activity
20232025
most citedThe potential of retrofitting existing coal power plants: a case study for operation with green iron

79 citations · 173 across the 10 of their papers we have counts for

collaborators

10 papers

physics.flu-dyn2025

Numerical Analysis of the Stability of Iron Dust Bunsen Flames

Thijs Hazenberg, Daniel Braig, Johannes Mich +2

This article presents numerical simulations of the response of an iron dust Bunsen flame to particle seeding changes. A validated numerical model is used to study the impact of par…

physics.flu-dyn2025

Analyzing Iron Dust Bunsen Flames using Numerical Simulations

Thijs Hazenberg, Danial Braig, Michal A. Fedoryk +7

This article presents numerical simulations of an iron dust Bunsen flame. The results are validated against experimental results. The burning velocity is extracted from the 3D simu…

physics.flu-dyn20242 cited

Advantages of the adoption of a generalized flame displacement velocity as a central element of flamelet theory

Hernan Olguin, Pascale Domingo, Luc Vervisch +2

In combustion theory, flames are usually described in terms of the dynamics of iso-surfaces of a specific scalar. The flame displacement speed is then introduced as a local variabl…

physics.flu-dyn202426 cited

Can flamelet manifolds capture the interactions of thermo-diffusive instabilities and turbulence in lean hydrogen flames? -- An a-priori analysis

Hannes Böttler, Driss Kaddar, Federica Ferraro +3

Flamelet-based methods are extensively used in modeling turbulent hydrocarbon flames. However, these models have yet to be established for (lean) premixed hydrogen flames. While fl…

physics.flu-dyn202311 cited

Dynamic stabilization of a hydrogen premixed flame in a narrow channel

Faizan Habib Vance, Arne Scholtissek, Philip de Goey +2

Combustion of hydrogen can help in reducing carbon-based emissions but it also poses unique challenges related to the high flame speed and Lewis number effects of the hydrogen flam…

physics.flu-dyn202312 cited

Application of dense neural networks for manifold-based modeling of flame-wall interactions

Julian Bissantz, Jeremy Karpowski, Matthias Steinhausen +5

Artifical neural networks (ANNs) are universal approximators capable of learning any correlation between arbitrary input data with corresponding outputs, which can also be exploite…