University of Waterloo
Engineering 6 (E6)
Phone: 519-888-4567
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Contact the Department of Chemical Engineering
Friday, January 29, 2016 — 1:45 PM EST
ABSTRACT: Thin porous materials are found in many critical applications such as battery and fuel cell electrodes, wound dressings, filtration membranes, fabrics and paper, to name a few. The standard body of porous media techniques and theories have been developed for rock and soil pertaining to reservoirs and aquifers. Consequently, studying transport processes in thin porous materials generally requires developing new approaches, both experimental and modeling.
Friday, January 22, 2016 — 1:45 PM EST
ABSTRACT: Lattice Boltzmann methods, due to their amenability to parallelization and ability to handle geometrically complex boundaries, are appealing for simulating flows with particles, droplets, and bubbles when experimental observations and manipulations are not possible. This talk will present recent advances in the use of these methods for simulating droplet coalescence and particle motion in confined geometries.
Friday, January 15, 2016 — 1:45 PM EST
ABSTRACT: Molecular transport spanning multiple phases and drastically different length scales occurs in our daily life and controls our health and surrounding environment; such transport phenomena include greenhouse gas generation from combustion of fossil fuels and drug transport and delivery within the human body.
Thursday, January 14, 2016 — 2:30 PM EST
Thursday, January 14, 2016 — 9:30 AM EST
Friday, January 8, 2016 — 1:30 PM EST
Thursday, January 7, 2016 — 3:30 PM EST
ABSTRACT: With the advent of the Internet of Things (IoT), smart devices and smart manufacturing, the amount of data collection has grown exponentially in a manner analogous to the Moore's law. The explosion in data availability, variety and size have enabled engineering, medicine, science and finance to heavily invest in data-based learning projects. Some of the successful learning projects, include The Human Genome Project, Google Flu Trends, Tesla Self-Driving Car Project and GE Industrial IoT.