7 papers
Super-resolution of turbulent reacting flows on complex meshes using graph neural networks
Priyabrat Dash, Konduri Aditya, Christos E. Frouzakis +1
State-of-the-art deep learning models have been extensively utilized to reconstruct small-scale structures from coarse-grained data in turbulent flows. However, their application h…
Analysis of In-cylinder Flow Structures and Turbulence in a Laboratory Scale Engine using Direct Numerical Simulations
Bogdan A. Danciu, George K. Giannakopoulos, Mathis Bode +1
In-cylinder flow structures and turbulence characteristics are investigated using direct numerical simulations (DNS) in a laboratory-scale engine at technically relevant engine spe…
Direct Numerical Simulation of Hydrogen Combustion in a Real-Size IC Engine
Bogdan A. Danciu, George K. Giannakopoulos, Mathis Bode +1
This study presents the first Direct Numerical Simulation (DNS) of hydrogen combustion in a real-size internal combustion engine, investigating the complex dynamics of ignition, fl…
KinetiX: A performance portable code generator for chemical kinetics and transport properties
Bogdan A. Danciu, Christos E. Frouzakis
We present KinetiX, a software toolkit to generate computationally efficient fuel-specific routines for the chemical source term, thermodynamic and mixture-averaged transport prope…
Deciphering boundary layer dynamics in high-Rayleigh-number convection using 3360 GPUs and a high-scaling in-situ workflow
Mathis Bode, Damian Alvarez, Paul Fischer +10
Turbulent heat and momentum transfer processes due to thermal convection cover many scales and are of great importance for several natural and technical flows. One consequence is t…
Flow reconstruction in time-varying geometries using graph neural networks
Bogdan A. Danciu, Vito A. Pagone, Benjamin Böhm +2
The paper presents a Graph Attention Convolutional Network (GACN) for flow reconstruction from very sparse data in time-varying geometries. The model incorporates a feature propaga…