Experimental and numerical study of CO2 plume diffusion in a confined space. (February 2023)
- Record Type:
- Journal Article
- Title:
- Experimental and numerical study of CO2 plume diffusion in a confined space. (February 2023)
- Main Title:
- Experimental and numerical study of CO2 plume diffusion in a confined space
- Authors:
- Li, Guangying
Wang, Jiyun
Wang, Mingyan
Zong, Ruowen - Abstract:
- Abstract: In this paper, heavy gas diffusion in a confined space has been investigated. The effects of barrier and source intensity on CO2 diffusion are explored by the small-scale experiments and computational fluid dynamics (CFD) methods. Six different turbulence models are selected to predict the gas concentrations. By comparing these experimental values with the simulated ones, it is found that all models can effectively predict the concentration variation with time, and SST k-ω model is most close to the ideal model compared with others. Three source-barrier distances and three CO2 flow rates have been set up for the study. In this confined space, the main flow is concentrated in the region near the ground. The existence of barriers in the space will have a dilution effect on the high-concentration plume near the ground of the near-source area and a barrier effect on the low-concentration plume in the far-source area. The changes in source intensity have notable impact on the gas concentrations. This study can provide an experimental basis for the risk assessment in the confined spaces, as well as an experimental and data reference for large-scale CFD simulations. Highlights: A combination of small-scale experiments and computational fluid dynamics (CFD) has been used to investigate the pattern of CO2 diffusion in confined spaces. Six different turbulence models are chosen to predict gas concentrations. Barriers in confined spaces not only impede the diffusion of gases,Abstract: In this paper, heavy gas diffusion in a confined space has been investigated. The effects of barrier and source intensity on CO2 diffusion are explored by the small-scale experiments and computational fluid dynamics (CFD) methods. Six different turbulence models are selected to predict the gas concentrations. By comparing these experimental values with the simulated ones, it is found that all models can effectively predict the concentration variation with time, and SST k-ω model is most close to the ideal model compared with others. Three source-barrier distances and three CO2 flow rates have been set up for the study. In this confined space, the main flow is concentrated in the region near the ground. The existence of barriers in the space will have a dilution effect on the high-concentration plume near the ground of the near-source area and a barrier effect on the low-concentration plume in the far-source area. The changes in source intensity have notable impact on the gas concentrations. This study can provide an experimental basis for the risk assessment in the confined spaces, as well as an experimental and data reference for large-scale CFD simulations. Highlights: A combination of small-scale experiments and computational fluid dynamics (CFD) has been used to investigate the pattern of CO2 diffusion in confined spaces. Six different turbulence models are chosen to predict gas concentrations. Barriers in confined spaces not only impede the diffusion of gases, but also have a significant dilution effect in the near-source region. Changes in source intensity have the greatest impact on gas concentrations. … (more)
- Is Part Of:
- Journal of loss prevention in the process industries. Volume 81(2023)
- Journal:
- Journal of loss prevention in the process industries
- Issue:
- Volume 81(2023)
- Issue Display:
- Volume 81, Issue 2023 (2023)
- Year:
- 2023
- Volume:
- 81
- Issue:
- 2023
- Issue Sort Value:
- 2023-0081-2023-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-02
- Subjects:
- Confined space -- Heavy gas diffusion -- Turbulence modeling -- Barriers -- CFD simulation
Chemical industries -- Safety measures -- Periodicals
660.2804 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09504230/ ↗
http://www.journals.elsevier.com/journal-of-loss-prevention-in-the-process-industries/ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jlp.2022.104949 ↗
- Languages:
- English
- ISSNs:
- 0950-4230
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5010.562000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26036.xml