journal article·2021-12Open access

Experimental and numerical analysis on the effectiveness of GFRP wrapping system on timber pile rehabilitation

Weena Lokuge, Omar Otoom, Rahmin Borzou, Satheeskumar Navaratnam, Nilupa Herath, David Thambiratnam

Abstract

Rehabilitation using Glass Fibre Reinforced Polymer (GFRP) wrapping system is an innovative technique for rehabilitation of deteriorated timber structures exposed to severe environmental conditions. This paper investigates the effectiveness of rehabilitation using GFRP wrapping system for deteriorated timber piles due to splitting. An experimental investigation was conducted on undamaged and damaged short timber columns with three levels of splitting. Crane rail epoxy and underwater cementitious grout were used to fill the annulus between columns and GFRP jackets in the rehabilitated samples. All the samples were tested under axial compression loading. Axial peak and yield loads, ductility and energy absorption were discussed to assess the overall behaviour of timber columns. In addition, a finite element analysis was established to investigate the overall load-deformation performance of the tested samples and to validate the experimental results. Furthermore, an analytical prediction was performed based on Australian Standards along with an existing GFRP wrapped stress- strain model to determine the peak load capacity of the unwrapped and GFRP wrapped samples. The experimental results indicated that the GFRP wrapping system can restore the axial capacity and energy absorption of the damaged samples with high effectiveness was observed for samples infilled by the crane rail epoxy. Also, the results of numerical and analytical analysis showed a reasonable correlation with the experimental results.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Structural Behavior of Reinforced Concrete · Concrete Corrosion and Durability · Innovative concrete reinforcement materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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