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Identification and Characterization for Disruptions in the U.S. National Airspace System (NAS)

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arxiv 2502.18687 v1 pith:DEIAH3SX submitted 2025-02-25 eess.SY cs.SY

Identification and Characterization for Disruptions in the U.S. National Airspace System (NAS)

classification eess.SY cs.SY
keywords disruptionsdayssystemclusterresultstrafficairspaceanomaly
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Disruptions in the National Airspace System (NAS) lead to significant losses to air traffic system participants and raise public concerns. We apply two methods, cluster analysis and anomaly detection models, to identify operational disruptions with geographical patterns in the NAS since 2010. We identify four types and twelve categories of days of operations, distinguished according to air traffic system operational performance and geographical patterns of disruptions. Two clusters--NAS Disruption and East Super Disruption, accounting for 0.8% and 1.2% of the days respectively, represent the most disrupted days of operations in U.S. air traffic system. Another 16.5% of days feature less severe but still significant disruptions focused on certain regions of the NAS, while on the remaining 81.5% of days the NAS operates relatively smoothly. Anomaly detection results show good agreement with cluster results and further distinguish days in the same cluster by severity of disruptions. Results show an increasing trend in frequency of disruptions especially post-COVID. Additionally, disruptions happen most frequently in the summer and winter.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Augmenting airline networks using airside-to-airside buses to strengthen system resilience under disruptions

    math.OC 2026-06 unverdicted novelty 5.0

    Replacing 10 regional air routes with airside buses under a $10M budget reduces simulated passenger delays by 8% on disrupted days and 6% on nominal days.