About

Professor Antonino Ferrante is a faculty member at the UW William E. Boeing Department of Aeronautics & Astronautics, serving as a Professor of Applied Mathematics. His research areas include engineering and energy, fluids, fluid mechanics, and turbulence. He is also an adjunct professor and an affiliate of the eScience Institute. His work focuses on fluid mechanics and turbulence, contributing to the understanding of complex fluid behaviors within engineering contexts.

Research topics

• Computer Science
• Physics
• Mechanics
• Geometry
• Materials science
• Engineering
• Simulation
• Optics
• Thermodynamics
• Aerospace engineering
• Mathematics

Selected publications

• A coupled volume-of-fluid/pressure-correction method for incompressible gas-liquid flows with phase change

  Journal of Computational Physics · 2025-07-23 · 1 citations

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• On the interaction of Taylor length-scale size droplets and homogeneous shear turbulence – CORRIGENDUM

  Journal of Fluid Mechanics · 2024-04-10

  erratumOpen accessSenior author

  The reader should be aware of the following typographical errors.The errors are first presented and highlighted in red.The corrected text follows, highlighted in blue.These were purely typographical errors which were not in our codes developed to produce the results presented in the paper.

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• Contributors

  Elsevier eBooks · 2023-01-01

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• Physics of two-way coupling in particle-laden homogeneous isotropic turbulence

  Elsevier eBooks · 2023-01-01

  book-chapter1st authorCorresponding
  PublisherDOI

• On the interaction of Taylor length-scale size droplets and homogeneous shear turbulence

  Journal of Fluid Mechanics · 2023-09-28 · 8 citations

  articleOpen accessSenior authorCorresponding

  The main objective of the present work is to explain the physical mechanisms occurring in droplet-laden homogeneous shear turbulence (HST) with a focus on the modulation of turbulence kinetic energy (TKE) caused by the droplets. To achieve such an objective, first, we performed direct numerical simulations (DNS) of HST laden with droplets of initial diameter approximately equal to twice the Taylor length scale of turbulence, droplet-to-fluid density and viscosity ratios equal to ten and a 5 % droplet volume fraction. We investigated the effects of shear number and Weber number on the modulation of TKE for $Sh \approx 2$ and $4$ , and $0.02 \le {{We_{rms}}} \le 0.5$ . Then, we derived the TKE equations for the two-fluid, carrier-fluid and droplet-fluid flow in HST and the relationship between the power of surface tension and the rate of change of total droplet surface area, providing the pathways of TKE for two-fluid incompressible HST. Our DNS results show that, for ${{We_{rms}}} = 0.02$ , the rate of change of TKE is increased with respect to the single-phase cases, for ${{We_{rms}}} = 0.1$ , the rate of change of TKE oscillates near the value for the single-phase cases and, for ${{We_{rms}}} = 0.5$ , the rate of change of TKE is decreased with respect to the single-phase cases. Such modulation is explained from the analysis of production, dissipation and power of surface tension in the carrier-fluid and droplet-fluid flows. Finally, we explain the effects of droplets on the production and dissipation rate of TKE through the droplet ‘catching-up’ mechanism, and on the power of the surface tension through the droplet ‘shearing’ mechanism.

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• RAIN EROSION: FROM MULTI-PHYSICS MODELLING TO EFFICIENT & COST-EFFECTIVE CERTIFICATION

  2023-01-01

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• Temporal accuracy of FastRK3

  Journal of Computational Physics · 2022-12-14 · 6 citations

  articleSenior authorCorresponding
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• Law of incipient separation for turbulent flows over airfoils as inferred by Reynolds-averaged Navier–Stokes

  Physics of Fluids · 2022-07-16 · 3 citations

  articleSenior authorCorresponding

  Lu, Aithal, and Ferrante [“Law of incipient separation over curved ramps as inferred by Reynolds-averaged Navier–Stokes,” AIAA J. 59, 196–214 (2021)] discovered a law that predicts the incipience of flow separation over curved ramps by knowing only a few geometrical parameters of the ramp and the Reynolds number of the flow. In that spirit, we have searched for a similar law for airfoils by performing simulations of incompressible turbulent flows over 32 NACA (National Advisory Committee for Aeronautics) airfoils using Reynolds-averaged Navier–Stokes (RANS) equations. First, we have carried out verification and validation of RANS against the experimental measurements by A. J. Wadcock (“Investigation of low-speed turbulent separated flow around airfoils,” NASA Contractor Report No. 177450, 1987), which show the accuracy of the RANS prediction at small angles of attack when flow separation begins to occur on the upper side of the airfoil. Then, we have investigated the effects of the angle of attack, airfoil thickness, and camber on the incipience of flow separation for the Reynolds number based on airfoil chord Rec∈[1.64×106,6×106]. From the analysis of the RANS results, we have determined a law for predicting the incipience of turbulent flow separation over airfoils that relies only on airfoil's newly defined characteristic slope, thickness, camber, and Rec.

  PublisherDOI

• From DNS to MANN-LES of droplet-laden isotropic turbulence

  Science Talks · 2022-12-02 · 1 citations

  articleOpen access1st authorCorresponding

  The interaction of liquid droplets with turbulence is relevant to both environmental flows and engineering applications, e.g., rain formation and spray combustion. In this seminar, I will present how we proceeded from studying the physical mechanisms of droplet/turbulence interaction via direct numerical simulation (DNS) to modeling such flow by creating the mixed artificial neural network (MANN) approach for large-eddy simulation (LES).First, in order to perform direct numerical simulation (DNS) of droplet-laden decaying isotropic turbulence, we developed a new pressure-correction method, FastP* (Dodd and Ferrante, 2014), for simulating incompressible two-fluid flows with large density and viscosity ratios between the two phases, coupled with a novel volume-of-fluid (VoF) method (Baraldi et al., 2014). Then, we performed DNS of finite-size droplets of diameter approximately equal to the Taylor length-scale of turbulence in decaying isotropic turbulence (Dodd and Ferrante, 2016). We derived the turbulence kinetic energy (TKE) equations for the two-fluid, carrier-fluid and droplet-fluid flow. This allowed us to explain the pathways for TKE exchange between the carrier turbulent flow and the flow inside the droplet (Dodd and Ferrante, 2016). Next, we developed a new methodology for the spectral analysis of multiphase flows using wavelets (Freund and Ferrante, 2019). We proposed a decomposition of the wavelet energy spectrum into three contributions corresponding to the regions where the wavelet is entirely contained in the carrier phase, entirely contained in a droplet, or partially contained in both carrier and droplet fluids (Freund and Ferrante, 2019). Finally, via analysis of the DNS results both in physical and spectral space, the physical mechanisms we revealed helped us to propose a model for large-eddy simulation (LES) of such flow (Freund and Ferrante, 2021). The main challenge in this endeavor is that the presence of the droplets introduces additional subgrid-scale (SGS) closure terms to the filtered governing equations of motion. The results of a priori analysis showed that they are all significant enough to warrant modeling. Thus, we proposed a new modeling approach that we called mixed artificial neural network (MANN) (Freund and Ferrante, 2021) large-eddy simulation (LES) because it is a mixed LES model that uses the standard Smagorinsky SGS stress model in the carrier flow, and artificial neural networks to predict the SGS closure terms at the interface. Furthermore, we have performed the first a posteriori analysis of such flow for droplets of different Weber numbers showing the agreement of the MANN LES with the filtered DNS results. Finally, the MANN LES approach could be applied to other multiphase turbulent flows due to its ease of implementation, adaptability, and performance.

  PublisherOA PDFDOI

• Analysis of droplet evaporation in isotropic turbulence through droplet-resolved DNS

  International Journal of Heat and Mass Transfer · 2021 · 56 citations

  • Mechanics
  • Materials science
  • Thermodynamics
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Recent grants

• CAREER: Petascale DNS of Evaporating Droplet-Laden Homogeneous Turbulence

  NSF · $663k · 2011–2018

Frequent coauthors

• S. Elghobashi

  University of California, Irvine

  40 shared

• Michael Dodd

  Stanford University

  27 shared

• Abhiram B. Aithal

  University of Washington

  17 shared

• Francesco Lucci

  13 shared

• Madeline Samuell

  University of Washington

  10 shared

• Owen Williams

  University of Washington

  10 shared

• Matthew Robbins

  Seattle University

  9 shared

• Andreas K. Freund

  7 shared

Labs

• Computational Fluid Mechanics LabPI

Education

• Postdoc, Mechanical & Aerospace Engineering

  University of California Irvine

  2007

• Ph.D., Mechanical & Aerospace Engineering

  University of California Irvine

  2004

Awards & honors

• NSF CAREER Award (2011)
• Associate Fellow of the AIAA (2022)
• AIAA Associate Fellow (2022)
• Belgian Government Prize, von Karman Institute (1997)
• American Physical Society (APS) News Undergraduate research…