Title: Data to support "Large Scale Application of Self-Healing Concrete: Design, Construction and Testing"

Citation
Davies RE, Teall O, Pilegis M, et al. (2018). Data to support "Large Scale Application of Self-Healing Concrete: Design, Construction and Testing". Cardiff University. https://doi.org/10.17035/d.2018.0055749445

Dataset Details

Publisher: Cardiff University

Date (year) of data becoming publicly available: 2018

Data format: .pdf, .bmp, .set, .dat, .im, .vc7, .exp, .jpeg, .xlsx, .xls, .csv, .txt, .doc, .png, .tdms, .avi, .mov, .mp4, .xml

Software Required: (.set, .dat, .im7,.vc7, .exp) Requires DaVis 8.3 Software, from LaVision GmbH.
(.tdms) Requires National Instruments (NI) software - data has been exported to excel.

Estimated total storage size of dataset: Less than 1 terabyte

Number of Files In Dataset: 11621

DOI : 10.17035/d.2018.0055749445

DOI URL: http://doi.org/10.17035/d.2018.0055749445

Related URL: http://www.RM4L.com

Description
This dataset was generated during a self-healing concrete site trial which was part of the Materials for Life (M4L) research project. This project was EPSRC funded and was carried out by the Universities of Cardiff, Bath and Cambridge to investigate the development of self-healing cementitious construction materials.

This was widely reported as the UK’s first site trial of self-healing concrete. The trial comprised the in-situ construction of five concrete panels using a range of self-healing technologies within the site compound of the A465 Heads of the Valleys Highway upgrading project, in South Wales. Four self-healing techniques were used both individually and in combination with one another. They were: (i) the use of microcapsules developed by the University of Cambridge, in collaboration with industry, containing mineral healing agents, (ii) bacterial healing using the expertise developed at Bath University, (iii) the use of a shape memory polymer (SMP) based system for crack closure and (iv) the delivery of a mineral healing agent through a vascular flow network. Both of the latter, (iii) and (iv), were the product of research undertaken at Cardiff University.
The dataset contains information on the design, construction, testing, and monitoring of these trial panels and can be divided into the following sub sections:

• Construction data
  • Calculations
  • Design Drawings
  • Equipment orders
  • Material orders
  • RAMS and Permits
  • Programme
• Progress photos
  • Preparation base wall
  • Panel setup before casting
  • Casting day photos
  • Panels after casting
  • Panel B activation
  • Testing week
  • Monitoring
  • Final testing
• Raw data
  • Concrete
  • Crack measurement (DEMEC) readings
  • Digital image correlation (DIC)
  • Loading activation data
  • Microscope images
  • Ultrasonic measurements
  • Weather data
• Processed data
  • DID Site trial processed DaVis
  • DIC site trial processed Images
  • Loading and activation data

The primary findings of the research work is publishedat https://www.frontiersin.org/articles/10.3389/fmats.2018.00051Further detailed information and insight can be found in Dr Olvier Teall’s PhD thesis at http://orca.cf.ac.uk/id/eprint/100250