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Identification of reactive contaminant sources in a water distribution system under the conditions of data uncertainties

机译：在数据不确定性条件下识别供水系统中反应性污染物源

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Water distribution systems are designed for fast and efficient transport of the drinking water and mixing of chlorine to maintain the required disinfectant levels in the system. Thus, any contaminant if injected in the system would also spread quickly through the network and can have serious impact on public health if consumed. Contaminant injected during any intentional contamination event can be chemical or biological, the nature of which may remain unknown. Practically it's not possible to monitor any system for the presence of all possible chemical or biological contaminants. However, the distribution systems are routinely monitored for several water quality parameters like chlorine, pH, etc. Any contaminant injected in the system would react with water and chlorine leading to the increased degradation of the chlorine levels in the system. In our past work we developed methodology to use routine chlorine measurements as a surrogate to identify a contamination event in a WDS. An evolutionary algorithm based approach simulation-optimization was developed to identify the contaminant source characteristics (i.e., location of the contaminant source, time of start of injection and injection pattern) during a contamination event under conditions of uncertainty about the reaction kinetics of the contaminant in the system. The investigation was extended to study the source characterization problem under different uncertain reaction conditions. We present here a detailed analysis of source characterization problem for the reactive contaminants and the simulation-optimization methodology developed. Case studies carried out on a number of water distributions systems will be reported.
机译：水分配系统旨在快速有效地输送饮用水并混合氯气，以维持系统中所需的消毒剂水平。因此，如果将任何污染物注入系统，也会迅速通过网络传播，如果被消耗，则会对公共健康产生严重影响。在任何故意的污染事件中注入的污染物可以是化学的或生物的，其性质可能仍然未知。实际上，不可能监视任何系统是否存在所有可能的化学或生物污染物。但是，会定期监控分配系统中的几个水质参数，例如氯，pH等。注入系统的任何污染物都会与水和氯反应，导致系统中氯含量的下降加剧。在过去的工作中，我们开发了使用常规氯测量值作为替代方法来识别WDS中污染事件的方法。开发了一种基于进化算法的方法模拟优化，以在污染事件中在不确定污染物反应动力学的条件下识别污染物源的特性（即，污染物源的位置，注入的开始时间和注入方式）。系统。扩展了研究范围，以研究在不同不确定反应条件下的源表征问题。在这里，我们对活性污染物的源表征问题和开发的仿真优化方法进行了详细分析。将报告在许多水分配系统上进行的案例研究。

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