Researchers in Australia are developing digital twins to monitor the performance of urban infrastructure and make intelligent maintenance decisions.
Bridges, roads, railways, pipelines and power transmission towers must be inspected regularly to ensure safely, but advanced technologies such as wireless sensors and machine learning can eliminate the need for frequent inspections, saving time and money and reducing the risks of working on hazardous sites, explain Mojtaba Mahmoodian, Kevin Zhang and Sujeeva Setunge from RMIT University’s School of Engineering in an article for The Conversation.
With a digital twin, wireless sensors on the structure transfer performance data to a virtual copy of the assets, allowing engineers to identify deformations, deflections, cracks or even stresses due to various loads (such as traffic or wind). They can then make critical maintenance decisions about which structural elements need to be repaired or replaced, and when this must be done, to ensure the infrastructure is safe. The intelligent digital twin model can even suggest appropriate maintenance decisions.
Digitalising the way we look after our infrastructure can make the process more accurate and less costly in the long term, with cost savings of 20-30% compared to traditional labour-intensive practices, the authors say. Given the huge costs of monitoring infrastructure – in the US, for example, bridge inspections alone cost $1.35bn a year – the potential savings are huge.
At RMIT, engineers are currently focused on bridge and port infrastructure but the technology can also be used for railways, water and wastewater pipelines, liquefied natural gas (LNG), oil and gas pipelines, offshore platforms, wind turbines and power transmission towers.
For further insight into how smart tech will change the face of the built environment, read Osborne Clarke’s report Future Proof Real Estate: Is the property sector ready for the 2020s?
Tags: digital twins
