Research Associate / Senior Research Associate - LCO Characterisation CFD

University of Bristol
London
6 months ago
Applications closed

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The role

We are seeking a motivated interdisciplinary researcher to join the University of Bristol, as part of the Airbus led Aerospace Technology Institute / IUK funded DAWS2 project. The work involves the prediction of Limit Cycle Oscillations (LCOs) for preparation for wind tunnel / flight tests of aircraft wings incorporating a semi-aeroelastic hinge (SAH). CFD tools coupled with FE structural models will be developed to predict LCOs on highly flexible wings incorporating the SAH.

As part of the role, it would be expected that the candidate works closely with Airbus and other partners in the DAWS2 project, making regular presentations, writing progress reports and completing project deliverables. The successful candidate will be part of a team of researchers working on different aspects of the DAWS2 project.

DAWS2 (Development of Advanced Wing Solutions) will focus on the development of Ultra Efficient technologies to cut fuel burn and weight, independent of the fuel choice, for a new high build rate product using wing span as a key enabler.


What will you be doing?
Develop CFD / FE based simulation tools for application to High Aspect Ratio Wing (HARW) / SAH configurations to predict LCOs.Evaluate results from the simulations in comparison with low order simulations and experimental tests.Undertake technical discussions with other partners in DAWS2 and researchers across the University of Bristol.Present results from this work at regular progress meetings.Produce written technical reports to meet the required deliverables of DAWS2 and also publish conference and journal papers arising from this work as appropriate.
You should apply if
A 1st class degree in Aerospace or Mechanical Engineering (or related subject).Experience of unsteady numerical aeroelastic modelling of aircraft wings using high fidelity methods (e.g. CFD and FE).Experience in the analysis and interpretation of data sets, including search and optimisation.Excellent oral and written communication skills.Proactive self-starter able to define & produce new processes & procedures.Inquisitive nature with an interest & skills in problem-solving.

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