2021
DOI: 10.1007/s00231-021-03097-8
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Numerical investigation of expandable graphite suppression on metal-based fire

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Cited by 10 publications
(4 citation statements)
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“…The solid pyrolysis model was developed with user-defined functions (UDF) which describe the solid thermal degradation process and porous properties of the sample. UDF allows customization for boundary conditions [ 52 ], material properties [ 53 , 54 ], source terms [ 4 ] and model parameters [ 55 , 56 ]. The Wall-Adapting Local Eddy-viscosity was employed to resolve the subgrid-scale eddies, and the Moss-Brookes semi-empirical soot model was implemented to handle the soot concentration within the cone computational domain [ 57 ].…”
Section: Methodsmentioning
confidence: 99%
“…The solid pyrolysis model was developed with user-defined functions (UDF) which describe the solid thermal degradation process and porous properties of the sample. UDF allows customization for boundary conditions [ 52 ], material properties [ 53 , 54 ], source terms [ 4 ] and model parameters [ 55 , 56 ]. The Wall-Adapting Local Eddy-viscosity was employed to resolve the subgrid-scale eddies, and the Moss-Brookes semi-empirical soot model was implemented to handle the soot concentration within the cone computational domain [ 57 ].…”
Section: Methodsmentioning
confidence: 99%
“…Under the Eulerian-Lagrangian framework, computational fluid dynamics coupled with discrete phase model (CFD-DPM) is a viable approach to predict the complex interactive fire behaviours associated with suppression effects. This approach has been widely employed for numerical fire suppression studies [34][35][36][37][38]. In this study, Fire Dynamic Simulator (FDS) version 6.7.4 has been employed to simulate a compartment fire with droplet suppression effects.…”
Section: Methodsmentioning
confidence: 99%
“…Mathematical equations are applied to describe the fluid motion by physical characterization, usually in partial differential form, called governing equations. These applications encompass performance assessment, behavioral predictions, and the substitution of impractical tests, such as those involving fire dynamics [65][66][67][68], chemical mechanisms and transportation of soot particles [69][70][71][72][73], contribution toward numerical database for fire safety standards [74][75][76][77][78][79], etc. Therefore, understanding the fundamental thermal degradation kinetics will contribute to thermal runaway analysis in the battery-CFD modelling framework.…”
Section: Cfd Modelmentioning
confidence: 99%