Building Simulation

, Volume 7, Issue 5, pp 439–454 | Cite as

Sub-zonal computational fluid dynamics in an object-oriented modelling framework

  • Marco Bonvini
  • Mirza Popovac
  • Alberto Leva
Review Article Indoor/Outdoor Airflow and Air Quality


Airflow modelling is of fundamental importance for evaluating ventilation performance and energy consumption in buildings, and various approaches to the problem—starting from purely empirical up to the CFD ones—have been proposed and evaluated in the past years. Moreover, since the ultimate goal is whole building modelling, airflow simulation needs coupling with Energy Simulation (ES), in order to assess the overall energy performance. Due to the substantial differences between the software employed for airflow and ES, co-simulation is very often felt as the only way to handle such a problem. For example, in recent years a lot of effort has been spent in to couple ES and CFD tools. This paper proposes an alternative, in the form of an approach for solving the Navier-Stokes equations in a general multi-domain modelling framework. Since co-simulation is not involved, the correctness of the numerical solution relies on a single solver, thus being really transparent to the analyst. This is a first step towards a whole building simulation tool embedded in a unique framework capable of performing energy analysis, computing airflows, and representing control systems.


computational fluid dynamics object-oriented modeling airflow simulation building simulation Modelica 


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  1. Allard F, Dorer V, Feustel H (1990). Fundamentals of the multizone airflow model—COMIS. Technical Note 29, Air Infiltration and Ventilation Centre, Coventry, UK.Google Scholar
  2. Arias D (2006). Advances on the coupling between a commercial CFD package and a component-based simulation program. In: Proceedings of 2nd National IBPSA-USA Conference, Cambridge, MA, USA, pp. 231–237.Google Scholar
  3. Beausoleil-Morrison I (2000). The adaptive coupling of heat and air flow modelling within dynamic whole-building simulation. PhD thesis, University of Strathclyde, UK.Google Scholar
  4. Betts PL, Bokhari IH (2000). Experiments on turbulent natural convection in an enclosed tall cavity. International Journal of Heat and Fluid Flow, 21: 675–683.CrossRefGoogle Scholar
  5. Blay D, Mergui S, Niculae C (1992). Confined turbulent mixed convection in the presence of horizontal buoyant wall jet. Fundamentals of Mixed Convection, ASME HTD, 213: 65–72.Google Scholar
  6. Bonvini M, Leva A, Zavaglio E (2012). Object-oriented quasi-3d sub-zonal airflow models for energy-related system-level building simulation. Simulation Modelling Practice and Theory, 22: 1–12. Cellier FE, Kofman E (2006). Continuous System Simulation. New York: Springer.CrossRefGoogle Scholar
  7. Chen Q (2009). Ventilation performance prediction for buildings: A method overview and recent applications. Building and Environment, 44: 848–858.CrossRefGoogle Scholar
  8. Chen Q, Xu W (1998). A zero equation turbulence model for indoor airflow simulation. Energy and Buildings, 28: 137–144.CrossRefGoogle Scholar
  9. Crawley DB, Lawrie LK, Winkelmann FC, Buhl WF, Erdem AE, Pedersen CO, Liesen RJ, Fisher DE (1997). What next for building energy simulation—A glimpse of the future. In: Proceedings of IBPSA International Conference, Prague, Czech Republic, pp. 395–402.Google Scholar
  10. Fluent (2006). Fluent 6.3 User's Guide.Google Scholar
  11. Ljubijankic M, Nytsch-Geusen C, Rädler J, Löffler M (2011). Numerical coupling of Modelica and CFD for building energy supply systems. In: Proceedings of 8th International Modelica Conference, Dresden, Germany.Google Scholar
  12. Mattsson S, Elmqvist H, Otter M (1998). Physical system modeling with Modelica. Control Engineering Practice, 6: 501–510.CrossRefGoogle Scholar
  13. Modelica (2013). Modelica Association, Available: Scholar
  14. Mora L, Gadgil A, Wurtz E (2003). Comparing zonal and CFD model predictions of isothermal indoor airflows to experimental data. Indoor Air, 23: 77–85.CrossRefGoogle Scholar
  15. Ostlund P, Stavaker K, Fritzson P (2010). Parallel simulation of equation-based models on CUDA-enabled GPUs. In: Proceedings of 9th Workshop on Parallel/High-Performance Object-Oriented Scientific Computing, Reno, NV, USA, pp: 5:1–5:6.Google Scholar
  16. Patankar S (1980). Numerical Heat Transfer and Fluid Flow. London, UK: Taylor and Francis.zbMATHGoogle Scholar
  17. Pedersen CO, Fisher DE, Liesen RJ, Strand RK, Taylor RD, Buhl WF, Winkelmann FC, Lawrie LK, Crawley DB (1997). Energybase: The merger of BLAST and DOE-2. In: Proceedings of IBPSA International Conference, Prague, Czech Republic, Volume III, pp. 1–8.Google Scholar
  18. Ren Z, Stewart J (2003). Simulating air flow and temperature distribution inside buildings using a modified version of COMIS with sub-zonal divisions. Energy and Buildings, 35: 257–271.CrossRefGoogle Scholar
  19. Restivo A (1979). Turbulent flow in ventilated room. PhD Thesis, University of London, UK.Google Scholar
  20. Sahlin P (2000). The methods of 2020 for building envelope and HVAC systems simulation—Will the present tools survive? In: Proceedings of CIBSE Conference, Dublin, Ireland.Google Scholar
  21. Sahlin P, Eriksson L, Grozman P, Johnsson H, Shapovalov A, Vuolle M (2004). Whole-building simulation with symbolic DAE equations and general purpose solvers. Building and Environment, 39: 949–958.CrossRefGoogle Scholar
  22. Trčka M, Hensen JL, Wetter M (2009). Co-simulation of innovative integrated HVAC systems in buildings. Journal of Building Performance Simulation, 2: 209–230.CrossRefGoogle Scholar
  23. Trčka M, Hensen JL, Wetter M (2010). Co-simulation for performance prediction of integrated building and HVAC systems—An analysis of solution characteristics using a two-body system. Simulation Modelling Practice and Theory, 18: 957–970.CrossRefGoogle Scholar
  24. Versteeg H, Malalasekera W (2007). An Introduction to Computational Fluid Dynamics: The Finite Volume Method. Upper Saddle River, NJ, USA: Pearson Prentice Hall.Google Scholar
  25. Wetter M (2009). Modelica library for building heating, ventilation and air-conditioning systems. In: Proceedings of 7th International Modelica Conference, Como, Italy.Google Scholar
  26. Wetter M, Haugstetter C (2006). Modelica versus TRNSYS—A comparison between an equation-based and a procedural modeling language for building energy simulation. In: Proceedings of 2nd National IBPSA-USA Conference, Cambridge, MA, USA.Google Scholar
  27. Wetter M, Zuo W, Nouidui TS (2011). Recent developments of the Modelica buildings library for building heating, ventilation and air-conditioning systems. In: Proceedings of 8th International Modelica Conference, Dresden, Germany.Google Scholar
  28. Zhai Z (2003). Developing an integrated building design tool by coupling building energy simulation and computational fluid dynamics programs. PhD Thesis, Massachusetts Institute of Technology, USA.Google Scholar
  29. Zhai Z, Chen Q (2004). Numerical determination and treatment of convective heat transfer coefficient in the coupled building energy and CFD simulation. Building and Environment, 39: 1001–1009.CrossRefGoogle Scholar
  30. Zuo W, Chen Q (2010). Fast and informative flow simulations in a building by using fast fluid dynamics model on graphics processing unit. Building and Environment, 45: 747–757.CrossRefGoogle Scholar
  31. Zuo W, Hu J, Chen Q (2010). Improvements in FFD modeling by using different numerical schemes. Numerical Heat Transfer, Part B: Fundamentals, 58: 1–16.CrossRefGoogle Scholar

Copyright information

© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Lawrence Berkeley National LaboratoryBerkeleyUSA
  2. 2.Austrian Institute of Technology, Energy DepartmentViennaAustria
  3. 3.Dipartimento di Elettronica Informazione e BioingegneriaPolitecnico di MilanoMilanoItaly

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