UNSW Water Research Centre, School of Civil & Environmental Engineering, University of New South Wales, New South Wales, 2052, Australia.
UNESCO Centre for Membrane Science and Technology, University of New South Wales, New South Wales, 2052, Australia.
Water Res. 2017 Oct 1;122:269-279. doi: 10.1016/j.watres.2017.05.057. Epub 2017 May 30.
Ultrafiltration is an effective barrier to waterborne pathogens including viruses. Challenge testing is commonly used to test the inherent reliability of such systems. Performance validation seeks to demonstrate the adequate reliability of the treatment system. Appropriate and rigorous data analysis is an essential aspect of validation testing. In this study we used Bayesian analysis to assess the performance of a full-scale ultrafiltration system which was validated and revalidated after five years of operation. A hierarchical Bayesian model was used to analyse a number of similar ultrafiltration membrane skids working in parallel during the two validation periods. This approach enhanced our ability to obtain accurate estimations of performance variability, especially when the sample size of some system skids was limited. This methodology enabled the quantitative estimation of uncertainty in the performance parameters and generation of predictive distributions incorporating those uncertainties. The results indicated that there was a decrease in the mean skid performance after five years of operation of approximately 1 log reduction value (LRV). Interestingly, variability in the LRV also reduced, with standard deviations from the revalidation data being decreased by a mean 0.37 LRV compared with the original validation data. The model was also useful in comparing the operating performance of the various parallel skids within the same year. Evidence of differences was obtained in 2015 for one of the membrane skids. A hierarchical Bayesian analysis of validation data provides robust estimations of performance and the incorporation of probabilistic analysis which is increasingly important for comprehensive quantitative risk assessment purposes.
超滤是一种有效的水传播病原体（包括病毒）屏障。挑战性试验通常用于测试此类系统固有的可靠性。性能验证旨在证明处理系统具有足够的可靠性。适当和严格的数据分析是验证测试的一个重要方面。在这项研究中，我们使用贝叶斯分析来评估经过五年运行后经过验证和重新验证的全规模超滤系统的性能。使用分层贝叶斯模型分析了两个验证期内同时运行的多个类似超滤膜片的性能。这种方法增强了我们获得性能变异性准确估计的能力，特别是在某些系统片的样本量有限时。这种方法能够定量估计性能参数中的不确定性，并生成包含这些不确定性的预测分布。结果表明，经过五年的运行后，每个膜片的平均性能下降了约 1 个对数减少值（LRV）。有趣的是，LRV 的变异性也降低了，与原始验证数据相比，重新验证数据的标准差平均降低了 0.37 LRV。该模型还可用于比较同年中各个平行膜片的运行性能。在 2015 年，一个膜片的性能存在差异。对验证数据的分层贝叶斯分析提供了性能的稳健估计，并进行了概率分析，这对于全面的定量风险评估目的越来越重要。
