Towards resilient smart monitoring of geostructures

Uncertain ground conditions and poor visualisation of data are the root of around 30% of project overruns and/or additional costs in Swedish infrastructure projects. Additionally, the uncertainty in ground conditions has been shown to account for 20-55% increases in embedded carbon during construction of ground engineering structures, which are typically made of steel and concrete. The amount of materials used can be significantly reduced by bringing the Observational Method to full fruition, by combining numerical forecasting models with field monitoring results using data-assimilation. Thus, the heterogeneous spatially and temporally distributed measurement data of a typical construction project can be intelligently combined to understand the complex system behaviour, and this knowledge can be exploited in future projects. Realising this ambition is not simple, but still achievable. This project will address this challenge by developing smart monitoring solutions for geostructures.As part of the proposed project, a s software tool to combine geotechnical site investigation data and advanced numerical modelling with heterogeneous monitoring data for high-fidelity forecasting will be created. This so-called data assimilation approach helps to maximise the value of monitoring data by improving the quality, and by enabling the prediction of future states using numerical models that have been updated using several sources of monitoring data. This increases the reliability of monitoring data and model predictions for geostructures. The proposed data-assimilation approach enables early warning systems and scenario-based forecasting, thus reducing uncertainty, costs, improving safety and increasing (climate) resilience of infrastructure. Most importantly, the approach will enable high fidelity control of complex systems in urban settings where environmental concerns are a major issue.

Partner organizations

  • Ramböll AB (Private, Denmark)
Start date 01/06/2020
End date 31/05/2023

Page manager Published: Tue 14 Dec 2021.