1. Introduction to Integrated Process Modeling, Advanced Control, and Data Analytics in Optimizing Polyolefin Manufacturing2. Selection of Property Methods and Estimation of Physical Properties for Polymer Process Modeling3. Reactor Modeling, Convergence Tips and Data-Fit Tool4. Free Radical Polymerizations: LDPE and EVA5. Ziegler-Natta Polymerization: HDPE, PP, LLPDE and EPDM6. Free Radical and Ionic Polymerizations: PS and SBS Rubber7. Improved Polymer Process Operability and Control through Steady-State and Dynamic Simulation Models8. Model-Predictive Control of Polyolefin Processes9. Application of Multivariate Statistics to Optimizing Polyolefin Manufacturing10. Applications of Machine Learning to Optimizing Polyolefin Manufacturing11. A Hybrid Science-Guided Machine Learning Approach for Modeling Chemical and Polymer Processes
Y.A. Liu, Alumni Distinguished Professor at Virginia Tech, is an award-winning teacher of sustainable design and practice, and industrial sustainable design projects. American Society for Engineering Education honored Liu with the George Westinghouse Award for excellence in engineering education and Fred Merryfield Design Award for excellence in teaching and research of sustainable design. The Chemical Manufacturers Association honored Liu with the National Catalyst Award for excellence in chemical education. Niket Sharma received his PhD in chemical engineering and M. Eng. in computer science with specialization in machine learning from Virginia Tech in 2021. He is currently a Senior Engineer at Aspen Technology, Boston, where he is working on the development of machine learning and hybrid modeling applications combining chemical engineering and data science principles. His Ph.D. dissertation focused on integrated process modelling and big data analytics for optimizing polyolefin manufacturing.