An Approach to Interpreting Critical Indoor Pollution Scenes of a Whole Building with Limited Sensor Outputs
To maintain a healthful and secure indoor environment,it is critical to quickly identify contaminant source conditions (locations,strengths and release histories) so the source can be controlled and removed.This paper introduces a probability concept based inverse modelling method the adjoint probability method to identify potential indoor pollutant sources with limited pollutant sensor readings.The paper establishes the corresponding adjoint equations for both computational fluid dynamics (CFD) and multi-zone airflow models,which can be used to calculate the source location and travel time probabilities of an observed contamination.A two-stage integrated inverse modelling algorithm is proposed that can interpret critical indoor air quality (IAQ) scenes for a whole building with few sensor outputs.Preliminary research results for locating an indoor pollutant source in a residential building with different sensing conditions have been presented,which confirms the feasibility and accuracy of the developed method.The paper discusses the further research directions and applications.
Indoor air quality Source identification Inverse modelling Adjoint probability method
Xiang Liu John Zhai
Department of Civil,Environmental and Architectural Engineering,University of Colorado,UCB 428,ECOT 441,Boulder,CO 80309-0428 USA
国际会议
The First International Conference on Building Energy and Environment(第一届建筑能源与环境国际会议)
大连
英文
2281-2288
2008-07-01（万方平台首次上网日期，不代表论文的发表时间）