Experimental data for loads on tunnel linings including distributed optical fiber sensing and digital image correlation
https://doi.org/10.5878/dvcn-bg03
The data is collected during experiments that aims to reproduce loading conditions in shotcrete tunnel linings. The data includes strain measurements from distributed optical fiber sensors, image series taken simultaneously by two cameras for digital image correlation purposes and load-, displacement- and pressure measurements by load cells, LVDTs and pressure gauges respectively. Supplementary data including material testing and 3D-scans before and after each run is also included. The material testing data includes concrete cube compression tests, wedge splitting tests and tensile tests of cores drilled from the main specimens. A detailed description of the experimental setup and execution is described in the data paper:
Documentation files
Documentation files
Citation and access
Citation and access
Data access level:
Creator/Principal investigator(s):
Research principal:
Data contains personal data:
No
Citation:
Language:
Method and outcome
Method and outcome
Data format/data structure:
Data collection - Laboratory experiment
Data collection - Laboratory experiment
Mode of collection:
Laboratory experiment
Description of the mode of collection:
Distributed optical fiber sensors, photography, 3D-scanning, measurements for load cells, LVDTs and pressure gauges
Data collector:
- Chalmers University of Technology
Opens a new window at ror.org.
ROR
Source of the data:
- Research data
- Physical objects
Sample
Sample
Name:
CS50G
Description of sample:
Specimen loaded with a small cone, 50 mm thick concrete top layer and a ground substrate surface
Name:
CS50H
Description of sample:
Specimen loaded with a small cone, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
CS100H
Description of sample:
Specimen loaded with a small cone, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
CS100G
Description of sample:
Specimen loaded with a small cone, 100 mm thick concrete top layer and a ground substrate surface
Name:
CL50G
Description of sample:
Specimen loaded with a large cone, 50 mm thick concrete top layer and a ground substrate surface
Name:
CL50H
Description of sample:
Specimen loaded with a large cone, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
CL100G
Description of sample:
Specimen loaded with a large cone, 100 mm thick concrete top layer and a ground substrate surface
Name:
CL100H
Description of sample:
Specimen loaded with a large cone, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
BL50G
Description of sample:
Specimen loaded with a large lifting bag, 50 mm thick concrete top layer and a ground substrate surface
Name:
BL50H
Description of sample:
Specimen loaded with a large lifting bag, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
BL100G
Description of sample:
Specimen loaded with a large lifting bag, 100 mm thick concrete top layer and a ground substrate surface
Name:
BL100H
Description of sample:
Specimen loaded with a large lifting bag, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
BS50G
Description of sample:
Specimen loaded with a small lifting bag, 50 mm thick concrete top layer and a ground substrate surface
Name:
BS50H
Description of sample:
Specimen loaded with a small lifting bag, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Name:
BS100G
Description of sample:
Specimen loaded with a small lifting bag, 100 mm thick concrete top layer and a ground substrate surface
Name:
BS100H
Description of sample:
Specimen loaded with a small lifting bag, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Administrative information
Administrative information
Responsible department/unit:
Architecture and Civil Engineering
Contributor(s):
Funding
Funding
Funding agency:
- Swedish Transport Administration
Opens a new window at ror.org.
ROR
Award number:
TRV2021/66599
Award title:
SensIT - Verification and forecasting of technical functional requirements on concrete tunnel lining - sensor-based forecasting method with artificial intelligence
Funding information:
The purpose of the project is to contribute to the development of methods for information acquisition via sensors that can be used to forecast and verify technical functional requirements using Artificial Intelligence.
The starting point and background are tunnel casings of fibre-reinforced shotcrete. The construction consists of a complex material and there is often a lack of detailed information about the surrounding mountains. The material and the rock work together as the load-bearing system, which together gives an uncertainty about its function.
Topic and keywords
Topic and keywords
Swedish Standard Classification of Research Subjects 2025:
Relations
Relations
Website:
Publications
Publications
Citation:
Jansson, A., Fernandez, I., Berrocal, C.G., & Rempling, R. (2024). Experimental dataset for loads on hard rock shotcrete tunnel linings in a laboratory environment. Data in Brief, Volume 57, December 2024. https://doi.org/10.1016/j.dib.2024.110920
