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Statistical analysis of fibre variability in composites manufacture

This project is no longer listed on and may not be available.

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  • Full or part time
    Prof M Tretyakov
    Prof F Ball
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Multidisciplinary collaborations are a critical feature of material science research enabling integration of data collection with computational and/or mathematical modelling. This PhD study provides an exciting opportunity for an individual to participate in a project spanning research into composite manufacturing, stochastic modelling, statistical analysis and scientific computing. The project is integrated into the EPSRC Centre for Innovative Manufacturing in Composites, which is led by the University of Nottingham and delivers a co-ordinated programme of research in composites manufacturing.

This project focuses on the development of a manufacturing route for composite materials capable of producing complex components in a single process chain based on advancements in the knowledge, measurement and prediction of uncertainty in processing. The outcome of this work will enable a step change in the capabilities of composite manufacturing technologies to be made, overcoming limitations related to part thickness, component robustness and manufacturability as part of a single process chain, whilst yielding significant developments in mathematics and statistics with generic application in the fields of stochastic modelling and inverse problems.

The specific aims of this project are: (i) statistical analysis of fibber placements based on textile and composite material data sets; (ii) statistical analysis and stochastic modelling of permeability of textiles and composites; (iii) efficient sampling techniques of stochastic permeability. A student will obtain an excellent grasp of various statistical and stochastic techniques (e.g., spatial statistical methods, use of random fields, Monte Carlo methods), how to apply them, how to work with real data and how to do related modelling and simulation. This knowledge and especially experience are transferable to other applications of statistics and probability.

The PhD programme contains a training element, the exact nature of which will be mutually agreed by the student and their supervisors.

We require an enthusiastic graduate with a 1st class honours in Mathematics (in exceptional circumstances a 2(i) class degree can be considered), preferably at the MMath/MSc level, with good programming skills and williness to work as a part of an interdisciplinary team. A candidate with a solid background in statistics and stochastic processes will have an advantage.

Funding Notes

The studentship is available for a period of three and a half years from September/October 2015 and provides a stipend and full payment of Home/EU Tuition Fees. Students must meet the EPSRC eligibility criteria.

Informal enquiries should be addressed to Prof. Michael Tretyakov, email: [Email Address Removed].
To apply, please access: Please ensure you quote ref: SCI/1262X1. This studentship is open until filled. Early application is strongly encouraged.

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