Professor Jeffrey Bergthorson, Alternative Fuels Laboratory, McGill University.
In order to address climate change, we must transition to a low-carbon economy. Many clean primary energy sources, such as solar panels and wind turbines, are being deployed and promise an abundant supply of clean electricity in the near future. The key question becomes how to store, transport, and trade this clean energy in a manner that is as convenient as fossil fuels. The Alternative Fuels Laboratory (AFL) at McGill University is actively researching the use of recyclable metal fuels as a key enabling technology for a low-carbon society. Metal fuels, reduced using clean primary energy, have the highest energy density of any chemical fuel and are stable solids, simplifying storage, transport, and trade. This presentation will overview the concept of using metals as circular carbon-free fuels and the methods to harness the chemical energy contained in the metal fuels. Metal particles can ignite and burn as sparks, which act as micro-diffusion reactors that release heat at discrete points. The rapid release of energy from ignited and burning particles leads to a new combustion regime, termed discrete flames, whose rate of propagation is independent of the heat-release rate and which are predicted to exhibit interesting propagation and quenching behavior.
Professor Bob Koch, Departmental of Mechanical Engineering, University of Alberta.
More information is available on his website: https://sites.ualberta.ca/~ckoch/
Hydrogen and Hydrogen/Diesel dual fuel in internal combustion engines are receiving renewed interest due to the requirements in reducing global CO2 emissions. This technology could provide an effective solution for heavy duty applications such as long haul freight trucks. However, due to stringent emission regulations and the requirement to optimize the engine performance and durability, complex and costly engine control systems are needed. A control oriented modeling approach is used to design and test the control in simulation using a combination of simple physics based and data driven models. To implement this complex model based control on an engine in realtime, machine learning methods are used. This speeds up the control calculations so they can be experimentally implemented on a 4.5 liter Diesel engine. A summary of the modeling and control methods and initial engine results will be presented.
Professor Beth Weckman, Department of Mechanical and Mechatronics Engineering, University of Waterloo
Detailed understanding of how parameters such as smoke, heat and toxic gases develop in our modern fire environments is critical to reducing death, injury and losses due to fire, as well as lessening the overall costs of insurance and emergency response. Advancements in the area of fire research, however, can be challenging as they often require use of a multi-scale approach with iterative improvement in insight into fire and combustion dynamics at small scales coupled to examination of how this translates to the behaviour and development of fire environments at larger scales. At large scale, the overall fire environment is also quite variable as it is affected by building design, fuel consumption, fire growth rates and amount of air available. These, in turn, govern the evolution of fire effluents (toxic gases, aerosols) and spread of heat and smoke. Recently, increased use of synthetic polymers has led to fires with potential to grow much faster than those burning traditional materials like wood and cotton. In modern residences, this is coupled with changes in building design to improve energy efficiency which has led to homes with less air exchange to ventilate a fire. Together, fuel type and ventilation affect our modern fire environments but whilst traditional fire environments (well-ventilated and legacy fuels) have been much studied, characterization of fire environments involving newer synthetic fuels and transitions to limited ventilation conditions (significantly decreasing oxygen levels with time) is severely hampered by incomplete data. In part, this is due to challenges associated with conducting experimental research at the novel operating conditions encountered in modern fire environments. Without scientific information on the time-varying fuel burning rates, consequent fire heat release rates and evolution of smoke and gases in these fire situations, significant gaps will remain in our understanding and ability to predict the complex processes driving the behaviour of real-scale fires in modern, ventilation-limited environments. This makes it extremely difficult to critically assess potential changes in fire environments driven by use of new materials, adoption of new technologies or development of design strategies for energy conservation. Yet, knowledge of the evolution of these fire environments has important implications in design, fire fighter tactical decision-making, fire protection equipment and occupant safety.
A large, multi-year, multi-partner study into the behaviour of large-scale residential furniture fires is underway at University of Waterloo (UW) to begin to address this need. The study includes better characterization of different furniture materials and fire retardant strategies, coupled to exploring their impacts on development of ventilation-limited fires that might occur in modern energy efficient homes. Results expand the current database of information on both the fuels and fire environments and, with the knowledge gathered, advance understanding of the complex physical phenomena that drive fire development. This presentation will outline and compare results from several furniture fire tests conducted in the UW two-storey burn house structure, sealed and fitted with ventilation to mimic an energy-efficient residential building. Challenges encountered in developing the instrumentation necessary to track smoke evolution, as well as obtain consistent concentrations of O2, CO, CO2 and minor constituents at various locations through the structure will be outlined. A subset of the resulting data, paired with images from video cameras and more traditional measurements of fuel mass loss, temperature and doorway velocity, will be used to highlight some of the interesting features of the fire environments and flow patterns that occur across furniture designs. Connections between furniture type, ventilation conditions, flow patterns and hot gas migration through the structure paint a more holistic picture of the dynamic fire environment as it develops during these fires. Combined results provide critical data and new scientific insight into fire development which directly support next generation fire simulation, fire safety design and decision-making and, over the longer term, lead to intelligent AI-enabled fire monitoring, control and egress systems.