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Sensors 2012, 12(9), 11966-11988; doi:10.3390/s120911966

Optimization of Sampling Positions for Measuring Ventilation Rates in Naturally Ventilated Buildings Using Tracer Gas

Department of Engineering, Faculty Sciences and Technology, University of Aarhus, Blichers Allé 20, Tjele 8830, Denmark
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Received: 18 May 2012 / Revised: 24 August 2012 / Accepted: 24 August 2012 / Published: 30 August 2012
(This article belongs to the Section Physical Sensors)

Abstract

Finding out the optimal sampling positions for measurement of ventilation rates in a naturally ventilated building using tracer gas is a challenge. Affected by the wind and the opening status, the representative positions inside the building may change dynamically at any time. An optimization procedure using the Response Surface Methodology (RSM) was conducted. In this method, the concentration field inside the building was estimated by a three-order RSM polynomial model. The experimental sampling positions to develop the model were chosen from the cross-section area of a pitched-roof building. The Optimal Design method which can decrease the bias of the model was adopted to select these sampling positions. Experiments with a scale model building were conducted in a wind tunnel to achieve observed values of those positions. Finally, the models in different cases of opening states and wind conditions were established and the optimum sampling position was obtained with a desirability level up to 92% inside the model building. The optimization was further confirmed by another round of experiments. View Full-Text
Keywords: response surface methodology; optimal design; desirability; sampling positions; tracer gas response surface methodology; optimal design; desirability; sampling positions; tracer gas
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Shen, X.; Zong, C.; Zhang, G. Optimization of Sampling Positions for Measuring Ventilation Rates in Naturally Ventilated Buildings Using Tracer Gas. Sensors 2012, 12, 11966-11988.

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