Identification of Failure Prediction Criteria using Acoustic Emission for GFRP Bridge Deck Panels

摘要

Fiber reinforced composites has emerged as a new alternative material for use in bridge deck panels. However, the lack of design codes and standards has prevented its use from becoming widely accepted. A study is conducted on the AE results from full-scale GFRP honeycomb sandwich bridge deck panels. The objective, through the use of AE monitoring and analysis, is to identify failure prediction criteria and/or a methodology that would provide a determination of the structural integrity of the panels during field inspection of in-service FRP bridge decks. Monitoring was conducted using five broadband sensors in selected locations during a 3-point bending test over an 8-foot span. Collected data is analyzed using comparison and intensity analysis, linear location and waveform analysis. The characterization of damage, fiber breakage, matrix cracking, and delamination are the contributing factors to the investigated criteria. While Felicity ratios for the original specimens fell within expected values, the repaired specimens were generally higher than 0.85. The use if linear location is an important tool for damage location in specimens that provide no visual damage cues. Further investigation is needed with waveform analysis to accurately identify and train a neural network for waveform classification for use in the field.