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Sellafield monitors nuclear waste with NPL technique


The National Physical Laboratory (NPL) has deployed its High Accuracy Inspection System (HAIS) to the Sellafield nuclear site in Cumbria.

Pile Fuel Storage Pond at Sellafield (CR: Sellafield Ltd)
Pile Fuel Storage Pond at Sellafield (CR: Sellafield Ltd)

The HAIS technique was developed by NPL using digital image correlation technology, an imaging technique well suited for monitoring integrity and conditions of materials.

Encapsulated waste products have been stored at the Sellafield site for years, and the range of waste products is expected to increase over the next decade as the site evolves.

Inspection of the waste stores is vital for safe storage, but the process is time-consuming. In-situ measurements and deployment techniques are required to demonstrate control and allow appropriate mitigating action where necessary, and reduce dose to workers who currently provide ad-hoc measurement capability.

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Using HAIS, regular inspections can be carried out up to 16m deep into low-level waste stores. HAIS deploys a camera vertically into an inspection port and takes a series of images of the waste storage at pre-determined points. 

It then uses digital image correlation to analyse previous image sets and quantifies changes over time including corrosion, movement, vibration and dirt or water ingress. The inspection technique uses in-situ automated technology in dark store environments where traditional communication channels or power sources are absent.

Areas of concern can be highlighted and monitored, enabling small changes such as signs of unexpected degradation to be detected sooner than by using traditional manual inspection techniques.

Deploying HAIS to monitor waste stores can lead to a greater understanding of the evolution of nuclear materials and how it impacts on long-term safe storage, NPL said. For example, measuring the properties of materials in-situ allows for a better understanding of how much heat is being generated by the material and what the storage system needs to tolerate it.

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By increasing the predictability of the environment and helping to infer waste behaviour in existing waste stores, the system can provide information for influencing new store design and improvement of existing store conditions.

“At NPL we are interested in developing techniques to make measurements less subjective and to minimise human variability,” said Dr Nick McCormick, NPL principal research scientist. “The automation ensures the inspector can concentrate on areas of potential concern and use their skills to efficiently make an accurate assessment of conditions.”



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