Thermal comfort in transitional spaces of buildings is established from a field study conducted in the cool season of Bangkok, Thailand. IL involved 302 indoor subjects occupying either air-conditioned or naturally ventilated environments and 291 outdoor subjects who were leaving the indoors. The data were analysed by using a calculating method, "Griffiths" values, giving neutral temperatures, and a quadratic regression for thermal acceptability.
The calculation of airflows is of great importance for detailed building thermal simulation computer codes, these airflows most frequently constituting an important thermal coupling between the building and the outside on one hand, and the different thermal zones on the other. The driving effects of air movement, which are the wind and the thermal buoyancy, are briefly outlined and we look closely at their coupling in the case of buildings, by exploring the difficulties associated with large openings.
The requirements to know indoor thermal comfort ask for a more detailed study of room temperature responses. Although CFO (Computational Fluid Dynamics) techniques can be applied successfully to the prediction of indoor temperature distributions, using them for the dynamic calculation of temperatures and air flows is still a very expensive expenditure. For indoor climate control systems, it is necessary to make quick calculations of the dynamic temperature distributions in a room.
To control the indoor thermal environment within the comfortable range, the dynamic temperature distributions and flows of room air must be correctly predicted. While the CFO (Computational Fluid Dynamics) technique can be used to carry out such a prediction task, its drawback is also obvious: too time-consuming. To solve this problem, the dynamic temperature distributions can be predicted with some fixed air flow fields calculated with CFD codes. That is, sacrifice the dynamics of indoor air flows and only preserve the dynamics of the temperature distributions.
A three-dimensional drift-flux model for particle movements in turbulent airflows in buildings is presented. The interaction between the carrier air and the particles has been treated as a one-way coupling, assuming the effect of particles on air turbulence is negligible due to low solid loadings and comparatively small particle settling velocities. Turbulence effects are modelled with a standard K-E model. Wall functions are applied at near-wall grid points. Aerosol measurements carried out under turbulent room flow conditions are used to validate the numerical calculations.
The pressure field in fluid systems reflects the flow configuration. Measurements of the pressure along the perimeter of a slot ventilated room have been conducted for different room sizes. The momentum of the jet at the end of the room is decreased with increasing room length. The impingement region (region where the influence of the opposing wall is present) starts, independent of room size, when the distance from the supply device is about 70% of the room length. Corner flows could not be predicted by CFD using the linear eddy viscosity or standard stress models. However.
This paper presents a comparison of predictions from a duct efficiency model developed by the authors with measured real-time heating n, system efficiency measurements from six site-built residential homes with natural gas furnaces in the Puget Sound region. The model takes into account the interaction between supply and return side losses, the interaction between conduction and air leakage losses, the interaction rs between unbalanced leakage and natural infiltration, and the recovery of heat through the building envelope from ducts in various locations 1) within the home.
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