TY - JOUR
T1 - Operational Reliability of the Airport System
T2 - 13th Conference on Transport Engineering, CIT 2018
AU - Rodríguez-Sanz, Álvaro
AU - Fernández, Beatriz Rubio
AU - Comendador, Fernando Gómez
AU - Valdés, Rosa Arnaldo
AU - Cordero García, José Manuel
AU - Bagamanova, Margarita
N1 - Publisher Copyright:
© 2018 The Authors. Published by Elsevier Ltd.
PY - 2018
Y1 - 2018
N2 - Airports are intermodal nodes that can act as disruption drivers throughout the entire transport system. To ensure the robustness of the transport network, airport managers and policy makers need means to assess operational reliability and delve into its precursors. This paper develops a model to evaluate potential malfunctions of an airport, through the definition of proactive performance indicators. The model is based on the Multi-State Systems (MSS) reliability theory, as a natural extension of classical binary-state evaluation: airports present different performance levels and several failure modes with various effects on the entire system performance (degradation). The operational reliability assessment is achieved with random processes (Markov) methods. The analysis is focused on the airspace-airside integrated infrastructure, using a dynamic spatial boundary associated with the Extended Terminal Maneuvering Area (E-TMA) concept. The study evaluates the ‘visit’ of an aircraft to the E-TMA, which consists of three separate sections: (a) final approach; (b) turnaround process; and (c) initial climb segment. The reliability model represents a framework to test different ‘what-if’ scenarios and to reduce uncertainty by categorizing different behavior patterns. Therefore, it allows us to predict how probable is for the system to enter a degraded state. The methodology is validated through a case study at Madrid Airport (LEMD): a collection of nearly 34,000 aircraft turnarounds is used to statistically determine the system operational characteristics. The main contribution of this paper is to provide a mechanism to monitor and forecast the system’s state, as a way to proactively assess the operational reliability of airports.
AB - Airports are intermodal nodes that can act as disruption drivers throughout the entire transport system. To ensure the robustness of the transport network, airport managers and policy makers need means to assess operational reliability and delve into its precursors. This paper develops a model to evaluate potential malfunctions of an airport, through the definition of proactive performance indicators. The model is based on the Multi-State Systems (MSS) reliability theory, as a natural extension of classical binary-state evaluation: airports present different performance levels and several failure modes with various effects on the entire system performance (degradation). The operational reliability assessment is achieved with random processes (Markov) methods. The analysis is focused on the airspace-airside integrated infrastructure, using a dynamic spatial boundary associated with the Extended Terminal Maneuvering Area (E-TMA) concept. The study evaluates the ‘visit’ of an aircraft to the E-TMA, which consists of three separate sections: (a) final approach; (b) turnaround process; and (c) initial climb segment. The reliability model represents a framework to test different ‘what-if’ scenarios and to reduce uncertainty by categorizing different behavior patterns. Therefore, it allows us to predict how probable is for the system to enter a degraded state. The methodology is validated through a case study at Madrid Airport (LEMD): a collection of nearly 34,000 aircraft turnarounds is used to statistically determine the system operational characteristics. The main contribution of this paper is to provide a mechanism to monitor and forecast the system’s state, as a way to proactively assess the operational reliability of airports.
KW - Airport operations
KW - Markov processes
KW - Multi-state systems
KW - Performance assessment
KW - Reliability analysis
UR - http://www.scopus.com/inward/record.url?scp=85100741844&partnerID=8YFLogxK
U2 - 10.1016/j.trpro.2018.11.002
DO - 10.1016/j.trpro.2018.11.002
M3 - Article
AN - SCOPUS:85100741844
VL - 33
SP - 363
EP - 370
JO - Transportation Research Procedia
JF - Transportation Research Procedia
SN - 2352-1465
Y2 - 6 June 2018 through 8 June 2018
ER -