Reference author: Donovan Chaffart

Chaffart, D. ., Rasoulian, S. ., & Ricardez-Sandoval, L. A. (2016). Distributional uncertainty analysis and robust optimization in spatially heterogeneous multiscale process systems. AIChE Journal, 62, 2374-2390. https://doi.org/10.1002/aic.15215

Wang, H. ., Chaffart, D. ., & Ricardez-Sandoval, L. A. (2019). Modelling and optimization of a pilot-scale entrained flow gasifier using artificial neural networks. Energy, 188. Retrieved from https://www.sciencedirect.com/science/article/pii/S0360544219317712 (Original work published 2019)

Chaffart, D. ., & Ricardez-Sandoval, L. A. (2018). Optimization and control of a thin film growth process: A hybrid first principles/artificial neural network based multiscale modelling approach. Computers & Chemical Engineering, 119. Retrieved from https://www.sciencedirect.com/science/article/pii/S0098135418306379 (Original work published 2018)

Chaffart, D. ., & Ricardez-Sandoval, L. A. (2018). Robust optimization of a multiscale heterogeneous catalytic reactor system with spatially-varying uncertainty descriptions using polynomial chaos expansions. The Canadian Journal of Chemical Engineering, 96, 113-131. https://doi.org/10.1002/aic.15215

Chaffart, D. ., & Ricardez-Sandoval, L. A. (2017). Robust dynamic optimization in heterogeneous multiscale catalytic flow reactors using polynomial chaos expansion. Journal of Process Control, 60, 128-140. https://doi.org/10.1016/j.jprocont.2017.07.002

Kimaev, G. ., Chaffart, D. ., & Ricardez-Sandoval, L. A. (2020). Multilevel Monte Carlo applied for uncertainty quantification in stochastic multiscale systems. AIChE Journal, 66. Retrieved from https://aiche.onlinelibrary.wiley.com/doi/full/10.1002/aic.16262 (Original work published 2020)

Chaffart, D. ., Shi, S. ., Ma, C. ., Lv, C. ., & Ricardez-Sandoval, L. A. (2023). A semi-empirical force balance-based model to capture sessile droplet spread on smooth surfaces: A moving front kinetic Monte Carlo study. Physics of Fluids, 35. Retrieved from https://aip.scitation.org/doi/full/10.1063/5.0139638 (Original work published 2023)

Guan, Y. ., Chaffart, D. ., Liu, G. ., Tan, Z. ., Zhang, D. ., Wang, Y. ., Li, J. ., & Ricardez-Sandoval, L. A. (2022). Machine learning in solid heterogeneous catalysis: Recent developments, challenges and perspectives. Chemical Engineering Science, 248. Retrieved from https://www.sciencedirect.com/science/article/pii/S0009250921007892 (Original work published 2022)

Chaffart, D. ., Shi, S. ., Ma, C. ., Lv, C. ., & Ricardez-Sandoval, L. A. (2022). A Moving Front Kinetic Monte Carlo Algorithm for Moving Interface Systems. The Journal of Physical Chemistry B, 126. Retrieved from https://pubs.acs.org/doi/full/10.1021/acs.jpcb.1c10389 (Original work published 2022)

Chaffart, D. ., & Ricardez-Sandoval, L. A. (2022). A three dimensional kinetic Monte Carlo defect-free crystal dissolution model for biological systems, with application to uncertainty analysis and robust optimization. Computers & Chemical Engineering, 157. Retrieved from https://www.sciencedirect.com/science/article/pii/S0098135421003641 (Original work published 2022)