Project archive

In this page you can find open-access publications, datasets, media and materials related with the outcomes of the project.

Journal Papers

Conference Contributions

PhD Theses

  • A. Cuéllar, “AI-based sensing of turbulent wall-bounded flows”. (expected date of defense December 2024)
  • I. Tirelli, “Data-driven enhancement of optical measurement techniques“. (expected date of defense March 2025)
  • J. Chen, “Complete flow description from combination of incomplete measurements“. (expected date of defense June 2025)
  • L. Franceschelli, “Active flow control solutions for noise reduction in jet flows“. (expected date of defense September 2026)
  • Q. Li Hu, “Data-driven modelling of turbulent flows under active flow control”. (expected date of defense March 2027)

Dissemination Activities

Seminars and Presentations

Organization of Workshops and Events

Datasets and Codes

PROJECT TIMELINE

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December 2024

Particle Image Velocimetry 2024, von Karman Institute Lecture Series and Events

  • “Volumetric PIV methods”, by S. Discetti
  • “Data-driven methods to enhance PIV measurements”, by S. Discetti

The Lecture series directors were Prof. Stefano Discetti, from Universidad Carlos III de Madrid, Spain and Prof. Miguel Mendez from the von Karman Institute, Belgium.

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SEPTEMBER 2024

Actuation manifold from snapshot data

L. Marra, G.Y. Cornejo Maceda, A. Meilán-Vila, V. Guerrero, S. Rashwan, B.R. Noack, S. Discetti, A. Ianiro (2024), “Actuation manifold from snapshot data“. Journal of Fluid Mechanics, 996:A26.

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SEPTEMBER 2024

Limited wall-sensor availability affects flow estimation with 3D-GANs

A. Cuéllar, A. Ianiro, S. Discetti (2024), “Some effects of limited wall-sensor availability on flow estimation with 3D-GANs“. Theoretical and Computational Fluid Dynamics.

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AUGUST 2024

3D-GANS for 3D channel flow estimation from wall measurements

A. Cuéllar, A. Güemes, A. Ianiro, O. Flores, R. Vinuesa, S. Discetti (2024), “Three-dimensional generative adversarial networks for turbulent flow estimation from wall measurements“. Journal of Fluid Mechanics, 991:A1.

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May 2024

E​RCOFTAC Spring Festival 2024

Hosting the ERCOFTAC Spring Festival 2024 in Universidad Carlos III de Madrid. Co-organized by the European Research Community On Flow, Turbulence and Combustion.

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APRIL 2024

Blind denoising procedure based on deep autoencoders (AE)

F. Gu, S. Discetti, Y. Liu, Z. Cao, D. Peng (2024), “Denoising image-based experimental data without clean targets based on deep autoencoders“. Experimental Thermal and Fluid Science, 156, 111195.

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March 2024

EUROMECH colloquium 631 “Control of skin friction and convective heat transfer in wall-bounded flows”

Organization of the colloquium in Universidad Carlos III de Madrid. Co-sponsored by the ERC Starting Grant GloWing (grant n. 803082) and Proof of Concept Grant DeLaH (grant n. 101138326).

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february 2024

Complete flow characterization using  PINNs and field data

A. Moreno Soto, A. Güemes, S. Discetti (2024) “Complete flow characterization from snapshot PIV, fast probes and physics-informed neural networks“. Computer Methods in Applied Mechanics and Engineering, 419, 116652.

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July 2023

Convective heat transfer in a TBL enhanced by LGAC published

R. Castellanos, A. Ianiro, S. Discetti (2023) “Genetically-inspired convective heat transfer enhancement in a turbulent boundary layer.” Applied Thermal Engineering, 230, 120621.

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May 2023

Project PI appointed deputy director for strategy and promotion of the Department of Aerospace Engineering.

Congratulations to Stefano Discetti who was appointed as deputy director for strategy and promotion of the Department of Aerospace Engineering! Official announcement here.

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December 2022

RaSeedGAN on Nature Machine Intelligence

A. Güemes, C. Sanmiguel Vila, S. Discetti (2022). “Super-resolution generative adversarial networks of randomly-seeded fields“. Nature Machine Intelligence, 4, 1165–1173.

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August 2022

KNN-PTV published

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june 2022

PI Stefano Discetti Interview at Fundación Madri+d

I. Tirelli, A. Ianiro, S. Discetti (2022). “An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification”. Experimental Thermal and Fluid Science, 110756.

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april 2022

Pressure from data-driven time-resolved PIV 

J. Chen, M. Raiola, S. Discetti (2022). “Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes”. Experimental Thermal and Fluid Science, 110647.

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april 2022

Awards of Excellence 2022, Social Council of the Universidad Carlos III de Madrid (UC3M)

The 14th Edition Awards of Excellence 2022, the Social Council of the Universidad Carlos III de Madrid (UC3M), has awarded our PI S. Discetti in the category of Young Doctoral Research Staff. Congratulations!

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february 2022

NEXTFLOW & ZARATHUSTRA joint workshop – 23 February 2022

A joint workshop of the ERC Starting Grant projects NEXTFLOW (Next-generation flow diagnostics for control) and ZARATHUSTRA (Revolutionizing advanced electrodeless plasma thrusters for space transportation). The workshop brought together the working teams of the two projects to discuss on common interests and foster collaboration.

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november 2021

Fundamentals and recent advances in Particle Image Velocimetry and Lagrangian Particle Tracking, von Karman Institute Lecture Series and Events

  • “Statistical methods to enhance PIV measurements”, by S. Discetti
  • “Tomographic Particle Image Velocimetry”, by S. Discetti

The Lecture series directors were Prof. Stefano Discetti, from Universidad Carlos III de Madrid, Spain and Prof. Miguel Mendez from the von Karman Institute, Belgium.

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september 2021

Invited Keynote Lecture at 19th International Symposium on Flow Visualization ISFV 19

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june 2021

Aeroseminar in TU Delft

“Pushing the limits of PIV with data-driven techniques”, by S. Discetti

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March 2021

Seminars on Aerospace Science and Technology in UC3M

Presentation of the ERC Starting Grant “NEXTFLOW”, by Stefano Discetti

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January 2021

Kick-off

Begining of the project NEXTFLOW

Acknowledgments :

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon H2020 research and innovation programme (grant agreement No 949085)