K-Means Clustering Applied to Reinforcement Corrosion
Wei Nair
Corresponding
University of Rajshahi
Fatima Bose
University of Chittagong
Vijay Rao
Cairo University
Abstract
Failures observed in existing tannery wastewater have highlighted the need for a deeper understanding of reinforcement corrosion. The study adopts k-means clustering as its principal tool for exploring the behaviour of tannery wastewater. Field trials conducted at 9 separate sites yielded consistent and reproducible estimates of reinforcement corrosion. The conclusions carry clear implications for the maintenance strategies adopted by operators.
Keywords:
reinforcement corrosionk-means clusteringinduction motorfatigue analysis
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