发表机构
Laboratoire Génie Industriel, CentraleSupélec, Université Paris-Saclay; Resallience by Sixense Engineering; Chair on Risk and Resilience of Complex Systems, Laboratoire Génie Industriel, CentraleSupélec, Université Paris-Saclay（巴黎萨克雷大学中央理工-高等电力学院工业工程实验室; Sixense Engineering Resallience; 巴黎萨克雷大学中央理工-高等电力学院工业工程实验室复杂系统风险与韧性讲席）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种结构化暴露建模框架，结合布尔系统与灾害模型，量化法国公路桥梁对极端温度的暴露，发现未来情景下暴露增加且空间不均，以支持基础设施适应气候变化。
AI 中文摘要
为稳定气候条件设计的物理基础设施支撑着人类日常生活的很大一部分。然而，气候变化重塑了极端气候强度的分布。因此，可能面临超过其设计阈值的极端事件的物理基础设施面临损坏风险，需要适应。适应的初步步骤是识别暴露于气候灾害的基础设施。本文旨在通过提供一种总体方法论来构建气候变化灾害的暴露建模。本文实例化了一个使用布尔暴露模型的框架，以评估物理系统可能如何暴露于气候灾害。该框架结合了用于基础设施的布尔系统模型和由极值统计信息驱动的布尔灾害模型。一个说明性案例研究量化了法国行政单位内公路桥梁对极端温度的暴露。结果表明，在未来气候情景和时间段内，暴露增加，且存在空间非均匀性。该框架支持多层次分析，并整合了非平稳气候极端事件，提供了一种结构化的暴露模型，以促进物理系统对气候变化的适应。
英文摘要
Physical infrastructures designed for stable climate conditions support a significant portion of daily human life activities. However, climate change reshapes the distributions of extreme climate intensities. As a result, physical infrastructures that may face extreme events exceeding their design thresholds risk damage and require adaptation. A preliminary step to adaptation is to identify exposed infrastructures to climate hazards. This paper aims to structure the exposure modeling to climate change hazards by providing an overall methodology. This paper instantiates a framework using the Boolean Exposure Model to assess how physical systems may be exposed to climate hazards. The framework combines a Boolean System Model for infrastructures and a Boolean Hazard Model informed by extreme value statistics. An illustrative case study quantifies the exposure of road bridges in French administrative units to extreme temperatures. Results indicate increasing exposure across future climate scenarios and time periods, with spatial non-uniformity. This framework supports multi-level analysis and integrates non-stationary climate extremes, providing a structured exposure model to facilitate the adaptation of physical systems to climate change.
