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:

Data contains personal data

Language

English

Method and outcome

Data format / data structure

Numeric

Text

Still image

Data collection

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
Sample: CS50G
Specimen loaded with a small cone, 50 mm thick concrete top layer and a ground substrate surface
Sample: CS50H
Specimen loaded with a small cone, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: CS100H
Specimen loaded with a small cone, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: CS100G
Specimen loaded with a small cone, 100 mm thick concrete top layer and a ground substrate surface
Sample: CL50G
Specimen loaded with a large cone, 50 mm thick concrete top layer and a ground substrate surface
Sample: CL50H
Specimen loaded with a large cone, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: CL100G
Specimen loaded with a large cone, 100 mm thick concrete top layer and a ground substrate surface
Sample: CL100H
Specimen loaded with a large cone, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: BL50G
Specimen loaded with a large lifting bag, 50 mm thick concrete top layer and a ground substrate surface
Sample: BL50H
Specimen loaded with a large lifting bag, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: BL100G
Specimen loaded with a large lifting bag, 100 mm thick concrete top layer and a ground substrate surface
Sample: BL100H
Specimen loaded with a large lifting bag, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: BS50G
Specimen loaded with a small lifting bag, 50 mm thick concrete top layer and a ground substrate surface
Sample: BS50H
Specimen loaded with a small lifting bag, 50 mm thick concrete top layer and a hydro-demolished substrate surface
Sample: BS100G
Specimen loaded with a small lifting bag, 100 mm thick concrete top layer and a ground substrate surface
Sample: BS100H
Specimen loaded with a small lifting bag, 100 mm thick concrete top layer and a hydro-demolished substrate surface
Source of the data: Research data, Physical objects

Geographic coverage

Administrative information

Responsible department/unit

Architecture and Civil Engineering

Contributor(s)

Ignasi Fernandez - Chalmers University of Technology, Architecture and Civil Engineering

Carlos Gil Berrocal - Chalmers University of Technology, Architecture and Civil Engineering

Rasmus Rempling - Chalmers University of Technology, Architecture and Civil Engineering

Funding

Funding agency: Swedish Transport Administration
Funding agency's reference number: TRV2021/66599
Project name on the application: 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

Research area

Infrastructure engineering (Standard för svensk indelning av forskningsämnen 2011)

Keywords

Tunnel construction, Load-bearing structures, Fibre optics, Concrete, Shotcrete

Publications

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
DOI: https://doi.org/10.1016/j.dib.2024.110920

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Published: 2024-10-18

Last updated: 2024-10-18