-
-
Available Formats
- Options
- Availability
- Priced From ( in USD )
-
Available Formats
-
- Immediate download
- $16.00
- Add to Cart
Customers Who Bought This Also Bought
-
AC-02-12-4 -- Monitoring HVAC Equipment Electrical Loads ...
Priced From $16.00 -
AC-02-08-3 -- Initial Investigations on Plenum Cable Fires
Priced From $16.00 -
AC-02-10-1 -- Economic Assessment of Low Firing Temperatu...
Priced From $16.00 -
AC-02-09-3 -- Cooling Tower—Model and Experimental Valida...
Priced From $16.00
About This Item
Full Description
CONTAMW is an indoor air quality analysis network model developed to determine airflow and contaminant concentrations in each compartment of a building. In addition to its applicability in indoor environment modeling, CONTAMW is also used to model smoke control systems in multi-story buildings. This study investigates whether this model can accurately predict smoke movement in a multi-story building by comparing its predictions with data from experiments conducted in the 10-story test facility of the National Research Council of Canada (NRC).
The 10-story experimental facility at NRC was designed to simulate the center core of a high-rise building, including corridors and stair and elevator shafts. Various vents on the external and internal walls can be opened or closed to simulate the leakage area of typical buildings. Comparisons with two sets of experimental data are presented in this paper. In the first experiment, a propane burner was used to produce a constant heat release rate of 1 MW. In the second experiment, a couch was used as the fuel with the average heat release rate being 730 kW. The measured CO2 concentrations and pressure in the stair shaft are compared with the results predicted using the model. The results indicate that the model underpredicts the CO2 concentrations. A large difference between predicted and measured pressure also exists. In addition, the two-zone model FIERAsmoke is used to predict CO2 concentrations in the stair shaft. The two-zone model predictions compare better with the experimental data than the predictions of the network model.
Units: SI