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

Engineering Proceedings

article

Mahesh Acharya¹  Luis Bedriñana²  Jared Cantrell¹  Ankit Bhaukajee³  Mustafa Mashal¹ 

[1] Department of Civil & Environmental Engineering, Idaho State University;Department of Civil Engineering, Universidad de Ingenieria y Tecnologia—UTEC;Farm Bureau Mutual Insurance Company of Idaho

关键词: UHPC;    titanium alloy bars;    durability;    bond strength;    machine learning;    transfer learning;    concrete structures;   

DOI  :  10.3390/engproc2023036016

来源: mdpi

【 摘 要 】

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.

【 授权许可】

Unknown