Predictive Modelling of Self-Compacting concrete (SCC) properties produced with the inclusion of with Ceramic tile powder

Authors

  • Umeh, Ifeanyi O Department of Civil Engineering, University of Nigeria, Nsukka, Enugu State Nigeria.
  • Oni Fazal O Department of Civil Engineering, University of Nigeria, Nsukka, Enugu State Nigeria.
  • Ozougwu, Chidiogo P Department of Civil Engineering, University of Nigeria, Nsukka, Enugu State Nigeria.
  • Uwemedidara, Akpan I Department of Civil Engineering, University of Nigeria, Nsukka, Enugu State Nigeria

Keywords:

SCC, Ceramic tile powder, superplasticizer, w/b ratio, Gene expression programming

Abstract

Predictive models are the up-start trend in concreting technology, most especially green concrete. The predictive model of self-compacting concrete SCC properties that integrate ceramic tile powder (CTP) as an admixture on some properties is the target of this study. Taguchi L9 optimization technique was adopted to optimize the applied process parameters that involved CTP, water to binder (W/B) and superplasticizers (SP). The percentages of CTP added were 0.0%, 10.0 %, 12.5% and 15.0 % of the cement mass. Three level were assigned to three parameters of CTP, W/B ratio and SP each in the L9 ( ) Taguchi mixed level orthogonal array, as the design of experiment (DoE). The results from the Taguchi optimization method were compiled and a machine leaning algorithm (ML), known as gene expression programming GEP was used to obtain models for the bulk density (BD), beam bulk density (BBD) and water absorption capacity (WAC) parameter.

Published

2025-10-06

Issue

Vol. 5 No. 3 (2025): UNIZIK Journal of Engineering and Applied Sciences

Section

Articles