Publication: HVAC & R Research
Publication Date: 01-SEP-07
Delivery: Immediate Online Access
Author: Zhang, Tengfei ; Chen, Qingyan (Yan) ; Lin, Chao-Hsin
Article Excerpt
INTRODUCTION
Currently only air temperature and barometric pressure are routinely measured in commercial aircraft cabins. These limited measurements are not sufficient when the environmental control system is not properly working, and they are not intended to be used to detect or monitor air-quality incidents (NRC 2002). The National Research Council has thus suggested monitoring other air-quality characteristics on commercial aircraft that include ozone, carbon monoxide, carbon dioxide, relative humidity, and fine particulate matter.
Without the presence of appropriate sensors in the aircraft, information on contaminant transport cannot be obtained in a timely fashion. It is speculated that during the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003, 22 passengers may have been infected by SARS on the flight from Hong Kong to Beijing (Olsen et al. 2003) due to possible release of the SARS virus from an infected passenger. If a SARS sensor had been available and properly placed in the airplane, it might have provided the SARS release information during the flight so necessary protective measures, such as using oxygen or masks, could have been taken. Furthermore, after the use of the nerve agent sarin to attack the Tokyo subway system in 1995 and the anthrax cases in Florida and Washington, DC, in 2001, there have been fears expressed of possible terrorist attacks by releasing chemical/biological agents in commercial airplanes. It would be beneficial to obtain the release information of chemical/biological agents in advance to protect passengers and crew. Thus, a suitable placement of sensors on commercial airplanes can play a critical role in monitoring cabin air to create a comfortable, healthy, and safe cabin environment for passengers and crew.
Typically, one would place a sensor at the air exhaust in an airliner cabin because the current air distribution system creates a mixing condition. The obtained measurement information, while useful, may be difficult to use to find contaminant sources, however (Zhang and Chen 2007a). Because of the dilution of the contaminant due to the strong mixing effect, the detection would need very sensitive sensors and a long time of exposure. Thus, by the time a contaminant is detected, the whole cabin may have been polluted. Previous research on airborne contaminant transport in a room showed that sensors can detect very different contaminant concentration levels at different locations (Zhai et al. 2003). Zhai et al. (2003) found that an early warning before the contaminant reached an occupant in the room was possible by placing sensors appropriately in the room. Since the room environment is similar to a cabin environment in terms of airflow and contaminant transport characteristics, it is also possible to obtain early warning data from sensors if they are placed in proper locations inside the cabin.
RESEARCH METHODS
In order to determine where to place sensors in an aircraft cabin, two research methods are available: experimental measurements and computer simulations. The experimental measurements would need to investigate sensor responses to different contaminants released at different locations. The best locations for sensors will be where the sensors can measure the highest contaminant concentrations in the least amount of time. Such experimental investigation would need a full-scale aircraft cabin. Due to different sensor sensitivities to different kinds of contaminants and many possible release scenarios, experimental measurements can be very expensive and time consuming to obtain.
Compared to the experimental measurements, computer simulations are much cheaper and more efficient. Computer simulations can use multizone models or computational fluid dynamics (CFD) modeling. Arvelo et al. (2002) used a modified multizone model to study the optimum placement of chemical/biological contaminant sensors in a building with nine offices and a hallway. The contaminant transport time in a zone was not considered since the multizone model assumes instantaneous mixing in each zone. The multizone model can only provide some macroscopic information about sensor placement. To obtain more accurate and detailed results one would turn to CFD modeling. Obenschain et al. (2004) studied optimal sensor placement during a chemical/biological contaminant threat in a city by using CFD modeling. In their study, the contaminant transport data was pre-computed and stored and then was interpreted with a nomograph technique. Their results depended on the assumed meteorological conditions because different wind directions can make the paths of contaminant transport vastly different. Lohner and Camelli (2005) conducted a detailed CFD study of optimal sensor placement for hazardous material transports going around buildings. They compared different sensor placements to account for contaminant transport in possible meteorological conditions. A sensor was assumed to have detected the contaminant once the contaminant concentration exceeded a threshold level. Zhai et al. (2003) studied the optimal sensor placement for chemical/biological agent releases in buildings. Their results show that CFD simulation can be used to identify the proper location for sensor deployment. Although chemical/biological agent dispersion in an enclosed environment is very fast, the sensors could give early warning to occupants in case of a terrorist attack. Clearly, the above review shows that CFD is more appropriate than the multi-zone model for this investigation.
In CFD simulations, one can assume hundreds of contaminant release scenarios and different sensor sensitivities and can compare sensor performance at most possible locations in an aircraft cabin with little cost. However, the commonly used CFD modeling by solving the Reynolds-Averaged Navier-Stokes equations with a turbulence model uses approximations, so there are uncertainties in...
NOTE: All illustrations and photos have been removed from this article.
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