(6ci) New Frontiers in Process Systems Engineering for Large Multiscale Chemical and Energy Networks

Research Interests: My research lies in the field of process systems engineering (PSE), and the overarching theme of my proposed research plan is to develop computational decision making tools to design and operate chemical, energy, biochemical, and agricultural systems in a sustainable and economic manner. Modern chemical plants contain nonlinear phenomena which occur on a wide range of spacial and temporal scales, and my future research aims to develop new theory and methods which can solve large, nonlinear, and multiscale optimization problems in a computationally efficient manner. Such multiscale problems often have multiple layers of optimization, and by recognizing the parallels between an optimization problem and a dynamic system, which both have inputs, state (dynamic system) or decision (optimization problem) variables, and outputs which are functions of these variables, one may be able to predict a priori the relationships between inputs and outputs of the inner optimization problems and reduce the difficulty required to solve the overall problem.

Building understanding of the interactions present in large scale systems through the PSE theory and tools I aim to develop is essential in bridging the so-called “valley of death” in scientific funding of new processes and products, thus enabling the transition of these new ideas from something that works great in a lab to something that can be made at scale sustainably and efficiently to make a difference in people’s lives. As such, I will always aim to forge collaborations with my future experimental colleagues to find relevant applications for the theory I develop. PSE tools are widely applicable to, for example, the production of new life-saving drugs, the incorporation of a new type of catalyst or chemical reactor in a chemical plant, or the implementation of a new type of battery into the power grid.

My previous research at the University of Minnesota demonstrates my ability for developing decision making tools for the specific application of combined chemical and renewable energy production. I have developed powerful optimization models which enable decision making for plant design[1], facility placement within a supply chain[2], and system operation[3]. Through this work, I was able to elucidate synergies between the chemical and renewable energy subsystems and take advantage of them for efficient operation and design, as well as better understand the tradeoffs of centralized vs. distributed production within a chemical supply chain. I also developed multiple new methods to improve the computational tractability of these and other optimization problems: first, I developed a community based approach which breaks down a large problem into smaller subproblems by finding groups that tightly interact internally but weakly interact with other groups[4,5]. Next, I developed a method for designing systems with time-varying operation whereby operating decisions are made independently from and used to inform design decisions [6]. This work has been recognized by multiple conference travel grants and best presentation awards.

Teaching Interests: My passion for teaching goes back to my childhood years where I would always check over my brother’s homework every night and explain to him when he did things incorrectly. I believe an effective teacher in chemical engineering needs to give each student two things: the knowledge of a “toolbox” that they can use to approach any problem that they may face in their career, and the wisdom to know which tool to use in which situation. I believe effective written and verbal communication is essential in achieving both of these goals and aim to make developing effective communication skills a key outcome for students in all classes I teach and the research group I lead. In my previous experience, I have TA’ed graduate courses in both linear algebra and transport phenomena. In both courses I have developed a comprehensive text document of lecture notes and problem solutions and been recognized with the department outstanding TA award. I have also taught recitations for the undergrad process control course, where I helped to develop recitation problems, taught two sections two times a week, and received an SRT average rating of 5.57/6. For my future teaching plans, I would feel confident teaching any of the core chemical engineering courses, although I have the most expertise in applied mathematics and control. I would also be interested in developing an “applied math and optimization in chemical engineering” course to be taken by seniors and first year graduate students for departments that do not already have a similar offering.

References

[1] Allman, A., Daoutidis, P. Optimal design of synergistic distributed renewable fuel and power systems. Renewable Energy (100), 2017, 78-89.

[2] Allman, A., Tiffany, D., Kelley, S., Daoutidis, P. A framework for ammonia supply chain optimization incorporating conventional and renewable generation. AIChE Journal (63), 2017, 43904402.

[3] Allman, A., Daoutidis, P. Optimal scheduling for wind-powered ammonia generation: effects of key design parameters. Chemical Engineering Research and Design (131), 2018, 5-15.

[4] Tang, W., Allman, A., Pourkargar, D.B., Daoutidis, P. Optimal decomposition for distributed optimization in nonlinear model predictive control through community detection. Computers and Chemical Engineering (111), 2018, 43-54

[5] Allman, A., Tang, W., Daoutidis, P. Towards a generic algorithm for identifying high-quality decompositions of optimization problems. In Proc. of the 13th International Symposium on Process Systems Engineering (2018).

[6] Allman, A., Palys, M.J., Daoutidis, P. Scheduling-informed optimal design of systems with time-varying operation: A wind-powered ammonia case study. AIChE Journal, 2018, submitted.