24 citations · 25 across the 4 of their papers we have counts for
5 papers
A convolutional autoencoder and neural ODE surrogate modeling framework applied to transient counterflow flames
Mert Yakup Baykan, Weitao Liu, Mohammad Rafi Malik +4
A novel convolutional autoencoder and neural ODE (CAE-NODE) framework is proposed for a reduced-order model (ROM) applied to transient 2D counterflow flames, as an extension of AE-…
Super-resolution of turbulent velocity fields in two-way coupled particle-laden flows
Ali Shamooni, Ruyue Cheng, Thorsten Zirwes +3
This paper introduces a deep learning-based super-resolution (SR) framework specifically developed for accurately reconstructing high-resolution velocity fields in two-way coupled…
Super-resolution of turbulent velocity and scalar fields using different scalar distributions
Ali Shamooni, Oliver T. Stein, Andreas Kronenburg
In recent years, sub-grid models for turbulent mixing have been developed by data-driven methods for large eddy simulation (LES). Super-resolution is a data-driven deconvolution te…
Carrier-phase DNS of ignition and combustion of iron particles in a turbulent mixing layer
Tien Duc Luu, Ali Shamooni, Andreas Kronenburg +9
Three-dimensional CP-DNS of reacting iron particle dust clouds in a turbulent mixing layer are conducted. The simulation approach considers the Eulerian transport equations for the…
Modelling nano-particle agglomeration using local interactions
Gizem Inci, Axel Arnold, Andreas Kronenburg +1
Nano-particle agglomeration plays an important role in processes such as spray drying and particle flame synthesis. These processes have in common that nano-particles collide at lo…