Novel integrated ozone contactor design and optimization tools which consist of an instrument that measures ozone decay kinetics, a program that performs predictive simulation, and an experimental method to examine mixing characteristics within the ozone contactor, were developed in this study.
A multi-channel stopped-flow reactor (MC-SFR) is an instrument that performs automatic, real-time, and continuous analysis of ozone decay kinetics in natural waters. Ozone Contactor Model (OCM) is the software to simulate the performance of full-scale ozone bubble-diffuser contactors in support of current and future regulations regarding pathogen and bromate control in drinking water. The MC-SFR and OCM developed in this study were further applied to simulate Cryptosporidium parvum oocyst log inactivation and bromate formation in Linnwood Water Plant Ozone Facility (LWPOF) at Milwaukee Water Works, Milwaukee, WI and model predictions were verified with experimental results. Three dimensional laser induced fluorescence(3DLIF) allowed real time characterization of mixing conditions in a physical model ozone contactors by capturing fluorescence image emitted from a laser dye (i.e. Rhodamine 6G) using a high speed CCD camera. 3DLIF system was applied to analyze the hydrodynamics of two representative types of ozone contactor: direct discharge side-stream venturi injector (SVI) and multi-chambered fine bubble diffuser (FBD). Experimental results verified the presence of circulative swirling related for low dispersion for SVI reactor and the existence of non-ideal flow including short circuiting and internal recirculation in FBD reactor. Finally, integrated tools were applied to the design of a new ozone contactor under planning stage to assess current design and to recommend the improvement.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/16224 |
Date | 18 May 2007 |
Creators | Kim, Doo-Il |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Dissertation |
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