Resilience metrics for lifelines
Service performance over time during and after disruption is described by robustness, rapidity of recovery and lost service, so that interventions can be compared on the same curve.
GCRI · 关键基础设施
Reliability and resilience engineering is the method this platform stewards for the network. It designs infrastructure to withstand, absorb and recover from failure through redundancy, diversity, protection and planned restoration, and it measures how well 系统 perform when stressed.
Reliability and resilience engineering studies how 系统 fail, how failures can be prevented and how systems absorb, adapt and recover from disruption. It addresses both technical components and the organisations that operate them. In 关键基础设施 and cities and built environment, resilience engineering identifies critical components and recovery bottlenecks across connected systems. It informs redundancy, spares and restoration priorities. The canonical description is on STEM Commons.
Service performance over time during and after disruption is described by robustness, rapidity of recovery and lost service, so that interventions can be compared on the same curve.
Component failure rates and network structure are combined to estimate service availability, and the components that dominate unavailability are identified.
Crews, spares and access are modelled to estimate restoration curves, and options to shorten them are compared.
西欧的夜间灯光、人口密度和洪水水体,来自 NASA GIBS。每个图层均标有各自日期。
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页面的基础设施暴露
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最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放;悬停可查看指针下的数值;重置可返回该区域。
基础设施风险暴露,以西欧为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by reliability and resilience engineering on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Outage and failure records | Failure rates | 观测 |
| Asset registers | Network composition | 已发布统计 |
| Restoration records from past events | Recovery curves | 观测 |
| Hazard scenarios | Stress inputs | 模型生成 |
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Critical infrastructure · Resilience engineering · Run R-6113
nodes: assets · edges: dependencies
| N3 | 1343 | 44 | Critical |
| N4 | 6363 | 14 | 正常 |
| N5 | 7309 | 6 | 正常 |
| N6 | 2249 | 36 | 正常 |
Reliability predictions are compared with field failure data. Exercises and post-event reviews check whether recovery performed as planned.
| 核查 | 如何开展 |
|---|---|
| Back-casting events | Models reproduce outage and restoration patterns of past events |
| Common-cause review | Redundant elements are checked for shared failure causes |
| Operator review | Assumptions about crews and spares are confirmed with operators |
Common-cause failures and rare events are hard to estimate from limited data. Human and organisational factors resist quantification.
A 危害足迹 会摧毁每一层中位置相同的资产;碎片化、层间依赖和幸存部分的过载随后使失效蔓延。3D 视图按深度将各层分开。这是使用明示示例数值的教学模型,不是预测。本页地图显示的是西欧;模型本身并不局限于某一地点。
控制措施
读数
| 步骤 | 交通运行(%) | 电力运行(%) | 电信运行(%) |
|---|---|---|---|
| 0 | 89 | 89 | 89 |
| 1 | 44 | 56 | 72 |
| 2 | 39 | 39 | 39 |
| 3 | 28 | 39 | 33 |
| 4 | 17 | 39 | 33 |
| 5 | 17 | 39 | 11 |
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
贯穿六大支柱,由 Nexus Consortium 牵头
Assembled from the Nexus Standards area profile 关键基础设施与关键实体: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
系统与耦合
控制措施
NS-0 章程与原则NS-3 风险记录 UNI(语法、旧编码对照、分配机构)NS-9 情境 UNI(部署、实例、计划实例)NS-10 政策和条款(机器可读的义务:定义、约束、评估和执行)NS-11 验证与监测(证据、证明、零信任符合性观测)NRS-H61 危害族:级联失效(NHS-1 sys.cascade)NRS-H94 危害族:系统性网络事件(NHS-1 cyber.systemic-cyber)NRS-H107 危害族:数字基础设施集中与单一化(NHS-1 tech.digital-concentration)NRS-K31 领域包概况:国家网络韧性(DOMAIN-031)NRS-K36 领域包概况:关键基础设施(DOMAIN-036)NRS-K48 领域包概况:金融系统韧性(DOMAIN-048)观测
示例地理范围
关键基础设施 stewards reliability and resilience engineering for the Consortium and reviews how it is applied across platforms.
模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。
The couplings between the systems in resilience engineering for infrastructure: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
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