(6x) Linear and Non-Linear Programming Techniques for System Identification and Green Engineering Applications

My research focuses on linear programming (LP) and non-linear programming (NLP) techniques for system identification and green engineering applications. To this end, I have explored interval analysis-based branch-and-bound techniques for parameter identification, assessment/synthesis of sustainable systems, graphical/analytical techniques for the global solution of the total annualized cost problem for a series of compressors, and the introduction of the novel concept of the attainable region for process networks. Throughout the course of my work, I have experienced first-hand the “curse of dimensionality” prevalent in non-linear optimization algorithms. Thus, I have applied analytical techniques, dimensionality reduction, convexification strategies, and functional analysis to identify global optima and to enhance the efficiency of their computation.

My global optimization expertise has prepared me well to pursue new research avenues in several areas, particularly optimal system identification, initial project feasibility assessment via attainable region concepts, and sustainability assessment and decision making. My strong mathematical and computational background will also allow me to contribute to collaborations that can benefit from this kind of expertise. Furthermore, I will disseminate all developed concepts and lessons learned into course-friendly materials to provide students opportunities to apply basic chemical engineering and optimization concepts to real-world green engineering problems.