1,720,969 research outputs found
On the Probabilistic Modeling of Runway Inter-departure Times
No full textThis paperr examines the validity of the Erlang distribution for runway service times. It uses high-fidelity surface surveillance data, for the first time, to model the probability distributions of runway service times and departure throughput, and to validate the Erlang service time assumption. The paper proposes several potential approaches to determine departure runway service time distributions from empirical data, and compares the results. In particular, it finds that a displaced exponential fit may be a better match to the empirical service time distribution than an Erlang distribution. However, the computational benefits offered by the Erlang service time distribution, its accurate reflection of the means and variances of the empirical service time and throughput distributions, and its ability to represent the tail of the service time distribution, make it attractive for use in queuing models of airport operations.National Science Foundation (U.S.) (Cyber-Physical Systems Award 0931843
A Queuing Model of the Airport Departure Process
No full textThis paper presents an analytical model of the aircraft departure process at an airport. The modeling procedure includes the estimation of unimpeded taxi-out time distributions and the development of a queuing model of the departure runway system based on the transient analysis of D/E/1 queuing systems. The parameters of the runway service process are estimated using operational data. Using the aircraft pushback schedule as input, the model predicts the expected runway schedule and takeoff times. It also estimates the expected taxi-out time, queuing delay, and its variance for each flight in addition to the congestion level of the airport, sizes of the departure runway queues, and the departure throughput. The proposed approach is illustrated using a case study based on Newark Liberty International Airport. The model is trained using data from 2011 and is subsequently used to predict taxi-out times in 2007 and 2010. The predictions are compared with actual data to demonstrate the predictive capabilities of the model.National Science Foundation (U.S.) (Award 0931843
Queuing Models of Airport Departure Processes for Emissions Reduction
Get PDFAircraft taxiing on the surface contribute significantly to the fuel burn and emissions at
airports. This paper investigates the possibility of reducing fuel burn and emissions from
surface operations through a reduction of the taxi times of departing aircraft. A novel
approach is proposed that models the aircraft departure process as a queuing system,
and attempts to reduce taxi times and emissions through improved queue management
strategies.
The departure taxi (taxi-out) time of an aircraft is represented as a sum of three components, namely, the unimpeded taxi-out time, the time spent in the departure queue,
and the congestion delay due to ramp and taxiway interactions. The dependence of the
taxi-out time on these factors is analyzed and modeled. The performance of the model is
validated through a comparison of its predictions with observed data at Boston’s Logan
International Airport (BOS). The reductions in taxi-out times from the proposed queue
management strategy are translated to reductions in fuel burn and emissions using ICAO
engine models for the taxi phase of the flight profile.United States. Federal Aviation Administration (PARTNER Center of Excellence)United States. National Aeronautics and Space Administration (Airspace Systems Program – Airportal Program
Dynamic Control of Airport Departures: Algorithm Development and Field Evaluation
No full textSurface congestion leads to significant increases in taxi times and fuel burn at major airports. In this paper, we formulate the airport surface congestion management problem as a dynamic control problem. We address two main challenges: the random delay between actuation (at the gate) and the server being controlled (the runway), and the need to develop control strategies that can be implemented in practice by human air traffic controllers. The second requirement necessitates a strategy that periodically updates the rate that departures pushback from their gates. We model the runway system as a semi-Markov process using surface surveillance data. We use this modeling framework to derive optimal pushback policies to control congestion. Finally, we present the results of the real-world implementation and field testing of this control protocol at Boston Logan International Airport.United States. Federal Aviation Administration (United States. Air Force Contract FA8721-05-C-0002
A comparison of aircraft trajectory-based and aggregate queue-based control of airport taxi processes
No full textThere is significant potential to decrease fuel burn, emissions, and delays of aircraft at airports by optimizing surface operations. A simple surface traffic optimization approach is to hold aircraft back at the gates based on aggregate information on surface queues. Depending on the level of surface surveillance and onboard equipage, it may also be possible to use a more complex approach, namely, to simultaneously optimize the surface trajectories of all taxiing aircraft. Using data from the Detroit Metropolitan Wayne County airport (DTW), this paper compares the benefits of the two approaches, and finds that at a relatively uncongested airport such as DTW, the aggregate queue-based approach only yields modest improvements in taxi-out time, while the trajectory-based approach yields a nearly 23% decrease in average taxi-out time (achieving the average unimpeded taxi-out time)
Impact of Heavy Aircraft Operations on Airport Capacity at Newark Liberty International Airport
Get PDFAviation System Performance Metrics (ASPM) departure and arrival rate data is collected for four common airport confi gurations at Newark Liberty International Airport (EWR) under Visual Meteorological Conditions (VMC) for the period 2007-2008. The effect of the number of Heavy (including Boeing 757) operations on overall airport throughput is then investigated. The investigation shows that Heavy departures and arrivals negatively impact overall airport capacity. Mechanisms by which controllers mitigate the e ffects of Heavy arrivals and departures are also identifi ed. A preliminary quanti fication of the impact of operations of Heavy aircraft is performed with a parametric estimation of the capacity of the airport. The findings of this empirical study highlight that Heavy aircraft departures introduce a very small effi ciency loss in terms of airport departure capacity. By contrast, under some runway con figurations, Heavy aircraft arrivals have a more detrimental e ffect on airport departure capacity
Demonstration of reduced airport congestion through pushback rate control
No full textAirport surface congestion results in significant increases in taxi times, fuel burn and emissions at major airports. This paper describes the field tests of a congestion control strategy at Boston Logan International Airport. The approach determines a suggested rate to meter pushbacks from the gate, in order to prevent the airport surface from entering congested states and to reduce the time that flights spend with engines on while taxiing to the runway. The field trials demonstrated that significant benefits were achievable through such a strategy: during eight four-hour tests conducted during August and September 2010, fuel use was reduced by an estimated 12,250–14,500 kg (4000–4700 US gallons), while aircraft gate pushback times were increased by an average of only 4.4 min for the 247 flights that were held at the gate
Impact of Arrivals on Departure Taxi Operations at Airports
Get PDFAircraft taxi operations are a major source of fuel burn and emissions on the ground. Given rising fuel prices and growing concerns about the contributions of aviation to air pollution and greenhouse gas emissions, recent research aims to develop strategies to reduce fuel burn at airports. In order to develop such strategies, an understanding of taxi operations and the factors that affect taxi-out times is required. This paper describes an analysis of taxi-out times at two major U.S. airports in order to identify the primary causal factors affecting the duration of taxi-out operations. Through an analysis of departures out of John F. Kennedy International Airport and Boston Logan International Airport, several variables affecting taxi-out times were identified, including primarily the number of arrivals and number of departures during the taxi-out operation of an aircraft. Previous literature suggests that the number of arrivals on the surface has limited influence on taxi-out times; however, this analysis demonstrates that the number of arrivals is in fact significantly correlated with taxi-out times. Furthermore, we find that arrivals have a greater impact on taxi-out times under runway configurations where there is increased interaction between arrivals and departures
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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