Damage Identification in NSM FRP Strengthened RC Beams Using Linear Mixed Effects Models

Abstract

The use of fibre reinforced polymers (FRP) in civil construction applications with near-surface mounted (NSM) method has gained considerable popularity worldwide and can produce confident strengthening and repairing systems for existing concrete structures.

The bond among FRP composites-concrete is very important to the accomplishment of the NSM FRP strengthening system. Different failure types (concrete crushing, FRP rupture, debonding) have been recorded in the literature about the bond among NSM FRP-adhesive-concrete.

Structural Health Monitoring (SHM) traditionally refers to the process of implementing monitoring systems to measure structural responses in real-time and to identify anomalies and/or damage at early stages. Until now, little research effort has been devoted to the identification of damage at its earliest stages for this kind of reinforcement technique. In this work we will use linear mixed effects models as a statistical tool to assess the structural integrity of our subject structures from electromechanical impedances captured from PZT sensors installed on NSM FRP RC beams to be inspected. This type of models is an extension of linear regressions models that describe the relationship between a responsive variable and independent variables. They contain both fixed effects and random effects. Fixed-effects terms are usually the regression part, while the random effects are generally associated with individual experimental units drawn from a population.