Showing papers in "International Journal of Aviation, Aeronautics, and Aerospace in 2021"

The Influence of Personality, Safety Attitudes, and Risk Perception of Pilots: A Modeling and Mediation Perspective

Abstract: Scott R. Winter Embry-Riddle Aeronautical University, scott.winter@mac.com Joseph R. Keebler Embry-Riddle Aeronautical University, joekeebler@gmail.com Tracy L. Lamb Embry-Riddle Aeronautical University, LAMBT4@my.erau.edu Richard Simonson Embry-Riddle Aeronautical University, simonsonr7@gmail.com Robert Thomas Embry-Riddle Aeronautical University, Bob.Thomas@erau.edu Stephen Rice Embry-Riddle Aeronautical University, scrice@outlook.com

Internet of Things 36-rotor Multicopter for Ionizing Radiation Surveying

Abstract: Svetoslav Zabunov Space Research and Technology Institute -Bulgarian Academy of Sciences, svetoslavzabunov@gmail.com Garo Mardirossian Space Research and Technology Institute -Bulgarian Academy of Sciences, garo.mardirossian@gmail.com Rositsa Miteva Institute of Astronomy and National Astronomical Observatory -Bulgarian Academy of Sciences, rmiteva@nao-rozhen.org Todor Kunchev Faculty of Medicine – Sofia University, drtodorkunchev@yahoo.co.uk

Pilot Visual Detection of Small Unmanned Aircraft on Final Approach during Nighttime Conditions

Abstract: Jon M. Loffi Oklahoma State University Main Campus, jon.loffi@okstate.edu Ryan J. Wallace Embry-Riddle Aeronautical University, ryan.wallace@erau.edu Samuel M. Vance Oklahoma State University Main Campus, matt.vance@okstate.edu Jamey Jacob Oklahoma State University Main Campus, jdjacob@okstate.edu Jared C. Dunlap Oklahoma State University Main Campus, jared.dunlap@okstate.edu Taylor A. Mitchell Oklahoma State University, taylor.mitchell@okstate.edu Dane C. Johnson Oklahoma State University, dane.johnson@okstate.edu

A Model for Inhalation of Infectious Aerosol Contaminants in an Aircraft Passenger Cabin

Abstract: Aerosol contamination of an aircraft cabin by infectious passengers is a concern of passengers, aircrew and the aviation industry This may be especially important during a pandemic, such as COVID-19, where the full extent of aerosol transmission is not well understood A statistical method to determine the number of infectious passengers on board along with a mathematical model estimating the contaminant concentration of aerosols in the cabin and the number of inhaled infectious particles by passengers is presented An example is used to demonstrated how the results can be estimated during normal operations and emergency conditions with malfunctions of the air conditioning and pressurization system which are responsible maintaining clean cabin air This type of information can assist the aviation industry in providing the end users of aircraft travel, i e passengers and aircrew, with reasonable cabin contaminant guidelines Accomplishing this in a timely manner requires the combination of modeling adjusted by experimentation Physically testing all aircraft for each of these conditions would be time consuming, expensive and impractical Incorporating a model towards solving these problems can serve to bridge the gaps between a finite number of experimental results

Support to Design for Air Traffic Management: An Approach with Agent-Based Modelling and Evolutionary Search

Abstract: Gabriella Gigante CIRA (Italian Aerospace Research Centre), g.gigante@cira.it Roberto Palumbo CIRA (Italian Aerospace Research Centre), r.palumbo@cira.it Domenico Pascarella CIRA (Italian Aerospace Research Centre), d.pascarella@cira.it Alessandro Pellegrini Sapienza University of Rome, pellegrini@diag.uniroma1.it Gabriella Duca ISSNOVA (Institute for Sustainable Society and Innovation), duca@issnova.eu Miquel Angel Piera Universitat Autònoma De Barcelona, miquelangel.piera@uab.cat Juan José Ramos Universitat Autònoma De Barcelona, juanjose.ramos@uab.es