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Improved Monitoring Protocol for Evaluating the Performance of a Sewage Treatment Works Based on Sensitivity Analysis of Mathematical Modelling

机译:基于数学建模敏感性分析的改进的污水处理厂性能监测协议

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Extensive historical data of a sewage treatment works are required by numerical models in order to simulate the biological processes accurately. However, the data are recorded mostly for daily operational purpose. They are basically not comprehensive enough to meet the modelling’s requirements. A comprehensive sampling protocol to accurately characterise the influent is required in order to determine all model components, which is very time-consuming and expensive. In a project of evaluating a sewage treatment works in Chongqing by using BioWin 4.1 for mathematical modelling, sensitivity analysis was conducted to determine the most critical parameters for process monitoring. It was found that influent characteristics, wasted sludge flow rate, water temperatures, DO levels of the biological tanks and five bio-kinetic parameters were the most influential parameters governing the plant performance. Therefore, apart from monitoring the effluent quality, regular checking of the afore-mentioned influential parameters can help examine the performance of a sewage treatment works. Moreover, operators of the sewage treatment works can conduct “what-if” analysis to determine how these most influential parameters can be adjusted to improve the treatment performance of the sewage treatment works.
机译:数值模型需要污水处理厂的大量历史数据,以便准确地模拟生物过程。但是,记录的数据主要用于日常操作。它们基本上不够全面,无法满足建模要求。为了确定所有模型组件,需要使用全面的采样协议来准确表征进水,这非常耗时且昂贵。在使用BioWin 4.1进行数学建模来评估重庆市污水处理厂的项目中,进行了敏感性分析,以确定用于过程监控的最关键参数。研究发现,进水特性,污泥浪费率,水温,生物池的溶解氧水平和五个生物动力学参数是决定工厂性能的最有影响的参数。因此,除了监测废水质量外,定期检查上述影响参数还有助于检查污水处理厂的性能。此外,污水处理厂的经营者可以进行“假设分析”,以确定如何调整这些最有影响力的参数来改善污水处理厂的处理性能。

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