An Approach to Interpreting Critical Indoor Pollution Scenes of a Whole Building with Limited Sensor Outputs

摘要

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.