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Novel Bayesian Approaches to Frequency Domain Modal Analysis

  • Full or part time
  • Application Deadline
    Friday, December 20, 2019
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

Project Description

One of the key technologies used in industry and academia to analyse and understand dynamic structures is modal analysis. This PhD project, based in the Dynamics Research Group at The University of Sheffield, aims to extend and enhance our current techniques through machine learning.

By considering statistical machine learning methods, the objectives of this project are to answer questions like:

• Have we collected enough data to confidently say something about a structure?

• Is noise in our test causing us to misidentify the behaviour of a structure?

• How many degrees of freedom do we have evidence for in the data?

• Can we automate the selection of a model for our system?

As well as being a technically interesting challenge, by developing tools to answer these questions, this project will provide methods for industrial practitioners to make confident decisions about the design and operation of engineering systems. Through form uncertainty quantification and management engineers can build more efficient structures and operate them with a higher degree of confidence. This project will provide an opportunity to explore how recent advances in machine learning can impact the way we address a traditional engineering problem.

About the Dynamics Research Group

The Dynamics Research Group (DRG) based in the Mechanical Engineering department at The University of Sheffield is a world leading research group focussed on nonlinear dynamics, structural health monitoring, vibration control, and smart materials and structures. As well as having 70+ members undertaking research in the group, there is access to unique facilities including the £12m Laboratory for Verification & Validation with capability to test dynamic structures under realistic environmental conditions. This provides an exciting and vibrant environment in which to perform state-of-the-art research.

How to Apply & Eligibility

1st or 2:1 degree in Engineering, Computer Science, Physics, Applied Mathematics or other Relevant Discipline

This funding is provided for home (UK) students. For further information about this project, please contact Dr Timothy Rogers (). To apply, please use our standard on-line PhD application form, including your CV and two references, and indicate on your form that you are replying to this advert. For further guidance on applying, please email
.

Funding Notes

This position is a 3.5 year studentship fully funded by The University of Sheffield, Department of Mechanical Engineering. The funding covers the cost of tuition fees and provides an annual tax-free stipend at the standard UK research rate (currently £15,009).

How good is research at University of Sheffield in Aeronautical, Mechanical, Chemical and Manufacturing Engineering?
Chemical and Biological engineering

FTE Category A staff submitted: 30.00

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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