Centre for Computational Science and Engineering

Group website: https://www.utias.utoronto.ca/ace/

Field(s): Computational Fluid Dynamics

The Aerospace Computational Engineering Lab focuses on the development and analysis of numerical methods for partial differential equations (PDEs) with applications in continuum mechanics with emphasis on aerodynamics. The goal of the group is to improve the reliability and autonomy of numerical simulations for complex phenomena. Here, reliability refers to the ability to estimate and control various sources of error in numerical predictions. Autonomy refers to the ability to complete the analysis with minimal user intervention.

Reliable and automated simulations play important roles in engineering design and analysis. A reliable solver accurately characterizes complex flow phenomena, in which user instincts may fail to identify relevant features. A reliable solver permits exploration of radically different designs, for which little prior knowledge exists. A reliable solver enables modern engineering challenges, such as robust optimization and real-time control. The group aims to provide reliable and automated computational tools that maximize their predictive potential and utility in understanding physical phenomena and ultimately making engineering decisions.

Much of the emphasis of the group is advanced numerical methods for PDEs. Examples of research topics currently pursued include the development of the following techniques:

1. Robust high-order methods and error estimation techniques to provide reliable prediction of complex aerodynamic flows.
2. Adaptive techniques for stochastic PDEs to quantify uncertainty associated with both model and discretization errors.
3. Topology optimization techniques for structures under model uncertainty. (Joint work with Prof. Prasanth Nair.)
4. Model reduction techniques for large-scale and high-dimensional engineering systems.

Group website: http://www2.mie.utoronto.ca/labs/bsl/

Field(s): Computational Fluid Dynamics

The primary research focus of the Biomedical Simulation Laboratory is the integration of computer modeling and medical imaging technologies in novel studies aimed at improving the understanding, diagnosis, and treatment of vascular disease.

Local blood flow patterns (hemodynamics) are thought to play an important key role in the development, diagnosis and treatment of vascular disease. Despite decades of active research, many questions remain unanswered about the role of hemodynamics in vascular disease. This is largely due to the fact that these key hemodynamic factors — shear stresses and residence times — are notoriously difficult to measure directly. With recent advances in medical imaging, it is possible to image vascular anatomy and disease non-invasively, with sub-millimeter resolution. Although in principle capable of measuring blood velocity as well, current imaging technology requires scan times that make routine extraction of hemodynamic factors difficult if not impossible. Computer modeling, however, has advanced to a stage where it is now possible to faithfully model pulsatile hemodynamics in realistic arterial models provided, for example, by non-invasive medical imaging.

Current research interests of the Biomedical Simulation Laboratory include: Hemodynamic factors in cardiovascular disease; integration of medical imaging and computational fluid dynamics (CFD); simulation of medical imaging; flow visualization; intersection of science and engineering with the arts and humanities.

Group website: http://arrow.utias.utoronto.ca/~groth/

Field(s): Computational Fluid Dynamics

Prof. Groth heads the CFD and Propulsion group at UTIAS. He is a theoretical and computational fluid dynamicist with expertise in parallel, adaptive mesh refinement (AMR), finite-volume schemes for compressible non-reacting and reactive flows. He also has expertise in the computation of non-equilibrium, rarefied, and magnetized flows, and the development of generalized transport models and solution methods following from kinetic theory. He is a leading researcher in high-performance computing, the simulation of laminar flames with detailed chemistry, and the development of reliable and robust numerical techniques for performing large-eddy simulations (LES) of turbulent reactive flows. He is also currently pioneering the development and application of high-order and AMR methods for high-speed compressible flows of gases and plasmas as well as reactive flows, the formulation of accurate and robust moment closure techniques for describing micro-physical processes in non-equilibrium, rarefied gases flows, as well as the multi-phase flows associated with liquid fuel atomization and soot formation gas-turbine engines. He has extensive experience in the simulation of gas-turbine combustor flows under high-pressure conditions through collaborative research efforts with various industrial partners, including Pratt & Whitney Canada, a leading manufacturer of gas turbine engines for aviation applications.

Group website: http://www.utias.utoronto.ca/research/computational-aerodynamics/

Field(s): Computational Fluid Dynamics, Optimization

The Computational Aerodynamics lab at the University of Toronto Institute for Aerospace Studies is focused on the application of aerodynamic shape optimization to the development of high-efficiency unconventional aircraft configurations. Aerodynamic shape optimization combines numerical optimization with computational fluid dynamics (CFD) to find optimal aerodynamic geometries, such as wings and complete aircraft, that minimize a specified objective function, such as drag, subject to constraints, such as lift.

This work is primarily motivated by the need for a significant reduction in greenhouse gas emissions by the commercial aerospace industry in the face of anthropogenic climate change. Reducing aviation’s greenhouse gas emissions is particularly challenging given that demand for air travel continues to increase. Hence transformative new technologies are needed. There are two major objectives in the lab’s research:

1. To advance the state of the art in algorithms for CFD as well as aerodynamic and aerostructural optimization.
2. To apply these algorithms to the development of drag reduction techniques and the next generation of aircraft with greatly reduced greenhouse gas emissions per passenger-km.

Towards achieving these goals, a number of different projects are being pursued. These include new algorithms for flow evaluation and optimization (including generalized summation-by-parts operators and implicit Runge-Kutta methods), geometry parameterization methodologies such as adaptive and progressive parameterization, and the application of these tools to the optimization of various unconventional aircraft configurations including box-wings, hybrid wing-bodies, lifting fuselage configurations, and truss-braced wings and to the investigation of active flow control techniques for drag reduction.

Group website: http://www.waves.utoronto.ca/prof/sarris

Field(s): Computational Fluid Dynamics, Optimization, Uncertainty Quantification

Our research covers fundamental aspects and advanced applications of numerical electromagnetics, related to emerging wireless communication and sensing technologies.

Emphasis is given on the formulation of high-order finite-difference methods, enhanced stability time-stepping schemes, multi-grid methods, uncertainty quantification and convex optimization techniques, as well as ray tracing and parabolic equation methods. These fundamental advances are applied to large-scale propagation problems arising in wireless communication channel modeling, propagation and radiation properties of meta-materials and meta-material/meta-surface based waveguides and antennas, as well as the design optimization of touch panel sensors, wireless power transfer and microwave hyperthermia systems.

Group website: http://bussmann.mie.utoronto.ca/

Field(s): Computational Fluid Dynamics, Thermofluids

Fluid-fluid interfaces play a dominant role in the behaviour of many industrial processes, in particular those that involve the coating (wetting) or separation (de-wetting) of solids. Examples of such processes include the extraction of bitumen from the tar sands, fabrication by ink-jet printing, drug delivery from micro- and nano-capsules, production of food such as ice cream and the stabilization of foams and emulsions.

The Interfacial Flow Laboratory is dedicated to the development of multiphase algorithms for laboratory scale simulation of multiphase flows. Such phenomena include, but are not limited to, contact angle dynamics, particulate flows, surface tension dominated flows, Marigoni flows and many others. Several computational codes have been developed for modelling such phenomena using accurate state of the art interface advection schemes and surface tension models primarily based on Volume-of-Fluid (VOF) formulations.

Additionally, the group focuses on applied areas such as modelling the production of paper/pulp, steam soot blowers, bitumen extraction and other industrial processes using available commercial and open source Computational Fluid Dynamics (CFD) software. The group has several industrial and academic collaborators. The group is lead by Professor Markus Bussmann.

Group website: http://modelics.utoronto.ca

Field(s): Computational Electromagnetics, Computational Fluid Dynamics, Model Order Reduction

The Modeling Engineering and Living Complex Systems (MODELICS) lab focuses on the computational modeling of complex systems arising in electrical engineering and in the life sciences.

Modeling techniques play nowadays a crucial role in engineering, and are becoming increasingly important in medicine. However, many systems of practical interest are extremely complex. An example is a modern microprocessor, which can include billions of transistors and millions of tiny wires that distribute signals and power. Another example is the human cardiovascular system, whose total length is about 100,000 km (2.5 times the circumference of the earth).

At MODELICS, we invent new computational algorithms for the modeling and simulation of highly-complex systems. Our expertise includes:

• computational electromagnetism (integral equations and finite difference methods),
• circuit simulation,
• model order reduction,
• computational fluid dynamics.

The algorithms developed by the MODELICS laboratory are applied to:

• the computer aided design of integrated circuits and printed circuit boards,
• the design of advanced antennas and metamaterials,
• the modeling of power cables for energy distribution,
• the simulation of blood flow in the human circulatory system in presence of cardiovascular diseases.

Group website: http://bazylak.mie.utoronto.ca/

Field(s): Advanced Materials, Thermofluids

The Thermofluids for Energy and Advanced Materials (TEAM) Laboratory focuses on the study and utilization of microfluidic and nanofluidic transport phenomena to achieve unique material designs, operation strategies, and water management techniques for clean energy technologies. In particular, we investigate thermofluidic transport in the porous media of polymer electrolyte membrane (PEM) fuel cells, PEM electrolyzers, and microfluidic fuel cells to achieve improved performance and design, as well as in geologic formations for carbon sequestration for long-term stability evaluation.