Advanced Building Simulation

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Developments in interoperability 215 Netherlands.” Building Simulation ’01, 7th International IBPSA Conference, Rio de Janeiro, Brazil, August 13–15, pp. 513–520. DOE (2003a). US Department of Energy. Building Energy Software Tool Directory. Washington, USA. Available from: http://www.eren.doe.gov/buildings/tools_directory/ DOE (2003b) US Department of Energy. EnergyPlus. Washington, USA. Available from: http://www.eren.doe.gov/buildings/energy_tools/energyplus/ Donn, M. (1999). “Quality assurance—simulation and the real world.” Building Simulation ’99, 6th International IBPSA Conference, Kyoto, Japan, September 13–15, pp. 1139–1146. Eastman, C.M. (1999). Building Product Models: Computer Environments Supporting Design and Construction. CRC Press, Boca Raton, FL, USA. Ekholm, A. and Fridqvist, S. (2000). “A concept of space for building classification, product modelling and design.” Automation in Construction, Vol. 9, No. 3, pp. 315–328. Geebelen, B. and Neuckermans, H. (2001). “Natural-lighting design in architecture: filling in the blanks.” Building Simulation ’01, 7th International IBPSA Conference, Rio de Janeiro, Brazil, August 13–15, pp. 1207–1213. Hand, J.W. (1998). Removing barriers to the use of simulation in the building design professions. PhD thesis. University of Srathclyde, Department of Mechanical Engineering, Energy Systems Research Unit, Glasgow, UK. Hitchcock, R.J., Piette, M.A., and Selkowitz, S.E. (1999). “A building life-cycle information system for tracking building performance metrics.” In Proceedings of the 8th International Conference on Durability of Building Materials and Components, May 30 to June 3, Vancouver, BC. IAI, International Alliance for Interoperability, (2002). Industry Foundation Classes, Release 2.2x. IAI web site, http://www.iai-international.org/iai_international/ ISO TC184/SC4 (1989–2003), ISO-STEP part standards. ITCON (2003). Vol. 8, Special Issue IFC—Product models for the AEC Arena, http://www.itcon.org/ Karlen, I. (1995a). “Construction Integration—from the past to the present.” In P. Brandon and M. Betts (eds) Integrated Construction Information, SPON, pp. 137–147. Karlen, I. (1995b). “Construction Integration—from the present to the past.” In P. Brandon and M. Betts (eds), Integrated Construction Information, SPON, pp. 148–158. Lockley, S. and Augenbroe, G. (2000). “Data integration with partial exchange.” International Journal of Construction Information Technology, Vol. 6, No. 2, pp. 47–58. Lubell, J. (2002). “From model to markup: XML representation of product data.” In Proceedings of the XML 2002 Conference, Baltimore, MD, December. Mac Randal, D. (1995). “Integrating design tools into the design process. Building Simulation ’95, 4th International IBPSA Conference, Madison, WI, USA, August 14–16, pp. 454–457. McElroy, L.B., Hand, J.W., and Strachan, P.A. (1997). “Experience from a design advice service using simulation.” Building Simulation ’97, 5th International IBPSA Conference, Prague, Czech Republic, September 8–10, Vol. I, pp. 19–26. McElroy, L.B., Clarke, J.A., Hand, J.W., and Macdonald, I. (2001). “Delivering simulation to the profession: the next stage?” Building Simulation ’01, 7th International IBPSA Conference, Rio de Janeiro, Brazil, August 13–15, pp. 831–840. Papamichael, K. (1999). “Application of information technologies in building design decisions.” Building Research & Information, Vol. 27, No. 1, pp. 20–34. Papamichael, K., Chauvet, H., La Porta, J., and Dandridge, R. (1999). “Product modeling for computer-aided decision-making.” Automation in Construction, Vol. 8, January. Thitisawat, M. (2003). IFC exam question report. Internal report, Georgia Institute of Technology.
216 Augenbroe van Treeck, C., Romberg, R., and Rank, E. (2003). “Simulation Based on the Product Model Standard IFC.” Building Simulation ’03, 8th International IBPSA Conference, Eindhoven, The Netherlands, pp.1293–1300. Wijsman, A. (1998). Performance Assessment Method (PAM) for the Dutch Building Thermal Performance Program VA114. Delft: TNO Building and Construction Research. XML (2003). Standard, http://www.w3.org/XML/
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Advanced Building Simulation
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First published 2003 by Spon Press
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vi Contents 8 Developments in inter
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viii Figures 3.12 Relation between
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x Figures 8.14 Workflow Modeling Wi
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Contributors D. Michelle Addington,
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Prologue Introduction and overview
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Prologue 3 two topics that represen
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Trends in building simulation 5 com
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Reality Space averaged treatment of
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Pervasive/invisible Web-enabled Des
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Trends in building simulation 11 in
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Trends in building simulation 13 ea
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Trends in building simulation 15 ba
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Trends in building simulation 17 1.
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Trends in building simulation 19 th
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and predictive simulation-based con
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Trends in building simulation 23 Fu
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Chapter 2 Uncertainty in building s
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Uncertainty in building simulation
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This completes the outline of the c
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and inputs may be a formidable task
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Kleijnen (1997), Reedijk (2000), an
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Table 2.1 Categories of uncertain m
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∆C p (-) 1.6 1.2 0.8 0.4 0.0 -0.4
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S d (h) 80 60 40 20 0 -80 2 Uncerta
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2.4.2 Uncertainty in wind pressure
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an experiment involving structured
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with their uncertainties, in terms
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Table 2.5 Expected utilities for de
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y a performance gain on another asp
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Simulation and uncertainty: weather
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makes every month normalized to a z
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Dry-bulb temperature (°F) 60 50 40
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(b) Compute today’s average tempe
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ackward. First, the average daily h
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a��sin(�)* ln[I SC * � D] (
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H = Total daily horizontal insolati
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Temperature (°C) or wind speed (m/
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Horizontal insolation (MJ/m 2 /day)
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References Simulation and uncertain
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Chapter 4 Integrated building airfl
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(a) (b) zone 6 5 4 3 2 1 3 1 Pre-he
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a different physical state variable
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West Zone n Zone m Figure 4.5 Examp
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Node n Figure 4.6 An example two zo
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The nodal pressures are then iterat
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when employing Newton-Raphson solut
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Integrated building airflow simulat
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25.9 15.9 13.7 10.2 7.2 4.2 0.0 10.
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Air temperature (°C) 40.0 35.0 30.
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It was found that the differences a
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of the problem. In any event, calib
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Resolution CFD Decision Reduced Dec
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Although most of the basic physical
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Chapter 5 The use of Computational
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CFD tools for indoor environmental
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the Reynolds average rules can be s
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3m Control room Enclosure 5.5 m Out
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y the room conditions. In fact, the
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Y/H Y/H 1 0.8 0.6 0.4 0.2 Plot-1 Pl
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magnitude computing time than the R
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Chapter 6 New perspectives on Compu
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New perspectives on CFD simulation
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law must be invariant to a transfor
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References New perspectives on CFD
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Chapter 7 Self-organizing models fo
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Self-organizing models for sentient
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SOM topo- SOM site 1 graphy 1 1 1 1
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Page 184 and 185: DC EL1 DC EL2 MC EL_1 DC EL3 E 1 MC
Page 186 and 187: technologies (Wouters 1998; Mahdavi
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Page 204 and 205: Chapter 8 Developments in interoper
Page 206 and 207: This chapter introduces the technol
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Page 212 and 213: Instances subset A Building Model S
Page 214 and 215: Import DT data Export DT data DT sc
Page 216 and 217: Data-centric approach no explicit p
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Page 232 and 233: Chapter 9 Immersive building simula
Page 234 and 235: Immersive building simulation 219 T
Page 236 and 237: Immersive building simulation 221 E
Page 238 and 239: Data generation Data preparation Ma
Page 240 and 241: Shear Velocity Acceleration Curvatu
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Page 244 and 245: etter than the others, they suffer
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Page 256 and 257: Calibrated tracker data Figure 9.30
Page 258 and 259: Immersive building simulation 243 g
Page 260 and 261: Immersive building simulation 245 H
Page 262 and 263: Epilogue Godfried Augenbroe and Ali
Page 264 and 265: Index accountability 13 accreditati
Page 266 and 267: performance assessment methods 109-
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