Afzali, Sayyed Faridoddin
Farahani, Farhang Jalali
Khan, Kamil A.
MacGregor, John F.
Madabhushi, Pranav Bhaswanth
Marlin, Thomas E.
Okeke, Ikenna J.
Sudaresan Ramesh, Praveen
Swartz, Chris L. E.
Supervised by Dr. Chris Swartz
B.Sc. Chemical Engineering, University of Waterloo (2006)
M.A.Sc. Chemical Engineering, University of Waterloo (2008)
PhD Chemical Engineering, McMaster University (2016)
Engineering Co-op Student: Sanofi Pasteur Ltd., Toronto ON (2005)
Engineering Co-op Student: Apotex Inc., Toronto ON (2005)
Research Assistant: Stuart Energy Systems Corp., Mississauga ON (2004)
Large-scale dynamic optimization for design and operation of chemical processes
Our research is focused on the development of optimization-based solution techniques for design and operation of large-scale processes that are described using differential-algebraic equations (DAEs). In particular, the integrated design and control (IDC) of chemical processes has long been shown to be an affective approach for establishing agile plant designs. Current solution implementations that utilize dynamic optimization techniques have shown to be highly effective at simultaneously estabilishing economic and performance concious process designs. This has lead to larger plantwide applications of IDC which are highly computationally demanding, particularly when uncertainty is included and a multi-scenario dynamic optimization solution strategy is adopted. To combat the growing intractability of such multi-scenario formulations, our research seeks to investigate and develop solution strategies that incorporate decomposition techniques to break the otherwise large problem into several smaller and managable pieces that can be solved using parallel computing techniques.
- Washington, I., Swartz, C. L. E. A parallel structure exploiting nonlinear programming algorithm for multiperiod dynamic optimization, Computers & Chemical Engineering,, 103 151-164 (2017) [ Publisher Version ]
- Washington, I., Swartz, C. L. E. Multi-Period Dynamic Optimization for Large-Scale Differential-Algebraic Process Models under Uncertainty, Processes,, 3 (3) 541-567 (2015) [ Publisher Version| Open Access Version (free) ]
- Washington, I., Swartz, C. L. E. Design under uncertainty using parallel multi-period dynamic optimization, AIChE Journal, (2014) [ Publisher Version ]
Washington, I.D., T.A. Duever, and A. Penlidis. Mathematical Modeling of Acrylonitrile-Butadiene Emulsion Polymerization: Model Development and Validation. J. Macromol. Sci., Part A: Pure and Applied Chemistry, 47(8): 747-769, 2010.Conference Presentations
Washington, I.D. and C.L.E. Swartz, Parallel Computing Strategies for Large-Scale Dynamic Optimization Under Uncertainty, 2013 AIChE Annual Meeting, November 3-8, 2013. San Francisco, CA, USA.
Washington, I.D. and C.L.E. Swartz, Optimization of Large-Scale DAE Systems in Process Design & Control, International Conference of Applied Mathematics, Modeling and Computational Science (AMMCS) 2013, August 26-30, 2013. Waterloo, ON, Canada.
Washington, I.D. and C.L.E. Swartz, Optimal Design & Operation of Large-Scale Chemical Processes, 62nd Canadian Chemical Engineering Conference, October 15-17, 2012. Vancouver, BC, Canada.
Washington, I.D. and C.L.E. Swartz. On the Numerical Robustness of Differential-Algebraic Distillation Models. 61st Canadian Chemical Engineering Conference, October 23-26, 2011. London, ON, Canada.