Research Assistant/Associate in New optimisation algorithms for turbulent flows

Job summary

“New generation of optimisation algorithms for turbulent flows”  The central aim of the EPRSC-funded project is to develop the new generation of optimisation algorithms for turbulent flows.  When scale-resolving simulations (like DNS or LES) are employed to optimise time-average quantities (like lift or drag), existing algorithms that are based on adjoint sensitivity fail;   this is due to the chaotic nature of turbulence, a phenomenon...

Job listing information

  • Reference ENG01914
  • Date posted 3 November 2021
  • Closing date 2 December 2021

Job description

Job summary

“New generation of optimisation algorithms for turbulent flows” 

The central aim of the EPRSC-funded project is to develop the new generation of optimisation algorithms for turbulent flows.  When scale-resolving simulations (like DNS or LES) are employed to optimise time-average quantities (like lift or drag), existing algorithms that are based on adjoint sensitivity fail;   this is due to the chaotic nature of turbulence, a phenomenon popularly known as the `butterfly effect'. Recently a new approach, called least squares shadowing, was proposed to overcome his problem.  The resulting algorithm however does not scale well for turbulent flows.

In this project, we plan to devise and develop new shadowing algorithms that achieve superior computational efficiency by exploiting known structural properties that are unique to turbulence. Specifically, we will leverage tools that provide compact representation of turbulent fluctuations, such as Resolvent Analysis and Proper Orthogonal Decomposition, to obtain efficient shadowing algorithms that are tailored to turbulent flows. We will demonstrate the performance of the newly developed methods to flow reconstruction using data assimilation in a boundary layer flow. Collaborators in this work are researchers from University of Southampton, MIT and University of Reading.

Duties and responsibilities


  • Perform DNS (or LES) of wall-founded flows and extract reduced order models

  • Couple the shadowing approach with these models

  • Assess performance when applied to wall-bounded turbulent flows.

  • Investigate the tangent equation and analyse the properties of the unstable directions (covariant Lyapunov vectors)

  • Draft journal papers.

  • Attend relevant workshops and present at conferences

Essential requirements

Those appointed at Research Associate level

Hold a PhD (or equivalent) in Engineering or a closely related discipline.

 

Those appointed at Research Assistant level

A first / masters degree (or equivalent) in Engineering or a closely related discipline.

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant level.

Further information

Further Information

 

*This post is full time, fixed term for 42 months (or until 31 Mar 2025 whichever is earliest)

Should you require any further details on the role please contact: Prof. G. Papadakis

 

For queries regarding the recruitment process please contact Lisa Kelly: l.kelly@imperial.ac.uk

 

 

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About Imperial College London

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Additional information

Please note that job descriptions cannot be exhaustive, and the post-holder may be required to undertake other duties, which are broadly in line with the above key responsibilities.

Imperial College is committed to equality of opportunity and to eliminating discrimination. All employees are expected to follow the Imperial Values & Behaviours framework. Our values are: 

  • Respect              
  • Collaboration
  • Excellence          
  • Integrity
  • Innovation

In addition to the above, employees are required to observe and comply with all College policies and regulations.

We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender identity, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion.

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