Relevant bibliographies by topics / Flight Delay

Academic literature on the topic 'Flight Delay'

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Published: 4 June 2021
Last updated: 27 April 2022

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Journal articles on the topic "Flight Delay"

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Zheng, Zhe, Wenbin Wei, and Minghua Hu. "A Comparative Analysis of Delay Propagation on Departure and Arrival Flights for a Chinese Case Study." Aerospace 8, no. 8 (August 4, 2021): 212. http://dx.doi.org/10.3390/aerospace8080212.

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In recent years, flight delay costs the air transportation industry millions of dollars and has become a systematic problem. Understanding the behavior of flight delay is thus critical. This paper focuses on how flight delay is affected by operation-, time-, and weather-related factors. Different econometric models are developed to analyze departure and arrival delay. The results show that compared to departure delay, arrival delay is more likely to be affected by previous delays and the buffer effect. Block buffer presents a reduction effect seven times greater than turnaround buffer in terms of flight delays. Departure flights suffer more delays from convective weather than arrival flights. Convective weather at the destination airport for flight delay has a greater impact than at the original airport. In addition, sensitivity analysis of flight delays from an aircraft utilization perspective is conducted. We find that the effect of delay propagation on flight delay differs by aircraft utilization. This impact on departure delay is greater than the impact on arrival delay. In general, specific to the order of flights, the previous delay increases the impact on flight on-time performance as a flight flies a later leg. Buffer time has opposite effects on departure and arrival delay, with the order increasing. A decrease in buffer time with the order increasing, however, still has a greater reduction effect on departure delay than arrival delay. Specific to the number of flights operated by an aircraft, the more flights an aircraft flies in a day, the more the on-time performance of those flights will suffer from the previous delay and buffer time generally.
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Cao, Yakun, Chenping Zhu, Yanjun Wang, and Qingyun Li. "A Method of Reducing Flight Delay by Exploring Internal Mechanism of Flight Delays." Journal of Advanced Transportation 2019 (December 30, 2019): 1–8. http://dx.doi.org/10.1155/2019/7069380.

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This paper explores the internal mechanism of flight departure delay for the Delta Air Lines (IATA-Code: DL) from the viewpoint of statistical law. We roughly divide all of delay factors into two sorts: propagation factor (PF), and nonpropagation factors (NPF). From the statistical results, we find that the distribution of the flight departure delay caused by only NPF exhibits obvious power law (PL) feature, which can be explained by queuing model, while the original distribution of flight departure delay follows the shift power law (SPL). The mechanism of SPL distribution of flight departure delay is considered as the results of the aircraft queue for take-off due to the airports congestion and the propagation delay caused by late-arriving aircraft. Based on the above mechanism, we develop a specific measure for formulating flight planning from the perspective of mathematical statistics, which is easy to implement and reduces flight delays without increasing operational costs. We analyze the punctuality performance for 10 of the busiest and the highest delay ratio airports from 155 airports where DL took off and landed in the second half of 2017. Then, the scheduled turnaround time for all flights and the average scheduled turnaround time for all aircraft operated by DL has been counted. At last, the effectiveness and practicability of our method is verified by the flights operation data of the first half of 2018.
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Jacquillat, Alexandre. "Predictive and Prescriptive Analytics Toward Passenger-Centric Ground Delay Programs." Transportation Science 56, no. 2 (March 2022): 265–98. http://dx.doi.org/10.1287/trsc.2021.1081.

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Ground delay programs (GDPs) comprise the main interventions to optimize flight operations in congested air traffic networks. The core GDP objective is to minimize flight delays, but this may not result in optimal outcomes for passengers—especially with connecting itineraries. This paper proposes a novel passenger-centric optimization approach to GDPs by balancing flight and passenger delays in large-scale networks. For tractability, we decompose the problem using a rolling procedure, enabling the model’s implementation in manageable runtimes. Computational results based on real-world data suggest that our modeling and computational framework can reduce passenger delays significantly at small increases in flight delay costs through two main mechanisms: (i) delay allocation (delaying versus prioritizing flights) and (ii) delay introduction (holding flights to avoid passenger misconnections). In practice, however, passenger itineraries are unknown to air traffic managers; accordingly, we propose statistical learning models to predict passenger itineraries and optimize GDP operations accordingly. Results show that the proposed passenger-centric approach is highly robust to imperfect knowledge of passenger itineraries and can provide significant benefits even in the current decentralized environment based on collaborative decision making.
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Guo, Ziyu, Guangxu Mei, Shijun Liu, Li Pan, Lei Bian, Hongwu Tang, and Diansheng Wang. "SGDAN—A Spatio-Temporal Graph Dual-Attention Neural Network for Quantified Flight Delay Prediction." Sensors 20, no. 22 (November 11, 2020): 6433. http://dx.doi.org/10.3390/s20226433.

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There has been a lot of research on flight delays. But it is more useful and difficult to estimate the departure delay time especially three hours before the scheduled time of departure, from which passengers can reasonably plan their travel time and the airline and airport staff can schedule flights more reasonably. In this paper, we develop a Spatio-temporal Graph Dual-Attention Neural Network (SGDAN) to learn the departure delay time for each flight with real-time conditions at three hours before the scheduled time of departure. Specifically, it first models the air traffic network as graph sequences, what is, using a heterogeneous graph to model a flight and its adjacent flights with the same departure or arrival airport in a special time interval, and using a sequence to model the flight and its previous flights that share the same aircraft. The main contributions of this paper are using heterogeneous graph-level attention to learn the influence between the flight and its adjacent flight together with sequence-level attention to learn the influence between the flight and its previous flight in the flight sequence. With aggregating features from the learned influence from both graph-level and sequence-level attention, SGDAN can generate node embedding to estimate the departure delay time. Experiments on a real-world large-scale data set show that SGDAN produces better results than state-of-the-art models in the accurate flight delay time estimation task.
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Sherry, Lance. "A model for estimating airline passenger trip reliability metrics from system-wide flight simulations." Journal of Transport Literature 7, no. 2 (April 2013): 319–37. http://dx.doi.org/10.1590/s2238-10312013000200017.

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Analysis of the benefits of government modernization initiatives for airports or air traffic control are conducted using complex software models that simulate up to 60,000 flights per day. These flight-centric simulations do not model passenger flows and therefore do not account for passenger trip delays due to cancelled flights and missed connections, which account for up to 60% of the total passenger trip delays. This paper describes a closed-form model for estimating passenger trip reliability metrics from flight delay data from system-wide simulations. The outputs of the model, (i) percent passengers disrupted, (ii) average passenger trip delay, and (iii) total passenger trip delays, are derived from the probability of delayed flights and network structure parameters. The model highlights the role of network structure, in addition to flight on-time performance, on passenger trip reliability. These results have implications for government and industry initiatives to improve flight on-time performance through modernization, consumer protection, and the conduct of benefits analysis.
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Zheng, Zhe, Wenbin Wei, Bo Zou, and Minghua Hu. "How Late Does Your Flight Depart? A Quantile Regression Approach for a Chinese Case Study." Sustainability 12, no. 24 (December 17, 2020): 10553. http://dx.doi.org/10.3390/su122410553.

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Flight departure delays cost airlines and airports millions of dollars and become a systematic problem. The on-time performance at an airport is connected to and easily affected by delay propagation from previous operations of flights using the airport. In this paper, we employ both Ordinary Least Square (OLS) and quantile regressions to investigate the impact of various influencing factors on flight departure delay. By using historical flight records and weather information, the impacts of delay propagation-related and other factors are quantified to study the correlations between the explanatory and response variables. Three variables, including previous arrival delay, turnaround buffer time, and the first order of a day, are used to examine the propagation effects. We find that aircraft type, flying on a weekday, and being the first flight of a day have significant impacts on short departure delays. Ground buffer is conducive to mitigating delay propagation. For long delays, however, ground buffer cannot work in an efficient way, and the previous arrival effect is more important. Convective weather and aircraft type are the crucial factors in this situation. Interestingly, flying on a weekday suddenly becomes one of the main components under extreme delays. Meanwhile, propagated delay and airport congestion remain significantly impactful on the on-time performance.
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Atallah, Stephanie, and Susan Hotle. "Evaluation of Airport Size and Delay Causal Factor Effects on Delay Propagation Dissipation." Transportation Research Record: Journal of the Transportation Research Board 2676, no. 3 (November 17, 2021): 608–20. http://dx.doi.org/10.1177/03611981211055663.

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The International Civil Aviation Organization identifies departure and arrival punctuality as on-time key performance indicators. However, these metrics assume a flight’s delay is a result of either the origin or destination airport, providing limited information on where delay should be mitigated in the U.S. National Airspace System (NAS). This study evaluates the relationship between delay propagation magnitude, delay causal factor, airport size, and charged facility (airport or Air Route Traffic Control Center), to examine if certain delays take longer to dissipate. First, using flights from July 2018, results show that most delay propagation chains originate at large-hub airports. However, these delays were the quickest to recover. Second, this study presents a regression model, predicting total propagated delay using fixed effects based on the weather region where the original delay occurred. Each additional flight affected by downstream delay adds 18.7 min on average to total arrival delay in a propagation chain. Additionally, if weather was the original causal factor, total propagated delay increased by 11.6 min compared with non-weather delays. Lastly, this study compares delay propagation in July 2018 and July 2020. Results show uneven impacts of the coronavirus disease 2019 (COVID-19) across the large-hub airports. Some of the investigated airports did not witness large improvements in average delay per delayed flight, warranting further research in the future. While delay and delay propagation have not been completely eradicated in the NAS during the COVID-19 pandemic, findings suggest that both have significantly declined on average.
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Shao, Quan, Mengxue Shao, Yunpeng Bin, Pei Zhu, and Yan Zhou. "Flight Recovery Method of Regional Multiairport Based on Risk Control Model." Mathematical Problems in Engineering 2020 (April 29, 2020): 1–18. http://dx.doi.org/10.1155/2020/7105381.

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In the regional multiairport system, the contradiction between the limited operating resources and the large flight flow is serious, and the flight delays can easily lead to the occurrence of unsafe events. This paper investigates the abnormal flight recovery method in regional multiairport system based on risk control. The focus is to reschedule arrival-departure flights in real time with minimized delay time and risk probability. In this study, the risk about terminal area control and scene operation was considered in the analysis of the risk control model (RCM), which includes six key risk points: airspace control, flight conflict, ground service, apron support, ground control, and taxiing conflict. The mathematical model on flight recovery was constructed to solve minimized delay time and risk probability with MSINS (multistart algorithm with intelligent neighborhood selection). The data of a typical regional multiairport system in China were selected for experimental verification in order to compare the RCM with the traditional recovery model (TRM). The experimental results show that first, there are some hidden dangers in the traditional recovery methods of flight delay. Flight conflict and apron support are the risk points that need to be controlled most in the multiairport system. Secondly, for the effective solution with the shortest delay time, the RCM can reduce the overall operation risk of the system, but the flight delay time is a little longer. For the effective solution with the lowest risk probability, RCM can reduce the risk of system operation and the delay time of flights at the same time. Therefore, RCM can improve the security level of the system during abnormal flight recovery and ensure or even improve the recovery efficiency.
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Zhou, Hang, and Xinxin Jiang. "Research on Arrival/Departure Scheduling of Flights on Multirunways Based on Genetic Algorithm." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/851202.

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Aiming at the phenomenon of a large number of flight delays in the terminal area makes a reasonable scheduling for the approach and departure flights, which will minimize flight delay losses and improve runway utilization. This paper considered factors such as operating conditions and safety interval of multi runways; the maximum throughput and minimum flight delay losses as well as robustness were taken as objective functions; the model of optimization scheduling of approach and departure flights was established. Finally, the genetic algorithm was introduced to solve the model. The results showed that, in the program whose advance is not counted as a loss, its runway throughput is improved by 18.4%, the delay losses are reduced by 85.8%, and the robustness is increased by 20% compared with the results of FCFS (first come first served) algorithm, while, compared with the program whose advance is counted as a loss, the runway throughput is improved by 15.16%, flight delay losses are decreased by 75.64%, and the robustness is also increased by 20%. The algorithm can improve the efficiency and reduce delay losses effectively and reduce the workload of controllers, thereby improving economic results.
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Dermadi, Yedi, Shinta Devi Lukitasari, and Annisaa Nurhayati. "Weather Analysis of Flight Delay at Husein Sastranegara Airport." ITEJ (Information Technology Engineering Journals) 4, no. 2 (December 31, 2019): 89–98. http://dx.doi.org/10.24235/itej.v4i2.31.

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Flight is an activity that is very vulnerable to weather conditions. The accuracy of weather information strongly supports flight activities. The effects of bad weather on flights include flight delays and flight cancellations. Based on data on flight delays from the Directorate General of Air Transportation of the Ministry of Transportation from January to March 2019 at Husein Sastranegara Airport, it is known that 20-30% of flight delays are caused by weather constraints. To estimate flight delays based on weather forecasts, weather data analysis is carried out to determine the type of weather that is endangering flights and causing flight delays. The analysis was carried out using the K-NN and Random Forest algorithms
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Dissertations / Theses on the topic "Flight Delay"

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Yuan, Duojia, and S3024047@student rmit edu au. "Flight Delay-Cost Simulation Analysis and Airline Schedule Optimization." RMIT University. Aerospace, Mechanical, Manufacturing Engineering, 2007. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20080618.092923.

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In order to meet the fast-growing demand, airlines have applied much more compact air-fleet operation schedules which directly lead to airport congestion. One result is the flight delay, which appears more frequently and seriously; the flight delay can also significantly damage airline's profitability and reputation The aim of this project is to enhance the dispatch reliability of Australian X Airline's fleet through a newly developed approach to reliability modeling, which employs computer-aided numerical simulation of the departure delay distribution and related cost to achieve the flight schedule optimization. The reliability modeling approach developed in this project is based on the probability distributions and Monte Carlo Simulation (MCS) techniques. Initial (type I) delay and propagated (type II) delay are adopted as the criterion for data classification and analysis. The randomicity of type I delay occurrence and the internal relationship between type II delay and changed flight schedule are considered as the core factors in this new approach of reliability modeling, which compared to the conventional assessment methodologies, is proved to be more accurate on the departure delay and cost evaluation modeling. The Flight Delay and Cost Simulation Program (FDCSP) has been developed (Visual Basic 6.0) to perform the complicated numerical calculations through significant amount of pseudo-samples. FDCSP is also designed to provide convenience for varied applications in dispatch reliability modeling. The end-users can be airlines, airports and aviation authorities, etc. As a result, through this project, a 16.87% reduction in departure delay is estimated to be achieved by Australian X Airline. The air-fleet dispatch reliability has been enhanced to a higher level - 78.94% compared to initial 65.25%. Thus, 13.35% of system cost can be saved. At last, this project also achieves to set a more practical guideline for air-fleet database and management upon overall dispatch reliability optimization.
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Bai, Yuqiong. "ANALYSIS OF AIRCRAFT ARRIVAL DELAY AND AIRPORT ON-TIME PERFORMANCE." Master's thesis, University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2573.

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In this research, statistical models of airport delay and single flight arrival delay were developed. The models use the Airline On-Time Performance Data from the Federal Aviation Administration (FAA) and the Surface Airways Weather Data from the National Climatic Data Center (NCDC). Multivariate regression, ANOVA, neural networks and logistic regression were used to detect the pattern of airport delay, aircraft arrival delay and schedule performance. These models are then integrated in the form of a system for aircraft delay analysis and airport delay assessment. The assessment of an airport¡¯s schedule performance is discussed. The results of the research show that the daily average arrival delay at Orlando International Airport (MCO) is highly related to the departure delay at other airports. The daily average arrival delay can also be used to evaluate the delay performance at MCO. The daily average arrival delay at MCO is found to show seasonal and weekly patterns, which is related to the schedule performance. The precipitation and wind speed are also found contributors to the arrival delay. The capacity of the airport is not found to be significant. This may indicate that the capacity constraint is not an important problem at MCO. This research also investigated the delays at the flight level, including the flights with delay ¡Ý0 minute and the flights with delay ¡Ý15min, which provide the delay pattern of single arrival flights. The characteristics of single flight and their effect on flight delay are considered. The precipitation, flight distance, season, weekday, arrival time and the time spacing between two successive arriving flights are found to contribute to the arrival delay. We measure the time interval of two consecutive flights spacing and analyze its effect on the flight delay and find that for a positively delayed flight, as the time space increases, the probability of the flights being delayed will decrease. While it was possible to calculate the immediate impact of originating delays, it is not possible to calculate their impact on the cumulative delay. If a late departing aircraft has no empty space in its down line schedule, it will continue to be late. If that aircraft enters a connecting airport, it can pass its lateness on to another aircraft. In the research we also consider purifying only the arrival delay at MCO, excluding the flights with originating delay >0. The model makes it possible to identify the pattern of the aircraft arrival delay. The weather conditions are found to be the most significant factors that influence the arrival delay due to the destination airport.
M.S.
Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering
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Matsutani, Megumi. "Robust adaptive flight control systems in the presence of time delay." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/79339.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.
This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from department-submitted PDF version of thesis.
Includes bibliographical references (p. 161-165).
Adaptive control technology is a promising candidate to deliver high performance in aircraft systems in the presence of uncertainties. Currently, there is a lack of robustness guarantees against time delay with the difficulty arising from the fact that the underlying problem is nonlinear and time varying. Existing results for this problem have been quite limited, with most results either being local or at best, semi-global. In this thesis, robust adaptive control for a class of plants with global boundedness in the presence of time-delay is established. This class of plants pertains to linear systems whose states are accessible. The global boundedness is accomplished using a standard adaptive control law with a projection algorithm for a range of non-zero delays. The upper bound of such delays, i.e. the delay margin, is explicitly computed. The results of this thesis provide a highly desirable fundamental property of adaptive control, robustness to time-delays, a necessary step towards developing theoretically verifiable flight control systems.
by Megumi Matsutani.
Ph.D.
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Sarmadi, Sepehr 1977. "Minimizing airline passenger delay through integrated flight scheduling and aircraft routing." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/29401.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; and, (S.M.)--Massachusetts Institute of Technology. Operations Research Center, 2004.
Includes bibliographical references (p. 83-86).
Statistics show that airline flight delays and cancellations have increased continuously over the period from 1995 to 2000. During the same period, customer dissatisfaction and complaints have followed a similar, even more dramatic trend. In 2001, as a consequence of the September 1 th terrorist attacks and the resulting airline schedule reductions, delay levels decreased, but only temporarily. With growing passenger demands and stagnant capacity passenger delays and disruptions are again on the rise. Approaches to mitigate schedule disruptions include: 1) re-optimizing the schedule during operations after a disruption occurs. For example, an airline operations controller might decide to cancel or postpone some flight legs or to re-route some aircraft to recover the rest of the schedule; and 2) building robustness into the schedule in the planning stage. By robustness we mean the ability to absorb flight delays so these effects are minimized on passengers and crews. In many cases, trying to reduce delays in the planning stage can be less costly for the airlines, especially if the actions suggested to modify the schedule are not expensive. Pushing back a flight's departure time only ten minutes might cost the airline little but can potentially reduce the number of passenger misconnections given the stochastic nature of airline operations. Canceling a flight during operations for example, can be however very costly. The primary goal of this research is to propose planning models to re-route aircraft and re-time flight departures, either separately or simultaneously, in order to distribute slack time in the network optimally and reduce passenger delays. Using data from a major U.S. airline we observe that with our model, we can reduce flight and passenger delay levels.
by Sepehr Sarmadi.
S.M.
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Nilsson, Andreas. "Analysis of robustness and delay propagation in Scandinavian Airlines swedish flight traffic program." Thesis, KTH, Matematik (Inst.), 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-99174.

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Sun, He S. M. Massachusetts Institute of Technology. "An integrated model of flight and passenger delay for policy analysis in the National Air Transportation System." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104329.

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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2016.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 99).
Demand for air travel has increased over the years and so have airport delays and congestion. Delays have a huge impact on airline costs and influence the satisfaction of passengers, thus becoming an important topic of research in the field of air transportation. In recent literature, a Passenger Delay Calculator (PDC) was proposed to estimate passenger delays. The PDC computes passenger delays for a specified day based on actual flight schedules, fight cancellation information, and ticket booking information. However, since actual fight schedules are a necessary input, the PDC cannot be applied directly to hypothetical scenarios, in which different cancellation strategies are implemented and their impact on passenger delays are evaluated. A different model. Airport Network Delays (AND), has also been developed recently. The AND model estimates fight delays and relies on an input in which demand consists of the national planned fight schedule for any given day. In this thesis, we have attempted to incorporate these two models, the AND and the PDC, within a single framework, so that the resulting new integrated model can compute passenger delays without requiring an actual flight-schedule input. The integrated model would certainly increase the usefulness and applicability of the PDC since it could be used with hypothetical scenarios, different flight cancellation strategies, etc. We first describe the framework of the integrated model for studying flight delays and passenger delays at a daily scale. The integrated model includes four components: a Tail Recovery Model, Flight Cancellation Algorithms, a Refined Airport Network Delay (RAND) model, and the PDC. The Tail Recovery Model recovers missing tail numbers for many flights recorded in the Aviation System Performance Metrics (ASPM) database. The Flight Cancellation Algorithms implement alternative strategies for flight cancellations in the presence of large delays, such as cancelling flights with long flight delays or flights with a large ratio of flight delay divided by the seating capacity of the aircraft. The RAND model is an extension of the AND, in which two implicit assumptions of the AND model have been modified. The RAND model produces better estimates of flight delays in the sense of replicating actual flight delays obtained from the ASPM database. The overall integrated model is able to compute passenger delays and relies only on planned flight schedules rather than actual flight schedules. Moreover, the integrated model facilitates the study of factors that influence flight delays, such as weather conditions and demand fluctuations, and evaluates the impact of different cancellation strategies on passenger delays. Using actual data from different days, we conclude that passenger delays can be reduced on the busiest traffic days through improved flight cancellation strategies. In the second part of the thesis, we extend the RAND model to compute flight delays on a monthly scale using different capacity profiles as input. These capacity profiles can be directly obtained from Federal Aviation Administration (FAA) reports or constructed by using classical machine learning algorithms on airport-level data. We validate our estimation of flight delays by using data of January, 2008, showing that both the capacity profiles and the RAND perform well in terms of replicating the actual monthly flight delays. These results imply that an effort can be made to develop an integrated model incorporating the RAND, the PDC etc. at a monthly scale or even at any generic time scale.
by He Sun.
S.M. in Transportation
S.M.
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Bly, Elizabeth 1981. "Effects of reduced IFR arrival-arrival wake vortex separation minima and improved runaway operations sequencing on flight delay." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/28908.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.
Includes bibliographical references (p. 99-101).
(cont.) 65.6% and 67.0% and the average NAS delay by 24.3% and 24.7% relative to the FIFO and Serve-the-Longest-Queue algorithms respectively.
Two methods to improve runway throughput are evaluated in this thesis. The first, increasing runway capacity during periods of bad weather by reducing IFR arrival-arrival wake vortex separations. The second, increasing runway efficiency in all weather conditions using event sequencing algorithms. Two algorithms were studied: a Serve-the-Longest-Queue algorithm for flight sequencing coupled with a greedy heuristic algorithm for runway assignment and a mixed integer programming optimization algorithm for simultaneous flight sequencing and runway assignment. The MIT Extensible Air Network Simulation (MEANS) was used to simulate NAS op- erations to determine the potential benefits in terms of delay reduction for both methods. For the case where reduced IFR arrival-arrival wake vortex separations was studied, the Airport Runway Capacity Calculator (ARCC), developed in support of this work, was used to determine the increased capacity at eleven congested US airports. Results indicate that the total delay in the National Airspace System (NAS) could have been reduced by 31.8% over the month of January, 1999 (a reduction of 243,672 minutes) representing a benefit of 116 minutes per IFR hour. For the cases where the event sequencing algorithms were studied, the algorithms were only implemented at Newark Airport (EWR) and the resulting delay values were compared to the performance of a FIFO algorithm that is representative of existing operations. The flight delay for the Serve-the-Longest-Queue algorithm and the FIFO algorithm were similar, though relative performance depended on the airline schedule. The integer programming optimization algorithm out performed the other two algorithms significantly reducing the average delay at EWR by
by Elizabeth Bly.
S.M.
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8

Fabbiane, Nicolò. "Transition delay in boundary-layer flows via reactive control." Doctoral thesis, KTH, Stabilitet, Transition, Kontroll, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187173.

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Transition delay in boundary-layer flows is achieved via reactive control of flow instabilities, i.e. Tollmien-Schlichting (TS) waves. Adaptive and model-based control techniques are investigated by means of direct numerical simulations (DNS) and experiments. The action of actuators localised in the wall region is prescribed based on localised measurement of the disturbance field; in particular, plasma actuators and surface hot-wire sensors are considered. Performances and limitations of this control approach are evaluated both for two-dimensional (2D) and three-dimensional (3D) disturbance scenarios. The focus is on the robustness properties of the investigated control techniques; it is highlighted that static model-based control, such as the linear-quadratic- Gaussian (LQG) regulator, is very sensitive to model-inaccuracies. The reason for this behaviour is found in the feed-forward nature of the adopted sensor/actuator scheme; hence, a second, downstream sensor is introduced and actively used to recover robustness via an adaptive filtered-x least-mean-squares (fxLMS) algorithm. Furthermore, the model of the flow required by the control algorithm is reduced to a time delay. This technique, called delayed-x least-mean-squares (dxLMS) algorithm, allows taking a step towards a self-tuning controller; by introducing a third sensor it is possible to compute on-line the suitable time-delay model with no previous knowledge of the controlled system. This self-tuning approach is successfully tested by in-flight experiments on a motor-glider. Lastly, the transition delay capabilities of the investigated control con- figuration are confirmed in a complex disturbance environment. The flow is perturbed with random localised disturbances inside the boundary layer and the laminar-to-turbulence transition is delayed via a multi-input-multi-output (MIMO) version of the fxLMS algorithm. A positive theoretical net-energy- saving is observed for disturbance amplitudes up to 2% of the free-stream velocity at the actuation location, reaching values around 1000 times the input power for the lower disturbance amplitudes that have been investigated.
I den här avhandlingen har reglertekniska metoder tillämpats för att försena omslaget från ett laminärt till ett turbulent gränsskikt genom att dämpa tillväxten av små instabiliteter, så kallade Tollmien-Schlichting vågor. Adaptiva och modellbaserade metoder för reglering av strömning har undersökts med hjälp av numeriska beräkningar av Navier-Stokes ekvationer, vindtunnelexperiment och även genom direkt tillämpning på flygplan. Plasmaaktuatorer och varmtrådsgivare vidhäftade på ytan av plattan eller vingen har använts i experimenten och modellerats i beräkningarna. Prestanda och begränsningar av den valda kontrollstrategin har utvärderats för både tvådimensionella och tredimensionella gränsskiktsinstabiliteter. Fokus har varit på metodernas robusthet, där vi visar att statiska metoder som linjär-kvadratiska regulatorer (LQG) är mycket känsliga för avvikelser från den nominella modellen. Detta beror främst på att regulatorer agerar i förkompenseringsläge (”feed-foward”) på grund av strömningens karaktär och placeringen av givare och aktuatorer. För att minska känsligheten mot avvikelser och därmed öka robustheten har en givare införts nedströms och en adaptiv fXLMS algoritm (filtered-x least-mean-squares) har tillämpats.                  Vidare har modelleringen av fXLMS-algoritmen förenklats genom att ersätta överföringsfunktionen mellan aktuatorer och givare med en lämplig tidsfördröjning.  Denna  metod som kallas för dxLMS (delayed-x least-mean-squares) kräver att ytterligare en givare införs långt uppströms för att kunna uppskatta hastigheten på de propagerande instabilitetsvågorna. Denna teknik har tillämpats framgångsrikt för reglering av gränsskiktet på vingen av ett segelflygplan. Slutligen har de reglertekniska metoderna testas för komplexa slumpmässiga tredimensionella störningar som genererats uppströms lokalt i gränsskiktet. Vi visar att en signifikant försening av laminärt-turbulentomslag äger rum med hjälp av en fXLMS algoritm. En analys av energibudgeten visar att för ideala aktuatorer och givare kan den sparade energiåtgången på grund av minskad väggfriktion vara upp till 1000 gånger större än den energi som använts för reglering.
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9

Mollén, Katarina. "Water Depth Estimation Using Ultrasound Pulses for Handheld Diving Equipment." Thesis, Linköpings universitet, Institutionen för systemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117061.

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This thesis studies the design and implementation of an ultra-sonic water depth sounder. The depth sounder is implemented in a hand-held smart console used by divers. Since the idea of echo sounding is to measure the flight time between transmitting the signal and receiving the echo, the main challenge of this task is to find a time-of-flight (ToF) estimation for a signal in noise. It should be suitable for this specific application and robust when implemented in the device. The thesis contains an investigation of suitable ToF methods. More detailed evaluations of the matched filter, also known as the correlation method, and the linear phase approach are done. Aspects like pulse frequency and duration, speed of sound in water and underwater noise are taken into account. The ToF-methods are evaluated through simulation and experiments. The matched filter approach is found suitable based on these simulations and tests with signals recorded by the console. This verification leads to the implementation of the algorithm on the device. The algorithm is tested in real time, the results are evaluated and improvements suggested.
Denna rapport behandlar skattning av vattendjup med hjälp av ultraljudspulser och implementation av detta. Djupmätaren implementeras i en handhållen dykarkonsoll. Eftersom grundidén i ekolodning är att mäta tiden mellan att pulsen skickas iväg och att ekot tas emot är en stor del av utmaningen att hitta en lämplig metod för att skatta flykttiden för en signal i brus. Metoden ska passa för detta användingsområde och vara robust. Rapporten tar upp tidigare forskning gjord inom flykttidsestimering. De metoder som utvärderas för implementation är det matchade filtret, också kallad korrelationsmetoden, och linjär fas-metoden. Andra aspekter som avvägs och utreds är pulsfrekvens och pulsvaraktighet, ljudets hastighet och brus under vattnet. Metoderna för att skatta flykttid utvärderas genom simuleringar. Det matchade filtret bedöms vara lämpligt baserat på dessa simuleringar och experiment med data inspelad med konsollen. Denna verifikation leder till att algoritmen implementeras på konsollen. Den implementerade algoritmen testas i realtid, resultaten utvärderas och förbättringar föreslås.
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Knotková, Martina. "Ochrana spotřebitele v letecké dopravě." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-7684.

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The thesis is focused on dynamically developing field of the air transportation. It is based on rights and duties of airlines and consumers. It is mapping the most important current law moves of Czech Republic which has been changed and agreed for a consumer protection. It describes consumer rights in the case of a flight delay and cancellation, refusal of entry on the plane and in the case of baggage problems. It also touches the issues of advertised price of plane tickets. It is followed by the analysis of current situation of the observance of consumer rights and their point of view on some controversial topics.
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Books on the topic "Flight Delay"

1

McFarland, Richard E. CGI delay compensation. Moffett Field, Calif: Ames Research Center, 1986.

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Leeuwen, S. Storm van. A simple and low cost system to measure delay times in pneumatic systems. Amsterdam: National Aerospace Laboratory, 1990.

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Grantham, William D. Piloted simulator study of allowable time delay in pitch flight control systems of a transport airplane with negative static stability. Hampton, Va: Langley Research Center, 1987.

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Horowitz, Scott J. Measurement and effects of transport delays in a state-of-the-art F-16C flight simulator. Brooks Air Force Base, Tex: Air Force Systems Command, Air Force Human Resources Laboratory, 1987.

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United States. Congress. Senate. Committee on Commerce, Science, and Transportation. Airline service improvements: Hearing before the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Tenth Congress, first session, April 11, 2007. Washington: U.S. Government Printing Office, 2013.

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Aviation, United States Congress House Committee on Transportation and Infrastructure Subcommittee on. Reasons for, and reporting of, airline flight delays: Hearing before the Subcommittee on Aviation of the Committee on Transportation and Infrastructure, House of Representatives, One Hundred Fourth Congress, first session, July 27, 1995. Washington: U.S. G.P.O., 1996.

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Flight Mechanics Symposium (1997 Goddard Space Flight Center). Flight Mechanics Symposium 1997: Proceedings of a conference sponsored by NASA Goddard Space Flight Center at Goddard Space Flight Center, Greenbelt, Maryland, May 19-21, 1997. Edited by Walls Donna M, Goddard Space Flight Center, and United States. National Aeronautics and Space Administration. Washington, DC: National Aeronautics and Space Administration, 1997.

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New York (State). Legislature. Senate. Standing Committee on Consumer Protection. In the matter of public hearing on airline passengers and long flight delays: What can be done to improve conditions? [Clifton Park, N.Y.]: Candyco Transcription Service, Inc, 2007.

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United States. Congress. House. Committee on Transportation and Infrastructure. Subcommittee on Aviation. H.R. 1407, the Airline Delay Reduction Act: Hearing before the Subcommittee on Aviation of the Committee on Transportation and Infrastructure, House of Representatives, One Hundred Seventh Congress, first session, April 26, 2001. Washington: U.S. G.P.O., 2001.

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National Research Council (U.S.). Transportation Research Board, Airport Cooperative Research Program, and United States. Federal Aviation Administration, eds. Guidebook for airport irregular operations (IROPS) contingency planning. Washington, D.C: Transportation Research Board, 2012.

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Book chapters on the topic "Flight Delay"

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Chen, HaiYan, JianDong Wang, and Hao Yan. "Modeling of Flight Delay State-Space Model." In Advanced Research on Computer Education, Simulation and Modeling, 26–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21783-8_5.

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Rahul, R., S. Kameshwari, and R. Pradip Kumar. "Flight Delay Prediction Using Random Forest Classifier." In Lecture Notes in Electrical Engineering, 67–72. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3690-5_7.

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Chakrabarty, Navoneel, Tuhin Kundu, Sudipta Dandapat, Apurba Sarkar, and Dipak Kumar Kole. "Flight Arrival Delay Prediction Using Gradient Boosting Classifier." In Advances in Intelligent Systems and Computing, 651–59. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1498-8_57.

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Ionescu, Lucian, Claus Gwiggner, and Natalia Kliewer. "Empirical and Mechanistic Models for Flight Delay Risk Distributions." In Operations Research Proceedings, 577–82. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00795-3_86.

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Alla, Hajar, Lahcen Moumoun, and Youssef Balouki. "Flight Arrival Delay Prediction Using Supervised Machine Learning Algorithms." In Advances in Intelligent Systems and Computing, 231–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72588-4_16.

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Dange, Priyanka, and Bhairavi Savant. "Efficient Design of Drone Flight Control Using Delay Tolerant Algorithm." In Lecture Notes in Electrical Engineering, 233–48. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8391-9_17.

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Daldır, Irmak, Nedret Tosun, and Ömür Tosun. "Performance Evaluation of Machine Learning Techniques on Flight Delay Prediction." In Trends in Data Engineering Methods for Intelligent Systems, 165–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79357-9_16.

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Flad, Nina, Frank M. Nieuwenhuizen, Heinrich H. Bülthoff, and Lewis L. Chuang. "System Delay in Flight Simulators Impairs Performance and Increases Physiological Workload." In Engineering Psychology and Cognitive Ergonomics, 3–11. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07515-0_1.

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Chen, Hongwei, Shenghong Tu, and Hui Xu. "The Application of Improved Grasshopper Optimization Algorithm to Flight Delay Prediction–Based on Spark." In Complex, Intelligent and Software Intensive Systems, 80–89. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79725-6_8.

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Liu, Yi, Yefeng Ma, Qing Deng, Yi Liu, and Hui Zhang. "Public Opinion Analysis and Crisis Response in Mass Incidents: A Case Study of a Flight Delay Event in China." In Web-Age Information Management, 77–86. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11538-2_8.

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Conference papers on the topic "Flight Delay"

1

Ionita, Achim, Aristide Halanay, Achim Ionita, and Aristide Halanay. "Delay induced oscillations." In 22nd Atmospheric Flight Mechanics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1997. http://dx.doi.org/10.2514/6.1997-3502.

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Fagin, Chris, and John Ventura. "Flight Delay Prediction Problem." In International Engineering Science Technology Online Conference. CLOUD PUBLICATIONS, 2020. http://dx.doi.org/10.23953/cloud.iestoc.458.

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Novianingsih, Khusnul, and Rieske Hadianti. "Modeling flight departure delay distributions." In 2014 International Conference on Computer, Control, Informatics and Its Applications (IC3INA). IEEE, 2014. http://dx.doi.org/10.1109/ic3ina.2014.7042596.

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Yang, Kun. "Research on Chinese Flight Delay." In 2016 International Conference on Economics, Social Science, Arts, Education and Management Engineering. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/essaeme-16.2016.89.

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JOHNSON, WILLIAM, and MATTHEW MIDDENDORF. "Simulator transport delay measurement using steady-state techniques." In Flight Simualtion Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1988. http://dx.doi.org/10.2514/6.1988-4619.

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MERRIKEN, MICHAEL, WILLIAM JOHNSON, JEFFERY CRESS, and GARY RICCIO. "Time delay compensation using supplementary cues in aircraft simulator systems." In Flight Simualtion Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1988. http://dx.doi.org/10.2514/6.1988-4626.

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SMITH, R. "Reducing transport delay through improvements in real-time program flow." In Flight Simulation Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-4147.

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"Flight delay prediction model for Airlines." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8621998.

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Xu, Yiyang, Luyao Liu, Xichen Gao, and Fanyu Frank Zeng. "Analysis of Factors in Flight Delay." In Proceedings of the 2019 2nd International Conference on Mathematics, Modeling and Simulation Technologies and Applications (MMSTA 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/mmsta-19.2019.36.

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Tao, Jiang, Hua Man, and Li Yanling. "Flight delay prediction based on LightGBM." In 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE, 2021. http://dx.doi.org/10.1109/iccasit53235.2021.9633431.

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Reports on the topic "Flight Delay"

1

Toale, Patrick Alan. A Study of the decay pi0 ---> e+ e- e+ e- using K(L) ---> pi0 pi0 pi0 decays in flight. Office of Scientific and Technical Information (OSTI), January 2004. http://dx.doi.org/10.2172/1419196.

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