My research aims to develop efficient, reliable, and automatable methods for simulation, sensitivity analysis, and optimization of chemical process systems that present numerical difficulties. This work lies at the intersection of process systems engineering, algorithm development, and applied mathematics. Areas of particular interest include:
• nonsmooth optimization, to handle discrete switching in process systems due to changes in phase, flow regime, or operating mode,
• deterministic global optimization, for nonconvex optimization problems arising in process safety, thermodynamics, design, and control, and
• dynamic optimization of batch and semi-batch systems, and for use in process control.
My approach involves adapting, developing, and applying tools such as:
• automatic differentiation, for efficient sensitivity analysis,
• adjoint sensitivity analysis, to reduce the computation required for dynamic optimization,
• convex underestimator generation, to provide useful bounding information for global optimization, and
• nonsmooth analysis, to model switching systems.