Nothing Special   »   [go: up one dir, main page]

Mirmohammadsadeghi et al., 2019 - Google Patents

Enhancements to the runway capacity simulation model using the asde-x data for estimating airports throughput under various wake separation systems

Mirmohammadsadeghi et al., 2019

View PDF
Document ID
16551882306488169363
Author
Mirmohammadsadeghi N
Hu J
Trani A
Publication year
Publication venue
AIAA Aviation 2019 Forum

External Links

Snippet

II. Introduction irport capacity continues to be an important topic in the development of the next generation aviation system (NextGen). FAA predicts an annual 1.9% increase in commercial and general aviation operations in the next 20 years [1], additional passenger …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G5/00Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003Flight plan management
    • G08G5/0039Modification of a flight plan

Similar Documents

Publication Publication Date Title
Sun et al. Modeling aircraft performance parameters with open ADS-B data
Mirmohammadsadeghi et al. Enhancements to the runway capacity simulation model using the asde-x data for estimating airports throughput under various wake separation systems
Gallego et al. Analysis of air traffic control operational impact on aircraft vertical profiles supported by machine learning
DeLaura et al. Modeling convective weather avoidance in enroute airspace
Wang et al. Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion
Kolos-Lakatos The influence of runway occupancy time and wake vortex separation requirements on runway throughput
Holzäpfel et al. Assessment of wake-vortex encounter probabilities for crosswind departure scenarios
Murça et al. A data-driven probabilistic trajectory model for predicting and simulating terminal airspace operations
Sun et al. Modeling and inferring aircraft takeoff mass from runway ADS-B data
Tee et al. Modelling and simulation studies of the runway capacity of Changi Airport
Meijers et al. A data-driven approach to understanding runway occupancy time
Chou et al. A machine learning application for predicting and alerting missed approaches for airport management
Salgueiro et al. Aircraft Takeoff and Landing Weight Estimation from Surveillance Data
Mirmohammadsadeghi et al. Prediction of runway occupancy time and runway exit distance with feedforward neural networks
Hu et al. Runway occupancy time constraint and runway throughput estimation under reduced arrival wake separation rules
Mirmohammadsadeghi Improvements to airport systems capacity and efficiency using computer models and tools
Schumann et al. Aircraft wake-vortex encounter analysis for upper levels
Kawagoe et al. Analyzing stochastic features in airport surface traffic flow using cellular automaton: Tokyo international airport
Ongkowijoyo et al. Optimizing the utilization of third runway in Soekarno Hatta International Airport using time space analysis
Thipphavong Reducing aircraft climb trajectory prediction errors with top-of-climb data
Kos et al. Probabilistic wake vortex induced accident risk assessment
Mirmohammadsadeghi et al. Enhancements to the runway exit design interactive model using a hybrid simulation approach for estimating runway occupancy times at airports
Jarry et al. Toward novel environmental impact assessment for ANSPs using machine learning
Khadilkar Analysis and modeling of airport surface operations
Herrema et al. Typical additional spacing-buffer to apply at 4DME for delivering separation minima