26 citations · 75 across the 11 of their papers we have counts for
11 papers · 1 filter
Uncovering flame physics with machine learning: application to the reaction rate in hydrogen flames
Antonio Attili, Ludovico Nista, Tommaso Baffetti +6
Convolutional Neural Networks (CNNs) are used as analytical tools to investigate the relationship between the progress variable field and the local chemical source term in lean pre…
Large-eddy simulations of a lean hydrogen premixed turbulent jet flame with tabulated chemistry
Emiliano M. Fortes, Eduardo J. Pérez-Sánchez, Temistocle Grenga +3
Large-eddy simulations (LES) of a planar turbulent lean hydrogen-air jet flame at Re = 11000 are performed using a tabulated flamelet model based on mixture-averaged diffusion that…
Dynamic mixed turbulence modeling using a super-resolution generative adversarial approach
Ludovico Nista, Christoph D. K. Schumann, Temistocle Grenga +3
A dynamic mixed super-resolution model (DMSRM) for large-eddy simulations (LESs) is proposed, which combines the traditional dynamic mixed model (DMM) formulation with the generati…
ZipGAN: Super-Resolution-based Generative Adversarial Network Framework for Data Compression of Direct Numerical Simulations
Ludovico Nista, Christoph D. K. Schumann, Fabian Fröde +5
The advancement of high-performance computing has enabled the generation of large direct numerical simulation (DNS) datasets of turbulent flows, driving the need for efficient comp…
Analysis of thermodiffusive instabilities in hydrogen premixed flames using a tabulated flamelet model
Emiliano Manuel Fortes Soplanes, Eduardo Javier Pérez Sánchez, Ambrus Both +2
Preferential diffusion plays a critical role in the evolution of lean premixed hydrogen flames, influencing flame surface corrugation and overall flame behavior. Simulating such fl…
Three-dimensional numerical investigation of flashback in premixed hydrogen flames within perforated burners
Filippo Fruzza, Hongchao Chu, Rachele Lamioni +3
Predicting flashback represents a pivotal challenge in the development of innovative perforated burners for household appliances, especially for substituting natural gas with hydro…
Influence of adversarial training on super-resolution turbulence reconstruction
Ludovico Nista, Christoph David Karl Schumann, Mathis Bode +4
Supervised super-resolution deep convolutional neural networks (CNNs) have gained significant attention for their potential in reconstructing velocity and scalar fields in turbulen…
Physics-based reduced-order modeling of flash-boiling sprays in the context of internal combustion engines
Avijit Saha, Abhishek Y. Deshmukh, Temistocle Grenga +1
Flash-boiling injection is one of the most effective ways to accomplish improved atomization compared to the high-pressure injection strategy. The tiny droplets formed via flash-bo…
Dimensional Analysis of Vapor Bubble Growth Considering Bubble-bubble Interactions in Flash Boiling Microdroplets of Highly Volatile Liquid Electrofuels
Avijit Saha, Abhishek Y. Deshmukh, Temistocle Grenga +1
Electrofuels (e-fuels) produced from renewable electricity and carbon sources have gained significant attention in recent years as promising alternatives to fossil fuels for the tr…
Predictive data-driven model based on generative adversarial network for premixed turbulence-combustion regimes
Temistocle Grenga, Ludovico Nista, Christoph Schumann +4
Premixed flames exhibit different asymptotic regimes of interaction between heat release and turbulence depending on their respective length scales. At high Karlovitz number, the d…
A Reduced-order Model for Multiphase Simulation of Transient Inert Sprays
A. Deshmukh, T. Grenga, M. Davidovic +5
In global efforts to reduce harmful greenhouse gas emissions from the transport sector, novel bio-hybrid liquid fuels from renewable energy and carbon sources can be a major form o…