computer

Development of infiltration and interroom airflow calculation methods, driven by a concern for indoor air quality have led to a computer simulation of interroom contaminant movement. The model, which assumes fully mixed room air, shows that open doorways provide rapid mixing between rooms in buildings using forced air heating. It also confirms that it is most energy efficient to remove the contaminant nearest its source. Detailed modeling of the variations in contaminant concentration within a room is not presently feasible for long term energy analysis simulations.

A computational procedure to predict expected rates of natural ventilation for buildings at the design stage is investigated. This procedure integrates three computational methods, namely one to predict temperature induced pressures, another to compute wind generated pressure distributions around buildings, and the third to analyse the networks of resulting air flows in buildings. Experiments show that these methods are valid. The three methods can be used not only for the prediction of natural ventilation, but also for many other environmental engineering applications, e.g.

In order to obtain means for determining realistic convective heat transfer coefficients, a hierarchy of interacting and interdependent calculation methods have been developed by the authors. Both higher and lower level models have been used to develop and verify an 'intermediate level' computer code, which formed the basis for generating input convective heat transfer data for dynamic building models. The contribution considers the computation of convective heat exchange within three-dimensional, rectangular enclosures when buoyancy effects are significant.

A program is presented which runs on Apricot, Sirius and IBM-PC microcomputers and calculates the heating energy requirements of single zone, intermittently heated buildings with reasonable accuracy. Calculation of preheating energy is based on the average internal temperature concept of CIBS Energy Code 2. Solar gains and long-wave radiation losses are treated crudely on the basis of regression equations for radiation as a function of daily average external temperature for different periods of the day.

Describes an investigation to show that the hourly, daily and monthly energy needs of simple buildings can be estimated using only limited available weather data for the location. The data needed are the mean daily maximum and mean daily minimum temperatures and the average clearness index for each month. Uses a residential building in Ottawa, Canada for the analysis, using a computer program ENERPASS.