New Optical Imaging and Analysis Techniques for the Early Detection and Quantification of Corrosion on Special Nuclear Materials Packages

This PhD research will focus on designing novel signal and image processing techniques using a combination of state-of-the art Deep Neural Networks and Traditional methods to segment, analyse and quantify corrosion products on materials used in special nuclear materials packages including stainless steel and aluminium extrusions. The work will be conducted in collaboration with University of Manchester (funded by Sellafield and FIND CDT) who will corrode a series of stainless steel and aluminium coupons over time with chlorides of interest for which the chloride index will be known in each experiment. Corrosion coupons will be imaged at regular intervals throughout their lifetime using a range of optical sensor technologies including Stereomicroscopy, Optical Microscopy, Laser Confocal Microscopy, LIBS and RAMAN (University of Manchester) through to RGB and Hyperspectral Imaging (University of Strathclyde). Novel algorithms will be designed at the University of Strathclyde (UoS) to analyse images of all modalities which will result in the creation of a set of multiscale image analysis techniques to detect and quantify corrosion from the microscopic to macroscopic scale using spatial and spectral information. The acquisition of the described dataset, combined with the proposed analysis routines, will be a first-of-their-kind suite of tools to detect - with confidence - the earliest point at which corrosion products can be robustly identified in all imaging technologies. It is anticipated that the detection ability and sensitivity of the sensors will be enhanced by the design of our proposed image analysis routines which will also fuse data from an optimal set of sensors to be identified in this study. Fundamentally, this research will be made possible through the analysis of microscopic imaging (to provide reliable ground truth of the earliest presence of corrosion) and spectroscopic analysis techniques combined with full knowledge of all chlorides used to induce corrosion and sophisticated monitoring and analysis of the entire corrosion lifecycle on a range of metals of interest.
From an academic perspective, the proposed research aims to make the following key novel contributions:

-Introduction of new techniques for processing and analyzing corrosion products at the macroscopic scale for inspection purposes using data from a diverse set of advanced optical sensor technology.
-Design, implementation and testing of new corrosion detection tools by advancing state-of-the-art Machine Learning techniques for data fusion and classification of a range of complementary, multimodal, optical sensors.
-Creation of novel corrosion chronology analysis algorithms capable of modelling the progression of corrosion over time. Once developed using data gathered for training, this will be applied to unseen inspection footage and used to predict corrosion progression and help identify any necessary intervention to prevent adverse outcomes.
-Robust validation of the proposed array of optical sensor technology when combined with our proposed techniques using expert microscopy and materials science (UoM).
-Creation of a unique, information-rich dataset gathered using a suite of state-of-the-art optical sensor technology. To the best of the authors' knowledge, this will be the first dataset of its kind to allow the time-lapse analysis of corrosion product lifecycle from the microscopic to macroscopic scale alongside the underlying chemical properties of the materials understudy.

Complementing our Pathways to Impact document, here we state the expected real-world impact, which is of course the leading priority for our industrial partners. Their confidence that the proposed CDT will deliver valuable scientific, engineering and commercial impact is emphasized by their overwhelming financial support (£4.38M from industry in the form of cash contributions, and further in-kind support of £5.56M).

Here we summarize what will be the impacts expected from the proposed CDT.

(1) Impact on People
(a) Students
The CDT will have its major impact on the students themselves, by providing them with new understanding, skills and abilities (technical, business, professional), and by enhancing their employability.
(b) The UK public
The engagement planned in the CDT will educate and inform the general public about the high quality science and engineering being pursued by researchers in the CDT, and will also contribute to raising the profile of this mode of doctoral training -- particularly important since the public have limited awareness of the mechanisms through which research scientists are trained.

(2) Impact on Knowledge
New scientific knowledge and engineering know-how will be generated by the CDT. Theses, conference / journal papers and patents will be published to disseminate this knowledge.

(3) Impact on UK industry and economy
UK companies will gain a competitive advantage by using know-how and new techniques generated by CDT researchers.
Companies will also gain from improved recruitment and retention of high quality staff.
Longer term economic impacts will be felt as increased turnover and profitability for companies, and perhaps other impacts such as the generation / segmentation of new markets, and companies receiving inward investment for new products.

(4) Impact on Society
Photonic imaging, sensing and related devices and analytical techniques underpin many of products and services that UK industry markets either to consumers or to other businesses. Reskilling of the workforce with an emphasis on promoting technical leadership is central to EPSRC's Productive Nation prosperity outcome, and our CDT will achieve exactly this through its development of future industrially engaged scientists, engineers and innovators. The impact that these individuals will have on society will be manifested through their contribution to the creation of new products and services that improve the quality of life in sectors like transport, dependable energy networks, security and communications.

Greater internationalisation of the cohort of CDT researchers is expected from some of the CDT activities (e.g. international summer schools), with the potential impact of greater collaboration in the future between the next generations of UK and international researchers.