Toward predictive multiscale models for HiGee devices
- Author
- Bing Wang (UGent) , Siyuan Chen (UGent) , Hamed Hoorijani (UGent) , Qingang Xiong, Kevin Van Geem (UGent) and Yi Ouyang (UGent)
- Organization
- Project
-
- Francqui Start-Up Grant
- IGNITE – Innovative Gas-Liquid Systems: Visualization and Modelling for Electrified Reactor Design
- Electrification of thermocatalytic decomposition of methane using computational fluid dynamics
- OPTIMA - Optimal CO2 post-combustion capture process through advanced thermal integration and vortex technology
- Abstract
- High gravity (HiGee) devices exploit centrifugal fields and layers, enlarges interfacial areas, and accelerates mixing, heat, and mass transfer, increasing rates in fast reaction systems. A workflow links mechanistic descriptions, computational fluid dynamics reactor simulations, and process-level simulations while identifying gaps at interfaces where turbulence, mass transfer, and kinetics dominate. Priorities include rotation-aware turbulence closures, turbulence-chemistry interaction models for gas-liquid flows, and subgrid or molecular descriptions for reduced-order and process models. Advances drawing on combustion and aerothermodynamics will enable predictive design and scale-up of HiGee devices.
- Keywords
- LIQUID FLOW, SIMULATION, BED, CFD, ABSORPTION, TURBULENCE, KINETICS, MEA
Downloads
-
(...).pdf
- full text (Published version)
- |
- UGent only
- |
- |
- 2.26 MB
-
(...).docx
- full text (Accepted manuscript)
- |
- UGent only (changes to open access on 2026-08-06)
- |
- Word
- |
- 1.45 MB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01KKVCS3D92FRP5Y40JC5H709V
- MLA
- Wang, Bing, et al. “Toward Predictive Multiscale Models for HiGee Devices.” CURRENT OPINION IN CHEMICAL ENGINEERING, vol. 51, 2026, doi:10.1016/j.coche.2026.101230.
- APA
- Wang, B., Chen, S., Hoorijani, H., Xiong, Q., Van Geem, K., & Ouyang, Y. (2026). Toward predictive multiscale models for HiGee devices. CURRENT OPINION IN CHEMICAL ENGINEERING, 51. https://doi.org/10.1016/j.coche.2026.101230
- Chicago author-date
- Wang, Bing, Siyuan Chen, Hamed Hoorijani, Qingang Xiong, Kevin Van Geem, and Yi Ouyang. 2026. “Toward Predictive Multiscale Models for HiGee Devices.” CURRENT OPINION IN CHEMICAL ENGINEERING 51. https://doi.org/10.1016/j.coche.2026.101230.
- Chicago author-date (all authors)
- Wang, Bing, Siyuan Chen, Hamed Hoorijani, Qingang Xiong, Kevin Van Geem, and Yi Ouyang. 2026. “Toward Predictive Multiscale Models for HiGee Devices.” CURRENT OPINION IN CHEMICAL ENGINEERING 51. doi:10.1016/j.coche.2026.101230.
- Vancouver
- 1.Wang B, Chen S, Hoorijani H, Xiong Q, Van Geem K, Ouyang Y. Toward predictive multiscale models for HiGee devices. CURRENT OPINION IN CHEMICAL ENGINEERING. 2026;51.
- IEEE
- [1]B. Wang, S. Chen, H. Hoorijani, Q. Xiong, K. Van Geem, and Y. Ouyang, “Toward predictive multiscale models for HiGee devices,” CURRENT OPINION IN CHEMICAL ENGINEERING, vol. 51, 2026.
@article{01KKVCS3D92FRP5Y40JC5H709V,
abstract = {{High gravity (HiGee) devices exploit centrifugal fields and layers, enlarges interfacial areas, and accelerates mixing, heat, and mass transfer, increasing rates in fast reaction systems. A workflow links mechanistic descriptions, computational fluid dynamics reactor simulations, and process-level simulations while identifying gaps at interfaces where turbulence, mass transfer, and kinetics dominate. Priorities include rotation-aware turbulence closures, turbulence-chemistry interaction models for gas-liquid flows, and subgrid or molecular descriptions for reduced-order and process models. Advances drawing on combustion and aerothermodynamics will enable predictive design and scale-up of HiGee devices.}},
articleno = {{101230}},
author = {{Wang, Bing and Chen, Siyuan and Hoorijani, Hamed and Xiong, Qingang and Van Geem, Kevin and Ouyang, Yi}},
issn = {{2211-3398}},
journal = {{CURRENT OPINION IN CHEMICAL ENGINEERING}},
keywords = {{LIQUID FLOW,SIMULATION,BED,CFD,ABSORPTION,TURBULENCE,KINETICS,MEA}},
language = {{eng}},
pages = {{10}},
title = {{Toward predictive multiscale models for HiGee devices}},
url = {{http://doi.org/10.1016/j.coche.2026.101230}},
volume = {{51}},
year = {{2026}},
}
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: