Toolkit to improve resilience of critical ports and dependent national supply chain systems against extreme sea level rise (storm surge) events

提高关键港口和相关国家供应链系统抵御极端海平面上升（风暴潮）事件的能力的工具包

• 批准号: NE/N01295X/1
• 负责人: Taku Fujiyama
• 金额: $ 18.89万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FN01295X%2F1
• 关键词: Toolkit; improve; resilience; critical; ports

As a first stage in the analysis of storm surge risks to UK port infrastructure and supply chain operation, this project aims to improve the resilience of the port of Immingham and its critical biomass/coal transport link to power stations. The project includes the following three activities: WF1: To refine and operationalize an innovative artificial neural network (ANN) extreme sea-level prediction model (NE/M008150/1) for application at Immingham (with potential application for other UK ports, especially within estuaries). WF2: To translate predicted surge height and duration to risks to infrastructure (equipment, facilities) and operations (i.e. impacts on biomass/coal flows) through stakeholder engagement. WF3: Incorporate railway infrastructure and freight train movements to UCL's MARS model (used in NE/M008150/1) to predict the cascading impacts on the power sector.

作为分析风暴激增风险对英国港口基础设施和供应链运营的第一阶段，该项目旨在提高Immingham港口及其关键的生物质/煤炭运输与电站的弹性。该项目包括以下三个活动：WF1：用于完善和运营创新的人工神经网络（ANN）极端海平面预测模型（NE/M008150/1），以在Immingham应用河口）。 WF2：通过利益相关者的参与，将预测的电涌高度和持续时间转化为基础设施（设备，设施）和操作（即对生物质/煤炭流的影响）的风险。 WF3：将铁路基础设施和货运列车运输纳入UCL的火星模型（用于NE/M008150/1中），以预测对电力部门的级联影响。

项目成果

Combining machine learning with computational hydrodynamics for prediction of tidal surge inundation at estuarine ports

• DOI: 10.1016/j.piutam.2017.09.005
• 发表时间: 2017-01-01
• 期刊: IUTAM SYMPOSIUM ON STORM SURGE MODELLING AND FORECASTING
• 作者: French, Jon;Mawdsley, Robert;Achuthan, Kamal
• 通讯作者: Achuthan, Kamal