Digital Underground Construction

PI: Byrne, Byron

Department: Engineering Science (DF)

Growing populations and the effects of climate change have placed unprecedented pressures on water and wastewater systems worldwide. A substantial amount of new buried infrastructure is required in the UK alone ‒ and efficient use of underground space appears the most viable, if not the only, sustainable solution. Whilst construction is beginning to enjoy exciting innovations, these relate primarily to above-ground activities. Similar advances underground have been obstructed by key residual uncertainties relating to structural interaction with soil. This is because systems to measure and monitor 'soil-structure interaction' (SSI) during underground construction simply do not exist. This is particularly important for (micro-) tunnelling, shafts and deep excavations where 'soil-structure interaction (SSI)' plays a crucial role in the construction process. Solving these uncertainties is essential to achieve UK government targets of 50% reduction in emissions and 33% reduction in costs by 2025.

To overcome these limitations, Dr Sheil's team has developed a novel soil contact stress sensor by combining (a) a new 'box-type' sensor structure, (b) state-of-the-art fibre optic strain sensing and (c) machine learning. The team have obtained first proof-of-principle data and have validated a prototype sensor. This project aims to bring these sensors to technology readiness level 7 by integration these sensors within a real-time monitoring system and demonstrating their impact in an operational construction environment. At the end of the project we will seek follow-on capital venture investment to spin out a company with the construction sector as the initial primary market; this case study will be used to help attract that investment.