Statistics – Computation
Scientific paper
Oct 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009adspr..44..942l&link_type=abstract
Advances in Space Research, Volume 44, Issue 8, p. 942-948.
Statistics
Computation
Scientific paper
The air of indoor cabin environments is susceptible to contamination by airborne microbial pathogens. A number of air treatment processes are available for inactivation or removal of airborne pathogens; included among these processes is ultraviolet (UV) irradiation. The effectiveness of UV-based processes is known to be determined by the combined effects of UV dose delivery by the reactor and the UV dose-response behavior of the target microbe(s). To date, most UV system designs for air treatment have been based on empirical approaches, often involving crude representations of dose delivery and dose-response behavior. The objective of this research was to illustrate the development of a UV system for disinfection of cabin air based on well-defined methods of reactor and reaction characterization. UV dose-response behavior of a test microorganism was measured using a laboratory (bench-scale) system. Target microorganisms (bacterial spores) were first applied to membrane filters at sub-monolayer coverage. The filters were then transferred to a humidity chamber at fixed relative humidity (RH) and allowed to equilibrate with their surroundings. Microorganisms were then subjected to UV exposure under a collimated beam. The experiment was repeated at RH values ranging from 20% to 100%. UV dose-response behavior was observed to vary with RH. For example, at 100% RH, a UV dose of 20 mJ/cm2 accomplished 99.7% (2.5 log10 U) of the Bacillus subtilis spore inactivation, whereas 99.94% (3.2 log10 U) inactivation was accomplished at this same UV dose under 20% RH conditions. To determine reactor behavior, UV dose-response behavior was combined with simulated results of computational fluid dynamics (CFD) and radiation intensity field models. This modeling approach allowed estimating the UV dose distribution delivered by the reactor. The advantage of this approach is that simulation of many reactor configurations can be done in a relatively short period of time. Moreover, by following this approach of “numerical prototyping”, it is possible to “build” and analyze several virtual reactors before the construction of a physical prototype. As such, this procedure allows effective development of efficient reactors.
Blatchley Ernest R.
Lim Soojung
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