Existing aircraft noise models often rely on static databases and fail to comprehensively account for dynamic environmental and operational factors, resulting in relatively significant prediction errors in a single flight noise event. To make up these issues, a noise attenuation model integrating ellipsoid and nonlinear function has been proposed for the first time, this paper will further improve our previously proposed model. The key improvements are two aspects: firstly, geometric constraints derived from the analysis of NPD database to combined to ensure that the noise attenuation curve remains physically reasonable, overcoming the limitations of previously pure data fitting. Secondly, the objective function is redefined, thereby reducing the errors that assuming a constant sound source level in the original model, and improving the model's balance and extrapolation performance. The comparison results show that the ME, MAE and fluctuation range of the calibration and validation errors have all been reduced to some extent. The improved model also obtains a more balanced error distribution in predicting the EPNL. The sound level attenuation curves generated are more concentrated, and closer to the noise attenuation process in real environments. It is more conducive to analyze the noise attenuation characteristics of aircraft noise and establish corresponding noise databases. Furthermore, the model simulates the directivity of noise propagation through a simple geometric parameter adjustment of ellipsoid model, demonstrating a good environmental adaptability. The value of these enhancements not only lies in combining physical laws with data fitting, further enhancing the performance of the model, but also offering a new research direction for developing a more adaptable, interpretable, and reliable aircraft noise model.

Aiming at the impact of thunderstorms on safety and economy during Aircraft navigation, a dynamic 4D self-adaptive trajectory planning in thunderstorm weather is proposed. First, the three-dimensional coordinate parameter equation related to the time variable is introduced to build the dynamic thunderstorm weather. Then, a model of aircraft motion state is constructed based on the kinematics principle, and the trajectory is simulated by sampling the velocity in a velocity space that conforms to aircraft performance and flight safety requirements. Finally, algorithm calculates the distance between the aircraft and thunderstorm clouds in complex environments, the flight angle, and other indicators, and the entropy weight is calculated, and screened to obtain the optimal trajectory in thunderstorm weather scenes. The experimental results show that the algorithm has planned safe flight path while meeting the requirements of aircraft performance, avoiding the impact of thunderstorms on the aircraft. The reliability and superiority of the model have been verified.

Airport Traffic Control Tower (ATCT) is one of the most important facilities at civil aviation airports. The location and height of ATCT will directly affect the controller's observation and judgment. In order to evaluate and compare the visibility capability of different tower construction schemes, a comprehensive evaluation method is set up. This method includes building an index system of obligatory and preference indicators, forming calculation methods for each indicator, and establishing a comprehensive evaluation model. In the evaluation model, two networks have been constructed based on Coefficient Strategy (CS) and Level Strategy (LS) respectively. Selecting a certain airport in East China as a case study, CS-BP and LS-BP network models of 5-10-1 in topology have been set up after 12000 typical samples for training respectively. The research results show that LS-BP network has the smaller Mean Squared Error (MSE) and greater regression coefficient compared to CS-BP network. And the results of CS-BP were similar to Traditional Strategy (TS). Therefore, selecting LS-BP network to evaluate calculated indicators of given schemes and considering that scheme 3 was best. The entire method can serve as a reference for decision-making by air traffic control unit.

Flight delays have become the main research objective for airports to improve efficiency and control costs, as an important indicator to measure flight delays, departure flight normal rate (DFNR) plays a more crucial role in influencing airport planning decisions. Theoretical research mainly focuses on reducing total delays, simulation methods can not consider delays caused by non-ground operation limitations, resulting in too ideal DFNR. In order to evaluate DFNR better in the airport's planning and operational schemes, this paper proposes an evaluation method for DFNR, which models the probability distribution of flight delay caused by various uncertain factors, and combines the departure delay from AIRTOP simulation caused by the ground operational restrictions of airport. The genetic algorithm is used to solve the various parameters in the model. Taking an airport for example, the DFNRs of 10 situations is calculated. The results show that the number of delay factors has a relatively small impact on the results, the calculation results of proposed model are consistent with the expected results and can better reflect the differences of situations compared to simulation, so the calculation results of proposed model are more reasonable and can be used as a decision-making reference. Besides, the value of delay threshold has a significant impact on the calculation results of DFNR.

Comparing with currently domestic way of departure from closely spaced parallel runways (CSPR), paired departures from CSPR significantly reduces the departure time interval between leading aircraft and trailing aircraft, thus improving the airport runway capacity. This paper mainly studies the departure time interval of paired departure from CSPR. Firstly, through the position error probability model, a collision risk assessment model for paired departure aircrafts is constructed. Then, based on the departure process, the distance calculation model of paired departure aircrafts is established. The impact of different types of aircrafts on collision probability is considered, and the departure time intervals of two situations are calculated. The calculation results show that when the departure time interval is more than calculated threshold, the collision probability is below target level of safety, and the departure time interval can be greatly reduced. This may help the studies on the collision risk of paired departure from CSPR in the future.

Objective. To establish a rapid objective method for detection fatigue of air traffic controllers (ATCs) to meet fatigue management requirements. Methods—A fatigue detection method established by combining a modified psychomotor vigilance test scene with the test of the percentage of eyelid closure over the pupil over time (PERCLOS). The subjects’ PERCLOS value, reaction time and error rate during detection were simultaneously obtained and integrated into the fatigue value. The detection time was compressed to 5 min and the result obtained just completed detection. The established method was applied to a field test at one area control unit in China. 19 ATC volunteers were recruited and divided into two groups as a test group before duty and a fatigue control group after duty. The detection results indicated that the method was valid to detect out ATCs’ fatigue from work and was suitable to control work environment. Conclusions—The rapid method of fatigue detection for air traffic controllers before duty was successfully developed, which would serve as an effective tool for air traffic controller fatigue management.

This paper addresses the towing process of airplanes as part of airport ground service. We propose the distributed strategy which lets the tractors provide push-back services for the aircraft in the same service area preferentially and introduce a mathematical model which includes the service time, the vehicle driving and several optimization objective functions. The main objective function minimizes the mismatches between tractors and aircraft and the delay time of push-back. To solve the multiobjective problem with bias, we develop the improved NSGA-II algorithm by setting preference for evolution and designing crossover and mutation programs pertinently. Computational results show the superior behavior of the given method compared to the methods of artificial experience, traditional algorithm and centralized strategy based on the actual data in a large airport.

When connecting taxiways of the civil aviation airport are failure under emergencies, the ground network of airport will be impacted, which could lead to the collapse in serious cases. In order to study the impact of connecting taxiway failure on the airport ground network (AGN), with starting from the operating reality, it defines the stability of the AGN, and puts forward the connecting taxiway utilization rate, the average time of connecting taxiway occupancy, and the cumulative use time of connecting taxiway occupancy. At the same time, it proposes the hypothesis conditions, sets parameters, and builds the simulation model. Through simulating one, two, or all connecting taxiways failure, it analyzes the impact on the AGN. According to the simulation results, on the single-runway civil aviation airport, with building more connecting taxiways, the stability of the AGN is stronger, and the construction cost is higher which is not good for airport sustainability and the high-quality development of the civil aviation.

The fatigue of air traffic controllers (ATCs) attracts much attention recently because it seriously threatens civil aviation safety. The aim of the paper is to compare the fatigue of ATCs at real work and at labs. The ATCs from one busy terminal control unit in China were recruited in this study. Sixty-three ATCs at real work and sixty-two ATCs on their simulator training as two compared groups filled in the Stanford Sleepiness Scales before, in the middle, and after their work/training. Statistical results showed that both work and training were able to make ATC fatigue levels increased. The fatigue levels between two groups showed no difference before their work/training. It was worth to notice that the increase of fatigue levels after their work was significantly bigger than that after their training. This discovery indicates that the ATC fatigue at work is hard to simulate at labs and it is necessary to do field investigations to learn ATC real fatigue status at work for their fatigue management.