Capetillo, A, Noakes, CJ and Sleigh, PA (2015) Computational fluid dynamics analysis to assess performance variability of in-duct UV-C systems. Science and Technology for the Built Environment, 21 (1). pp. 45-53. ISSN 2374-4731
Abstract
UV-C is becoming a mainstream air sterilisation technology, and is marketed in the form of energy saving and infection reduction devices. An accurate rating of device performance is essential to ensure appropriate microbial reduction yet avoid wastage of energy due to over performance. This paper demonstrates the potential benefits from using computational fluid dynamics (CFD) to assess performance. A CFD model was developed using discrete ordinate (DO) irradiation modeling and Lagrangian particle tracking to model airborne microorganisms. The study calculates UV dose received by airborne particles in an in-duct UV system based on published EPA experimental tests for single, four lamp and eight lamp devices. Whereas the EPA tests back calculated UV dose from measured microorganism inactivation data, the CFD model directly computes UV dose, then determines inactivation of microorganisms. Microorganism inactivation values compared well between the CFD model and the EPA tests, but differences between UV dosages were found due to uncertainty in microorganism UV susceptibility data. The study highlighted the need for careful consideration of test microorganisms and a reliable data set of UV susceptibility values in air to assess performance. Evaluation of the dose distribution demonstrated the importance of creating an even UV field to minimize the risk of ineffective sterilization of some particles while not delivering excessive energy to others.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2015, ASHRAE. This is an Accepted Manuscript of an article published by Taylor & Francis in Science and Technology for the Built Environment on 06/01/2015, available online: http://wwww.tandfonline.com/10.1080/10789669.2014.968512 |
Dates: |
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Institution: | The University of Leeds |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Nov 2014 11:55 |
Last Modified: | 10 Mar 2016 16:43 |
Published Version: | http://dx.doi.org/10.1080/10789669.2014.968512 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/10789669.2014.968512 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:81368 |