A recent report from Department for Business, Energy & Industrial Strategy and Innovate UK in July 2021 revealed that the UK composite end-product market in 2019 was estimated at £2.8B and expected to grow to £4.3B by 2035. Composites have found their application in a wide range of industries including aerospace, defence, automotive and wind energy.
Due to their highly desirable material property of being lightweight, strong and durable, composite plates and shells are widely used as structural components of aircraft and wind turbines. Reliable numerical simulations to understand the mechanical behaviours and dynamics of these structures are vital to the utilisation of composite materials. This leads to more efficient designs and better products with minimal waste helping to address sustainability and net-zero challenges.
Numerical modelling of composite plates and shells typically involves using Conservation laws and Material laws to solve the governing boundary-value problems. While the former is universal to all types of materials and physical phenomena, the latter is empirical and uncertain as it is based on various experiment observations. This uncertainty causes modelling errors and contributes to the discrepancy between numerical predictions and real physical behaviours. Traditionally, once the material laws are constructed, all the experimental data will be disregarded causing significant waste of resources and the valuable data is not fully exploited. To tackle this, the data-driven approach performs calculations directly from experiment data while still ensuring the satisfaction of the conservation laws and physical constraints. Additionally, this approach enables uncertainty quantification as the statistical information contained in the data is preserved.
The proposed research aims at developing and implementing an efficient and expandable data-driven framework to model composite plates and shells by utilising material experiment data while maintaining the physical compatibility. The success of this project will result in (i) a novel framework to incorporate real-life data into the numerical modelling circle of composite structures while maintaining physical laws and (ii) broadened knowledge of the newly emerged and promising area of data-driven modelling within the wider field of Computational Mechanics.
This project aligns with one of The Grand Challenges published by the UK Government in January 2021 (Artificial Intelligence and data) which aims to help putting the country at the forefront of the industries of the future.
The successful candidate will have unlimited access to the Faculty’s Oswald supercomputer cluster for code deployment and running simulations in parallel. They will also be supported to make all codes/tools developed from this project open-sourced for reproducibility. These can also be used in small and medium-sized enterprises in structural engineering, at no cost, to reduce their reliance on commercial software and to assist with their numerical modelling needs.
The successful candidate should have a keen interest in Computational Mechanics. Prior knowledge of finite element methods and programming language, e.g. C++, Python, or MATLAB, is desirable but not mandatory.
Academic Enquiries
This project is supervised by Dr Hoang Nguyen. For informal queries, please contact [Email Address Removed]. For all other enquiries relating to eligibility or application process please use the email form below to contact Admissions.
Funding Information
Home and International students (inc. EU) are welcome to apply. The studentship is available to Home and International (including EU) students and includes a full stipend at UKRI rates (for 2022/23 full-time study this is £17,668 per year) and full tuition fees. Studentships are also available for applicants who wish to study on a part-time basis over 5 years (0.6 FTE, stipend £10,600 per year and full tuition fees) in combination with work or personal responsibilities).
Please also see further advice below of additional costs that may apply to international applicants.
Eligibility Requirements:
- Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
- Appropriate IELTS score, if required.
- Applicants cannot apply for this funding if they are already a PhD holder or if currently engaged in Doctoral study at Northumbria or elsewhere.
Please note: to be classed as a Home student, candidates must meet the following criteria:
- Be a UK National (meeting residency requirements), or
- have settled status, or
- have pre-settled status (meeting residency requirements), or
- have indefinite leave to remain or enter.
If a candidate does not meet the criteria above, they would be classed as an International student. Applicants will need to be in the UK and fully enrolled before stipend payments can commence, and be aware of the following additional costs that may be incurred, as these are not covered by the studentship.
- Immigration Health Surcharge https://www.gov.uk/healthcare-immigration-application
- If you need to apply for a Student Visa to enter the UK, please refer to the information on https://www.gov.uk/student-visa. It is important that you read this information very carefully as it is your responsibility to ensure that you hold the correct funds required for your visa application otherwise your visa may be refused.
- Check what COVID-19 tests you need to take and the quarantine rules for travel to England https://www.gov.uk/guidance/travel-to-england-from-another-country-during-coronavirus-covid-19
- Costs associated with English Language requirements which may be required for students not having completed a first degree in English, will not be borne by the university. Please see individual adverts for further details of the English Language requirements for the university you are applying to.
How to Apply
For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/
For applications to be considered for interview, please include a research proposal of approximately 1,000 words and the advert reference (e.g. RDF23/…).
Deadline for applications: 27 January 2023
Start date of course: 1 October 2023 tbc
Continue with Facebook
