Kimberley B. McAuley, Queen’s University
Chemical Engineering
Professor
Kingston, Ontario
kim.mcauley@chee.queensu.ca
Office:
(613) 533-6000 ext. 32768
Expert In
Bio/Research
Kim McAuley's research group develops mathematical models of chemical and biochemical processes. Her students derive equations to describe rates of chemical reactions and the movement of chemical species and energy within multi-phase systems. The models are used by companies and other academic re...
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Bio/Research
Kim McAuley's research group develops mathematical models of chemical and biochemical processes. Her students derive equations to describe rates of chemical reactions and the movement of chemical species and energy within multi-phase systems. The models are used by companies and other academic researchers to predict product quality, production rates and the effectiveness of operating and control strategies. Some models also help medical physicists understand the influence of chemistry on the effectiveness of gel dosimeters used for 3-D verification of radiation doses for cancer treatment.
One of the most difficult problems faced by modelers is determining appropriate values for parameters that appear in model equations. Prof. McAuley leads a research project on Advanced Parameter Estimation Tools for Building Mathematical Models of Chemical Processes, which is sponsored by MITACS and several companies. Models are being developed to help companies simulate, monitor, optimize and control their industrial processes and novel methods are being developed for estimating parameters in a variety of challenging situations including:
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One of the most difficult problems faced by modelers is determining appropriate values for parameters that appear in model equations. Prof. McAuley leads a research project on Advanced Parameter Estimation Tools for Building Mathematical Models of Chemical Processes, which is sponsored by MITACS and several companies. Models are being developed to help companies simulate, monitor, optimize and control their industrial processes and novel methods are being developed for estimating parameters in a variety of challenging situations including:
Click to Shrink <<