The factors that affect the performance of UV disinfection systems are well-known and measureable. Mathematical models exist that can be used to provide accurate predictions of UV disinfection system performance; in addition, analytical and diagnostic methods are available that can
provide comprehensive information regarding the behavior of UV photoreactors. However, existing design and validation methods for these systems do not employ these tools to their full potential. A new design and validation protocol is proposed based on available methods and models. The
method includes measurements of parameters that influence UV system behavior, including flow rate, UVT, lamp power, influent viable indicator organism concentration (N0), and UV dose-response behavior. Measurements of these parameters are repeated to allow measurement of mean and
variability in input parameters. In turn, these parameters are applied to a CFD-I model in a stochastic approach to allow assessment of variability in reactor performance. Model predictions are validated with data from Lagrangian Actinometry and biodosimetry experiments that are performed
over the anticipated operating envelop using a full-scale reactor intended for use at the given facility. The validated model can then be used to predict reactor behavior, including variability, by interpolation over the range of conditions within the validation envelope. This method has the
potential to yield reactor designs that are more reliable and efficient than those that are developed based on existing methods.
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