Andreas Sjölander

Lecturer and researcher at the Division of Concrete Structures. The main focus of my research is on the assessment of existing structures and, in particular, the risk assessment related to cracks in concrete tunnel linings. In TACK-II, we continue our towards creating a semi-autonomous inspection method for tunnels. The project is funded by Formas and is a collaboration between researchers at the Division of Concrete Structures and Geoinformatics at KTH and the Sapienza University of Rome. In the project, we will compare the results from digital and human inspections to show the potential of digital inspection methods.

PrintCrete is a collaboration project that, among others, includes RISE, Lund University and ABB. My part in the project includes the structural assessment of 3D-printed concrete structures.

SensIT is a project run by Chalmers which includes the work of PhD student August Jansson. The aim of the project is to combine the use of fibre-optic sensors in the shtocrete with an AI framework to create a forecast model for maintenance and alarm limits for the shotcrete lining. My part in this project includes numerical modelling of bolt-anchored and fibre-reinforced shotcrete in contact with hard rock. In particular, the aim is to verify experimental data and create synthetic data to train an AI model.

In my role as senior researcher at Svensk Vattenkraft Centrum, I'm involved as a supervisor for PhD student Jonas Enzell, who investigates failure modes of concrete buttress dams. Moreover, I'm working in a project to create a forecast model for ice loads on concrete dams. In the project we are measuring the ice load on two dams in Sweden using a custom designed large scale panel.

Project	Link	Image
TACK-II - An AI Framework for Automated Tunnel and Assessment	Homepage
Fibre materials in tunnels
PrintCrete - 3D Printing of Concrete Elements	PrintCrete
SensIT - Sensor-Based Forecast Method using AI	SensIT
Forecasting of Ice Load