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An Adaptive Resilience Approach for a High Capacity Railway

Mario Di Nardo(1*), Mariano Clericuzio(2), Teresa Murino(3), Marianna Madonna(4)

(1) Department of Chemical, Materials and Production Engineering, University of Naples Federico II, Italy
(2) Department of Chemical, Materials and Production Engineering, University of Naples Federico II, Italy
(3) Department of Chemical, Materials and Production Engineering, University of Naples Federico II, Italy
(4) University of Naples Federico II, Italy
(*) Corresponding author


DOI: https://doi.org/10.15866/irece.v11i3.19025

Abstract


Any event can be analyzed as a system, which is a set of parts performing a specific function. Systems that do not have simple interconnections are called complex. A qualitative and quantitative systems behaviour analysis is lead in the literature review.  The issue of resilience needs particular attention and is defined as the ability of a system to resist, adapt, recover from unpredictable events. The concept of resilience is evaluated in a railway network, generally more sensitive to disruption than the road ones. The study focuses on a high capacity railway section in the presence of a breakdown. The goal is to have a general reliability evaluation of an automatic logic reconfiguration, from its implementation to its operating phases. The added value of this formalization methodology consists of using fundamental knowledge of both the system's functioning and malfunctioning. The controller verifies an operational failure of the first processing device and while a failure controller initiates line execution. In order to quantify the system recovery, a simulation-based model is proposed through the case study. The Resilience Indicator (RI) is evaluated on the whole railway line. This study analyzes, in terms of reliability, the impact of several decisions on the maintenance of the system. Finally, the results are compared with an acceptability threshold through the evaluation of the recovery function proposed.
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Keywords


Complex System; Resilience; Failure; Railway; Automatic Reconfiguration

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