Date of Award

2008

Degree Type

Thesis

Degree Name

Master of Engineering Science

Program

Civil and Environmental Engineering

Abstract

Superelastic shape memory alloys (SMAs) have the ability to recover plastic deformations upon unloading. This unique property has motivated researchers to utilize them as primary reinforcement for RC structures located in seismic regions. The lack of understanding the behaviour of SMA RC sections is constraining their use. This thesis investigates the flexural behaviour of SMA RC sections. The validity of the flexural design equations provided by the Canadian Standards for SMA RC sections is evaluated. The load-deflection behaviour of SMA RC members is also investigated. The results are used to assess the applicability of available deflection models for SMA RC members. Artificial neural networks (ANNs) are used to develop a new deflection model. The thesis provides flexural design equations that allow engineers to accurately design SMA RC members for strength and serviceability requirements.

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