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 …
The multi-scale challenges of biomass fast pyrolysis and bio-oil upgrading: Review of the state of art and future research directions
M Sharifzadeh, M Sadeqzadeh, M Guo… - Progress in Energy and …, 2019 - Elsevier
Biomass fast pyrolysis is potentially one of the cheapest routes toward renewable liquid
fuels. Its commercialization, however, poses a multi-scale challenge, which starts with the …
fuels. Its commercialization, however, poses a multi-scale challenge, which starts with the …
Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …
processes in science and engineering. In the current review, we focus on the applications of …
Digital twins in pharmaceutical and biopharmaceutical manufacturing: a literature review
The development and application of emerging technologies of Industry 4.0 enable the
realization of digital twins (DT), which facilitates the transformation of the manufacturing …
realization of digital twins (DT), which facilitates the transformation of the manufacturing …
Deep neural network-based hybrid modeling and experimental validation for an industry-scale fermentation process: Identification of time-varying dependencies …
Kinetic modeling of fermentation processes is difficult due to the use of micro-organisms that
follow complex reaction mechanisms. Kinetic models are usually not perfect owing to …
follow complex reaction mechanisms. Kinetic models are usually not perfect owing to …
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 …
Hybrid modelling of water resource recovery facilities: status and opportunities
Mathematical modelling is an indispensable tool to support water resource recovery facility
(WRRF) operators and engineers with the ambition of creating a truly circular economy and …
(WRRF) operators and engineers with the ambition of creating a truly circular economy and …
[HTML][HTML] Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems
The increasing availability of data, due to the adoption of low-cost industrial internet of things
technologies, coupled with increasing processing power from cloud computing, is fuelling …
technologies, coupled with increasing processing power from cloud computing, is fuelling …
Integrating process dynamics in data-driven models of chemical processing systems
Data-driven models require high-fidelity data of sufficient quantity and granularity. This is
challenging in a complex chemical processing system due to frequent sensor breakdown …
challenging in a complex chemical processing system due to frequent sensor breakdown …
A framework of hybrid model development with identification of plant‐model mismatch
Y Chen, M Ierapetritou - AIChE Journal, 2020 - Wiley Online Library
Hybrid modeling has attracted increasing attention in order to take advantage of the
additional data to improve process understanding. Current practice often adopts mechanistic …
additional data to improve process understanding. Current practice often adopts mechanistic …