Recent trends on hybrid modeling for Industry 4.0
The chemical processing industry has relied on modeling techniques for process monitoring,
control, diagnosis, optimization, and design, especially since the third industrial revolution …
control, diagnosis, optimization, and design, especially since the third industrial revolution …
Advances in surrogate based modeling, feasibility analysis, and optimization: A review
A Bhosekar, M Ierapetritou - Computers & Chemical Engineering, 2018 - Elsevier
The idea of using a simpler surrogate to represent a complex phenomenon has gained
increasing popularity over past three decades. Due to their ability to exploit the black-box …
increasing popularity over past three decades. Due to their ability to exploit the black-box …
Bayesian reaction optimization as a tool for chemical synthesis
Reaction optimization is fundamental to synthetic chemistry, from optimizing the yield of
industrial processes to selecting conditions for the preparation of medicinal candidates …
industrial processes to selecting conditions for the preparation of medicinal candidates …
Overview of surrogate modeling in chemical process engineering
K McBride, K Sundmacher - Chemie Ingenieur Technik, 2019 - Wiley Online Library
The ability to accurately model and simulate chemical processes has been paramount to the
growing success and efficiency in process design and operation. These improvements …
growing success and efficiency in process design and operation. These improvements …
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
A hybrid science‐guided machine learning approach for modeling chemical processes: A review
This study presents a broad perspective of hybrid process modeling combining the scientific
knowledge and data analytics in bioprocessing and chemical engineering with a science …
knowledge and data analytics in bioprocessing and chemical engineering with a science …
Evolution of concepts and models for quantifying resiliency and flexibility of chemical processes
This paper provides a historical perspective and an overview of the pioneering work that
Manfred Morari developed in the area of resiliency for chemical processes. Motivated by …
Manfred Morari developed in the area of resiliency for chemical processes. Motivated by …
Obey validity limits of data-driven models through topological data analysis and one-class classification
Data-driven models are becoming increasingly popular in engineering, on their own or in
combination with mechanistic models. Commonly, the trained models are subsequently …
combination with mechanistic models. Commonly, the trained models are subsequently …
Integrating tactical planning, operational planning and scheduling using data-driven feasibility analysis
O Badejo, M Ierapetritou - Computers & Chemical Engineering, 2022 - Elsevier
Supply chain operations and scheduling are well-studied problems in the literature.
Although these problems are related, they are often solved sequentially. This uncoordinated …
Although these problems are related, they are often solved sequentially. This uncoordinated …
A novel feasibility analysis method for black‐box processes using a radial basis function adaptive sampling approach
Z Wang, M Ierapetritou - AIChE Journal, 2017 - Wiley Online Library
Feasibility analysis is used to determine the feasible region of a multivariate process. This
can be difficult when the process models include black‐box constraints or the simulation is …
can be difficult when the process models include black‐box constraints or the simulation is …