Stress-strain behavior of square concrete columns confined with hybrid B-CSM composites and development of novel prediction models

dc.contributor.authorPhromphat Thansirichaisree
dc.contributor.authorHisham Mohamad
dc.contributor.authorAli Ejaz
dc.contributor.authorPanumas Saingam
dc.contributor.authorQudeer Hussain
dc.contributor.authorSuniti Suparp
dc.date.accessioned2026-05-08T19:14:51Z
dc.date.issued2024-2-29
dc.description.abstractThis paper presents a comprehensive investigation into the behavior of concrete confined with hybrid Basalt and Chopped Strand Mat (B-CSM) fibers. The newly proposed B-CSM confinement technique substantially enhances the brittle compressive stress-strain behavior, leading to a noteworthy increase in peak strength (approximately 90%) and ultimate strain (approximately 461%). The efficiency of B-CSM confinement is affected by the strength of plain concrete, with lower-strength specimens indicating a more pronounced enhancement. The performance of existing analytical models for FRP confinement in predicting ultimate strength and strain in B-CSM confined concrete is assessed, highlighting the need for tailored models. Regression-based equations are proposed for characteristic points along the stress-strain curve, enabling accurate prediction of material behavior. The predicted stress-strain curves exhibit a high level of agreement with experimental results. These findings provide valuable insights for the design and application of B-CSM confinement techniques in structural engineering, facilitating improved performance and ductility of concrete structures under compressive loading conditions.
dc.identifier.doi10.1016/j.jcomc.2024.100448
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/14750
dc.publisherComposites Part C Open Access
dc.subjectStructural Behavior of Reinforced Concrete
dc.subjectInnovative concrete reinforcement materials
dc.subjectStructural Load-Bearing Analysis
dc.titleStress-strain behavior of square concrete columns confined with hybrid B-CSM composites and development of novel prediction models
dc.typeArticle

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