Resilience framework for seaport infrastructure under extreme wind
A. Balbi (University of Genova)
Omar Kammouh (TU Delft - System Engineering)
G. P. Cimellaro (Politecnico di Torino)
M. P. Repetto (University of Genova)
More Info
expand_more
Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.
Abstract
The efficient transportation of goods is vital for the economic growth of communities, making developing and maintaining seaport infrastructure an essential component of the marine transportation system. Given their geographic locations, ports are consistently at risk from natural hazards, making the resilience of port infrastructure an essential goal. Despite considerable progress in resilience research, there remains a gap in methods tailored explicitly to assessing port resilience, particularly under extreme wind events. Current approaches often do not capture the full complexity of port systems, as they tend to focus on isolated aspects, such as structural resilience. This paper introduces the PORT Resilience Framework, addressing these gaps by evaluating resilience through a comprehensive list of indicators gathered from various legitimate sources. The indicators are then organized under four comprehensive resilience dimensions: Physical Infrastructure, ICT (i.e., Information and Communication Technology) and Equipment; Organization and Business Management; Resources and Economic Development; and Territory, Environment, and Stakeholders. This classification is summarized under the acronym "PORT." This paper also introduces a method for aggregating resilience indicators by considering their performance before and after a specific hazard, transforming the data into a quantifiable Loss of Resilience index. The approach is applied to a case study, assessing the resilience of a real Terminal against wind action using real data sourced from the port management. The case study analysis revealed that human resources and quay operations were the most critical factors affecting recovery, with insufficient staffing leading to prolonged recovery periods. The study further demonstrated that post-disruption activity surges, captured by different serviceability function methodologies, often created operational bottlenecks, challenging the port's overall recovery.
help_outline