Restoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole. Since cities are comprised of many dependent lifeline systems, the pattern of the restoration of each lifeline system can have an impact on one or more others. Due to the often uncertain and complex interactions between dense lifeline systems and their individual operations at the urban scale, it is typically unclear how different patterns of restoration will impact the overall recovery of lifeline system functioning. A difficulty in addressing this problem is the siloed nature of the knowledge and operations of different types of lifelines. Here, a city-wide, multi-lifeline restoration model and simulation are provided to address this issue. The approach uses the Graph Model for Operational Resilience, a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time. A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake. The model comprises municipal water and wastewater, power distribution, and transport systems. The model includes 1725 entities from within these sectors, connected through 6456 dependency relationships. Simulation of the model shows that water distribution and wastewater treatment systems recover more quickly and with less uncertainty than electric power and road networks. Understanding this uncertainty will provide the opportunity to improve data collection, modeling, and collaboration with stakeholders in the future.

恢复受大灾影响的城市社区的生命线服务对于整个城市的恢复至关重要。由于城市由许多依赖的生命线系统组成，因此每种生命线系统的恢复模式可能会对一个或多个其他生命周期产生影响。由于密集的生命线系统及其在城市范围内的个体运营之间常常存在不确定和复杂的相互作用，因此通常不清楚不同的恢复方式将如何影响生命线系统功能的总体恢复。解决此问题的困难是不同类型生命线的知识和操作的孤立性。在这里，提供了一个全市范围的多生命线恢复模型和仿真来解决这个问题。该方法将图模型用于运营弹性，一个数据驱动的离散事件模拟器，可以模拟危害影响的空间和功能级联以及随着时间的推移恢复的模式。构建了北温哥华区的新型案例研究模型，并针对7.3级参考地震进行了模拟。该模型包括市政给水和废水，配电和运输系统。该模型包括来自这些部门的1725个实体，它们通过6456个依赖关系进行连接。该模型的仿真表明，与电力和道路网络相比，供水和废水处理系统的恢复速度更快，不确定性也更小。了解这种不确定性将为将来改善数据收集，建模和与利益相关者的协作提供机会。