WP4 – Digitalisation and automation: smart soil stabilisation

Photo above: Digilev 3D-modelling (Photo: NGI)

Research tasks

• T.4.1 Perform non‐destructive monitoring of the soil treatment process in the laboratory (WP1)
• T.4.2 Design and test DFOS and S‐wave velocity probes to monitor the soil stabilisation in the field
• T.4.3 Implement and validate the developed equipment at field scale (WP3)
• T.4.4 Adopt data mining techniques to identify correlations between execution parameters, monitoring data and engineering properties of stabilised soil
• T.4.5 Translate the obtained findings from the WPs 1 to 4 into an automated design framework

Theoretical approach and methodology

To date, the properties of improved soil are predominantly measured using destructive methods. Latest sensing technologies and geophysical methods are promising and novel tools to map temporal and spatial changes of the properties of stabilised soil. Adopting and validating non‐destructive techniques to monitor ground improvement works can result in a data revolution in soil stabilisation. Translating these data into an automated design framework will create innovation.

WP4 will be devoted to generating high‐quality data of stabilised soil and data analysis. The application of DFOS and S‐wave velocity measurements for monitoring the soil stabilisation process will first be tested at laboratory scale which will provide a solid foundation to subsequently adopt these techniques in the field.

The purpose‐made column experiments (WP1) will provide a controlled environment to test and validate the performance of these techniques. An optical fibre probe, which can be pushed into the soil directly after mixing and remains there for the entire lifetime of the stabilised soil, will be designed and tested to conduct distributed temperature and strain sensing.

WP4 will additionally develop an S‐wave velocity measurement system for stabilised soil. The possibility of adopting an optical fibre to determine the S‐wave velocity of the stabilised soil beneath the fibre will also be explored. Initial work on this topic by the consortium partner University College Dublin showed promising results. These monitoring techniques will be tested at the field tests (WP3).

WP4 will analyse the obtained field data to evaluate the applicability and performance of the different techniques to monitor the soil stabilisation in real‐time and explore data mining techniques to detect patterns between execution data, monitoring data and engineering properties. Finally, WP4 will translate the generated knowledge into a data‐driven design framework that enables automation of soil stabilisation.