Offers “Airbus”

Expires soon Airbus

PhD – Aero-acoustic sources reconstruction in a noisy environment - 10461561 - (m/f).

  • Apprenticeship
  • Toulouse (Haute-Garonne)
  • Energy / Materials / Mechanics

Job description



Airbus Operations SAS

Airbus is a global leader in aeronautics, space and related services. In 2018 it generated revenues of € 64 billion and employed a workforce of around 134,000. Airbus offers the most comprehensive range of passenger airliners. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as one of the world's leading space companies. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide.

Our people work with passion and determination to make the world a more connected, safer and smarter place. Taking pride in our work, we draw on each other's expertise and experience to achieve excellence. Our diversity and teamwork culture propel us to accomplish the extraordinary - on the ground, in the sky and in space.

Job Description

Contact :
You can apply online on our career site (https://www.airbus.com/careers.html) by attaching your CV and cover letter to this job offer.

By submitting your CV or application, you consent to Airbus using and storing your information for the purpose of tracking your application or future employment. This information will only be used by Airbus

Description of the job :
Complying with community noise certification rules and cabin noise guarantees while minimizing the impact on aircraft weight and efficiency is a key objective for the acoustic department at a time where environmental requirements are continuously stringing.

In order to assess the potential benefit of new well-sized acoustic design solutions, numerous flight tests are performed and, most of the time, in a noisy environment.

Task & accountabilities :
This PhD aims at providing a statistical engine noise model based on microphones installed on an aircraft fuselage.

The primary goal is to be able to predict the sound generation mechanisms by using equivalent sources method. Once identified, these equivalent sources can be numerically re-propagated to synthetize, for example, the complex acoustic field on the fuselage (in amplitude and in phase) and its transmission through the fuselage inside the cabin.

Three main challenges will be addressed in this PhD:

- Definition of the equivalent sources, which must reproduce the same statistical (e.g. correlation) and spatial (e.g. directivity) properties as the actual sources, even when they relate to complex mechanisms such as jet noise or fan noise.

- Propagation which suffers various distortion effects to be accounted for, due to existence of speed gradients in the flow and in the turbulent boundary layer on the fuselage skin.

- Extraction of acoustic contribution in the presence of high level of background noise with advanced denoising techniques.

Required skills :
Very solid knowledge in Signal Processing and Aero acoustics.

Good knowledge in computer programming (Linux, Python, Matlab)

The following soft skills are primordial to ensure a good experience and that the mission be a success:

- Rigor
- Curiosity
- Self driven
- Good interpersonal and communication skills
- Autonomy/proactivity
- Analysis and synthesis skills
- Advanced level of French and advanced level of English

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Make every future a success.
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