26 citations · 72 across the 13 of their papers we have counts for
15 papers
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…
Effect of fuel stratification length scale on thermodiffusively unstable lean hydrogen flames
Filippo Fruzza, Sofiane Al Kassar, Rachele Lamioni +2
Lean premixed hydrogen flames are highly susceptible to thermodiffusive instabilities, which generate complex cellular structures and enhance propagation speed. In practical combus…
Effect of a magnetostatic field on laminar premixed hydrogen-air flames
Tristan Lapaire, Sofiane Al Kassar, Antonio Attili +1
Magnetic fields have shown potential to affect flame characteristics; however, the mechanisms of interaction are not fully understood. This paper investigates the effect of magneti…
Turbulent hydrogen premixed flames at high pressure and high temperature
Sofiane Al Kassar, Sara Cantagalli, William Lauder +2
The combined influence of elevated pressure and temperature, representative of gas-turbine operating conditions, on lean premixed hydrogen flames is investigated using Direct Numer…
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…
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…
Efficient and accurate calculation of dispersion relations for intrinsically unstable premixed flames
Sofiane Al Kassar, Lukas Berger, Pasquale E. Lapenna +3
Premixed flames are susceptible to hydrodynamic and thermodiffusive instabilities that wrinkle the flame front and lead to complex multiscale patterns. They strongly impact the fla…
Effect of transverse gust on free-falling plates
Jawahar Sivabharathy Samuthira Pandi, Ahmet Gungor, Chandan Bose +2
The effects of transverse gusts on free-falling plates are investigated using two-way coupled fluid-structure interaction simulations for a Galilei number (Ga) between 10 and 50 an…
Local manifold learning and its link to domain-based physics knowledge
Kamila Zdybał, Giuseppe D'Alessio, Antonio Attili +3
In many reacting flow systems, the thermo-chemical state-space is known or assumed to evolve close to a low-dimensional manifold (LDM). Various approaches are available to obtain t…
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…
Adjoint-Based Sensitivity Analysis of Steady Char Burnout
Ahmed Hassan, Taraneh Sayadi, Vincent LeChenadec +2
Simulations of pulverised coal combustion rely on various models, required in order to correctly approximate the flow, chemical reactions, and behavior of solid particles. These mo…
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…
Mode coupling behavior of a Lennard Jones binary mixture: a comparison between bulk and confined phases
A. Attili, P. Gallo, M. Rovere
We present a quantitative comparison at equivalent thermodynamical conditions of bulk and confined dynamical properties of a Lennard Jones binary mixture upon supercooling. Both sy…
Inherent Structures and Kauzmann Temperature of Confined Liquids
A. Attili, P. Gallo, M. Rovere
Calculations of the thermodynamical properties of a supercooled liquid confined in a matrix are performed with an inherent structure analysis. The liquid entropy is computed by mea…