Home / PhD Opportunities / Embedded Strain Sensors for Process Monitoring and Digital Twinning
Open now | University of Surrey | In-service availability | AWE
Embedded Strain Sensors for Process Monitoring and Digital Twinning
Develop embedded sensing solutions for in-situ monitoring and digital twinning of composite structures, with direct relevance to civil and defence nuclear systems and space hardware.
Lead Supervisor
Dr Andrew Viquerat
University of Surrey
Industry Partner
AWE
Confirmed
Project Start
1 October 2026
Target Background
Aerospace, Mechanical or Civil Engineering, Materials Science, Physics
Second Supervisor
Prof. Mark J. Whiting
University of Surrey
Industrial Funding
AWE
Confirmed
Advert Close Date
31 August 2026
Programme
4 year Engineering Doctorate (EngD)
with industry placement
Project summary
Aims and objectives
Aim: develop and embed fibre-based strain and strain-sensing systems in polymers and composites to enable in-situ monitoring and digital twinning of degradation processes in civil and defence nuclear applications, and space hardware.
Objectives:
Define application needs. Identify representative polymer composite components and derive practical sensing requirements: strain ranges, accuracy, spatial resolution, environmental limits (temperature, radiation, humidity, vacuum) and lifetime targets.
Select and characterise suitable sensing technologies. Review and compare candidate embedded sensing approaches including fibre-optic sensors (FBGs, distributed sensing), piezoelectric elements, shape-memory alloy fibres and advanced functional fibres. Down-select a small set of promising options and characterise their basic performance (sensitivity, stability, robustness) in simple host materials.
Develop practical embedding and manufacturing strategies. Integrate the selected sensors into representative polymer composite manufacturing routes. Establish embedding methods that preserve structural integrity, ensure good mechanical coupling, and provide manageable routing of fibres and leads.
Evaluate sensing performance under loading and ageing. Subject embedded-sensor specimens to controlled mechanical loading (static and fatigue) and relevant ageing conditions (thermal cycling, moisture, and where feasible radiation or surrogates).
Link measurements to digital twins and derive design guidelines. Develop simplified numerical models of selected specimens and use inverse or data-assimilative methods to infer internal states from sensor data. From the combined experimental and modelling work, produce design guidelines and concept demonstrators for embedded structural health monitoring in both nuclear and space applications.
Alignment to STAND-UP impact targets
>50% reduction in overall build or decommissioning process time (not applicable)
>40% reduction in maintenance time
>30% reduction in person hours on builds (not applicable)
Apply for this project
Contact the lead supervisor or programme team to discuss your interest. Full application instructions are on the How to Apply page.
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This doctoral programme will develop embedded sensing solutions for in-situ monitoring and digital twinning of composite structures, with direct relevance to both terrestrial defence and civil nuclear systems, and space hardware. The focus is on integrating strain and strain-related sensors within structural materials and manufacturing routes, so that degradation processes (matrix cracking, delamination, fibre breakage, creep, and radiation or thermo-oxidative ageing) can be detected and quantified throughout service life.
The project will survey and down-select suitable sensing fibres and transduction mechanisms, including fibre-optic (Fibre Bragg Gratings, distributed sensing), piezoelectric, shape-memory alloy and advanced functional fibres (such as CNT-based or magnetic fibres). These will be embedded via representative manufacturing or forming processes for relevant polymer and composite architectures.
Experimental campaigns will generate strain and damage-state data under controlled loading and ageing conditions representative of the target application environments (thermal cycling, UV radiation exposure, vacuum and outgassing constraints where appropriate). These data will be used to calibrate and validate simplified digital twins, potentially using inverse finite-element methods, to infer internal damage states from sparse sensor measurements.
The outcome will be a set of design guidelines and demonstrator components showing how embedded sensing can enable structural health monitoring and life-extension strategies for safety-critical components and access-limited structures.
Ready to apply?
Read the entry requirements, application process and FAQs on the How to Apply page.