Pollutant transport and dispersion in large indoor spaces: A status report for the large space effort of the Interiors Project

Gadgil, Ashok; Finlayson, Elizabeth U.; Fischer, M. L.; Price, Phillip N.; Thatcher, Tracy L.; Craig, M.J.; Hong, Ki-Sup; Housman, Jeffrey A.; Schwalbe, Carrie A.; Wilson, D.; Wood, Jason; Sextro, R.G.

doi:10.2172/779725

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…The experiments and modeling work described in this work were limited to isothermal flows. Future work will need to address predictions under non‐isothermal conditions in more realistic geometries such as the full‐scale atrium described in Gadgil et al. (2000).…”

Section: Discussionmentioning

confidence: 99%

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Pollutant dispersion in a large indoor space. Part 2: Computational fluid dynamics predictions and comparison with a scale model experiment for isothermal flow

et al. 2004

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CFD modeling of pollutant transport is becoming increasingly common but high quality comparisons between CFD and experiment remain rare. Our results provide such a comparison. We demonstrate that the standard k-epsilon model provides good predictions for both transient and fully developed pollutant concentrations for an isothermal large space where furnishings are unimportant. This model is less computationally intensive than a large eddy simulation or low Reynolds number k-epsilon model.

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Section: Discussionmentioning

confidence: 99%

“…Their predictions were in good agreement with the experimental data. A larger bibliography of relevant published literature, including purely experimental and purely computational work, is given in Gadgil et al. (2000).…”

Section: Introductionmentioning

confidence: 99%

Pollutant dispersion in a large indoor space. Part 2: Computational fluid dynamics predictions and comparison with a scale model experiment for isothermal flow

et al. 2004

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“…Roy et al (1994) used a CFD code to predict contaminant dispersion in a kitchen-hood geometry. Gadgil et al (2000) provide a brief review of experimental and computational research investigations of pollutant dispersion in indoor spaces.…”

Section: Introductionmentioning

confidence: 99%

Indoor pollutant mixing time in an isothermal closed room: an investigation using CFD

Gadgil

Lobscheid

Abadie

et al. 2003

Atmospheric Environment

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We report computational fluid dynamics (CFD) predictions of mixing time of a point pulse release of a pollutant in an unventilated mechanically mixed isothermal room. The aims of the study are to determine (1) the adequacy of the standard RANS two-equation (k-ε) turbulence model to predict the mixing times under these conditions, and (2) the extent to which the mixing time is a feature of the room airflow, rather than the source location within the room. CFD simulations modeled the twelve mixing time experiments performed by Drescher et al. (1995) in an isothermal sealed room for a point pulse release. Predictions of mixing time were found in good agreement with experimental measurements, over an order of magnitude variation in blower power. Additional CFD simulations were performed to investigate the relation between pollutant mixing time and pollutant source location. Seventeen source locations were investigated for five different blower power configurations in the room. Results clearly show large dependence of the mixing time on the room airflow, with some dependence on source location. We further explore dependence of mixing time on the local airflow properties (velocity and turbulence intensity) at the source location. Implications for our findings for positioning air-toxic sensors in rooms are also discussed.

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“…Even with the computationally less-expensive RANS method, hours of computer time may be required to calculate the airflows for a small room (Gadgil et al, 2000 and confidence, such that an optimal response strategy can still be executed.…”

Section: Computational Fluid Dynamicsmentioning

confidence: 99%

Bayesian based design of real-time sensor systems for high-risk indoor contaminants

Sreedharan¹

2007

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The sudden release of toxic contaminants that reach indoor spaces can be hazardous to building occupants. To respond effectively, the contaminant release must be quickly detected and characterized to determine unobserved parameters, such as release location and strength. Characterizing the release requires solving an inverse problem. Designing a robust real-time sensor system that solves the inverse problem is challenging because the fate and transport of contaminants is complex, sensor information is limited and imperfect, and real-time estimation is computationally constrained.This dissertation uses a system-level approach, based on a Bayes Monte Carlo framework, to develop sensor-system design concepts and methods. I describe three investigations that explore complex relationships among sensors, network architecture, interpretation algorithms, and system performance. The investigations use data obtained from tracer gas experiments conducted in a real building.The influence of individual sensor characteristics on the sensor-system performance for binary-type contaminant sensors is analyzed. Performance tradeoffs among sensor 2 accuracy, threshold level and response time are identified; these attributes could not be inferred without a system-level analysis. For example, more accurate but slower sensors are found to outperform less accurate but faster sensors.Secondly, I investigate how the sensor-system performance can be understood in terms of contaminant transport processes and the model representation that is used to solve the inverse problem. The determination of release location and mass are shown to be related to and constrained by transport and mixing time scales. These time scales explain performance differences among different sensor networks. For example, the effect of longer sensor response times is comparably less for releases with longer mixing time scales.The third investigation explores how information fusion from heterogeneous sensors may improve the sensor-system performance and offset the need for more contaminant sensors. Physics-and algorithm-based frameworks are presented for selecting and fusing information from noncontaminant sensors. The frameworks are demonstrated with door-position sensors, which are found to be more useful in natural airflow conditions, but which cannot compensate for poor placement of contaminant sensors.The concepts and empirical findings have the potential to help in the design of sensor systems for more complex building systems. The research has broader relevance to additional environmental monitoring problems, fault detection and diagnostics, and system design. i

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Pollutant transport and dispersion in large indoor spaces: A status report for the large space effort of the Interiors Project

Cited by 6 publications

References 27 publications

Pollutant dispersion in a large indoor space. Part 2: Computational fluid dynamics predictions and comparison with a scale model experiment for isothermal flow

Pollutant dispersion in a large indoor space. Part 2: Computational fluid dynamics predictions and comparison with a scale model experiment for isothermal flow

Indoor pollutant mixing time in an isothermal closed room: an investigation using CFD

Bayesian based design of real-time sensor systems for high-risk indoor contaminants

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