当前位置: X-MOL 学术J. Water Process. Eng. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Dynamic resilience for biological wastewater treatment processes: Interpreting data for process management and the potential for knowledge discovery
Journal of Water Process Engineering ( IF 7 ) Pub Date : 2021-06-21 , DOI: 10.1016/j.jwpe.2021.102170
Timothy G. Holloway , John B. Williams , Djamila Ouelhadj , Gong Yang

Climate change, population growth and increasing regulation are causing wastewater treatment plants to become increasingly stressed, especially in countries like the UK, where many of these systems date back to the early part of the 20th century. Understanding resilience dynamics for these ageing wastewater assets represents a fundamental step in classifying multi-dimensional water stressors toward preventing severe pollution incidents. This paper explores the potential of a novel dynamic resilience approach to assess and predict the dynamic resilience of biological wastewater treatment based on the separation of stressor events (cause) and process stress (effect) to consider the deviation from reference conditions. The approach presented provides a fundamental link between (1) conventional activated sludge modelling methodologies, (2) actual biological wastewater process instrument data (potential for knowledge discovery) and (3) the characterisation of dynamic resilience in wastewater treatment processes. Results first present the dynamic resilience approach by modelling simulated shock flow conditions on an activated sludge plant, then incorporates ten years of wastewater process instrument data to demonstrate the actual dynamic resilience. The aim is to represent the “dynamic resilience” as self-ordering windows, a visual knowledge base (three dimensional, heat map), which operational staff can easily interpret. The outcomes presented suggest that such an approach is feasible and has the potential for real-time identification of conditions that result in pollution incidents based on actual historical process instrument data (knowledge discovery). Also, the methods presented could be extended to develop an improved understanding of wastewater system resilience under a range of future stressor scenarios.



中文翻译:

生物废水处理过程的动态弹性:解释过程管理的数据和知识发现的潜力

气候变化、人口增长和日益严格的监管导致污水处理厂面临越来越大的压力,尤其是在英国这样的国家,其中许多系统的历史可以追溯到 20 世纪初期。了解这些老化废水资产的弹性动态代表了对多维水资源压力因素进行分类以防止严重污染事件的基本步骤。本文探讨了一种新的动态弹性方法的潜力,该方法基于分离压力事件(原因)和过程压力(效果)来评估和预测生物废水处理的动态弹性,以考虑与参考条件的偏差。所提出的方法提供了 (1) 传统活性污泥建模方法之间的基本联系,(2) 实际生物废水处理仪器数据(知识发现的潜力)和 (3) 废水处理过程中动态弹性的表征。结果首先通过对活性污泥厂的模拟冲击流条件进行建模来展示动态弹性方法,然后结合十年的废水处理仪器数据来证明实际的动态弹性。目的是将“动态弹性”表示为自排序窗口,一个可视化知识库(三维,热图),操作人员可以轻松解释。所呈现的结果表明,这种方法是可行的,并且有可能根据实际的历史过程仪器数据(知识发现)实时识别导致污染事故的条件。还,

更新日期:2021-06-21
down
wechat
bug