activity
20152020
most citedUsing Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows

10 citations · 16 across the 6 of their papers we have counts for

collaborators

9 papers

physics.flu-dyn2020

Turbulent flame speed and reaction layer thickening in premixed jet flames at constant Karlovitz and increasing Reynolds numbers

Antonio Attili, Stefano Luca, Dominik Denker +2

A series of Direct Numerical Simulations (DNS) of lean methane/air flames was conducted in order to investigate the enhancement of the turbulent flame speed and modifications to th…

physics.chem-ph2020

Theoretical single droplet model for particle formation in flame spray pyrolysis

Yihua Ren, Jinzhi Cai, Heinz Pitsch

In the current work, we develop a single droplet model to describe particle formation in multicomponent-liquid droplet combustion. Both the gas-to-particle conversion and droplet-t…

cs.LG201910 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…

physics.comp-ph2019

Theoretical analysis and kinetic modeling on hydrogen addition and abstraction by H radical of 1,3-cyclopentadiene and the associated chain-branching reactions

Qian Mao, Liming Cai, Heinz Pitsch

Cyclopentadiene (CPD) is an important intermediate in the combustion of fuel and the formation of aromatics. In the present study, the kinetics and thermodynamic properties for hyd…

physics.comp-ph20193 cited

Deep learning at scale for subgrid modeling in turbulent flows

Mathis Bode, Michael Gauding, Konstantin Kleinheinz +1

Modeling of turbulent flows is still challenging. One way to deal with the large scale separation due to turbulence is to simulate only the large scales and model the unresolved co…

physics.flu-dyn2019

Analysis of Premixed Flame Kernel/Turbulence Interactions under Engine Conditions based on DNS Data

Tobias Falkenstein, Seongwon Kang, Heinz Pitsch

Although the evolution of premixed flames in turbulence has been frequently studied, it is not well understood how small flames interact with large-scale turbulent flow motion. Sin…