Clustering-based identification for the prediction of splitting tensile strength of concrete

Tutmez B.

COMPUTERS AND CONCRETE, vol.6, no.2, pp.155-165, 2009 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 2
  • Publication Date: 2009
  • Doi Number: 10.12989/cac.2009.6.2.155
  • Journal Name: COMPUTERS AND CONCRETE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.155-165
  • Inonu University Affiliated: Yes

Abstract

Splitting tensile strength (STS) of high-performance concrete (HPC) is one of the important mechanical properties for structural design. This property is related to compressive strength (CS), water/binder (W/B) ratio and concrete age. This paper presents a clustering-based fuzzy model for the prediction of STS based on the CS and (W/B) at a fixed age (28 days). The data driven fuzzy model consists of three main steps: fuzzy clustering, inference system, and prediction. The system can be analyzed directly by the model from measured data. The performance evaluations showed that the fuzzy model is more accurate than the other prediction models concerned.