Weather-induced single point of failure assessment methodology for railways

铁路部门对英国的经济和社会运作具有越来越大的重要性。与2002 - 2003年相比，乘客使用量增加了50%以上，货运量也以类似的速度增长（铁路监管办公室，2015年）。在保持可靠的服务方面，网络铁路（NR）面临着双重挑战，即在日常基础上应对天气事件的影响，同时规划和实施长期适应工作。在这两个时间尺度上为有针对性的成本效益行动提供信息至关重要的是更好地理解DfT Brown Review（2014）所称的“单点故障”：对社会和经济产生大规模影响的铁路网关键部分，例如2014年2月Dawlish海堤的倒塌。该项目旨在制定一种变革性的数据驱动方法，以绘制天气引起的自然灾害的关键程度，作为改善极端事件管理和气候变化适应优先级的基本步骤。关键是由专家主导的网络关键性指标，可用于确定网络上最关键的位置。这将使NR能够确定适应工作将在何处获得最佳效益，同时还有助于在极端事件期间分配资源和运营决策，降低与中断相关的成本并改善对客户的服务。该项目有以下目标：1.从网络铁路的角度定义关键性的关键决定因素.根据目标1.3中确定的决定因素制定关键性指标。在网络铁路路线上演示该指标，并确定轨道的网络关键路段。4.就适应行动和极端事件管理的影响征求意见。研究结果旨在适用于NR的整个网络，并将为NR拥有和运营的20，000英里轨道和2，500个站点的决策提供信息。为了具有成本效益，该指标的使用需要将网络中断减少约0.1 - 0.2%，通过更智能地分配资源/适应行动来实现，这些地区的天气相关事件对网络中断的影响最大。我们相信，通过将该项目的成果整合到上述现有的NR系统中，该公司将能够保守地将与天气相关的破坏减少3 - 5%，这将每年节省150万至250万英镑。这些对NR的直接节省将进一步乘以英国PLC的全部经济节省，有助于提高国家生产力，并通过更具弹性的流动性对社会的非货币化利益产生影响。关键词：极端天气;气候变化;铁路运输;中断;恢复力;业务连续性

The rail sector is of great and growing importance to the economic and social functioning of the UK. Passenger usage has increase by over 50% compared to 2002-2003, with the amount of freight carried growing at a similar rate (Office of Rail Regulation, 2015). In maintaining a reliable service, Network Rail (NR) faces the twin challenges of responding to the impacts of weather events on a day-to-day basis whilst planning and implementing long-term adaptation work. Of critical importance to informing targeted cost-effective actions at both timescales is a better understanding of what the DfT Brown Review (2014) termed 'single-points of failure': critical sections of the rail network which have large scale impacts for society and economy, as exemplified by the collapse of the Dawlish Sea Wall in February 2014. This project aims to produce a transformative data-driven approach to map the criticality to weather-induced natural hazards as a fundamental step in both improved extreme event management and climate change adaptation prioritisation. Key to this is an expert-led metric for network criticality which can be used to identify the most critical locations on the network. This will allow NR to determine where adaptation work will have optimal benefit, whilst also aiding the allocation of resources and operational decisions during extreme events, reducing disruption-related costs and improving service to customers. The project has the following objectives:1. Define the key determinants of criticality from Network Rail's perspective.2. Formulate a criticality metric based on the determinants identified in objective 1.3. Demonstrate the metric on a Network Rail route and identify network-critical sections of track.4. Elicit views on implications for adaptation actions and extreme event management.The results are designed to be applicable to the entirety of NR's network and would inform decisions made on the 20,000 miles of track and 2,500 stations that NR owns and operates. To be cost-effective, the utilisation of the metric will need to enable a reduction in network disruption of around 0.1-0.2%, achieved through smarter allocation of resources/adaptation actions to those areas where the consequences of weather-related incidents in terms of network disruption is greatest. We believe that by integrating the results of this project into the existing NR systems described above, the company will be able to target conservatively a reduction of 3-5% of weather-related disruption, which would yield annual savings of £1.5-£2.5 million. These direct savings to NR would be multiplied further by the full economic savings to UK PLC, contributing to improved national productivity, and would also have impact on non-monetised benefits to society through more resilient mobility. Keywords: extreme weather; climate change; rail transport; disruption; resilience; business continuity