Prediction of Ultimate Bond Strength between Ultra-High Performance Concrete and Titanium Alloy Bars Using a Machine Learning Approach

Abstract

This research discusses the viability of the next-generation novel materials, e.g., titanium alloy bars (TiABs) and ultra-high-performance concrete (UHPC) that have potential to be utilized in civil infrastructures, e.g., bridges, in combination with machine learning (ML) techniques. Since UHPC and TiABs have been demonstrated to be a realistic alternative to traditional construction materials for civil infrastructures, it is important to characterize bond performance of reinforcing, i.e., TiABs embedded in UHPC. The research utilizes improvement of ML techniques, e.g., transfer learning (TL) to predict the bond strength of TiABs in UHPC.

Keywords

• UHPC
• titanium alloy bars
• durability
• bond strength
• machine learning
• transfer learning