuminance (lx) 120 10
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186 Mahdavi Valve state (%) 120 24
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188 Mahdavi Mahdavi, A. (2001b).
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190 Augenbroe One-to-one interfacin
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192 Augenbroe initiatives began in
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194 Augenbroe vendors. The descript
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196 Augenbroe All data Version 2 Bu
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198 Augenbroe Figures 8.2-8.4 are e
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200 Augenbroe Figure 8.7 Sample ExE
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202 Augenbroe of analysis tools and
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204 Augenbroe Design activities Ana
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206 Augenbroe Design information St
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208 Augenbroe Figure 8.14 Workflow
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AF NAME: VERSION: SYSTEM: System bo
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212 Augenbroe Only a very rudimenta
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214 Augenbroe References Amor, R.,
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216 Augenbroe van Treeck, C., Rombe
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218 Malkawi Table 9.1 Development o
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220 Malkawi 9.2 Immersive building
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222 Malkawi established using a dat
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224 Malkawi the effects of the chan
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226 Malkawi Figure 9.7 Structured g
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228 Malkawi 9.2.2.1 Registration As
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230 Malkawi Table 9.3 Sensor techno
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232 Malkawi +Z 30° Frankfurt plane
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234 Malkawi 9.3 Example cases To il
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236 Malkawi collected in real-time
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238 Malkawi (a) (b) Figures 9.26 Pa
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240 Malkawi Figure 9.27 Viewer with
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242 Malkawi X Y Rotation VRML Figur
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244 Malkawi environments more power
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246 Malkawi Rangaraju, N. and Tek,
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248 Epilogue The desire for shared
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250 Index decision-making 2, 10, 14
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252 Index validation of simulation