Deicing is a complex process involving many actors including pilots, air traffic controllers and the deicing crew. In this context, communication mistakes can easily happen but can also have terrible consequences. The goal of the research project is to identify high risk areas of communication for aircraft ground deicing. Analyze of the voice interaction between the different actors involved with conversation analysis will be the starting point. After identifying problems in the communication process, the research will propose an improved approach to communication.
The main objective of this project is to investigate the performance of LiN-cryogenic technologY, as well as, high pressure cooling (HPC) in turning of hard-to-cut aerospace materials. The performance of cryogenic machining and HPC will be compared to flood coolant to establish the optimum conditions for each cooling technique, in terms of material removal rate, tool life, and surface integrity (surface finish, microstructure and residual stresses).
In the airline industry, crew planning is an essential task that every airline will face. Flight crew expenses constitute the second largest operating cost (Kohl and Karisch. 2004), second only to the rising cost of fuel. Crew planning refers to the assignment of flight segments to pilots and flight attendants so that they start and end at their base city, do not work more than the allowed time, etc.
In this project, a novel torque measurement technique based on piezoelectric sensors will be proposed to overcome the constraints posed by traditional methods such as strain gauges, magnetic pickups etc. Specially designed disks which are connected to the sensor will be mounted on the shaft. The proposed method will be used to compare relative twist in the shaft based on the phase difference between the disks. The angle of twist is then correlated to the torque applied. The proposed technique can be used as a low cost solution for torque measurement or rotating components.
Currently, when man-made objects in orbit around the Earth need to be disassembled or repaired, a humancontrolled robotic manipulator is used. The object in question is often not designed to be modified in this manner, and only 1 in 4 human operators at MDA (the partner organization) are able to successfully complete these notoriously challenging tasks. The goal of the proposed project is to design a computer program to learn from the successful human operators with the end result being a novel artificial intelligence that can perform these repairs autonomously, i.e.
This research project aims to prototype and evaluate a computer system supporting the creation of data-driven domain ontologies.
The first phase consists in creating a working prototype of a computer application supporting:
1) Preliminary research;
2) Creation of an interactive and visual computer interface allowing the visual concept mapping of a domain, its entities; define relationships between those entities and define attributes and parameters of those entities and relationships;
In this project we will evolve the design of the Sinclair Interplanetary (SI) ST-16 small satellite star tracker (SSST). With this redesign we wish to improve the sensor accuracy by an order of magnitude, while maintaining a slew tolerance of up to 1 deg/sec, with >99% availability.. For clarity, in this proposal we will refer to the improved star tracker design as the ST-20. The new design will feature improvements to the sensors optics, sensor processing algorithms, and calibration and focusing procedures.
In concert with Sinclair Interplanetary (SI), we are proposing a MITACS Elevate Postdoctoral Fellowship for Mr. Tom Dzamba under the supervision of Prof. John Enright, a researcher at Ryerson University. In the course of this fellowship, Mr. Dzamba will lead the redevelopment of the SI ST-16 star tracker in order to improve its measurement accuracy by a factor of ten. The ST-16 is a small instrument that allows a spacecraft to make precise measurements of its own orientation. Dr. Enright and Mr.
The amount of emissions to the atmosphere is currently an important environmental concern as policy makers and Heads of State are starting to demonstrate a strong interest in energy efficient transportation, in particular energy efficient aircraft. However, current autopilot technology will often not take into account the energy used to perform a given maneuver which can lead to potentially larger fuel consumption and larger atmospheric emissions than what is strictly necessary. The task of energy optimization is typically left to a flight management system (FMS).
Airlines take the extra effort required to figure out what is the best route that their aircrafts should take so as to minimize additional costs from non-revenue flights or idle time. One way to di this is to first generate large numbers of feasible routes and then assign flights to a subset of them so as to cover all flight legs. It is clear that the quality of the resulting solution depends highly on both the number of routes we generate anf also the diversity among the routes.