Stress Testing and Climate Adaptation: Using Simulation to Assess the Resilience of Transport Systems and Evaluate Potential Improvements
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2025
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Doctoral Thesis
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Abstract
Transport systems play a vital role in ensuring societal well-being and economic stability, yet they are susceptible to disruptions caused by natural hazards. Such disruptions can severely impact the services they provide and lead to significant economic and socio-economic consequences. For climate-induced hazards, such as extreme rainfall, the accelerating pace of climate change is expected to increase both their frequency and intensity in many locations, placing additional stress on these systems. To address these challenges, infrastructure managers must not only assess the resilience of their systems but also implement interventions that enhance their capacity to withstand and recover from such events.
Given the frequency and severity of the adverse effects of climatic hazard events and the increasing complexity of infrastructure systems, advanced methods are needed to accurately assess resilience and plan resilience enhancing interventions. Quantitative simulation-based methods have emerged as effective tools for capturing such complexities and their associated uncertainties, offering a more comprehensive assessment than previously possible, thereby providing an improved basis for decision-making.
The primary objective of this doctoral research was to advance the state-of-the-art in the use of simulation-based methodologies for assessing the resilience of transport systems and evaluating possible resilience enhancing interventions. The research developed methods that not only contributed to scientific knowledge but are also applicable in real-world scenarios. In particular, the developed methods improve the understanding of how various parts of transport systems, including the physical infrastructure, its environment, and the responsible organization, interact and evolve over time under scenarios of stress and improvement. This enables infrastructure managers to better understand and identify system vulnerabilities, evaluate the dynamic impacts of interventions, and plan to improve the resilience of their systems.
The first major contribution of this research is the development of a simulation-based methodology for defining, setting up, and evaluating resilience-enhancing interventions. This methodology addresses key requirements of an effective simulation-based decision-support tool. The first requirement is capturing the diversity of intervention types, including those that can be done on the physical infrastructure, e.g., retrofitting vulnerable assets, those on the environment, e.g., building a flood protection wall, and those related to the organization, e.g., hiring more crews to expedite restoration. Other requirements include incorporating the spatial and temporal characteristics of interventions, modeling the interactions between interventions when combined into portfolios, and accounting for the uncertainties that affect their performance. By addressing these aspects, the methodology provides infrastructure managers with a more comprehensive understanding of how different interventions or combinations thereof can enhance system resilience.
The second contribution focuses on the assessment of system resilience through stress testing. Stress tests represent hypothetical scenarios designed to help determine if a transport system can continue to provide an acceptable level of service when subjected to one or more potentially disruptive events. The proposed stress testing methodology systematically defines, sets up, and executes various types of stress tests across different parts of the system. This includes not only hazard-based stress tests but also those that examine the performance of assets, user behavior, and organizational aspects, such as recovery management. By introducing a comprehensive stress testing method, this research offers a more nuanced analysis of vulnerabilities in transport systems that can inform the planning of resilience-enhancing interventions.
One significant challenge in resilience assessment is the vast number of potential stress tests that can be conducted. To address this, the third major contribution of this dissertation presents a novel computation-free methodology that assesses resilience under each stress test without the need for simulations. A stress test ranking measure was then introduced, indicating the potential impact of each stress test on resilience. This enables transport infrastructure managers to rank and prioritize stress tests accordingly and select a subset of them for more detailed assessment. By doing so, it ensures efficient use of computational resources while concentrating on scenarios with the highest potential to result in lowest resilience levels.
All proposed methodologies were demonstrated through real-world applications, with case studies involving a transportation system of roads and bridges in Switzerland exposed to extreme rainfall scenarios resulting in flooding, and landslides. The case studies illustrated the practical utility of the developed methods by assessing the resilience of the investigated transport system, together with modeling and evaluating multiple interventions and intervention portfolios. Several stress tests were defined and executed, and the proposed prioritization methodology was applied to rank candidate stress tests for further investigation.
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03859 - Adey, Bryan T. / Adey, Bryan T.
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG