Active Chemistry Engineering

The University of Sheffield and Synthotech Limited KTP 24_25 R3

In plain English

AI plain-English summary

Robots will soon listen for leaks in underground water pipes using new sonic sensing technology, rather than relying on excavation or guesswork. Water companies lose billions of litres of treated water each year through leaks and cracks in ageing pipe networks. Current detection methods are slow, expensive, and often miss small defects until they become major bursts. This project aims to close a skills gap in computer simulation, data analysis, and model validation—the foundational science needed to make sonic sensors work reliably on robots that crawl through pipes. Without this capability, the sensors cannot distinguish a hairline crack from normal pipe noise. If successful, the technology could allow water utilities to inspect entire networks continuously, without digging up roads or shutting off supply. Leaks would be found and fixed before they waste water or cause sinkholes. The same approach might eventually extend to gas pipelines, sewers, or industrial fluid systems—anywhere a quiet, mobile listener can catch a problem before it becomes a crisis.

View original technical description
To support the development of new sonic sensing technologies to work on robots to detect leaks and wall defects in water pipelines. The skills gap to address is around computer simulations, data analysis and model validation. The gap is supporting this new development and capability with foundational science.

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Original classification

Knowledge Transfer Partnership

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