Tag: Conference Presentation

Stinchfield, S. Jan, J.C. Morgan, M.A. Zamarripa, C.D. Laird. “An Optimization Formulation for Designing Process Families with Cost Savings from Economies of Numbers”, Abstract accepted to Foundations of Computer Aided Process System Design (FOCAPD), 2024.

Stinchfield, J.P. Watson, Carl D. Laird, “Progressive Hedging Decomposition for Solutions of Large-Scale Process Family Design Problems”, Abstract accepted to the joint conference of the European Symposium on Computer Aided Process Engineering (ESCAPE) and Process Systems Engineering (PSE) 2024.

Stinchfield, J.C. Morgan, M.A. Zamarripa, C.D. Laird. “Economies of Numbers Formulations for Optimal Process Family Design of Carbon Capture Systems.” Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023.

Giridhar, N., Q.M. Le, D. Bhattacharyya, D.A. Allan, and S.E. Zitney, “Optimal Operation of Solid Oxide Electrolysis Cell Considering Long Term Physical and Chemical Degradation and System Performance,” Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023.

Giridhar, N., Q.M. Le, D. Bhattacharyya, D.A. Allan, and S.E. Zitney, “Dynamic Modeling of the Synergistic Effects of Chemical and Thermo-Mechanical Degradation of Solid Oxide Cells,” Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023.

Cho, S., J. Tovar-Facio, I.E. Grossmann, B.P. Omell, C.D. McLean, R. Tumbalam-Gooty, P.A. Tominac, A.P. Burgard, J.D. Siirola, J. Shinn, “Optimization of Infrastructure Planning of Reliable and Carbon-neutral Power Systems: Application to San Diego County,” Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023

Beahr, D., D. Bhattacharyya, D.A. Allan, and S.E. Zitney, “Augmented Control Using Reinforcement Learning and Conventional Process Control,” Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023.

L. Ammari, E.S. Johnson, G. Stinchfield, T. Kim, M. Bynum, W.E. Hart, J. Pulsipher, C.D. Laird, “Mixed-Integer Programming Representations of Linear Model Decision Tree Surrogates”, Abstract accepted to AIChE Annual Meeting, Orlando, FL, November 5-10, 2023.

Bayramoglu, S., G. Nemhauser, and N. Sahinidis, “Learning to Branch with Interpretable Machine Learning Models”, 2023 INFORMS Annual Meeting, Phoenix, AZ, October 15-18, 2023.

S. Zitney, “Multi-scale Modeling and AI/ML Tools for the Optimization of Advanced Energy Systems”, SAMI Tech Talk, Aug 16, 2023.

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