Research Studentship in Mechanical Failure Prediction using non-Real Time Condition Monitoring

4-year D.Phil. studentship

EPSRC Industrial CASE Studentship with Schlumberger Gould Research Centre

Supervisor: Dr Alice Cicirello

This studentship is being jointly offered by the University of Oxford and the Schlumberger Cambridge Research Centre under the EPSRC Industrial CASE award scheme.

In the process of Well Construction (planning, drilling, and completion of oil and gas wells), the mechanical tools that constitute the drilling assembly are subjected to extremely harsh conditions, experiencing high pressures and temperatures, and high levels of shock and vibration. Understanding how these tools wear and fatigue during the drilling process is critical to efficiently constructing wells. This project focuses on developing strategies to monitor the condition of the tools after being used to make informed decision as to whether that tool can be re-used or corrective maintenance is required. The project will involve investigation of non-destructive testing techniques, data-driven modelling of how mechanical components may fatigue, and the ability to predict the probability of a component failing during next use,

The project will therefore allow the development of expertise in:
• Advanced modelling techniques
• Laboratory Scale Experiments
• State of the art non-destructive testing
• Data Analytics and Data Science.

Eligibility

This studentship is funded through the UK Engineering and Physical Sciences Research Council (EPSRC) Industrial Cooperative Awards in Science & Technology (CASE) Award Scheme and is open to both UK students (full award – fees plus stipend) and EU students (partial award – fees only). Full details of the EPSRC eligibility requirements can be found here
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Award Value

University course fees are covered at the level set for UK/EU students (£7730 in 2019-2020 academic year). The stipend (tax-free maintenance grant) will be £15,009 for the first year, and at least this amount for a further three years.

Candidate Requirements

Prospective candidates will be judged according to how well they meet the following criteria:

• A first class honours degree in Engineering or Physics with advanced level courses in mechanics; structural dynamics and/or signal processing.
• Experience of experimental research in the field of structural dynamics and/or structural health monitoring demonstrated by a publication at an international conference, journal or first class final year project report;
• Excellent English written and spoken communication skills;
The following skills are desirable but not essential:
• Ability to program in Matlab and/or Python
• Experience of Abaqus or similar Finite Element software package;

Application Procedure

Informal enquiries are encouraged and should be addressed to Dr Alice Cicirello ([Email Address Removed]).

Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website.

Please quote 19ENGIN_AC in all correspondence and in your graduate application.

Application deadline: noon on 26 April 2019

Start date: 1 October 2019