Systems Seminar - Larry Biegler: New Paradigms for Optimization of Chemical and Energy Processes

Optimization models are encountered in all facets of process engineering, from model and process development, to process synthesis and design, and finally to process operations, control, scheduling and planning. Challenges include synthesis of efficient, reliable optimization strategies that can be embedded within the work process, providing sensitivity of the optimal solution to exogenous inputs, and robustness of the solution to uncertainties. This talk discusses three new paradigms that lead to significant advances to address these challenges. First, equation-oriented (EO) optimization strategies have led to the solution of problems with potentially millions of variables and thousands of degrees of freedom. Second, enabling NLP tools handle optimization models with complementarity conditions can model nonsmooth switches as well as phase changes in equilibrium systems, which arise in in distillation columns, pipelines, complex heat exchangers and reservoir models. Finally, detailed models for molecular dynamics, density functional theory or computational fluid dynamics (CFD) resist reformulation in EO form and are often handled through reduced models (RMs). Recently, RM-based trust region frameworks have been developed that guarantee convergence to the optimum of the original detailed model (ODM), through the solution of RM-based trust region strategies with recourse to ODM evaluatons. These new approaches will been demonstrated on process flowsheets that include detailed PDE models, including CFD models.