Flight Delay Time Research Articles

Reliable and robust scheduling of airport operation resources by simulation optimization feedback and conflict resolution

Reliable and robust airport flight ground service resources collaborative scheduling has emerged as an issue of major concern at congested airports, which has great significance on airport service quality and operation efficiency. Due to the uncertainty of the service process of multiple vehicles in airport ground operations, the combination of simulation and optimization (sim-opt) techniques has been proven to be an effective means to solve the collaborative scheduling problem. However, existing models still have limitations on the reliability of feasible solutions and the robustness of evaluations. In this work, we developed a conflict resolution based sim-opt framework that combines the search capability of mathematical optimization models with the ability of simulation models to describe uncertainty. The dynamic window is introduced to divide the flight zone into multiple sub-intervals, which allows for iterative search and evaluation of the optimal schedule solution while reducing model calculation time. Additionally, a matching algorithm based on slack and tight constraints is proposed to optimize the possible resource requirements of each vehicle, thereby improving the initial schedule solution’s search depth and reliability. Furthermore, a conflict resolution feedback mechanism between adjacent windows is constructed to optimize the scheduling plan, reducing misjudgment and omission of the optimal solution and enhancing the sim-opt framework’s robustness. Finally, experiments on real airport datasets of three different scales demonstrate that our proposed method efficiently allocates resources with a smaller flight delay time as well as reducing total vehicle cost time during the flight ground service process.

Additional flight delays and magnetospheric–ionospheric disturbances during solar storms

Although the sun is really far away from us, some solar activities could still influence the performance and reliability of space-borne and ground-based technological systems on Earth. Those time-varying conditions in space caused by the sun are also called solar storm or space weather. It is known that aviation activities can be affected during solar storms, but the exact effects of space weather on aviation are still unclear. Especially how the flight delays, the top topic concerned by most people, will be affected by space weather has never been thoroughly researched. By analyzing huge amount of flight data (~ 4 × 106 records), for the first time, we quantitatively investigate the flight delays during space weather events. It is found that compared to the quiet periods, the average arrival delay time and 30-min delay rate during space weather events are significantly increased by 81.34% and 21.45% respectively. The evident negative correlation between the yearly flight regularity rate and the yearly mean total sunspot number during 22 years also confirms such correlation. Further studies show that the flight delay time and delay rate will monotonically increase with the geomagnetic field fluctuations and ionospheric disturbances. These results indicate that the interferences in communication and navigation during space weather events may be the most probable reason accounting for the increased flight delays. The above analyses expand the traditional field of space weather research and could also provide us with brand new views for improving the flight delay predications.

Measurement of temperature dependent shear modulus using frequency dependent SAWs ToF delay in laser-induced temperature gradient

Phase velocity of surface acoustic waves(SAWs) is frequency dependent when propagate on medium with inhomogeneous elasticity over depth. In this work, frequency dependent Time-of-Flight (ToF) variation of SAWs induced by a local and dynamic heating was applied for measurement of temperature dependent shear modulus. Laser-generated broad-band SAWs propagated through the material with elastic properties and density modified by dynamic inhomogeneous temperature field induced by a millisecond laser heating. Sample with spatial dependent material properties introduces phase velocity dispersion in the SAW propagation. As consequence, ToF of SAW becomes frequency dependent. Frequency dependent ToF variation curves at two time instants respected to laser heating were measured by time–frequency analysis together with a differential technique. Free fitted parameters, temperature dependent shear modulus and surface temperature distribution were evaluated by solving the inverse problem by fitting the experimental ToF variation curves into the theoretical ones by means of the differential evolution method. The inversed temperature dependent parameter of shear modulus of Ti–6Al–4V alloy was in good agreement with literature value.

Locally generalised multi-agent reinforcement learning for demand and capacity balancing with customised neural networks

Reinforcement Learning (RL) techniques are being studied to solve the Demand and Capacity Balancing (DCB) problems to fully exploit their computational performance. A locally generalised Multi-Agent Reinforcement Learning (MARL) for real-world DCB problems is proposed. The proposed method can deploy trained agents directly to unseen scenarios in a specific Air Traffic Flow Management (ATFM) region to quickly obtain a satisfactory solution. In this method, agents of all flights in a scenario form a multi-agent decision-making system based on partial observation. The trained agent with the customised neural network can be deployed directly on the corresponding flight, allowing it to solve the DCB problem jointly. A cooperation coefficient is introduced in the reward function, which is used to adjust the agent’s cooperation preference in a multi-agent system, thereby controlling the distribution of flight delay time allocation. A multi-iteration mechanism is designed for the DCB decision-making framework to deal with problems arising from non-stationarity in MARL and to ensure that all hotspots are eliminated. Experiments based on large-scale high-complexity real-world scenarios are conducted to verify the effectiveness and efficiency of the method. From a statistical point of view, it is proven that the proposed method is generalised within the scope of the flights and sectors of interest, and its optimisation performance outperforms the standard computer-assisted slot allocation and state-of-the-art RL-based DCB methods. The sensitivity analysis preliminarily reveals the effect of the cooperation coefficient on delay time allocation.

Absolute ν Mass Measurement with the DUNE Experiment.

Time of flight delay in the supernova neutrino signal offers a unique tool to set model-independent constraints on the absolute neutrino mass. The presence of a sharp time structure during a first emission phase, the so-called neutronization burst in the electron neutrino flavor time distribution, makes this channel a very powerful one. Large liquid argon underground detectors will provide precision measurements of the time dependence of the electron neutrino fluxes. We derive here a new ν mass sensitivity attainable at the future DUNE far detector from a future supernova collapse in our galactic neighborhood, finding a sub-eV reach under favorable scenarios. These values are competitive with those expected for laboratory direct neutrino mass searches.

Effects of humidity and temperature on the non-linear elasticity of rocks

SUMMARY Small velocity changes, associated with the non-linear response of rocks within the Earth, have been measured from dense arrays of seismometers to observe crustal deformation, the influence of solar heating and in situ pore pressure changes. Characterization of the non-linear elastic response of rocks provides new insight into rock microstructure and possibly new ways to determine the presence and type of fluid in the pore space. We conducted a long-term experiment to understand the influence of humidity and temperature on the non-linear elastic properties (NEPs) of rocks. The relative velocity change (dv/v), a NEP, is computed from the time of flight delay caused by the presence of a superposed high amplitude ultrasonic signal in a sandstone sample within a controlled environmental chamber. Our phenomenological model for diffusion of humidity into the pore space fits the dv/v data exceptionally well, showing the dv/v is a linear function of humidity. We subtract the dv/v predicted by the humidity diffusion model from the measured dv/v to get a residual dv/v. This residual dv/v can be well fit by a temperature diffusion model in which the dv/v is a linear function of temperature. We suggest that dv/v is a sensitive indicator of moisture in pore spaces of rock and the temperature of the rock.

An Improved Genetic Algorithm-Based Traffic Scheduling Model for Airport Terminal Areas

This paper takes the airport terminal area as the main research content and combines genetic algorithm with airport terminal area analysis theory to analyze and study the traffic scheduling in the airport terminal area. Based on the study of traditional traffic scheduling techniques and key techniques of genetic algorithms, this paper participates in the actual project of genetic algorithm-based traffic scheduling, analyzes the requirements of the project, focuses on the design and implementation of the traffic scheduling algorithm module in the genetic algorithm-based traffic scheduling system, and conducts further research on the pathfinding by constraints submodule. In this paper, the flight approach and departure sequencing problem and runway allocation problem are the main research objects. The dynamic optimal scheduling model of flight approach and departure is established by considering the interests and demands of airlines and airports, and a new scheduling algorithm is proposed. In this paper, a brief introduction to the airport terminal area is given, and the feasibility of the approach/departure optimal scheduling is introduced from the perspective of airlines with a long-range parallel two-runway airport as the research background. Secondly, through the analysis of the flight approach and departure process and the study of the approach and departure cooperative optimization strategy, a single-runway flight approach and departure traffic scheduling model under the joint sequencing strategy is established with the optimization objective of minimizing the total flight delay time, and the model is solved by using the sliding time window algorithm. Then, based on the single-runway scheduling model, a multirunway multiobjective flight optimal scheduling model is established with the objectives of minimizing total delay time, increasing runway throughput per unit time and fairness of flight delay time allocation, and a dynamic algorithm (STW-GA) combining sliding time window algorithm and dual-structured chromosome genetic algorithm is proposed to solve the model.

Airport and route classification by modelling flight delay propagation

Flight delay can be divided into the root and propagated delays for identification and analysis of airports/routes that have a great influence on actual flight delay using flight operations raw data (tower logs) for South Korean domestic flights. In addition, the presented concept of “generated delay” classifies airports as affecting other airport delays or affected by other airport delays. The generated delay refers to the delay time at a particular airport/route, and this delay thereafter actually propagates to other airports/routes. In this study, the generated and propagated delays were displayed on a two-dimensional graph, and the airports/routes were grouped according to delay characteristics. Group A represented airports with high generated and propagated delays, and group B represented airports that are highly affected by delays of preceding airports/routes. Group C represents airports where newly formed delays affect other airport delays, but these airports mitigate delays from other airports. Airports in group D have relatively low delays and propagation. Thus, we targeted airports belonging to groups A and C because of their delay propagation impact on other routes/airports, which must be reduced by decreasing the root delay from targeted routes/airports. Among the airports, Jeju international airport (CJU) had the highest average delay time and propagated flight delay time with similar averaged generated delay times. Among the routes, departure flights from various airports to CJU had significant propagation effects on the subsequent flights. CJU and related routes have a very large impact on domestic flight delays because South Korean domestic airline routes are concentrated on CJU. However, there has been no quantitative analysis, and it is meaningful that the quantitative analysis results were presented in this study. In addition, we suggest that other airports such as GMP (Gimpo), CJJ (Cheongju), WJU (Wonju), and KUV (Gunsan) have a significant impact on domestic flight delays.

Characteristic Analysis of Flight Delayed Time Series

Abstract In order to analyze the characteristics of airport flight delayed time series, based on the construction of flight delay time series, firstly, the K-means algorithm is used to cluster the time series of delayed departures. Secondly, combining with R/S analysis method of Fractal theory, Hurst index of the series is calculated, and Fractal characteristics of the series are analyzed. Then, the VAR (Vector Auto Regression) model is constructed, and Impulse Response Function (IRF) and Variance Decomposition are conducted to explore the impact of the fluctuation of flight delay time series on the future delay. The results show that K-means algorithm divides the time series into five categories, and each category has significant characteristics. Hurst index values of different time series are in the interval of (0.5, 1), indicating that the time series have good fractal characteristics. Through the IRF and Variance Decomposition of VAR model, results show that the time series are significantly affected by random pulses, and the prediction changes of the series come from multiple time series fluctuations. The prediction results show that the flight delay time series is predictable.

SGDAN-A Spatio-Temporal Graph Dual-Attention Neural Network for Quantified Flight Delay Prediction.

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.

Flight Recovery Method of Regional Multiairport Based on Risk Control Model

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.

Research on the Problem of Sorting Parallel Runway Aircraft in Terminal Area Based on Genetic Algorithm

Serious air traffic congestion often occurs in busy airports and terminal areas, which seriously interferes with the normal operation of flights, resulting in a large number of flight delays, causing huge economic losses to airlines, and also the affecting the safe operation of flights in the terminal area. This study takes the two-runway airport as the research object, establishes the parallel runway arrival flight sequencing model and designs the double-encoded genetic algorithm, uses a pair of chromosomes to determine the runway allocation and landing sequence number of the arriving flight, and arranges the flight landing sequence and the runway. The simulation experiments were carried out on 10 flights that were about to land at a certain time in the airport, the experimental results show that the algorithm achieves flight sorting and runway allocation optimization, compared with the current FCFS (First Come First Served) algorithm, it can effectively reduce flight delay time and improve the utilization efficiency of the airport terminal area.

Multiple objective solution approaches for aircraft rerouting under the disruption of multi-aircraft

This paper considers a multi-objective aircraft recovery problem for airline disruption. An integer programming formulation is first established based on connection network with three conflicting objectives, where the first objective minimizes the total deviation from original flight schedules, the second objective minimizes the maximal flight delay time, and the third objective minimizes the number of aircraft actually attended in swapping. Optimal analysis is provided for a small scale aircraft recovery problem with the last two objectives and then one polynomial time algorithm for aircraft recovery problem after the disruption to multi-aircraft in a fleet at an airport. One heuristic combined ε-constraints method and neighborhood search algorithm is designed for large scale disruption recovery problem. The results obtained from computational experiment illustrate effectiveness and efficiency of the heuristic. The outcome of this research could provide theoretical and practical supports for airlines to reduce flight delays.

Understanding the Trade-Off Between Maximum Passenger Throughput and Airline Equity in Allocating Capacity Under Severe Weather Conditions

When the capacity at an airport is reduced because of weather conditions, a ground delay program (GDP) is implemented to resolve the discrepancy between demand for arrival slots and the available arrival slots on a given day. GDPs currently ration the available arrival slots via the proportion of arrivals that exist in the schedule by airline (this practice is termed ration by schedule) with an emphasis on equity among the airlines. Existing rationing schemes do not explicitly consider the number of passengers delayed. This study examined the passenger impacts of a focus on seat throughput in reduced capacity conditions for a GDP at a single airport with consideration for airline equity. An optimization model was developed by using the number of seats available in an aircraft as a proxy for number of passengers and an equity term to estimate airline equity implications. A comparison of the current GDP rationing scheme with one focused on seat delay showed that with no change in the total flight delay time periods, passenger throughput could be improved with a threshold placed on equity. The trade-off between airline equity and passenger throughput and the implications of these results are discussed.

Lorentz invariance violation and generalized uncertainty principle

There are several theoretical indications that the quantum gravity approaches may have predictions for a minimal measurable length, and a maximal observable momentum and throughout a generalization for Heisenberg uncertainty principle. The generalized uncertainty principle (GUP) is based on a momentum-dependent modification in the standard dispersion relation which is conjectured to violate the principle of Lorentz invariance. From the resulting Hamiltonian, the velocity and time of flight of relativistic distant particles at Planck energy can be derived. A first comparison is made with recent observations for Hubble parameter in redshift-dependence in early-type galaxies. We find that LIV has two types of contributions to the time of flight delay $\Delta t$ comparable with that observations. Although the wrong OPERA measurement on faster-than-light muon neutrino anomaly, $\Delta t$, and the relative change in the speed of muon neutrino $\Delta v$ in dependence on redshift $z$ turn to be wrong, we utilize its main features to estimate $\Delta v$. Accordingly, the results could not be interpreted as LIV. A third comparison is made with the ultra high-energy cosmic rays (UHECR). It is found that an essential ingredient of the approach combining string theory, loop quantum gravity, black hole physics and doubly spacial relativity and the one assuming a perturbative departure from exact Lorentz invariance. Fixing the sensitivity factor and its energy dependence are essential inputs for a reliable confronting of our calculations to UHECR. The sensitivity factor is related to the special time of flight delay and the time structure of the signal. Furthermore, the upper and lower bounds to the parameter, $\alpha$ that characterizes the generalized uncertainly principle, have to be fixed in related physical systems such as the gamma rays bursts.

KASS 비행시험 및 검사 시 고려사항 분석

Method establishment needs for recent shortening the flight path, fuel reduction, reduction of the flight delay time, increase of the route capacity like as relieve congested airspace and solving future demand. However, As the existing conventional navigation systems is impossible to be resolved. Hereupon, SBAS has been developed with using the GNSS. ICAO has recommended that SBAS need to be operated with aircraft operation from 2025, korea is also developing KASS in accordance with the recommendation. In this paper, before the 2022 KASS will be completed, KASS can be expected using for flight test and inspection as analyzing KASS flight test and relative specifications.

Improved Air Traffic Management through fuzzy approach on Conflict Detection and Resolution using Smart Antenna

Air traffic management is responsible for smooth air traffic. Although it is done by lot of computations with human interactions, the system will be at its best if there are reduced computations and less flight delay time. This system deals with an introduction of fuzzy rules at the point where they are conflict detection. So with the set of rules implying on the detection, resolution can be made on the basis of fuzzy rules. Ensuring the separation and other criteria in lieu with other aircrafts, the resolution is computed. The computations are reduced either by spatial separation or temporal separation. In the present system there is hardly any conflict detection or decision support. The conflict detection computes and derives with the resolution which reaches the ATC (Air traffic control). This paper describes how fuzzy ideas are used with the conflict detection and how the decision support is made with reduced calculations and improved air traffic flow with a reduced delay Index Terms: ATC, conflict detection, Optimization, AOC, Sensors, Smart Antenna

Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.

Real‐time air traffic flow management: Expectations and probabilities of delay

AbstractAir traffic flow management is carried out with a view to maintaining smooth aircraft traffic. Real‐time air traffic flow control is to carry out the air traffic flow control responsive to a real situation in real time by express use of the present situation of the desired terminal region and the radar information.With a view to such real‐time air traffic flow management, this paper derives equations for the holding delay time expectation value of aircraft requesting take‐off, the delay time expectation value within the terminal, holding generating probability, delay generating probability in the terminal, and the flight delay generating probability. If in the future any departure‐regulating procedure for reducing the flight delay time of the aircraft requesting take‐off is developed based on the values found from these equations, it becomes possible to carry out the air traffic flow management adaptively to a real situation.

Dark matter

I review the evidence for the “missing mass” and discusses several of the proposed candidates: baryons, neutrinos, axions and WIMPs. Baryonic dark matter, the simplest hypothesis, is not consistent with a flat universe and standard big bang light element nucleosynthesis. The non-detection of time of flight delay in the arrival time of the neutrinos from SN1987a rules out the electron neutrino as a galactic dark matter candidate. Observations of dwarf galaxy may rule out any neutrino species as a viable dark matter candidate. Baryonic dark matter, black holes, axions and WIMPs may be detected or ruled out by current and future experiments.