COMPRESSIVE STRENGTH MODELLING OF CONCRETE MIXED WITH FLY ASH AND WASTE CERAMICS USING k-NEAREST NEIGHBOR ALGORITHM

Abstract

Excessive materials are being manufactured, and along with it are the waste products that are
being produced due to the rapid growth of industries. In the Philippines, wastes such as fly ash and damaged
ceramics are being considered as a construction material since there are recent researches that proved their
properties are comparable to cement and aggregates. In this study, compressive strength tests (ASTM C 39)
were conducted to obtain the compressive strength of the concrete mixed with varying amounts fly ash and
waste ceramics. Moreover, specimens were also subjected to varying days of curing to assess their strength
development. Due to the availability of a wide range of data, machine learning model, such as the k-nearest
neighbor, were also considered; it can predict an unknown target parameter without consuming tremendous
time and resources. Thus, this study aimed to provide a k-nearest neighbor model that will serve as a
reference 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 knearest neighbor model used was validated to ensure the predictions are acceptable.