ARTIFICIAL NEURAL NETWORK (ANN) MODELLING OF CONCRETE MIXED WITH WASTE CERAMIC TILES AND FLY ASH

Authors

  • Kenneth Jae T. Elevado
  • Joenel G. Galupino
  • Ronaldo S. Gallardo

Keywords:

Compressive strength, waste utilization, fly ash, ceramics, artificial neural network

Abstract

Waste generation has been the result of a growing demand in the construction industry. Thus,
waste utilization has been one of the considerations in the construction industry towards sustainability. In the
Philippines setting, many types of research were conducted to support the claim that wastes such as fly ash
and waste ceramics have properties that are comparable to cement and aggregates. The American Concrete
Institute standards were referred in the mix design of the specimens. This study incorporated the use of fly
ash in the replacement of Type 1 Portland Cement and the substitution of waste ceramic tiles in replacing
gravel as the coarse aggregates. Moreover, specimens were also subjected to varying days of curing to assess
their strength development. Machine learning, namely Artificial Neural Network (ANN), was considered
since there was an available wide range of data. This study aimed to provide an Artificial Neural Network
(ANN) algorithm that will serve as a model to predict the compressive strength of concrete while
incorporating waste ceramic tiles as a replacement to coarse aggregates while varying the amount of fly ash
as a partial substitute to cement. The Artificial Neural Network (ANN) model used was validated to ensure
the predictions are acceptable.

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Published

2018-06-22

How to Cite

Kenneth Jae T. Elevado, Joenel G. Galupino, & Ronaldo S. Gallardo. (2018). ARTIFICIAL NEURAL NETWORK (ANN) MODELLING OF CONCRETE MIXED WITH WASTE CERAMIC TILES AND FLY ASH. GEOMATE Journal, 15(51), 154–159. Retrieved from https://geomatejournal.com/geomate/article/view/1035