Posts By: Jennifer Li

aUToronto SAE Autodrive Challenge Round 1 Year 4 Safety Video

In this video, we showcase the University of Toronto’s autonomous vehicle Zeus, our design strategy, our design workflow, and our future outlook.

“Our Year 4 self-driving competition is in full swing. This video introduces our car and some of the technical details.” – Prof. Angela Schoellig

**Like the video to get us up to 15 bonus points in the competition** 🙂


Prasanth Nair recognized with Connaught Innovation Award

Professor Prasanth Nair of the University of Toronto Institute for Aerospace Studies in the Faculty of Applied Science & Engineering has received a Connaught Innovation Award to support his computational framework, known as Deep Bayesian Analytics Engine (DBAE).

“In collaboration with my graduate student, Trefor Evans, I developed a novel, deep learning architecture coupled to a Bayesian analytics engine, which together forms a powerful and highly flexible computational framework for decision support in complex engineering applications,” says Nair, a Canada Research Chair in Computational Modeling and Design Optimization Under Uncertainty.

Full article: Prasanth Nair recognized with Connaught Innovation Award

Researchers at U of T use physics model to study spread of COVID-19 respiratory droplet ‘clouds’

After nearly a year of studying COVID-19, scientists are still grappling with fundamental questions – including understanding the dominant modes of transmission and predicting how “superspreading” events arise. A newly improved model produced by engineers and physicists could help.

Associate Professor Swetaprovo Chaudhuri of the University of Toronto Institute for Aerospace Studies and his colleagues have developed what they called a “first-principles modelling approach” to understanding the factors that affect COVID-19 spread.

Researchers at U of T use physics model to study spread of COVID-19 respiratory droplet ‘clouds’

Posted in PEC

Understanding Dangerous Droplet Dynamics

Researchers who study the physics of fluids are learning why certain situations increase the risk that droplets will transmit diseases like COVID-19.

At the 73rd Annual Meeting of the American Physical Society’s Division of Fluid Dynamics, the scientists offered new evidence showing why it’s dangerous to meet indoors—especially if it’s cold and humid, and even if you’re more than six feet away from other people. They suggested which masks will catch the most infectious droplets. And they provided new tools for measuring super-spreaders.

“Present epidemiological models for infectious respiratory diseases do not account for the underlying flow physics of disease transmission,” said University of Toronto engineering professor Swetaprovo Chaudhuri, one of the researchers.

Understanding Dangerous Droplet Dynamics

Posted in PEC

Understanding the spread of COVID-19 through physics-based modeling

Professor Swetaprovo Chaudhuri of the University of Toronto Institute of Aerospace Studies (UTIAS) normally spends his time thinking about the motion of fluids through jet engines.

Now, that expertise is being used to understand the spread of COVID-19.

“In aircraft engines, fuel is injected into the combustor in a fine spray of droplets with sizes somewhat similar to what is ejected while coughing or sneezing,” he says. “While the specific conditions of a respiratory spray are different, the same fundamental physics are involved.”

Back in March, as the pandemic ramped up across Canada and other nations, Chaudhuri called up some long-time collaborators: Professor Abhishek Saha at the University of California San Diego, and Professor Saptarshi Basu of the Indian Institute of Science.

Together, they started to consider what it would take to adapt the physics-based models traditionally used for their work in combustion to instead describe the processes involved in transmitting the new virus.

Understanding the spread of COVID-19 through physics-based modeling

Posted in PEC

Flight Research Facilities

Front Cockpit Workstation

Rear Cockpit
The front cockpit is used for fixed wing research. Opincius electric control loading is used to provide force feedback on all the controls. Out-the-window visuals are presented by 3 sony monitors projecting through infinity optic displays units. A touch-screen based glass cockpit is used to display all instruments.
Opinicus control loading
The column, wheel and pedal forces are provided by Opinicus Corp. REALFeel 4000X force loader units. Two autothrottle channels are provided by REALFeel 2000RC force loader units.
Out-of-the-window visuals

Images are projected into 3 seperate windows by 24in Sony Multiscan colour (CRT) monitors. Each monitor projects through a VITAL II infinity optics window box. The resolution in each window is 1280×1024 pixels. The nominal field of view for each monitor is 40° x 30° resulting in a pixel resolution of approximately 2 arcminutes. See the figure below for the as displayed field of view.The forces are generated by electric DC servo motors coupled to a two stage, low inertia, zero backlash speed reducer which in turn is linked via a push pull rod to a force transducer and the flight controls linkage. The autothrottles are moved through a backdrive feature to their desired deflections. The system is operated by a digital computer which is coupled to the simulator’s flight computer via a fiber optic cable and a reflective memory interface. The manufacturer specifies a force loop frequency response of greater than 100Hz.

The 4000X control loaders can produce a continuous force output of ±412 lb and much larger peak values. Their stroke is ±2 in. The control column has a travel range of 5.5 in (14cm) forward and 9.3 in (24 cm) aft. The control wheel has a travel range of ±120°. The pedals have a travel range of ±2.6 in (6.6 cm). The 2000RC control loaders can produce a continuous torque output of ±XXX with a continuous rotational capability.


Field of View

Rear Cockpit Workstation

Front Cockpit
The rear cockpit is used for rotary-wing research. McFadden hydraulic control loading is used to provide force feedback on the cyclic controls. Out-the-window visuals are presented on either a Kaiser helmet display system or a CAE fibre-optic helmet mounted display system. Rate-gyros and a Polhemus magnetic head tracker are used to estimate head motions, with the gyros being used to generate lead. A touch-screen based glass cockpit is used to display all instruments.
McFadden Hydraulic Control

The cyclic stick control forces are provided by a McFadden Systems Inc. Model 292B Universal Variable Digital Cockpit Control Force Loading System. The stick forces are generated by rotary servo actuators of the limited rotation vane type with hydrostatic bearings. An electro-hydraulic servo valve controls each of the two actuators using analog electrical signals fro the digital unit’s digital-to-analog converter. Differential pressure and angular position transducers are used to provide feedback for the force and modeling loops. A digital control loop closes the force generation process with a 5 kHz update rate. The manufacturer specifies a 80 Hz bandwidth for this loop. The mathematical model that generates force commands to the system in response to stick displacement also runs at 5 kHz. This model can have its parameters updated in real-time at up to 1 kHz.

The system can generate a maximum force of ±150 lb at the stick’s hand grip on both axes. The maximum pitch displacement is ±15.3° (±7.37 in) and the maximum roll displacement is ±15.5° (±7.47 in). The force resolution is better than 0.1 lb at the hand grip.

Kaiser Helmet
Kaiser Helmet
CAE Fibre-optic Helmet
The CAE helment system uses 3 red, green and blue CRTS for each eye and the images are carried to the optics mounted on the helmet by 4 million coherent optic fibres.

CAE Fibre Optic Helmet

Main Simulator Components

Flight Simulator
Both cockpits are mounted on a CAE 300 series hydraulic motion system. Up to five channels of Evans and Sutherland 6500Q image generators are available to render the visual scene. The flight equations and other real-time calculations are performed on a 8 processor Concurrent iHawk.
CAE 300 Series Motion System

The CAE 300 Series Hydraulic Motion Base is a six degree-of-freedom Stewart platform. The six actuators have a stroke of 91.4cm, a bore of 8.9 cm and are equipped with hydrostatic bearings. Power for the system is provided by 3 37.3kW squirrel cage induction motors with matching variable displacement in-line pumps. The measured motion characteristics of the system are:

Bandwidth of 10Hz (3dB point)
Bandwidth of 5Hz (90° phase-nominal, can be extended)
Dynamic threshold < 67ms
Hysteresis < 1mm per actuator
The motion envelope (1 Dof at a time is),

CAE 300 Series Motion System
SimFusion 6500Q
  • simENGINE™ graphics cards with ATI graphics processors
  • Fill rate 12 Gpix/sec peak
  • Anti-aliasing 2 to 24 samples
  • Polygons 186M tri/sec peak
  • Channel syncronization
  • Trilinear mipmap texture anti-aliasing
  • Up to 2048×2048 texture map
  • 256MB memory
  • Texture compression
  • LOD (24 levels)
  • 32 bit true color
  • Gamma correction
Concurrent iHawk

Transient growth induced by surface roughness in a Blasius boundary layer

This is a link to an invited talk I gave for a workshop organised by the Isaac Newton Institute Mathematical Sciences at Cambridge University in Sept. 2008. Abstract & Video

2019 Flight Systems & Control Lab

Happy Holidays ! (Dec 19th) – This year we are joined by previous alumni and visiting scholars of FSC community. As the highlight of the night, the dinner was finished with the Secret Santa gift exchange. FSC lab members and Professor Liu thank everybody for celebrating with us and wish our friends a happy holiday.

fsc party

The picture was taken at the end of the event with everybody showing the present they received!

fsc party

New Furnitures ! (Dec 18th) – New furnitures arrived. A brand new look for the office.

FSC office

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