Trends in building simulation 23 Fujii, H. and Tanimoto, J. (2003). “Coupling building simulation with agent simulation for exploration to environmental symbiotic architectures.” In Eighth IBPSA Conference on <strong>Building</strong> <strong>Simulation</strong>, Eindhoven. Godfried Augenbroe and Jan Hensen (eds), August, pp. 363–370. Guimbretière, F. and Winograd, T. (2000). “FlowMenu: combining command, text, and data entry.” UIST’00, ACM, pp. 213–216. Holm, A., Kuenzel, H.M., and Sedlbauer, K. (2003). “The hygrothermal behavior of rooms: combining thermal building simulation and hygrothermal envelope calculation.” In Eighth IBPSA Conference on <strong>Building</strong> <strong>Simulation</strong>, Eindhoven. Godfried Augenbroe and Jan Hensen (eds), August, pp. 499–505. IBPSA (2003). Proceedings of First-eight <strong>Building</strong> <strong>Simulation</strong> Conferences, on CD, IBPSA (1989–2003). Jain, S. and Augenbroe, G. (2003). “A Methodology for Supporting Product Selection from e-catalogues.” In Robert Amor and Ricardo Jardim-Gonçalves (eds), Special Issue on eWork and eBusiness. ITCON, November. Liston, K., Fischer, M., and Winograd, T. (2001). “Focused sharing of information for multidisciplinary decision making by project teams.” ITCon (Electronic Journal of Information Technology in Construction), Vol. 6, pp. 69–81. Liu, D.L. and Nazaroff, W.W. (2002). “Particle penetration through windows.” In Proceedings Indoor Air 2002, pp. 862–867. Loomans, M.G.L.C., Bluyssen, P.M., and Ringlever-Klaassen, C.C.M. (2000). “Bioaerosolswhere should one measure them in a room?” In Proceedings Indoor Air 2002, pp. 443–448. Loveday, D.L., Kirk, G.S., Cheung, J.Y.M., and Azzi, D. (1997). “Intelligence in buildings: the potential of advanced modeling.” Automation in Construction, Vol. 6, pp. 447–461. Macdonald, I.A. (2002). “Quantifying the Effects of Uncertainty in <strong>Building</strong> <strong>Simulation</strong>.” PhD thesis. University of Strathclyde, July. McElroy, L. and Clarke, J.A. (1999). “Embedding simulation within the energy sector business.” In Proceedings of the <strong>Building</strong> <strong>Simulation</strong> ’99, Sixth International IBPSA Conference, Kyoto, pp. 262–268. MacIntyre, B. (2000). “Context-aware personal augmented reality.” Position paper at CHI’00 Workshop on Research Directions in Situated Computing, The Hague, The Netherlands. Mahdavi, A. (2001). “Distributed multi-disciplinary building performance computing.” In Proceedings of the 8th Europia International Conference Delft, R. Beheshti (ed.), The Netherlands, pp. 159–170. Mahdavi, A., Mustafa, A.I., Matthew, P., Ries, R., Suter, G., and Brahme, R. (1999). “The architecture of S2.” In Proceedings of the <strong>Building</strong> <strong>Simulation</strong> 99, Sixth International IBPSA Conference, Kyoto, September, Paper A-38. Malkawi, A. and Choudhary, R. (1999). “Visualizing the sensed environment in the real world.” Journal of the Human-Environment Systems, Vol. 3, No. 1, pp. 61–69. Malkawi, A. and Wambaugh, J. (1999). “Platform independent simulations: thermal simulation as an object”. In Proceedings of the 6th International <strong>Building</strong> <strong>Simulation</strong> Conference, Kyoto, Japan. Park, C., Augenbroe, G., Sadegh, N., Thitisawat, M., and Messadi, T. (2003). “Occupant response control systems of smart façades.” In Eighth IBPSA Conference on <strong>Building</strong> <strong>Simulation</strong>, Eindhoven. Godfried Augenbroe and Jan Hensen (eds), August, pp. 1009–1016. Pelletret, R. and Keilholz, W. (1999). “Coupling CAD tools and building simulation evaluators.” In Proceedings of the <strong>Building</strong> <strong>Simulation</strong> ’99, Sixth International IBPSA Conference, Kyoto, Japan, 13–15, pp. 1197–1202. Sahlin, P. (1996a). “Modelling and simulation methods for modular continuous systems in buildings.” Doctoral Dissertation KTH, Stockholm, Sweden (also available at http://www.brisdata.se/ida/literature.htm).
24 Augenbroe Sahlin, P. (1996b). NMF Handbook, An Introduction to the Neutral Model Format, NMF Version 3.02, ASHRAE RP-839. Report from <strong>Building</strong> Sciences, KTH, Stockholm. Schmidt, D.C. (1997). “Applying design patterns and frameworks to develop object-oriented communications software.” In P. Salus (ed.), Handbook of Programming Languages. Vol. I, MacMillian Computer Publishing. Sextro, R.G., Lorenzetti, D.M., Sohn, M.D., and Thatcher, T.L. (2002). “Modeling the Spread of Anthrax in <strong>Building</strong>s.” In Proceedings Indoor Air 2002, pp. 506–511. So, A.T. (1999). Intelligent <strong>Building</strong> Systems. Kluwer Academic, Boston. Sowell, E.F. and Haves, P. (1999). “Numerical performance of the SPARK graph-theoretic simulation program.” In Proceedings of <strong>Building</strong> <strong>Simulation</strong> 99, Sixth International IBPSA Conference, Kyoto, September, Paper A-05. Starner, T. (2002). “Thick clients for personal wireless devices.” IEEE Computer, Vol. 35, No. 1, pp. 133–135. Tan, K.C. and Li, Y. (2002). “Grey-box model identification via evolutionary computing.” Control Engineering Practice, Vol. 10, pp. 673–684. Tang, D. and Clarke, J.A. (1993). “Application of the object oriented programming paradigm to building plant system modelling.” In Proceedings of <strong>Building</strong> <strong>Simulation</strong> ’93, Third International IBPSA Conference, Adelaide. de Wit, M.S. (2001). “Uncertainty in predictions of thermal comfort in buildings.” Doctoral Dissertation, TU Delft, June. de Wit, S. and Augenbroe, G. (2001). “Uncertainty analysis of building design evaluations.” In Proceedings of BS01, 7th International IBPSA Conference, Rio, August, pp. 319–326.
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Simulation and uncertainty: weather
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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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Integrated building airflow simulat
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Although most of the basic physical
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Integrated building airflow simulat
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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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CFD tools for indoor environmental
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CFD tools for indoor environmental
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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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CFD tools for indoor environmental
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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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CFD tools for indoor environmental
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Chapter 6 New perspectives on Compu
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New perspectives on CFD simulation
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New perspectives on CFD simulation
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New perspectives on CFD simulation
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New perspectives on CFD simulation
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New perspectives on CFD simulation
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law must be invariant to a transfor
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New perspectives on CFD simulation
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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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Self-organizing models for sentient
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Self-organizing models for sentient
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DC EL1 DC EL2 MC EL_1 DC EL3 E 1 MC
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technologies (Wouters 1998; Mahdavi
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Self-organizing models for sentient
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and photometric properties, as well
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Self-organizing models for sentient
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exploratory implementations. The fi
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Self-organizing models for sentient
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Self-organizing models for sentient
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the electric light component of ill
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Chapter 8 Developments in interoper
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This chapter introduces the technol
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Developments in interoperability 19
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Developments in interoperability 19
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Instances subset A Building Model S
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Import DT data Export DT data DT sc
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Data-centric approach no explicit p
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Developments in interoperability 20
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Glazing system? Window area? Monday
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Chapter 9 Immersive building simula
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Data generation Data preparation Ma
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Shear Velocity Acceleration Curvatu
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etter than the others, they suffer
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quality CRT screens, wide field of
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Graphical representation Matrix (4D
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Figure 9.22 Test room—section. Wa
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(a) (b) Immersive building simulati
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Immersive building simulation 239 m
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Calibrated tracker data Figure 9.30
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Immersive building simulation 243 g
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Immersive building simulation 245 H
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Epilogue Godfried Augenbroe and Ali
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Index accountability 13 accreditati
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performance assessment methods 109-