Multi-fidelity reduced order modelling approach for the inverse identification of acoustic material properties (VAMOR DC10)

The Structural Mechanics and Coupled Systems Laboratory (LMSSC) of Cnam and the Marcus Wallenberg Laboratory
(MWL) for Sound and Vibration Research of KTH are searching for a young research engineer to join their team to work in the challenging Horizon Europe MSCA project VAMOR, leading to a joint doctoral degree from Cnam and KTH. Within this track, inverse identification approaches for characterising various acoustic materials (foams, composites, multilayer structures) will be investigated. This will be done by combining multi-fidelity approaches with reduced order models to develop efficient machine learning models that will be used in a global optimisation framework.

The Structural Mechanics and Coupled Systems Laboratory (LMSSC) of Cnam is searching for a young research engineer to join their team to work in the challenging Horizon Europe MSCA project VAMOR. The doctoral candidate will obtain a joint degree, co-supervised by the Marcus Wallenberg Laboratory (MWL) for Sound and Vibration Research of KTH.

Project:

Doctoral Candidate 10 (DC10) within VAMOR will develop novel inverse identification approaches for the characterisation of various acoustic materials by combining multi-fidelity approaches and reduced-order models. It will lead to the development of efficient machine learning models that will be used in a global optimizationframework. The first step is to determine the most appropriate material models and reduced-order models for the low-fidelity and high-fidelity models with the aim of efficiently evaluating the vibro-acoustic response. The second step would be to test this approach on an established test case to estimate its robustness and the speed-up as compared to other inverse techniques. Experimental tests may be considered for the validation of the approaches and/or the enrichment of the surrogate models. Finally, the proposed methodology will be applied to more challenging inverse problem identification: stochastic inverse identification, simultaneous identification of acoustic and/or elastic and/or viscoelastic properties of foams/composites/multilayer structures, or the multilevel optimization of material parameters. Ultimately, the developed techniques will be deployed to identify the properties of degraded materials on existing structures, such as the acoustic treatment of operating vehicles.

This doctoral project is part of a larger, multidisciplinary and international project VAMOR: "Vibro-Acoustic Model Order Reduction" (GA no. 101119903) funded under the Marie-Sklodowska-Curie Actions Doctoral Networks within the Horizon Europe Programme of the European Commission. VAMOR brings together a remarkable consortium, which combines research leading academic institutions - KU Leuven, Technische Universitaet Munchen (TUM), Technical University of Denmark (DTU), Kungliga Tekniska Hoegskolan (KTH), Université du Mans, Conservatoire National des Arts et Metiers (CNAM) - with a constantly innovating, wide variety of industrial partners working on software, material, testing, design and sound enhancement. VAMOR contributes to a more sustainable and quieter future for Europe. Noise pollution, recognized to have arisen as one of the key factors towards the degradation of the quality of life in European societies. In that context, efficient physics-based sound modelling is a key enabler towards not only optimized and sustainable acoustic profiles through efficient design procedures, but also affordable so-called digital twins that monitor product performance in real time. To this end, the overarching goal of VAMOR is to provide high level scientific and transferable skills training on a new generation of efficient vibro-acoustic modelling techniques, so-called model order reduction (MOR) strategies, to a group of high achieving, competent doctoral candidates to promote a quieter and more sustainable environment.

The joint PhD is supervised by Jean-François Deü, Lucie Rouleau and Luc Laurent from the Structural Mechanics and Coupled Systems Laboratory (LMSSC) of Cnam (https://www.lmssc.cnam.fr/en/equipe). The laboratory, located in the central area of Paris, currently counts >40 researchers mostly working on the development and validation of robust predictive models of dynamic coupled systems using adaptive treatments. The results of this research are mainly applied to the academic world, research centers and R&D department of high technology industries. The team has various industrial collaborations, mainly with aeronautics and naval industry. More information can be found on this website.

The PhD will be co-supervised by Romain Rumpler (KTH | Romain Rumpler) and Huina Mao (KTH | Huina Mao) from the Marcus Wallenberg Laboratory (MWL) for Sound and Vibration Research of KTH. The laboratory is part of the Department of Engineering Mechanics and remains the largest university centre in northern Europe for experimental work related to sound and vibration problems, in close collaboration with the Swedish based vehicle industry. The doctoral project will also be associated with the Centre for Eco2 Vehicle Design at KTH, a KTH hosted research Centre engaging in multi-disciplinary and multi-vehicular research to find solutions to cross-functional conflicts that exist at many levels of the broader vehicle system, bringing together research expertise from academia and industry.

Profile:

If you recognize yourself in the story below, then you have the profile that fits the project and the research group:

I have a master’s degree in engineering, physics or mathematics and performed above average in comparison to my peers. I am not in possession of a doctoral degree at the date of recruitment.
I am proficient in written and spoken English.
I haven't had residence or main activities in France for more than 12 months in the last 3 years.
During my courses or prior professional activities, I have gathered some basic experience with the basic physical principles of vibrations and/or acoustics and the related numerical modelling techniques, such as the Finite Element Method (FEM). I have a profound interest in machine learning approaches, model order reduction techniques and/or optimisation. Experience or interest in experimental testing would be appreciated.
As a potential PhD researcher of the Cnam, I want to perform research in a structured and scientifically sound manner, including reading technical papers, understanding the nuances between different theories and implementing and improving methodologies myself.
Based on interactions and discussions with my supervisors and the colleagues in my team, I set up and update a plan of approach for the upcoming one to three months to work towards my research goals. I work with a sufficient degree of independence to follow my plan and achieve the goals. I indicate timely when deviations of the plan are required, if goals cannot be met or if I want to discuss intermediate results or issues.
In frequent reporting, varying between weekly to monthly, I show the results that I have obtained, and I give a well-founded interpretation of those results. I iterate on my work and my approach based on the feedback of my supervisors which steer the direction of my research.
I feel comfortable to work as a team member and I am eager to share my results to inspire and be inspired by my colleagues.
I have a profound interest in advanced research strongly linked with industrial applications.
During my PhD I want to grow towards following up the project that I am involved in and representing the research group on project meetings or conferences. I see these events as an occasion to disseminate my work to an audience of international experts and research colleagues, and to learn about the larger context of my research and the research project.

Offer:

The possibility to study in a dynamic and international research environment in collaboration with industries and prominent universities worldwide.
You will receive a monthly gross salary of 2800€. The net income will result after the deduction of income tax, social contributions, and other permitted deductions that need to be considered. In addition to the net salary, you will receive a monthly mobility allowance of 420€. (Note that these amounts may vary).
An opportunity to pursue a joint PhD in Mechanical Engineering both from the Conservatoire National des Arts et Métiers and KTH, typically a 4-year trajectory, in a stimulating and ambitious research environment.
The place of employment is Paris, France. In the context of the joint degree, you will spend in total 18 months in Stockholm, Sweden. An additional 4-month secondment is included in Matelys, which is located in Lyon, France.
Ample occasions to develop yourself in a scientific and/or an industrial direction. Besides opportunities offered by the research groups, further doctoral training is provided in the framework of the MSCA Doctoral Network project VAMOR.

Interested?

Fill in the formulary http://r.cnam.fr/vamor-dc-application, and send the following documents to Lucie Rouleau (lucie.rouleau@lecnam.net) by email and mention VAMOR in the title:

full CV – mandatory
motivation letter – mandatory
full list of credits and grades of both BSc and MSc degrees (as well as their transcription to English if possible) – mandatory (when you haven't finished your degree yet, just provide us with the partial list of already available credits and grades)
proof of English proficiency (TOEFL, IELTS, …) - if available
two reference letters - if available
an English version of your MSC, or of a recent publication or assignment - if available

For more information please contact Lucie Rouleau (lucie.rouleau@lecnam.net), or Jean-François Deü (jean-francois.deu@cnam.fr) by mail and mention VAMOR in the title.