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Compression and Strain Predictive Models in Non-Structural Recycled Concretes Made from Construction and Demolition Wastes.

Evelio Teijón-López-ZuazoJorge López-RebolloLuis Javier Sánchez-AparicioRoberto Garcia-MartínDiego Gonzalez-Aguilera
Published in: Materials (Basel, Switzerland) (2021)
This work aims to investigate different predictive models for estimating the unconfined compressive strength and the maximum peak strain of non-structural recycled concretes made up by ceramic and concrete wastes. The extensive experimental campaign carried out during this research includes granulometric analysis, physical and chemical analysis, and compression tests along with the use of the 3D digital image correlation as a method to estimate the maximum peak strain. The results obtained show that it is possible to accurately estimate the unconfined compressive strength for both types of concretes, as well as the maximum peak strain of concretes made up by ceramic waste. The peak strain for mixtures with concrete waste shows lower correlation values.
Keyphrases
  • sewage sludge
  • heavy metals
  • mental health
  • machine learning
  • anaerobic digestion
  • data analysis
  • high density