Quantification of wastewater treatment resilience metrics

本项目的目的是开发一种度量标准来衡量污水处理厂的恢复能力。英国水务公司正在制定污水处理服务的弹性战略。这些策略的目的是了解废水系统如何应对极端或异常的冲击和压力事件，以及这将对提供给客户的服务和环境产生的潜在影响。在确定复原力风险后，将制定干预措施，以减轻、适应或应对未来的挑战。这些干预措施将寻求提供经得起未来考验的服务，或促进其迅速恢复，从而最大限度地减少服务故障。该战略的一个重点领域是了解废水处理过程的复原力。人们认识到，由气候变化、人口增长、基础设施老化等驱动的压力和冲击事件将增加进入处理厂的流量和负荷的可变性，并增加内部资产故障的发生。当前的资产基础和系统操作可能无法响应这些事件以防止故障，因此这些事件有可能导致服务中断、环境污染和声誉损害。根据所描述的影响，开发该项目的策略可以按以下步骤定义：*极端事件如何影响废水处理厂，以及工厂如何应对和从这些事件中恢复*如何量化压力源和发生的可能性*量化对废水过程的影响*使用哪些模型和工具将对废水过程的影响联系起来建立基线处理弹性的方法包括强调a系统有许多已定义的系统故障，并记录由此产生的应变。系统故障（压力）分为外部（即系统输入的变化）或内部（即系统边界内的变化）。在许多不同的大小和持续时间施加应力，以建立一系列可能的应变分布图。该分析的输出是一组应力-应变曲线。该方法应用于污水处理厂的“数字孪生体”。这是一个经过校准的处理厂的物理/生物/化学模型，由单独代表的过程单元建立。数字孪生现在通常应用于小规模和受控环境，例如制造过程或单一资产操作。一家大型水务公司的废水处理操作在科学、计算和工程方面提出了数字孪生规范和开发的严峻挑战。科学进步将涉及：a)具有重要空间范围的大型开放系统的数据采集和管理b)“系统的系统”中复杂环节的描述和模拟c)弹性度量的制定需要考虑许多不同的方面，这些方面与传统方法（例如金融、碳、气候、气候和气候）并不直接等同。将方法从大型工程（具有良好的数据可用性）扩展到大量具有较少数据可用性的小型工程，在不确定性方面提出了一个有趣的问题，建议采用随机方法。为了确保现在和将来提供可靠，有弹性和可持续的废水服务，英国水务公司致力于了解冲击和压力事件的影响。该项目将促进和加强这种理解，并允许有针对性的投资来应对韧性挑战。可量化指标的开发将使复原力得以跟踪。

The aim of this project is to develop a metric to measure the resilience of the wastewater treatment plant. UK water companies are developing their resilience strategy for wastewater service. The aim of these strategies is to understand how the wastewater system will respond to extreme or exceptional shock and stress events, and the potential impact this will have on the service provided to customers and to the environment. Upon identifying resilience risk, interventions will be developed to mitigate for, adapt to, or cope with future challenges. These interventions will seek to futureproof service provision or facilitate it to recover rapidly thereby minimising service failure.One focus area of the strategy is understanding the resilience of wastewater treatment processes. It is recognised that both stress and shock events, driven by climatic change, population growth, ageing infrastructure etc. will increase the variability of flows and loads of influent entering treatment works, and increase the occurrence of internal asset failures. The current asset base and system operation may be incapable of responding to these events in order to prevent failure, and as such these events have the potential to cause service disruption, environmental pollution and reputational damage.Following the impacts described a strategy to develop this project could be defined in the steps below:* How the extreme events can impact the wastewater treatment plants and how the plant cope and recover from such events* How to quantify the stressors and probability of occurrence* Quantify the impacts on the wastewater processes* Which models and tools to use to link the impact on the wastewater processesThe methodology for establishing baseline treatment resilience involves stressing a system with a number of defined system failures, and recording the resultant strain.System failures (stresses) are classified as either external (i.e. changes to the system input) or internal (i.e. changes within the system boundary). The stresses are applied at a number of varying magnitudes and durations to establish a range of possible strain profiles. The output of this analysis is a set of stress-strain curves. This methodology is applied to a 'Digital Twin' of the treatment works. This is a calibrated physical/biological/chemical model of the treatment works built up from individually represented process units. Digital twins are now routinely applied in small scale and controlled environments, e.g. manufacturing processes or single asset operation. A wastewater treatment operation for a large water company presents a stiff challenge in science, computing and engineering terms for the specification and development of a digital twin. The scientific advances would involve:a) Data acquisition and management for large, open systems with significant spatial extentb) Description and simulation of the complex links in a "system of systems" c) Development of a resilience metric requires consideration of a number of different aspects which are not straightforward to equate with conventional methods (e.g. financial, carbon, environmental)d) Extension of the method from large works (with good data availability) to large numbers of smaller works with much less data availability poses an interesting problem in terms of uncertainty suggesting a stochastic approachIn order to ensure reliable, resilient and sustainable wastewater service provision both now and into the future, UK water companies are committed to understanding the impact of shock and stress events. This project will enable and enhance this understanding and allow for targeted investment to tackle the resilience challenge. Development of quantifiable metrics will enable resilience to be tracked.