Search Results (4)

Pilot fatigue and alertness are critical for civil aviation safety. Intercontinental pilots are more prone to fatigue and sleepiness due to jet lag, prolonged workdays, and disrupted rhythms. The Civil Aviation Administration of China excused enlarged flight crews from mandatory layovers and reimposed flight duration restrictions during COVID-19. This study investigates the sleep quality and attentional performance of pilots on intercontinental flights. The fifteen pilots who performed intercontinental flights in different crew compositions wore a body movement recorder, which has been proven to accurately estimate sleep duration and sleep efficiency. The crew’s attentional performance and self-report were monitored at specified flight phases. In conclusion, the larger crews slept longer and more efficiently on board, particularly pilots in charge of takeoff and landing responsibilities. Crews on four-pilot layover flights were more alert before the takeoff of the inbound flights than exempt flights, but there was no significant difference towards the end of the mission. The new long-haul flight organization did not result in fatigue or decreased attention in the pilots. This study expands on the research by validating a novel intercontinental flight operation model under the COVID-19 scenario and highlighting critical spots for future fatigue management in various crew compositions. Full article

Background: Domestic workers, flight crews, and sailors are three vulnerable population subgroups who were required to travel due to occupational demand in Hong Kong during the COVID-19 pandemic. Objective: The aim of this study was to explore the social networks among three vulnerable population subgroups and capture temporal changes in their probability of being exposed to SARS-CoV-2 via mobility. Methods: We included 652 COVID-19 cases and utilized Exponential Random Graph Models to build six social networks: one for the cross-sectional cohort, and five for the temporal wave cohorts, respectively. Vertices were the three vulnerable population subgroups. Edges were shared scenarios where vertices were exposed to SARS-CoV-2. Results: The probability of being exposed to a COVID-19 case in Hong Kong among the three vulnerable population subgroups increased from 3.38% in early 2020 to 5.78% in early 2022. While domestic workers were less mobile intercontinentally compared to flight crews and sailors, domestic workers were 1.81-times in general more likely to be exposed to SARS-CoV-2. Conclusions: Vulnerable populations with similar ages and occupations, especially younger domestic workers and flight crew members, were more likely to be exposed to SARS-CoV-2. Social network analysis can be used to provide critical information on the health risks of infectious diseases to vulnerable populations. Full article

We analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of the airline business models. We obtain an unsupervised classification of airlines by performing a hierarchical clustering that uses a correlation coefficient computed between the average occurrence profiles of 4-motifs of airline networks as similarity measure. The hierarchical tree is highly informative with respect to properties of the different airlines (for example, the number of main hubs, airline participation to intercontinental flights, regional coverage, nature of commercial, cargo, leisure or rental airline). The 4-motif patterns are therefore distinctive of each airline and reflect information about the main determinants of different airlines. This information is different from what can be found looking at the overlap of directed links. Full article

Motivated by the growing technology of control and data processing as well as the increasingly complex designs of the new generation of gas turbine engines, a fully automatic control strategy that is capable of dealing with different aspects of operational and safety considerations is required to be implemented on gas turbine engines. An advanced practical control mode satisfaction method for the entire operating envelope of gas turbine engines is proposed in this paper to achieve the optimal transient performance for the engine. A constraint management strategy is developed to generate different controller settings for short-range fighters as well as long-range intercontinental aircraft engines at different operating conditions by utilizing a model predictive control approach. Then, the designed controller is tuned and modified with respect to different realistic considerations including the practicality, physical limitations, system dynamics, and computational efforts. The simulation results from a verified two-spool turbofan engine model and controller show that the proposed method is capable of maneuverability and/or fuel economy optimization indices while satisfying all the predefined constraints successfully. Based on the parameters, natural frequencies, and dynamic behavior of the system, a set of optimized weighting factors for different engine parameters is also proposed to achieve the optimal and safe operation for the engine at different flight conditions. The paper demonstrates the effects of the prediction length and control horizon; adding new constraints on the computational effort and the controller performance are also discussed in detail to confirm the effectiveness and practicality of the proposed approach in developing a fully automatic optimized real-time controller for gas turbine engines. Full article