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PhD Studentship: Fatigue Life Assessment Methods Under Fully-reversed Cyclic Loading (R ratio = -1) and Their Application in Aerospace Composite Structures

University of the West of England, Bristol - Faculty of Environment and Technology

Qualification Type: PhD
Location: Bristol
Funding for: UK Students, EU Students, International Students
Funding amount: The studentship is available from January 2022 for a period of three years, subject to satisfactory progress and includes a tax exempt stipend, which is currently £15,609 per annum.
Hours: Full Time
Placed On: 17th August 2021
Closes: 14th October 2021
Reference: 2022-JAN-FET05

An opportunity to apply for a full-time PhD in the Faculty of the Environment and Technology, UWE Bristol.  The studentship will be funded or part-funded by the Faculty of Environment and Technology: Ref 2022-JAN-FET05.

The expected start date of this studentship is January 2022

The closing date for applications is 14th October 2021. 

About the Studentship

For the aerospace industry, light-weight advanced composites are widely used to reduce CO2 emissions. Fatigue of composite structures is an important research topic and a key area for aircraft certification. Fatigue experiments are time-consuming and expensive. The acceleration of aircraft development cycles creates the need for replacing physical fatigue testing with robust numerical modelling. This is because numerical modelling can help reduce costs associated with fatigue testing and shorten the design cycle. So far, most existing fatigue models for composite structures have been developed for tension-tension fatigue (R ratio>0). Little modelling work has been done for tension-compression or fully-reversed fatigue (R ratio = -1). In this PhD project, the student will work with our industrial partner to address the below research questions:

  1. How to characterise fatigue crack growth rate under fully-reversed fatigue loading (R ratio = -1)?
  2. How to predict fully-reversed fatigue life (R ratio = -1) of composite structures using cohesive interface elements?
  3. How to use Artificial Neural Network (ANN) to predict fatigue crack growth rates at different R ratios?

It is expected that the student will have excellent numerical skills with a background understanding of the following:

  1. Finite element analysis using Abaqus, LS-DYNA or similar
  2. Computer programming using Matlab, Python or similar
  3. Composite mechanics
  4. Composites manufacturing
  5. Fatigue testing

For an informal discussion about the studentship, please email Dr Xiaodong Xu

Funding details

The studentship is available from January 2022 for a period of three years, subject to satisfactory progress and includes a tax exempt stipend, which is currently £15,609 per annum. 

In addition, full-time tuition fees will be covered for up to three years.

Eligibility criteria

Applicants must have a good first degree and ideally will have Masters.  Students from under-represented groups are particularly encouraged to apply.  The studentship is available both for UK and overseas applicants.

A recognised English language qualification is required.

How to apply

Please submit your application online. When prompted use the reference number 2022-JAN-FET05.  Applicants have the opportunity to discuss their studentship with Directors of Studies via a Webinar to take place on Wednesday 8th September 2021 from 10am to 12noon.  Please contact to reserve your place at this webinar.

Supporting documentation: you will need to upload your research proposal, all your degree certificates and transcripts and your proof of English language proficiency as attachments to your application so please have these available when you complete the application form.

References: you will need to provide details of two referees as part of your application.

Closing date

The closing date for applications is 14th October 2021.

Further information

It is expected that interviews will take place on weeks commencing 1st and 8th November 2021.  If you have not heard from us by 28th October, we thank you for your application but on this occasion you have n

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