Multi-Scale Modeling and Optimization for Electrification-based Decarbonization of the Chemical Industry
Thursday, September 17, 2026;
10:35am
Capone Learning Auditorium (CBEB 001)
Speaker: Dharik Mallapragada from New York University - NYU
The continued expansion of variable renewable electricity (VRE) deployment in the power grid is spurring interest in electrification-based decarbonization of chemical processes, which can take multiple forms including electrification of process heat and electrochemical systems that use electricity as the driving force for chemical reactions. These technology options must be evaluated alongside the operational dynamics of grids, which are simultaneously accommodating growing VRE supply and increasing demands from other end-uses (e.g., AI data centers). Here, we discuss the use of multi-scale modeling and optimization methods to inform the design of electrification technologies and their integration within industrial processes and the grid.
First, we discuss the design of internal electric resistance heated reactors for high-temperature, endothermic chemical reactions such as ethane steam cracking to produce ethylene, a key platform chemical. We show that the added design and operational degrees of freedom of such reactors can increase ethylene yields and reduce reactor size compared to conventional fossil-fuel fired reactors. However, these gains could also be accompanied by accelerated cooking, motivating the development of multi-scale, multi-objective optimization methods to evaluate reactor design and operation.
Second, we address a key barrier to industrial electrification-based decarbonization: accessing sufficient quantities of clean electricity in a cost-competitive manner. We will make the case for a new process design paradigm that departs from the conventional steady-state design basis by accounting for the value of operational flexibility in response to electricity supply dynamics. Through a water electrolysis case study, we will show how co-optimization of design and operation can identify flexible processes that are more economical than steady-state alternatives. However, achieving low carbon intensity via process electrification during the mid-transition, while the grid remains insufficiently decarbonized, may require additional clean energy procurement on behalf of the consumer. We evaluate different procurement strategies and find that their cost and emissions outcomes are sensitive to process flexibility as well as grid context and associated policies. This underscores the importance of integrated industrial-power system modeling to identify viable electrification pathways.
Dharik S. Mallapragada is an Assistant Professor in the Department of Chemical and Biomolecular Engineering, with a joint appointment in the Center for Urban Science and Progress, at New York University's Tandon School of Engineering. He leads the Sustainable Energy Transitions Group, whose research focuses on the design and optimization of technologies for energy and industrial system decarbonization and on developing computational methods, including open-source energy system models, to analyze how technology, resource constraints, and policies shape the energy transition. Prior to NYU, Prof. Mallapragada was a researcher at the MIT Energy Initiative, where he began his academic research career after spending nearly five years in the energy and chemical industry working on a range of sustainability-focused research topics. Prof. Mallapragada holds an M.S. and Ph.D. in Chemical Engineering from Purdue University and a B.Tech. in Chemical Engineering from the Indian Institute of Technology Madras, India.
Hosted by: Angela Dixon, adc12@psu.edu
How Safe Is Safe Enough? Ensuring Safety and Resilience in Critical Infrastructure Control Systems
Wednesday, September 16, 2026;
3:35-4:25 pm
254 Health and Human Development
Speaker: ROMULO MEIRA GOES from
Abstract: Critical infrastructure control systems (CIS), such as energy, transportation, and manufacturing, are expected to operate safely despite uncertain environments, unexpected failures, cyberattacks, and AI-enabled decision-making. Although modern control and verification techniques can provide safety guarantees, these guarantees are only as reliable as the assumptions on which they are built. In this talk, we focus on three questions: (1) How safe is a system when its environment deviates from the assumptions used during design? (2) Can a system recover safe operation after a disruption while continuing to function? (3) How can we leverage emerging AI technologies without sacrificing safety guarantees?
To address these questions, we use supervisory control theory of discrete-event systems to develop new methodologies for robustness analysis of controllers, recovery strategy synthesis, and AI-assisted decision verification. These methodologies enable engineers to characterize safe operating envelopes of controllers, identify realistic vulnerabilities, design controllers that restore safe operation, and formally validate AI-generated plans before deployment. We demonstrate how these methods enhance the safety and resilience of CIS through case studies in manufacturing systems.
Bio: Rômulo Meira-Góes is an Assistant Professor in the School of Electrical Engineering and Computer Science at the Pennsylvania State University. Previously, he was a postdoctoral researcher working with Eunsuk Kang, Stavros Tripakis, and Stéphane Lafortune at Carnegie Mellon University and the University of Michigan. In 2022, he received the CPS Rising Stars Award from the University of Virginia. He received his Ph.D. in Electrical and Computer Engineering from the University of Michigan in 2020, working with Stéphane Lafortune. Prior to the University of Michigan, he earned his B.S. degree in Electrical Engineering from the Universidade Tecnológica Federal do Paraná - Curitiba in 2015.
Hosted by: Lana Fulton, lub18@psu.edu