JOHN GATSIS

gatsis AT utias DOT utoronto DOT ca

University of Toronto Institute for Aerospace Studies
4925 Dufferin Street
Downsview, ON
M3H5T6

[John Gatsis]


Profile

I am a recent Ph.D. graduate from the University of Toronto Institute for Aerospace Studies. Thank you for visiting my website.

Curriculum Vitae

Available upon request.

Important Links & People

Supervisor: Professor David Zingg
Doctoral Examination Committee Chair: Professor Clinton Groth
Doctoral Examination Committee Member: Professor Hugh Liu
University of Toronto ROSI Student Service
Colleagues: UTIAS CFD Lab
Ph.D. Candidate: Mohammad Tabesh
UTIAS Webmail
Facebook: Me!
Toronto Math Tutor.
Toronto Tutor John Gatsis - Math, Physics and Chemistry tutoring services within the GTA.

Papers / Publications

A Fully-Coupled Newton-Krylov Algorithm for Aerodynamic Design Optimization
Co-authored by Professor D.W. Zingg
16th AIAA Computational Fluid Dynamics Conference from June 23-26, 2003
Orlando, USA

Conference Paper:Download PDF file
Conference Presentation:Download PDF file

A Fully-Coupled Algorithm For Aerodynamic Design Optimization
Co-authored by Professor D.W. Zingg
48th Annual CASI Conference on May 1, 2001
Toronto, Canada

Conference Paper:Download PDF file
Conference Presentation:Download PDF file

Results


[Turbulent transonic mach contour.]

This is a Mach number contour of a supercritical flow about a RAE2822 airfoil. This is a fully-turbulent flowfield, at a Mach number of 0.75 and an angle of attack of 3 degrees. Notice the stagnation region at the leading edge, the supersonic region, the lambda shock, and the shock-boundary-layer interaction including shock-induced flow separation. Finally, note the recirculation region on the upper surface of the airfoil at the trailing edge.
This simulation was conducted using a Newton-GMRES algorithm, which solved the discretized, compressible, steady Navier-Stokes equations with the Spalart-Allmaras turbulence model. On my desktop computer, this simulation took roughly 2 minutes.

[Invicsid cases contour.]

This is a 3D contour plot of CPU time versus angle of attack and freestream Mach number for flow about a symmetric NACA0012 airfoil. The Euler equations are used to model the flow. A fully Newton-GMRES algorithm is used to solve the discretized equations. Local preconditioning can be used to improve the algorithm's performance for low-Mach number flows and for flows with a Mach number in the neighbourhood of unity. Simulations for large angles of attack are not feasible since viscous effects are not described by the Euler equations.

AER307F Aerodynamics Course

Division of Engineering Science, Faculty of Applied Science and Engineering, Univeristy of Toronto

Fall 2003: Course instructor: John Gatsis
Fall 2004: Course instructor: John Gatsis
Fall 2005: Course instructor: Professor David Zingg
Fall 2006: Course instructor: John Gatsis
Fall 2007: Course instructor: John Gatsis
Current course instructor: Philippe Lavoie

The course website is on the UofT PORTAL. To access this site you must first login to your UTORID account. This course should appear under your courses.

Ph.D. Thesis

Preconditioning Techniques for a Newton-Krylov Algorithm for the Compressible Navier-Stokes Equations

Funded by the Ontario Graduate Scholarship Program (OGS & OGSST)

Supervisor: Professor D. W. Zingg

One of the key goals in computational fluid dynamics (CFD) is to create efficient flow solvers. The solution of analysis problems in industry is important in predicting the performance and in the design optimization of aircraft. In fact, the optimization process requires a large amount of flow solves to complete its task accurately. The compressible Navier-Stokes equations that describe the fluid flow are extremely difficult to solve numerically in an efficient manner. Furthermore, aerodynamic flows are typically turbulent and have high Reynolds numbers. This means that the flow solver must operate on a very fine computational grid to produce accurate results. However, with the larger system size, comes larger computational cost. A promising approach to solving these equations is to use Newton-Krylov methods. In Professor Zingg's research group at UTIAS, promising results using the GMRES (generalized minimum residual) Krylov subspace method have been found. However, the challenge with GMRES is choosing the best possible preconditioner for the system. Various techniques in preconditioning will be explored in this research. Some areas of exploration include algebraic multigrid, sparse approximate inverses, orderings, and Schwarz domain decomposition.

Course Research

Matrix Calculations / Numerical Linear Algebra
Professor Christara, University of Toronto, Department of Computer Science
Course Home Page

Numerical Solutions for Optimization Problems
Professor Wolkowicz, University of Waterloo, Department of Combinatorics and Optimization
Course Home Page

Air-Breathing Propulsion
Professor Sislian, University of Toronto, Institute for Aerospace Studies

The Finite Element Method
Professor Hansen, University of Toronto, Institute for Aerospace Studies

M.A.Sc. Thesis

A Fully-Coupled Algorithm for Aerodynamic Design Optimization

Funded by the Natural Science and Engineering Research Council of Canada (NSERC)

Supervisor: Professor D. W. Zingg

A fully-coupled algorithm is presented to solve aerodynamic design optimization problems. The discretized flow, adjoint, and optimality condition equations are solved as a single system of nonlinear equations using an inexact Newton method with linesearching. Quasi-1D, inverse, nozzle design and inviscid, 2D, inverse, airfoil shape design cases are solved, however the method is applicable to more general design cases. While the system is approximately twice as large as the system describing the flow solution, fewer iterations are required to find the optimum. The most important advantage of this method is that only a single flow solve is needed to perform the optimization, as opposed to the discrete adjoint method which requires several. Many improvements have been made to the algorithm, both in the system formation and solution method. The result is an algorithm that is reliable, robust, accurate, and fast in providing optimum solutions for the cases considered.

Course Research

Graduate Course: Unsteady Gasdynamics
Professor Gottlieb, University of Toronto, Institute for Aerospace Studies

Graduate Course: Fundamentals of Computational Fluid Dynamics
Professor Zingg, University of Toronto, Institute for Aerospace Studies

Graduate Course: Topics in Computational Fluid Dynamics
Professor Zingg, University of Toronto, Institute for Aerospace Studies

Graduate Course: Viscous Flows and Boundary Layers
Professor Walsh, University of Toronto, Institute for Aerospace Studies

Results

ARC1D Flow Solver
ARC1D Flow Solver Results:Download PDF file
1D Halving Linesearch Results:Download PDF file
1D Backtracking Linesearch Results:Download PDF file
A typical flow solution in 2D:Download PDF file

Final Report

Download PDF file
Download PS file
Visit the Canadian National Archives to get a copy at http://amicus.nlc-bnc.ca

B.A.Sc. Thesis

Feedback Control Systems for Automotive Aerodynamic Devices

Supervisor: Professor P. A. Sullivan

The objective of this thesis is to implement a feedback control system for automotive aerodynamic devices such as spoilers and stabilizers in order to achieve a higher degree of driver comfort, road handling, and traction.

I'd like to especially thank Dr. Phil Sullivan for his exceptional guidance. He has an important place in history for many reasons, including for his significant contribution to the safe return of the Apollo 13 astronauts.

Course Work

Year 4

Atmospheric Flight
Gasdynamics
Spacecraft Dynamics and Control I
Thesis
Complex Analysis
Aircraft Design
Advanced Mechanics of Structures
Aerospace Propulsion
Confronting Global Change
Robotics

Year 3

Dynamics
Fluid Mechanics
Mechanics of Solids and Structures
Partial Differential Equations
Control Systems
Aerodynamics
Scientific Computing
Economic Analysis and Decision Making
Materials Design and Engineering
Probability and Statistics

Year 2

Engineering Design
Chemical Processes
History of North American Technology
Calculus III - Vector Calculus
Physics IV - Quantum Mechanics
Differential Equations
Electric Circuits
Digital and Computer Systems
Varieties of Fiction
Physics II/III - Vibrations and Waves, and Thermal Physics

Year 1

Engineering, Society, and the Environment
Algorithms and Data Structures
Electricity and Magnetism
Linear Algebra
Calculus II
Chemistry
Structures and Materials
Computer Programming
Calculus I
Physics I - Mechanics

Course-Related Work and Projects

Engineering Design -- M.J. Malone

Mars Rescue Rover (MRR):Website

Fundamentals of Computational Fluid Dynamics -- D.W. Zingg

Convergence Acceleration by use of Multigrid in MATLAB:Download PDF file

Unsteady Gasdynamics -- J.J. Gottlieb

"New" Riemann Solver in C++:Header File and Code

Topics in Computational Fluid Dynamics -- D.W. Zingg

Hirsch's Nozzle and Shock Tube Exact Solutions:Download PDF file
ARC1D Flow Solver Results:Download PDF file
FLOMG Flow Solver Results:Download PDF file
Applied Upwinding Dissipation Schemes Results:Download PDF file
Applied Upwinding Dissipation Schemes Presentation:Download PDF file

Viscous Flows and Boundary Layers -- C.B. Walsh

Investigating the Spalart-Allmaras Turbulence Model Report:Download PDF file
Investigating the Spalart-Allmaras Turbulence Model Presentation:Download PDF file

Matrix Calculations / Numerical Linear Algebra -- C.C. Christara

Final Course Project:Download PDF file

Tutorial Service

***FREE*** Advanced Functions, Introductory Calculus, and Advanced Placement (AP) Calculus test preparation questions as well as Linear Algebra, and Science book

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Artwork

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