Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling

Liu, X.; Zhai, Zhiqiang

doi:10.1111/j.1600-0668.2007.00499.x

Cited by 93 publications

(34 citation statements)

References 7 publications

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Section: Introductionmentioning

confidence: 98%

“…Computational fluid dynamics (CFD) simulation tools have been frequently utilised for the simulation of the transportation of contaminants with ventilation flows [8][9][10][11][12]. These studies are capable of indicating various factors responsible for aerosol dispersion, as well as examining the source and airflow characteristics of the room that are driven by ventilation and temperature gradients.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The impact of the air distribution method in ventilated rooms on the aerosol particle dispersion and removal: The experimental approach

Jurelionis¹,

Gagyte²,

Prasauskas³

et al. 2015

Energy and Buildings

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

The impact of the air distribution method in ventilated rooms on the aerosol particle dispersion and removal: The experimental approach

Jurelionis¹,

Gagyte²,

Prasauskas³

et al. 2015

Energy and Buildings

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“…The study found that a grid number of 1.2×10 5 is appropriate for obtaining reasonably gridindependent solutions for this case, which thus was used for the following simulations. Figure 3 shows the simulated airflow field in the cabin, which was validated against physical experiment results (Liu and Zhai 2007b). Figure 4 presents the simulated dynamic contaminant concentration readings at the two sensor locations during the first 100 seconds after the contaminant was released.…”

Section: Fig 3 Aircraft Cabin Cfd Model Simulated Main Airflows Anmentioning

confidence: 99%

Principles and applications of probability-based inverse modeling method for finding indoor airborne contaminant sources

Zhai

Liu

2008

Build. Simul.

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Building indoor air quality (IAQ) has received growing attentions lately because of the extended time people spend indoors and the increasing reports of health problems related to poor indoor environments. Recent alarms to potential terrorist attacks with airborne chemical and biological agents (CBA) have further highlighted the research needs on building vulnerability and protection. To maintain a healthful and safe indoor environment, it is crucial to identify contaminant source locations, strengths, and release histories. Accurate and prompt identification of contaminant sources can ensure that the contaminant sources can be quickly removed and contaminated spaces can be effectively isolated and cleaned. This paper introduces a probability concept based prediction method -the adjoint probability method -that can track potential indoor airborne contaminant sources with limited sensor outputs. The paper describes the principles of the method and presents the general modeling algorithm and procedure that can be implemented with current computational fluid dynamics (CFD) or multi-zone airflow models. The study demonstrates the application of the method for identifying airborne pollutant source locations in two realistic indoor environments with few sensor measurement outputs. The numerical simulations verify the feasibility and accuracy of the method for indoor pollutant tracking applications, which forms a good foundation for developing an intelligent and integrated indoor environment management system that can promptly respond to indoor pollution episodes with effective detection, analysis, and control.

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“…Although Wang et al (2013) developed an original method to identify an unknown point source in steady-state flow and concentration field, the method is only applicable to identification of single point source. The probability-based CFD modeling which uses the results of CFD calculation for all the potential point sources has the same limitation though the method could identify the source location with very high accuracy by using the limited number of sensor(s) (Liu and Zhai 2008). Assuming that the potential locations of source(s) are limited, rapid identification of the source location(s) can be performed by using the limited number of sensors (Cai et al 2012(Cai et al , 2014.…”

Section: Introductionmentioning

confidence: 99%

Estimation of indoor contamination source location by using variational continuous assimilation method

et al. 2015

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Information on concentration of contaminants is important for management of indoor air quality. Recently, data assimilation techniques are used in order to accurately estimate location and intensity of contamination source in addition to concentration field. In this study, the variational continuous assimilation (VCA) method, which was originally developed in meteorological simulations, was applied to estimates of indoor air quality. The method modifies the governing equations of computational fluid dynamics (CFD) model by adding a correction term which reduces the error between original CFD calculation and observed data. In the mass conservation equation, the correction term can be assumed to be a pseudo source term. The validity of VCA method was confirmed by numerical experiments for two-dimensional steady-state calculation with the following procedures: (i) "true" concentration field was produced by CFD calculations with "true" concentration source; (ii) "pseudo-observation" data were extracted from "true" concentration field; (iii) the VCA method was applied to "false" CFD calculations without contamination source to produce "corrected" concentration field using "pseudo-observation" data; (iv) "corrected" concentration field and contamination source were compared with "true" dataset. The numerical experiments revealed the following findings: the VCA method can identify the area where the contamination source was located; and the VCA method can also reduce errors between "true" and CFD-calculated concentration field although the peak concentration was not well-estimated. These results suggest that the VCA method is a utilizable method to estimate concentration field, and location and intensity of contamination source.

show abstract

Location identification for indoor instantaneous point contaminant source by probability-based inverse Computational Fluid Dynamics modeling

Cited by 93 publications

References 7 publications

The impact of the air distribution method in ventilated rooms on the aerosol particle dispersion and removal: The experimental approach

The impact of the air distribution method in ventilated rooms on the aerosol particle dispersion and removal: The experimental approach

Principles and applications of probability-based inverse modeling method for finding indoor airborne contaminant sources

Estimation of indoor contamination source location by using variational continuous assimilation method

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