Recent trends on hybrid modeling for Industry 4.0

J Sansana, MN Joswiak, I Castillo, Z Wang… - Computers & Chemical …, 2021 - Elsevier
The chemical processing industry has relied on modeling techniques for process monitoring,
control, diagnosis, optimization, and design, especially since the third industrial revolution …

[HTML][HTML] Maximizing information from chemical engineering data sets: Applications to machine learning

A Thebelt, J Wiebe, J Kronqvist, C Tsay… - Chemical Engineering …, 2022 - Elsevier
It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …

[HTML][HTML] Multi-agent-based energy management of multiple grid-connected green buildings

SS Ghazimirsaeid, MS Jonban… - Journal of Building …, 2023 - Elsevier
Integration of distributed energy resources (DER) in electrical microgrids introduces
residential green buildings (RGB) with a promising decrement in fossil fuel consumption …

Liquid air as an emerging energy vector towards carbon neutrality: A multi-scale systems perspective

M Qi, J Park, I Lee, I Moon - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
Liquid air has recently emerged as a new energy vector that has the ability to reserve
considerable amounts of renewable energy as both cold and power. Liquid air used for …

[HTML][HTML] Process intensification 4.0: A new approach for attaining new, sustainable and circular processes enabled by machine learning

EA López-Guajardo, F Delgado-Licona… - … and Processing-Process …, 2022 - Elsevier
This paper reviews system-level transformations converging into the next generation of
Process Intensification strategies defined as PI4. 0. Process Intensification 4.0 uses data …

[HTML][HTML] A digital twin-based adaptive optimization approach applied to waste heat recovery in green steel production: Development and experimental investigation

L Kasper, P Schwarzmayr, F Birkelbach, F Javernik… - Applied Energy, 2024 - Elsevier
Renewable-dominated power grids will require industry to run their processes in
accordance with the availability of energy. At the same time, digitalization introduces new …

Intensification of catalytic reactors: a synergic effort of multiscale modeling, machine learning and additive manufacturing

M Bracconi - Chemical Engineering and Processing-Process …, 2022 - Elsevier
The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …

A review of ev battery utilization in demand response considering battery degradation in non-residential vehicle-to-grid scenarios

A Leippi, M Fleschutz, MD Murphy - Energies, 2022 - mdpi.com
Integrating fleets of electric vehicles (EVs) into industrial applications with smart grids is an
emerging field of important research. It is necessary to get a comprehensive overview of …

The integration of scheduling and control: Top-down vs. bottom-up

A Caspari, C Tsay, A Mhamdi, M Baldea… - Journal of Process …, 2020 - Elsevier
The flexible operation of continuous processes often requires the integration of scheduling
and control. This can be achieved by top-down or bottom-up approaches. We compare the …

Optimization of co-production air separation unit based on MILP under multi-product deterministic demand

F Kong, Y Liu, L Tong, W Guo, Y Qiu, L Wang - Applied Energy, 2022 - Elsevier
Optimizing gas distribution is one of the most important energy management issues in
process industries such as metallurgy and the chemical industry. The air separation unit …