activity
20152025
most citedComprehensive linear stability analysis for intrinsic instabilities in premixed ammonia/hydrogen/air flames

25 citations · 89 across the 11 of their papers we have counts for

collaborators

11 papers

physics.flu-dyn2025

Role of enthalpy transport in laminar premixed hydrogen flames at atmospheric and elevated pressures

Thomas L. Howarth, Terence Lehmann, Michael Gauding +1

This work discusses the role of diffusive enthalpy transport in relation to the origin of thermodiffusive instability and the resulting enhanced reactivity. Thermodiffusive effects…

physics.flu-dyn2025★ 3 cited

Effects of Intrinsic Flame Instabilities on Nitrogen Oxide Formation in Laminar Premixed Ammonia/Hydrogen/Air Flames

Terence Lehmann, Nikita Dimidziev, Thomas L. Howarth +2

This study investigates the characteristics of nitrogen oxide (NO) formation in two-dimensional (2D) laminar premixed ammonia/hydrogen/air flames and the impact of thermodiffusivel…

physics.flu-dyn2024★ 25 cited

Comprehensive linear stability analysis for intrinsic instabilities in premixed ammonia/hydrogen/air flames

Terence Lehmann, Lukas Berger, Thomas L. Howarth +4

Two-dimensional direct numerical simulations of planar laminar premixed ammonia/hydrogen/air flames are conducted for a wide range of equivalence ratios, hydrogen () fract…

physics.flu-dyn2022

Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data

Mathis Bode, Michael Gauding, Dominik Goeb +2

Models for finite-rate-chemistry in underresolved flows still pose one of the main challenges for predictive simulations of complex configurations. The problem gets even more chall…

physics.flu-dyn2022★ 9 cited

Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning

Mathis Bode, Michael Gauding, Jens Henrik Göbbert +3

In this paper, deep learning (DL) methods are evaluated in the context of turbulent flows. Various generative adversarial networks (GANs) are discussed with respect to their suitab…

cs.LG2019★ 10 cited

Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

Mathis Bode, Michael Gauding, Zeyu Lian +5

Turbulence is still one of the main challenges for accurately predicting reactive flows. Therefore, the development of new turbulence closures which can be applied to combustion pr…