Ventilation 1 Building performance modelling
Air temperature predictions in a naturally ventilated classroom with ambient temperature of 21C. In this case, the predicted dynamic thermal sensation for the manikin was -0.73 (slightly cool) with a natural ventilation flow rate of 14 litres/s/person
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of constant temperature, others specify a constant heat flux based on an assumption of the surrounding air conditions. Some models pay little or no attention to the
Taking human physiology into account can help when modelling for natural ventilation. PIctured is the Lee Valley indoor athletics stadium, east London
radiation exchange with the environment or make assumptions that lead to over-sizing of heating systems or show up natural ventilation to be far less feasible than it otherwise might be. In some cases, CFD models are used to derive empirically-based thermal comfort parameters such as predicted mean vote (PMV) and predicted percentage dissatisfied (PPD) of occupants.
In contrast, the work reported here uses a
computational manikin of human thermoregulation and thermal comfort embedded within the solution cycle of a CFD program to provide a fully coupled model capable of predicting the influence of temperature and velocity fields on human thermal comfort and the effect of human metabolism and sweat excretion on the surroundings. This provides the opportunity to model more realistic human geometries (and the boundary layer flows and heat transfer associated with this) as well as the convection, radiation and moisture transfer between the body and the surrounding environment. The work uses the IESD-Fiala model (Fiala, 1998),
which represents human thermal comfort using two interacting systems: the controlling active system; and the controlled passive system. The active system is a cybernetic model predicting the thermoregulatory defence reactions of the central nervous system such as shivering, skin blood flow and sweating. The passive system simulates the dynamic heat
transfer phenomena that occur inside the body and at its surface. The model also incorporates a physiologically based thermal comfort model that predicts human thermal sensation responses in steady state and transient conditions. A wide range of commercial CFD codes are currently
available, most of which provide facilities for the user to modify and extend the functionality of the CFD solver. In this project, model coupling between the ANSYS
62 CIBSE Journal September 2010
www.cibsejournal.com >
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