DC5: Long-Range Instabilities and Aeroacoustics; Tonal Mechanism, Reduced-Order Modelling and Control

PhD Position
Long-Range Instabilities and Aeroacoustics: Tonal Mechanism, Reduced-Order Modelling and Control

(MSCA-DN FairCFD, DC5)

This is much more than just a PhD position!

Within the FairCFD Doctoral Network, you will benefit from a unique three-fold experience:

–  Contribute to technological innovation in the field of Aerospace industry, in direct collaboration with an industrial partner (Onera), by developing advanced and efficient CFD strategies.

–  Take part in a network-wide interdisciplinary effort to define and promote numerical sustainability in scientific research.

–  Join a vibrant network of 15 doctoral candidates, across 9 European countries, with access to cutting-edge network events, high-level training to technical and transverse skills, and secondments in both academic and industrial environments.

 See our website for more details on the network’s philosophy and actions, along with description of the other PhD positions (https://www.imft.fr/faircfd/project-presentation/).

Scientific program

Background

Many tonal aeroacoustic phenomena – such as screech in underexpanded supersonic jets and tonal noise from airfoils – are understood as long-range hydrodynamic–acoustic instabilities sustained by global feedback loops. Existing analyses, however, often rely on highly idealised models (infinitely long, parallel or weakly non-parallel flows with prescribed periodic modulation) and purely linear mechanisms, which obscure where and how the feedback loop is actually closed, how the oscillation saturates, and how staging between different tonal branches occurs.

This project will develop new theoretical and numerical techniques tailored to long-range instabilities – combining global/local stability, resolvent and sensitivity analysis with nonlinear reduced-order approaches (normal-form theory and spectral-submanifold (SSM) theory) – and will apply them to realistic data generated from accurate 3D compressible LES and experiments. The goals are to (i) identify the active regions that sustain these instabilities, (ii) clarify once and for all the dominant mechanism generating tonal noise, and (iii) develop effective passive and active strategies to suppress or mitigate such instabilities and their acoustic emission. Supersonic jet screech will be the primary test case, with extension to airfoil / trailing-edge tonal noise where possible.

Selected references:

  1. Jordan, P. & Colonius, T. (2013). Wave packets and turbulent jet noise. Annual Review of Fluid Mechanics, 45, 173–195.
  2. Edgington-Mitchell, D. (2022). A unifying theory of jet screech. J. Fluid Mech. 945, A8.
  3. Fabre, D. et al. (2018). A practical review on linear and nonlinear global approaches to flow instabilities. Applied Mechanics Reviews, 70(6).
  4. Cenedese, M. et al. (2022). Data-driven nonlinear model reduction to spectral submanifolds. Nat. Commun. 13, 872.
  5. Beneddine, S., Mettot, C. & Sipp, D. (2015). Global stability analysis of underexpanded screeching jets. Eur. J. Mech. B/Fluids 49, 392–408.

Your research program

The PhD will build and apply a unified framework for long-range instabilities in aeroacoustics, moving beyond the limitations of existing models. In particular, we aim to:

  • Develop global and local weakly nonlinear stability and resolvent analyses for realistic finite-length configurations (underexpanded jets with shocks, jet–plate / impinging-jet setups, tonal airfoils), using high-fidelity compressible LES and experimental data.
  • Use direct and adjoint modes and different flow-decomposition techniques to identify and rank the active regions that close the hydrodynamic–acoustic feedback loop.
  • Discriminate among competing screech / tonal-noise mechanisms by comparing their predictions with global modes, resolvent structures, and experimental / LES data.
  • Construct nonlinear reduced-order models based on normal-form and SSM theory, calibrated via data-assimilation, and use sensitivity analysis to design and assess passive and active control strategies for screech and tonal-noise mitigation.

Where you will work

The PhD candidate will be enrolled at the University of Salerno (UNISA, Italy), where she/he will be based for most of the project and integrated into local research activities on aeroacoustics, hydrodynamic stability and high-fidelity simulations. A cotutelle agreement is planned with the IMFT (Institut de Mécanique des Fluides de Toulouse) – Université Paul Sabatier, Toulouse, where the candidate will spend dedicated research periods. During this time, a secondment at ONERA (Toulouse) is also foreseen, focusing on the development of numerical techniques and their application to realistic aeroacoustic configurations and industrially relevant datasets. In addition, short research stays and collaborations with TU Berlin, KTH Stockholm, Roma La Sapienza are planned, further broadening the international environment and the expertise available to the candidate.

Network activities

 Integration within the FairCFD Network

Within the FairCFD network, you will contribute mainly to WP1: Efficient physics-based numerical methods and WP2: Efficient data-based approaches. You will regularly exchange with other DCs of the network applying similar approaches to other problems, and/or applying different numerical methods to similar problems.

A secondment (a short research stay with other network partners) at ONERA-Toulouse (9 months) is planned during the PhD. During this period, the candidate will (1) implement efficient numerical techniques to perform global stability and resolvent analyses of shock-containing flows in realistic configurations, and (2) develop, in close collaboration with IMFT- Toulouse, new methodologies to identify the active regions of the instability and to build effective reduced-order models based on equivariant bifurcation and normal-form theory.

Interdisciplinary task: co-designing numerical frugality 

Beyond your individual research program described above, you will contribute along with all other FairCFD doctoral candidates to a network-wide multidisciplinary effort (WP5) addressing the environmental and societal dimensions of numerical simulation.
Each DC will participate in the definition of practical metrics for numerical frugality (computational cost, energy use, resource impact) and contribute data from their simulations to a collective meta-analysis. This initiative will be supported by interdisciplinary experts and accompanied by a dedicated DC in social sciences, who will lead a qualitative study on evolving practices in simulation across the network. Together, we aim to build concrete, informed recommendations for sustainable scientific computing.

Network Training Program — More Than Just a PhD

As a Doctoral Network funded by Marie Sklodowska-Curie Actions (MSCA-DN), FairCFD will offer to you a rich and engaging training experience, including

  • Four one-week training events; (i) an induction week devoted to team-building, open-science practices and sustainability issues, (ii) an Essential Skills Accelerator event combining aiming to to equip DCs with essential technical and transferable skills, (iii) a Hackathon event where DCs will collaborate in teams to solve complex physics problem and compare various simulation strategies in terms of precision and sobriety, and (iv) a Career and Leadership Development Forum Aiming to equip DCs with transferable skills essential for their future careers.
  • Five On-line courses combining technical training to state-of-the art simulation methods ranging from physics-based approaches to data-driven ones, exposition to industrial applications, along with Social, ethical and environmental aspects of decision-making in modelling practices.
  • Involvement in the organisation of scientific events, including a mini-symposium as part of a large-audience scientific conference, a scientific symposium allowing to share the output in terms of new methods, innovation, and applications to industrial processes, and a Societal colloquium to deliver the outputs of the multidisciplinary tasks of the network.

This programme is designed to support your growth as a researcher, innovator, and engaged citizen, fully equipped to lead the next generation of responsible simulation science. See our website for more details (https://www.imft.fr/faircfd/project-presentation/)                                                                    

Practical informations

Skills/Qualifications

  • Master’s degree (or equivalent) in fluid mechanics, applied mathematics, aerospace engineering, scientific computing, or related fields.
  • Strong background in fluid mechanics, numerical methods, PDEs, and/or data-driven modeling.
  • Interest in interdisciplinary research and open science.

Benefits

The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Doctoral Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). The salary includes a living allowance, a mobility allowance, and a family allowance (if applicable). The guaranteed PhD funding is for 36 months (i.e., EC funding, additional funding is possible, depending on the local Supervisor, and in accordance with the regular PhD time in the country of origin).

Eligibility criteria

According to the international mobility rules of the MSCA-DN program, the candidates must not have spent more than 12 months in the hosting country (Italy), during the 36 months preceding the starting of the PhD. Apart from this rule, worldwide applications are expected and encouraged.

Selection process

The recruitment process will adhere to the principles of equal opportunities, transparency and non-discrimination, in line with the European Charter for Researchers, and will actively promote diversity and gender balance. In particular, applications from female candidates are strongly encouraged, as women remain underrepresented in engineering disciplines.

To apply, please send a) a cover letter explaining your motivation for the selected position and the FairCFD network, b) CV including information on previous experience with emphasis on publications and presentations if applicable, c)  Academic transcripts and/or official certification demonstrating completion of, or current enrolment in, a Master’s degree (or equivalent), and d) 2 reference letters and/or contact details of 2 referees, to the following addresses: 

f.giannetti@unisa.it,  javier.sierra_ausin@onera.fr, david.fabre@imft.fr , application_faircfd@groupes.renater.fr

We will start considering applications from February 1, and the process will remain open up to May 30.  After examination of the received applications, shortlisted candidates will be invited for online interviews with the recruitment committee.

If you are interested in more than one position belonging to the FairCFD network, please apply to 2 positions at most and precise the second choice in your cover letter. Extra candidatures not respecting this rule will be discarded.

Additional comments

A start date will be negotiated with the successful candidate. Ideally start dates would be between March 2026 and June 2026, with a potential to extend the start date to October 2026.