A New Risk Monitoring Approach to Assess Infrastructure Performance

One of the most vulnerable elements of the built environment is critical infrastructure constructed near water bodies, as flowing water negatively impacts their performance [1]. Water-related hazards can increase degradation effects which can be the leading cause for their structural failure. The current practice to assess the condition of structures is typically based on visual inspections, which in many cases are carried out in challenging environmental conditions posing threats for the health and safety of inspectors, among other issues [2]. Important key points about the safety of the structures are often not captured by the visual inspections because these areas of interest are not accessible or visible by inspectors. Real-time monitoring of flood events together with other environmental and structural-related datasets are considered key to better understanding essential aspects of degradation effects at infrastructure. The difficulty in detecting seepage processes inside the body of geo-infrastructure with conventional methods also leads to irreversible impacts with significant disruption and costs to road asset owners, maintainers, and users. The need to obtain real-time information about the evolution of natural and climatic hazards is therefore considered necessary considering the ageing infrastructure, constructed near geomorphologically active rivers, and the extreme shifting climatic conditions.

This work investigated the development of a new risk-monitoring ecosystem to remotely assess the condition of infrastructure. The development of two sensing units with complementary characteristics to provide information about flood risk at bridge sites and seepage processes at road embankments is presented. The sensing system is based on a cloud-based interface with a web-based visualization tool that enables asset owners to monitor in real-time the health of infrastructure systems and receive early warnings when incoming data exceed predetermined threshold levels [1,2,3]. Finally, the potential application location of the sensing units is also discussed alongside the proposed threshold levels that will provide information about the low, medium, high, and very high-risk probability.

References

[1] Michalis, P., Saafi, M. and Judd, M. 2012. Wireless sensor networks for surveillance and monitoring of bridge scour. Proceedings of the XI International Conference Protection and Restoration of the Environment - PRE XI. Thessaloniki, Greece, pp. 1345–1354.

[2] Michalis, P. Xu., Y. and Valyrakis M. (2020). Current practices and future directions of monitoring systems for the assessment of geomorphological conditions at bridge infrastructure. River Flow 2020. Proceedings of the 10th Conference on Fluvial Hydraulics, Delft, Netherlands, 7-10 July. pp. 1-6.

[3] AlObaidi, K. and Valyrakis, M. (2021). Explicit linking the probability of entrainment to the flow hydrodynamics, Earth Surface Processes and Landforms, DOI: 10.1002/esp.5188.