Publications
2012
Chen, Y. Lisa; Wen, Jin
The selection of the most appropriate airflow model for designing indoor air sensor systems Journal Article
In: Building and Environment, vol. 50, pp. 34-43, 2012, ISSN: 0360-1323.
Abstract | Links | BibTeX | Tags: Airflow model selection, Computational fluid dynamics, Multizone model, Sensor system design, Zonal model
@article{CHEN201234,
title = {The selection of the most appropriate airflow model for designing indoor air sensor systems},
author = {Y. Lisa Chen and Jin Wen},
url = {https://www.sciencedirect.com/science/article/pii/S0360132311003568},
doi = {https://doi.org/10.1016/j.buildenv.2011.10.007},
issn = {0360-1323},
year = {2012},
date = {2012-01-01},
journal = {Building and Environment},
volume = {50},
pages = {34-43},
abstract = {Current indoor air sensor system design is mostly by intuition or experience rather than by design. Sensor systems that are intended to ensure the safety and well-being of building occupants should be systematically designed and their performance evaluated. The literature shows that selection of an airflow model for sensor system design has been either out of convenience (thus choosing a simpler multizone model) or for proven accuracy (thus choosing a more complex computational fluid dynamics (CFD) model). In this study, the most appropriate airflow model for use in designing indoor air sensor systems was selected without compromising design objectives for 12 test zones. The test zones differed in the diffuser location, furniture presence and location, and airtightness level. Simulated contaminant concentrations from multizone, zonal, and CFD models were used to design sensor systems that either minimized detection time or occupant exposure. In lieu of experimental data, the performance of the sensor systems designed using multizone and zonal model data were benchmarked using CFD data. The sensor systems designed using CFD data were considered the “best-performing” in lieu of actual performance data. It was found that multiple-sensor systems designed using multizone model (the simplest of the three airflow models tested) data performed just as well as the best-performing sensor systems. For 1-sensor systems, common engineering practices resulted in performance comparable to the best-performing ones. These results applied even though the test zones were not considered well-mixed, and furniture and infiltration was modeled.},
keywords = {Airflow model selection, Computational fluid dynamics, Multizone model, Sensor system design, Zonal model},
pubstate = {published},
tppubtype = {article}
}
Current indoor air sensor system design is mostly by intuition or experience rather than by design. Sensor systems that are intended to ensure the safety and well-being of building occupants should be systematically designed and their performance evaluated. The literature shows that selection of an airflow model for sensor system design has been either out of convenience (thus choosing a simpler multizone model) or for proven accuracy (thus choosing a more complex computational fluid dynamics (CFD) model). In this study, the most appropriate airflow model for use in designing indoor air sensor systems was selected without compromising design objectives for 12 test zones. The test zones differed in the diffuser location, furniture presence and location, and airtightness level. Simulated contaminant concentrations from multizone, zonal, and CFD models were used to design sensor systems that either minimized detection time or occupant exposure. In lieu of experimental data, the performance of the sensor systems designed using multizone and zonal model data were benchmarked using CFD data. The sensor systems designed using CFD data were considered the “best-performing” in lieu of actual performance data. It was found that multiple-sensor systems designed using multizone model (the simplest of the three airflow models tested) data performed just as well as the best-performing sensor systems. For 1-sensor systems, common engineering practices resulted in performance comparable to the best-performing ones. These results applied even though the test zones were not considered well-mixed, and furniture and infiltration was modeled.
2010
Chen, Y. Lisa; Wen, Jin
Comparison of sensor systems designed using multizone, zonal, and CFD data for protection of indoor environments Journal Article
In: Building and Environment, vol. 45, no. 4, pp. 1061-1071, 2010, ISSN: 0360-1323.
Abstract | Links | BibTeX | Tags: Computational fluid dynamics (CFD), Indoor airflow modeling, Multizone model, Sensor system design, Zonal model
@article{CHEN20101061,
title = {Comparison of sensor systems designed using multizone, zonal, and CFD data for protection of indoor environments},
author = {Y. Lisa Chen and Jin Wen},
url = {https://www.sciencedirect.com/science/article/pii/S0360132309003096},
doi = {https://doi.org/10.1016/j.buildenv.2009.10.015},
issn = {0360-1323},
year = {2010},
date = {2010-01-01},
journal = {Building and Environment},
volume = {45},
number = {4},
pages = {1061-1071},
abstract = {Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is mostly by intuition and experience rather than by systematic design. To develop a sensor system design methodology, the proper selection of an indoor airflow model is needed. Various indoor airflow models exist in the literature, from complex computational fluid dynamics (CFD) to simpler approaches such as multizone and zonal models. Airflow models provide the contaminant concentration data, to which an optimization method can be applied to design sensor systems. The authors utilized a subzonal modeling approach when using a multizone model and were the first to utilize a zonal model for systematic sensor system design. The objective of the study was to examine whether or not data from a simpler airflow model could be used to design sensor systems capable of performing just as well as those designed using data from more complex CFD models. Three test environments, a small office, a large hall, and an office suite were examined. Results showed that when a unique sensor system design was not needed, sensor systems designed using data from simpler airflow models could perform just as well as those designed using CFD data. Further, only for the small office did the common engineering sensor system design practice of placing a sensor at the exhaust result in sensor system performance that was equivalent to one designed using CFD data.},
keywords = {Computational fluid dynamics (CFD), Indoor airflow modeling, Multizone model, Sensor system design, Zonal model},
pubstate = {published},
tppubtype = {article}
}
Sensors that detect chemical and biological warfare agents can offer early warning of dangerous contaminants. However, current sensor system design is mostly by intuition and experience rather than by systematic design. To develop a sensor system design methodology, the proper selection of an indoor airflow model is needed. Various indoor airflow models exist in the literature, from complex computational fluid dynamics (CFD) to simpler approaches such as multizone and zonal models. Airflow models provide the contaminant concentration data, to which an optimization method can be applied to design sensor systems. The authors utilized a subzonal modeling approach when using a multizone model and were the first to utilize a zonal model for systematic sensor system design. The objective of the study was to examine whether or not data from a simpler airflow model could be used to design sensor systems capable of performing just as well as those designed using data from more complex CFD models. Three test environments, a small office, a large hall, and an office suite were examined. Results showed that when a unique sensor system design was not needed, sensor systems designed using data from simpler airflow models could perform just as well as those designed using CFD data. Further, only for the small office did the common engineering sensor system design practice of placing a sensor at the exhaust result in sensor system performance that was equivalent to one designed using CFD data.