Stochastic Air Traffic Flow Management for Demand and Capacity Balancing Under Capacity Uncertainty

This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.

Influential Node Ranking and Invulnerability of Air Traffic Cyber Physical System

To ensure flight safety,the complex network method is used to study the influence and invulnerability of air traffic cyber physical system(CPS)nodes.According to the rules of air traffic management,the logical coupling relationship between routes and sectors is analyzed,an air traffic CPS network model is constructed,and the indicators of node influence and invulnerability are established.The K-shell algorithm is improved to identify node influence,and the invulnerability is analyzed under random and selective attacks.Taking Airspace in Eastern China as an example,its influential nodes are sorted by degree,namely,K-shell,the improved K-shell(IKS)and betweenness centrality.The invulnerability of air traffic CPS under different attacks is analyzed.Results show that IKS can effectively identify the influential nodes in the air traffic CPS network,and IKS and betweenness centrality are the two key indicators that affect the invulnerability of air traffic CPS.

En-route Sector Complexity Control Strategies in Air Traffic Management

Along with the rapid development of air traffic, the contradiction between conventional air traffic management(ATM)and the increasingly complex air traffic situations is more severe,which essentially reduces the operational efficiency of air transport systems. Thus,objectively measuring the air traffic situation complexity becomes a concern in the field of ATM. Most existing studies focus on air traffic complexity assessment,and rarely on the scientific guidance of complex traffic situations. According to the projected time of aircraft arriving at the target sector boundary,we formulated two control strategies to reduce the air traffic complexity. The strategy of entry time optimization was applied to the controllable flights in the adjacent upstream sectors. In contrast,the strategy of flying dynamic speed optimization was applied to the flights in the target sector. During the process of solving complexity control models,we introduced a physical programming method. We transformed the multi-objective optimization problem involving complexity and delay to single-objective optimization problems by designing different preference function. Actual data validated the two complexity control strategies can eliminate the high-complexity situations in reality. The control strategy based on the entry time optimization was more efficient than that based on the speed dynamic optimization. A basic framework for studying air traffic complexity management was preliminarily established. Our findings will help the implementation of a complexity-based ATM.

Empirical Exploration of Air Traffic Control Behaviour at Terminal Maneuvering Area:From an Air Traffic Flow Aspect

In a large-volume,high-density traffic background,air traffic manifests fluid-like microscopical characteristics.The characteristics are formed by the micro tailing actions between individual aircraft.Aircraft headway refers to the time interval between successive flying aircraft in air traffic flow,which is one of the most important characteristics of air traffic flow.The variation in aircraft headway reveals the air traffic control behaviour.In this paper,we study the characteristics of air traffic control behaviours by analyzing radar tracks in a terminal maneuvering area.The headway in arrival traffic flow is measured after the determination of aircraft trailing relationships.The headway evolutionary characteristics for different control decisions and the headway evolutionary characteristics in different phase-states are discussed,and some interesting findings are gotten.This work may be helpful for scholars and managers in understanding the intrinsic nature of air traffic flow and in the development of intelligent assistant decision systems for air traffic management.

Prediction of Departure Aircraft Taxi Time Based on Deep Learning

With the continuous increase in the number of flights,the use of airport collaborative decision-making(ACDM)systems has been more and more widely spread.The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft blockout.The spatial-temporal-environment deep learning(STEDL)model is presented to improve the prediction accuracy of departure aircraft taxi-out time.The model is composed of time-flow sub-model(airport capacity,number of taxiing aircraft,and different time periods),spatial sub-model(taxiing distance)and environmental sub-model(weather,air traffic control,runway configuration,and aircraft category).The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%.The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.

Research on Operation of UAVs in Non-isolated Airspace

In order to explore the safe operation of UAVs in non-segregated airspace,a collision risk model for cylindrical UAVs based on conflict areas was constructed and the risk of conflict between manned and unmanned aerial vehicles was researched.According to the results of risk analysis,a strategy for solving the conflict of aircraft is proposed,and the risk assessment experiment of unmanned aerial vehicle(UAV)in non-isolated airspace conflict is carried out.The results show that under the experimental conditions,large unmanned aerial vehicles equipped with ADS-B,TCAS and other airborne sensing systems will indeed interfere with other aircraft in airspace when they enter non-isolated airspace.Especially when the number of aircraft in airspace is large,the automatic avoidance system of UAV will increase the avoidance time and trigger the safety alarm,but the safety level is still acceptable.This indicates that it is relatively safe for UAVs to enter non-isolated airspace under limited conditions.The results can be used as a reference for the safe operation of unmanned aerial vehicle(UAV)in non-isolated airspace.

Numerical Simulation of Wake Vortices Generated by an A330-200 Aircraft in the Nearfield Phase

In order to overcome the typical limitation of earlier studies,where the simulation of aircraft wake vortices was essentially based on the half-model of symmetrical rectangular wings,in the present analysis the entire aircraft(a typical A330-200 aircraft)geometry is taken into account.Conditions corresponding to the nearfield phase(takeoff and landing)are considered assuming a typical attitude angle of 7°and different crosswind intensities,i.e.,0,2 and 5 m/s.The simulation results show that the aircraft wake vortices form a structurally eudipleural four-vortex system due to the existence of the sweepback angle.The vortex pair at the outer side is induced by the pressure difference between the upper and lower surfaces of the wings.The wingtip vortex is split at the wing by the winglet into two smaller streams of vortices,which are subsequently merged 5 m behind the wingtip.Compared with the movement trend of wake vortices in the absence of crosswind,the aircraft wake vortices move as a whole downstream due to the crosswind to be specific,the 2 m/s crosswind can accelerate the dissipation of wake vortices and is favorable for the reduction of the aircraft wake separation.The 5 m/s crosswind results in significantly increased vorticity of two vortex systems:the wingtip vortex downstream the crosswind and the wing root vortex upstream the crosswind due to the energy input from the crosswind.However,the crosswind at a higher speed can accelerate the deviation of wake vortices,and facilitate the reduction in wake separation of the aircraft taking off and landing on a single-runway airport.

Analysis on Potential Conflict Frequency of Intersected Air Routes in Terminal Airspace Design

In order to obtain accurate conflict risks in terminal airspace design,the concept and calculation model of potential conflict frequency for intersected routes are proposed.Conflict frequency is represented by the product of horizontal conflict frequency and vertical conflict probability.The horizontal conflict frequency is derived from the probability density distribution of conflicts in a period of time.Based on the recorded radar trajectory data,the concept and model of ROUTE distance are proposed,and the probability density function of aircraft height at a specified ROUTE distance is deduced by kernel density estimation.Furthermore,vertical conflict probability and its horizontal distribution are achieved.Examples of three intersected arrival and departure route design schemes are studied.Compared with scheme 1,the conflict frequency values of the other two improved schemes decrease to53% and 24%,respectively.The results show that the model can quantify potential conflict frequency of intersected routes.

Fluctuations in airport arrival and departure traffic:A network analysis

Air traffic is a typical complex system, in which movements of traffic components （pilots, controllers, equipment, and environment）, especially airport arrival and departure traffic, form complicated spatial and temporal dynamics. The fluctuations of airport arrival and departure traffic are studied from the point of view of networks as the special correlation between different airports. Our collected flow volume data on the time-dependent activity of US airport arrival and departure traffic indicate that the coupling between the average flux and the fluctuation of an individual airport obeys a certain scaling law with a wide variety of scaling exponents between 1/2 and 1. These scaling phenomena can explain the interaction between the airport internal dynamics （e.g. queuing at airports, a ground delay program and following flying traffic） and a change in the external （network-wide） traffic demand （e.g. an increase in traffic during peak hours every day）, allowing us to further understand the mechanisms governing the collective behaviour of the transportation system. We separate internal dynamics from external fluctuations using a scaling law which is helpful for us to systematically determine the origin of fluctuations in airport arrival and departure traffic, uncovering the collective dynamics. Hot spot features are observed in airport traffic data as the dynamical inhomogeneity in the fluxes of individual airports. The intrinsic characteristics of airport arrival and departure traffic under severe weather is discussed as well.

Numerical analysis of ice accretion effects at super-cooled large droplet conditions on airfoil aerodynamics

Changes in flow field around NACA23012 airfoil from a clean condition to a super-cooled large droplet （SLD） condition were simulated, and variations in aerodynamic parameters were calculated using FLUENT. In the case of numerical simulation for a clean airfoil, flow field characteristics simulated agreed well with theory analysis, indicating that turbulence models and parameters setting are feasible. Aerodynamic parameters for iced airfoil were calculated using the same method and agreed with those measured test data under the same environment in icing wind tunnels by S. Lee. Conclusion is made that the numerical simulation is valid, and it can be an alternative to study ice accretion effects at the SLD condition on airfoil aerodynamics, leading to reduction in research cycle time and cost.

A Robust Conformer-Based Speech Recognition Model for Mandarin Air Traffic Control

This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition(ASR)technology in the Air Traffic Control(ATC)field.This paper presents a novel cascaded model architecture,namely Conformer-CTC/Attention-T5(CCAT),to build a highly accurate and robust ATC speech recognition model.To tackle the challenges posed by noise and fast speech rate in ATC,the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms.On the decoding side,the Attention mechanism is integrated to facilitate precise alignment between input features and output characters.The Text-To-Text Transfer Transformer(T5)language model is also introduced to handle particular pronunciations and code-mixing issues,providing more accurate and concise textual output for downstream tasks.To enhance the model’s robustness,transfer learning and data augmentation techniques are utilized in the training strategy.The model’s performance is optimized by performing hyperparameter tunings,such as adjusting the number of attention heads,encoder layers,and the weights of the loss function.The experimental results demonstrate the significant contributions of data augmentation,hyperparameter tuning,and error correction models to the overall model performance.On the Our ATC Corpus dataset,the proposed model achieves a Character Error Rate(CER)of 3.44%,representing a 3.64%improvement compared to the baseline model.Moreover,the effectiveness of the proposed model is validated on two publicly available datasets.On the AISHELL-1 dataset,the CCAT model achieves a CER of 3.42%,showcasing a 1.23%improvement over the baseline model.Similarly,on the LibriSpeech dataset,the CCAT model achieves a Word Error Rate(WER)of 5.27%,demonstrating a performance improvement of 7.67%compared to the baseline model.Additionally,this paper proposes an evaluation criterion for assessing the robustness of ATC speech recognition systems.In robustness evaluation experiments based on this criterion,the proposed model demonstrates a performance improvement of 22%compared to the baseline model.

State of rare earth elements in the rare earth deposits of Northwest Guizhou,China

We studied the states of rare earth elements in ore of the Xianglushan rare earth deposit. Rare earth ore samples were tested and examined by scanning electron microscope, electron probe, and chemical leaching. No independent rare earth minerals were detected by scanning electron microscope. Elements detected by the electronic probe for the in situ micro-zone of the sample included: O,Al, Si, Ca, Mg, Fe, Ti, K, Na, S, Cl, C, Cu, Cr, V, and Pt.Rare earth elements were not detected by electron probe.(NH_4)_2 SO_4,(NH_4)Cl, NaCl, and H_2 SO_4 were used as reagents in chemical leaching experiments that easily leached out rare earth elements under the action of 10%reagent, indicating that the rare earth elements in ore are mainly in the ionic state rather than present as rare earth minerals.

Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm

In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.

Cause Analysis of Consumer‑Grade UAV Accidents Based on Grounded Theory‑Bayesian Network

In order to reduce the accident rate of consumer-grade unmanned aerial vehicles(UAVs)in daily use scenarios,the accident causes are analyzed based on the accident cases of consumer-grade UAVs.By extracting accident causing factors based on the Grounded theory,the relationship between these factors is analyzed.The Bayesian network for consumer-grade UAV accidents is constructed.With the Grounded theory-Bayesian network,the probability of four types of accidents is inferred:fall,air collision,disappearance,and personal injury.With the posterior probability of each factor being reversely reasoned,the causal chain with the maximum probability of each accident is obtained.After the sensitivity of each factor is analyzed,the key nodes in the network accordingly are inferred.Then the causing factors of consumer-grade UAV accidents are analyzed.The results show that the probability of fall accident is the highest,the fall accident is associated with the probabilistic maximum causal chain of personal injury,and the sensitivity analysis results of each type of accident as the result node are inconsistent.

A time-optimal aircraft-following model based on Pontryagin's minimum principle

A time-optimal aircraft-following model is introduced to address air traffic flow interference by velocity reduction. The objective function is set up as minimizing the recovery time during which the separation minima are not infringed and the separation of the air traffic flow returns to the initial separation at the terminal time. Pontryagin＇s minimum principle is used to solve the optimum aircraft-following velocity control law. An analytical minimum safe following separation is also provided under the time-optimal control law. The simulation results show that the precision first-order tracking accuracy is achieved without losing the separation.

Airway Network Characteristics Based on Complex Network Model

Airway networks are the basic carriers of air traffic.Characterizing airway networks will significantly improve the operating efficiency of aviation.This study is targeted at the airway network composed of 1479 waypoints in 2018 of China.Together with spatial structures,traffic flow characteristics,and the dominating traffic flow,four airway network models are constructed from the perspective of complex networks,including physical airway network,airway traffic network,directed airway traffic network,and dominance-based directed airway traffic network.Then the topological characteristics of different networks are statistically analyzed by using typical network measure indices,and the differences of these indices among different networks are investigated.Thereby,composite indices are proposed.Statistical results show that the airway network under the influence of traffic flows exhibits richer heterogeneity and asymmetrical between-node relationship,and the distributions of indices among different networks are significantly different.Comparative analysis of composite indices and traffic flows show that some waypoints yield great results in multiple composite indices and traffic volumes;some waypoints display large results in multiple composite indices but low traffic flows,and other waypoints only perform well in certain composite indices.The importance levels of waypoints are divided,by the K-means method based on degree composite index,betweenness composite index and closeness composite index,into three levels,and the reasonableness of clustering results is validated by the statistical results of traffic flows,airport number,and flight delay.

An Optimization Method of Formation Flight for Minimizing Fuel Consumption

A method for formation flight trajectory optimization was established.This method aims at minimizing fuel consumption of a two-aircraft formation flight,without changing the original trajectory of the leader.Candidate flight pairs were selected from all international flights arriving at or departing from China in one day according to the requirement of the proposed method.Aircraft performance database Base of Aircraft Data(BADA)was employed in the trajectory computation.By assuming different fuel-saving percentages for the following aircraft,pre-flight plan trajectories of formation flight were optimized.The fuel consumption optimization effect under the influence of different trajectory optimization parameters was also analyzed.The results showed that the higher the fuel savings percentage,the longer the flight distance of formation flight,but the smaller the number of formation combinations that can be realized,which is limited by the aircraft performance.The following aircraft flying along the approximate actual flight trajectory can be benefited as well,and the optimal fuel-saving efficiency is related to the expected fuelsaving efficiency of formation flight.

Analysis of a Large-Scale Heavy Precipitation Weather Process in Northern China from September 17 to 20, 2021

In the autumn of 2021, China’s precipitation appears the distribution characteristics of “more in the South and less in the north”. Compared with the same period in history, the precipitation is more. The analysis is based on a large-scale heavy precipitation weather process in the middle and late September. The atmospheric circulation situation and weather situation of this precipitation process are mainly discussed. The results show that the low-pressure trough between the Balkesh Lake and Baikal Lake area made the cold air move eastward, and the warm and humid air flow extending westward was conducive to the enhancement of precipitation. The anticyclone circulation in the Sea of Japan transported the cold and humid air to the northeast of China. The southeast air flow around the subtropical high in the Western Pacific, the southwest air flow in the bay of the Bengal Bay and the South China Sea met in the southwest to produce precipitation and continued to move northward. They merged with the cold and humid air flow in the Northeast in the north of the Yangtze River, resulting in large-scale precipitation in northern China.

A case study of the consistency problem in the inverse estimation

Inverse technique is a widely used method in oceanography, but it has a problem that the retrieved solutions often violate model prior assumptions. To tune the model has consistent solutions, an iteration approach, which successively utilizes the posterior statistics for next round inverse estimation, is introduced and tested from a real case study. It is found that the consistency may become elusive as the determinants of solution and noise covariance matrices become zero in the iteration process. However, after several steps of such operation, the difference between posterior statistics and the model prior ones can be gradually reduced.

4D Trajectory Tracking Control for Aircraft Based on Point-to-Point Iterative Learning Control with Current-Cycle Feedback

A point-to-point iterative learning control method with the current-cycle feedback is proposed to enable aircraft to achieve an accurate four-dimensional(4D) trajectory tracking. To this end,the 4D trajectory tracking control problem is formulated into a point-to-point tracking control issue with an external disturbance. Then,the optimal point-to-point iterative learning control law is derived based on the successive projection method. Further,the current-cycle feedback error is added to the control law,so that the tracking error is reduced in both time and iteration domains. Finally,a numerical simulation is carried out using the kinematic model of an unmanned aerial vehicle and 4D trajectory data. Obtained results demonstrate that the proposed method can quickly reduce the trajectory tracking error even in the presence of gust interferences. Compared with the commonly used average velocity method and the velocity correction method,the proposed method makes full use of the past and current running data,and can continuously improve the accuracy of 4D trajectory tracking with the repetitive operation of aircraft between city pairs.