1. T. Varelmann, J. I. Otashu, K. Seo, A. Mitsos, M. Baldea, A Decoupling Strategy for Protecting Sensitive Information in Cooperative Optimization of Power Flow, AIChE Journal, 68(1), e17429, Jan. 2022 https://doi.org/10.1002/aic.17429
2. T. Varelmann, A. Lipow, M. Baldea, A. Mitsos, Advanced Feasibility Cuts in Decoupled Cooperative Optimization of Power Flow, Computers & Chemical Engineering, 157, 107635, Jan. 2022 https://doi.org/10.1016/j.compchemeng.2021.107635
3. M. T. Kelley, T. T. Do, M. Baldea, Evaluating the Demand Response Potential of Ammonia Plants, AIChE Journal, 68(3), e17552, Mar. 2022 https://doi.org/10.1002/aic.17552 (Editor’s Choice Article)
4. F. Lejarza, M. Baldea, An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products, European Journal of Operational Research, 297(3), 890-903, Mar. 2022 https://doi.org/10.1016/j.ejor.2021.04.057
5. M. T. Kelley, C. Tsay, Y. Cao, Y. Wang, J. Flores-Cerrillo, M. Baldea, A data-driven linear formulation of the optimal demand response scheduling problem for an industrial air separation unit, Chemical Engineering Science, 252, 117468, Apr. 2022 (Invited paper for the Special Issue on Digitalisation) https://doi.org/10.1016/j.ces.2022.117468
6. F. Lejarza, M. Baldea, Discovering governing equations via moving horizon learning: the case of reacting systems, AIChE Journal, 68(6), e17567, Jun. 2022 https://doi.org/10.1002/aic.17567 (invited paper for Special Issue on Artificial Intelligence in Chemical Engineering)
7. F. Lejarza, M. T. Kelley, M. Baldea, Closed-loop, feedback-based deterministic optimization is a robust approach for supply chain management under demand uncertainty, Industrial & Engineering Chemistry Research, 61(33),12153-12169 (Invited paper for the Special Issue honoring Joan F. Brennecke) https://doi.org/10.1021/acs.iecr.2c00099
8. I. Giannikopoulos, A. Skouteris, T. F. Edgar, M. Baldea, D. T. Allen, and M. A. Stadtherr, Probing the Impact of an Energy and Transportation Paradigm Shift on the Petrochemicals Industry, Industrial & Engineering Chemistry Research, 61(33), 12169-12179, May 2022 (Invited paper for the Special Issue honoring Joan F. Brennecke) https://doi.org/10.1021/acs.iecr.2c00309
9. F. Lejarza, M. Baldea, Data-Driven Discovery of Governing Equations for Dynamical Systems via Sparse Moving Horizon Optimization, Scientific Reports, 12, 11836, July 2022, https://doi.org/10.1038/s41598-022-13644-w
10. O. Santander, V. Kuppuraj, C. A. Harrison, M. Baldea, An open source FCC model to support developing and benchmarking process control and operations strategies, Computers & Chemical Engineering, 164, 107900, 2022, https://doi.org/10.1016/j.compchemeng.2022.107900
11. O. Santander, V. Kuppuraj, C.A. Harrison, M. Baldea, Integrated deep learning – production planning – economic model predictive control framework for large-scale processes. A fluid catalytic cracker – fractionator case study, Computers & Chemical Engineering, 167, 107977, Nov 2022, https://doi.org/10.1016/j.compchemeng.2022.107977
12. O. Santander, G. Giannikopoulos, M. A. Stadtherr, M. Baldea, An Integrated Stochastic Deep Learning – Short term Production Scheduling – Optimal Control Framework for General Batch Processes, Industrial & Engineering Chemistry Research, accepted https://doi.org/10.1021/acs.iecr.2c02638
13. O. Santander, V. Kuppuraj, C.A. Harrison, M. Baldea, Integrated production planning and model predictive control of a fluidized bed catalytic cracking – fractionator unit, Industrial & Engineering Chemistry Research, accepted 11/08/2022
14. X. Tang, M. Baldea, A Grid View on the Dynamics of Manufacturing Processes Participating in Demand Response Programs, Computers & Chemical Engineering, accepted 11/20/2022
