This paper is based on a dual approach (experimental and numerical) in order to predict the indoor air quality for small ventilated enclosures. The experimental part employs a ventilated test room and a tracer gas technique (constant method as gas injection) to estimate the diffusion of a pollutant. The gas used is the sulphur hexafluoride (F6S). The numerical approach is a CFD simulation, adding a convection - diffusion equation (to determine the local mass fraction of the pollutant) to the equations normally used to solve a turbulent flow.
Designers, professionals and practitioners are currently making evaluations and sizing ventilation systems and apparatus in Italy on the basis of the Italian standard UNI 10339. This prescriptive standard is relatively recent, being issued in June 1995.
Air handling units do not always function as planned: airflow rates are often larger than required, the recirculation rate is not at its set-point value and parasitic shortcuts sometimes decrease dramatically the ventilation efficiency. A dedicated diagnosis, based on the tracer gas dilution technique can easily detect such dysfunction, and help to cure the defects.
In laboratory experiments, we investigated the ability of two task/ambient conditioningsystems with air supplied from desk-mounted air outlets to efficiently ventilate the breathingzone of heated manikins seated at desks. In most experiments, the task conditioning systemsprovided 100% outside air while a conventional ventilation system provided additional spacecooling but no outside air. Air change effectiveness (i.e., exhaust air age divided by age of airat the manikins face) was measured.
Since reduction of ventilation rates in dwellings for economical reasons, it has been necessary to study whether this reduction had not been done to the detriment of indoor air quality. Several means of investigating were developed: experimental tests are indispensable but usually expensive that is why numerous research centres choose to model the thermoconvective fields in rooms.
The use of tracer gas is of great help in measuring airflow rates and detecting shortcuts in air handling units, and is essential for ventilation efficiency measurement. However, the planning of experiments, that is choosing tracer gas injection locations and air sampling locations, is not straightforward. Moreover, the mathematics used for interpretation are quite complex, and require elaborate calculations. Therefore, a measurement protocol and the corresponding interpretation algorithms are being developed and implemented in a user-friendly computer program.
A series of CFD and model experiments were carried out in order to find the most effective ventilation system in a separated refuse disposal facility. The ventilation system needed in the facility protects the working space from dust and odors generated by handling refuse. The desired ventilation system is to introduce the outdoor air from the one side of the working area and to exhausts the contaminated air through the opposite side of the refuse stock yard, so-called the unidirectional airflow ventilation.
In order to assess ventilation systems, ventilation and thermal comfort parameters are calculated. Parameters are temperature and ventilation efficiency and PMV I PPD. Two ventilation configurations are set: the supply grille is under the ceiling and tests are performed for 2 exhaust positions. Both are opposite the ceiling: the first one is under the ceiling and the second one is on the floor. In regards with extract position, the ventilation system is better when extract is on the floor. It appears that the air renewal does not influence neither ventilation nor temperature efficiency.
The general strategy adopted in the development of a computational tool performing the identification of parametric models based on the Residence Times Distribution (Rm) theory is exposed. Two main aspects of the modelling procedure are presented: the structural discrimination of the various solution schemes, and the parameters estimation step. The structural model determination is solved by a stochastic procedure based on a Simulated Annealing algorithm, while the parametric identification is solved by a nonlinear deterministic procedure.
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