Category: 2022 Publications

Parker, R., & Biegler, L. T. (2022). Dynamic modeling and nonlinear model predictive control of a moving bed chemical looping combustion reactor. IFAC-PapersOnLine, 55(7), 400-405. https://doi.org/10.1016/j.ifacol.2022.07.476.

Parker, R., Nicholson, B. L., Siirola, J., Laird, C. D., & Biegler, L. T. (2022). An implicit function formulation for nonlinear programming with index-1 differential algebraic equation systems. In Y. Yamashita & M. Kano (Eds.), 14th International Symposium on Process Systems Engineering (PSE2021+), Computer Aided Chemical Engineering, (Vol. 49, pp. 1141-1146). Elsevier. https://doi.org/10.1016/B978-0-323-85159-6.50190-1

Cho, S., Li, C., & Grossmann, I.E. (2022). Recent advances and challenges in optimization models for expansion planning of power systems and reliability optimization. Computers and Chemical Engineering, 165, 1079245. https://doi.org/10.1016/j.compchemeng.2022.107924

Okoli, C. O., Parker, R., Chen, Y., Ostace, A., Lee, A., Bhattacharyya, D., Tong, A., Biegler, L. T., Burgard, A. P., & Miller, D. C. (2022). Application of an equation-oriented framework to the formulation and parameter estimation of chemical looping reaction kinetic models. AIChE Journal 2022, 68(10). https://doi.org/10.1002/aic.17796

Sauk, B., & Sahinidis, N. V. (2022). Hyperparameter tuning of programs with HybridTuner. Annals of Mathematics and Artificial Intelligence, 91, 133–151. https://doi.org/10.1007/s10472-022-09793-3

Eslick, J. C., Zamarripa, M. A., Ma, J., M. Wang, M., Bhattacharya, I., Rychener, B., Pinkston, P., Bhattacharyya, D., Zitney, S. E., Burgard, A. P., & Miller, D. C. (2022). Predictive modeling of an existing subcritical pulverized-coal power plant for optimization: data reconciliation, parameter estimation, and validation. Applied Energy, 319. https://doi.org/10.1016/j.apenergy.2022.119226.

Biegler, L. T., D. C. Miller, D. C., & Okoli, C. O. (2022). Don’t search – Solve! Process optimization modeling with IDAES. In Bortz, M., & Asprion, N. (Eds.), Simulation and Optimization in Process Engineering, (pp. 33-53). Elsevier. https://doi.org/10.1016/B978-0-323-85043-8.00005-2

Eslick, J., Noring, A., Susarla, N., Okoli, C., Allan, D., Wang, M., Ma, J., Zamarripa, M., Iyengar, A., & Burgard, A. (2022). Technoeconomic evaluation of solid oxide fuel cell hydrogen-electricity co-generation concepts (DOE/NETL-2023/4322). Pittsburgh, PA: National Energy Technology Laboratory, U.S. Department of Energy. https://www.osti.gov/biblio/1960782

Ostace, A., Chen, Y., Parker, R., Okoli, C. O., Lee, A., Tong, A., Fan, L.-S., Biegler, L. T., Burgard, A. P., Miller, D. C., Mebane, D. S., & Bhattacharyya, D. (2022). Kinetic model development and Bayesian uncertainty quantification for the complete reduction of Fe-based oxygen carriers for chemical looping combustion. Chemical Engineering Science, 252. https://doi.org/10.1016/j.ces.2022.117512

Yin, X., & Gounaris, C. E. (2022). Search methods for inorganic materials crystal structure prediction. Current Opinion in Chemical Engineering, 35. https://doi.org/10.1016/j.coche.2021.100726

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