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16 January 2012
Development of a numerical optimization approach to ventilation system design to control airborne contaminant dispersion and occupant comfort
Keywords:
computational fluid dynamics, multi-objective optimization, genetic algorithm, thermal comfort, contaminant dispersion, ventilation design, response surface method, infection risk
Cite this article:
Islam Khan MA, Noakes CJ, Toropov VV.
Development of a numerical optimization approach to ventilation system design to control airborne contaminant dispersion and occupant comfort.
Building Simulation,
2012, 5(1): 39-50.
https://doi.org/10.1007/s12273-012-0058-7
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Airflow, contaminant concentration, and temperature distribution during heating and ventilation in a model room represented by a square cavity with inlet and outlet ports, have been studied. The aim of this work is concerned with the development and implementation of a practical and robust optimization scheme based on the combination of response surface methodology (RSM) and genetic algorithm (GA) with the aim of assisting hospital ward designers and managers/operators to enhance infection control (i.e., reduce the risk of airborne transmission) without compromising patient comfort and environmental impact.
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Development of a numerical optimization approach to ventilation system design to control airborne contaminant dispersion and occupant comfort
Abstract
Airflow, contaminant concentration, and temperature distribution during heating and ventilation in a model room represented by a square cavity with inlet and outlet ports, have been studied. The aim of this work is concerned with the development and implementation of a practical and robust optimization scheme based on the combination of response surface methodology (RSM) and genetic algorithm (GA) with the aim of assisting hospital ward designers and managers/operators to enhance infection control (i.e., reduce the risk of airborne transmission) without compromising patient comfort and environmental impact.
Keywords:
computational fluid dynamics, multi-objective optimization, genetic algorithm, thermal comfort, contaminant dispersion, ventilation design, response surface method, infection risk
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Publication history
Copyright
Acknowledgements
Publication history
Received: 05 September 2011
Revised: 21 November 2011
Accepted: 23 November 2011
Published:
16 January 2012
Issue date: March 2012
Copyright
© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2012
Acknowledgements
The authors would like to acknowledge the support of the Engineering and Physical Sciences Research Council (EPSRC) for funding this work.
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