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Computational fluid dynamics (CFD) plays a critical role in designing safe storage and transport systems for hydrogen. Fine mesh resolution and detailed chemistry are essential for the accurate prediction of self-ignition and deflagration-to-detonation (DDT) in hydrogenair mixtures. However, simulating H2 venting and explosion in real-life scenarios (e.g., with complex obstacle shapes and a large computational domain) involves tedious meshing effort and several mesh iterations to capture flame and shock locations. This paper addresses these challenges by assessing the capability of a detailed-chemistry approach combined with automated meshing based on a cut-cell technique and Adaptive Mesh Refinement (AMR). Furthermore, three different turbulence-chemistry interaction modelling approaches are compared for self-ignition and DDT scenarios: a homogeneous reactor model, an eddy dissipation model, and a flame thickening approach. | Computational fluid dynamics (CFD) plays a critical role in designing safe storage and transport systems for hydrogen. Fine mesh resolution and detailed chemistry are essential for the accurate prediction of self-ignition and deflagration-to-detonation (DDT) in hydrogenair mixtures. However, simulating H2 venting and explosion in real-life scenarios (e.g., with complex obstacle shapes and a large computational domain) involves tedious meshing effort and several mesh iterations to capture flame and shock locations. This paper addresses these challenges by assessing the capability of a detailed-chemistry approach combined with automated meshing based on a cut-cell technique and Adaptive Mesh Refinement (AMR). Furthermore, three different turbulence-chemistry interaction modelling approaches are compared for self-ignition and DDT scenarios: a homogeneous reactor model, an eddy dissipation model, and a flame thickening approach. | ||
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| + | == Abstract == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_7871705292126_abstract.pdf</pdf> | ||
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| + | == Full Paper == | ||
| + | <pdf>Media:Draft_Sanchez Pinedo_7871705292126_paper.pdf</pdf> | ||
Latest revision as of 16:06, 25 November 2022
Summary
Computational fluid dynamics (CFD) plays a critical role in designing safe storage and transport systems for hydrogen. Fine mesh resolution and detailed chemistry are essential for the accurate prediction of self-ignition and deflagration-to-detonation (DDT) in hydrogenair mixtures. However, simulating H2 venting and explosion in real-life scenarios (e.g., with complex obstacle shapes and a large computational domain) involves tedious meshing effort and several mesh iterations to capture flame and shock locations. This paper addresses these challenges by assessing the capability of a detailed-chemistry approach combined with automated meshing based on a cut-cell technique and Adaptive Mesh Refinement (AMR). Furthermore, three different turbulence-chemistry interaction modelling approaches are compared for self-ignition and DDT scenarios: a homogeneous reactor model, an eddy dissipation model, and a flame thickening approach.
Abstract
Full Paper
Document information
Published on 24/11/22
Accepted on 24/11/22
Submitted on 24/11/22
Volume Computational Solid Mechanics, 2022
DOI: 10.23967/eccomas.2022.200
Licence: CC BY-NC-SA license
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