A fast model for identifying multiple indoor contaminant sources by considering sensor threshold and measurement error

In an emergency where a hazardous contaminant is abruptly released into indoor air, identifying the characteristics of contaminant source promptly and accurately is very important to eliminate source, control contamination and protect people. An identification model is presented in this study for quickly identifying the exact locations and emissions rates of multiple indoor contaminant sources with constant emissions rates and known release time, by considering sensor thresholds and measurement errors. Through case studies in a three-dimensional room, the model was numerically demonstrated and validated, and thorough analyses were made on the effects of the sensor threshold and measurement error on model performance. The results suggest that the model has the potential to obtain accurate results in real-time allowing for high levels of sensor data loss and measurement error. Practical application: The presented identification model is applicable to a wide variety of indoor environments involving multiple continuous contaminant sources, such as the emission of volatile compounds from building materials or furniture, the leakage of toxic or inflammable gases from pipeline or vessels in trace amount. This study will hopefully contribute to developing more realistic source identification techniques with unknown release time and real sensor use.

[1]  Jelena Srebric,et al.  Application of Neural Networks Trained with Multi-Zone Models for Fast Detection of Contaminant Source Position in Buildings , 2007 .

[2]  Xianting Li,et al.  Accessibility: A New Concept to Evaluate Ventilation Performance in a Finite Period of Time , 2004 .

[3]  Amy Musser,et al.  An Analysis of Combined CFD and Multizone IAQ Model Assembly Issues | NIST , 2001 .

[4]  P V Nielsen,et al.  Computational fluid dynamics and room air movement. , 2004, Indoor air.

[5]  M Siddiqui,et al.  CFD analysis of dense gas dispersion in indoor environment for risk assessment and risk mitigation. , 2012, Journal of hazardous materials.

[6]  E. Rank,et al.  History source identification of airborne pollutant dispersions in a slot ventilated building enclosure , 2013 .

[7]  Ashok J. Gadgil,et al.  Towards improved characterization of high-risk releases using heterogeneous indoor sensor systems , 2011 .

[8]  Michael D. Sohn,et al.  Influence of indoor transport and mixing time scales on the performance of sensor systems for characterizing contaminant releases , 2007 .

[9]  Michael D. Sohn,et al.  Evaluating sensor characteristics for real-time monitoring of high-risk indoor contaminant releases , 2006 .

[10]  M. Sohn,et al.  Rapidly Locating and Characterizing Pollutant Releases in Buildings , 2000, Journal of the Air & Waste Management Association.

[11]  Bin Zhao,et al.  Prediction of transient contaminant dispersion and ventilation performance using the concept of accessibility , 2004 .

[12]  Fariborz Haghighat,et al.  Contaminant source identification within a building: Toward design of immune buildings , 2011, Building and Environment.

[13]  X Liu,et al.  Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling. , 2007, Indoor air.

[14]  Qingyan Chen,et al.  A zero-equation turbulence model for indoor airflow simulation , 1998 .

[15]  Xiaoliang Shao,et al.  An analytical expression for transient distribution of passive contaminant under steady flow field , 2012 .

[16]  James W. Axley,et al.  Multizone Airflow Modeling in Buildings: History and Theory , 2007 .

[17]  Q. Chen,et al.  Identification of contaminant sources in enclosed environments by inverse CFD modeling. , 2007, Indoor air.

[18]  Zhiqiang John Zhai,et al.  Prompt tracking of indoor airborne contaminant source location with probability-based inverse multi-zone modeling , 2009 .

[19]  X Liu,et al.  Inverse modeling methods for indoor airborne pollutant tracking: literature review and fundamentals. , 2007, Indoor air.

[20]  L. Wallace,et al.  Indoor particles: a review. , 1996, Journal of the Air & Waste Management Association.

[21]  Chia-Jung Hsu.  Numerical Heat Transfer and Fluid Flow , 1981 .

[22]  K. Sexton,et al.  Indoor air pollution: a public health perspective. , 1983, Science.

[23]  Xianting Li,et al.  Fast Identification of Multiple Indoor Constant Contaminant Sources by Ideal Sensors: A Theoretical Model and Numerical Validation , 2013 .

[24]  Q Chen,et al.  Identification of contaminant sources in enclosed spaces by a single sensor. , 2007, Indoor air.

[25]  Di Liu,et al.  History recovery and source identification of multiple gaseous contaminants releasing with thermal effects in an indoor environment , 2012 .