Nonlinear Modeling Parameters for Reinforced Concrete Columns Retrofitted with Fiber-Reinforced Polymer Jackets

Current seismic evaluation and retrofit guidelines and standards, such as the ASCE standard ASCE/SEI 41-23, Seismic evaluation and retrofit of existing buildings (ASCE 41), provide recommendations for nonlinear modeling parameters and acceptance criteria for as-built reinforced concrete (RC) structural components but do not address nonlinear modeling parameters and acceptance criteria for retrofitted RC structural components. This research addresses this gap by proposing ASCE 41-type nonlinear modeling parameters and acceptance criteria specifically for RC columns retrofitted with fiber-reinforced polymer (FRP) jackets. Using an experimental database of 70 FRP-jacketed RC columns with continuous or spliced longitudinal reinforcement, we propose formulations for predicting the nonlinear modeling parameters at lateral (anl) and axial failure (bnl), and residual strength ratio cnl. Additionally, the study demonstrates that the elastic response of FRP-jacketed columns can be predicted using existing effective stiffness and yield rotation models for as-built flexure-governed RC columns. Furthermore, this study recommends multipliers to anl and bnl to develop acceptance criteria aligned with the Immediate Occupancy, Life Safety, and Collapse Prevention performance objectives. The proposed nonlinear modeling parameters and acceptance criteria are recommended for adoption by seismic evaluation and retrofit guidelines.

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Publication Details

Journal
Journal of Composites for Construction
Published
2025-02-11
DOI
https://doi.org/10.1061/jccof2.cceng-4953
Citations
1
Primary Topic
Structural Behavior of Reinforced Concrete
Type
article
Field-Weighted Citation Impact
1.01
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article

Nonlinear Modeling Parameters for Reinforced Concrete Columns Retrofitted with Fiber-Reinforced Polymer Jackets

Eyitayo A. Opabola, Héctor García Matamoros
1 citations
Journal of Composites for Construction
Structural Behavior of Reinforced Concrete
1.01
article

Nonlinear Modeling Parameters for Reinforced Concrete Columns Retrofitted with Fiber-Reinforced Polymer Jackets

Eyitayo A. Opabola, Héctor García Matamoros
article en
1 citations

Abstract

Current seismic evaluation and retrofit guidelines and standards, such as the ASCE standard ASCE/SEI 41-23, Seismic evaluation and retrofit of existing buildings (ASCE 41), provide recommendations for nonlinear modeling parameters and acceptance criteria for as-built reinforced concrete (RC) structural components but do not address nonlinear modeling parameters and acceptance criteria for retrofitted RC structural components. This research addresses this gap by proposing ASCE 41-type nonlinear modeling parameters and acceptance criteria specifically for RC columns retrofitted with fiber-reinforced polymer (FRP) jackets. Using an experimental database of 70 FRP-jacketed RC columns with continuous or spliced longitudinal reinforcement, we propose formulations for predicting the nonlinear modeling parameters at lateral (anl) and axial failure (bnl), and residual strength ratio cnl. Additionally, the study demonstrates that the elastic response of FRP-jacketed columns can be predicted using existing effective stiffness and yield rotation models for as-built flexure-governed RC columns. Furthermore, this study recommends multipliers to anl and bnl to develop acceptance criteria aligned with the Immediate Occupancy, Life Safety, and Collapse Prevention performance objectives. The proposed nonlinear modeling parameters and acceptance criteria are recommended for adoption by seismic evaluation and retrofit guidelines.

Journal of Composites for ConstructionVol. 29(2)
University of California, Berkeley (US)
Sustainable cities and communities
Openalex Percentile: Top 28%
Structural Behavior of Reinforced Concrete
1.01
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Nonlinear Modeling Parameters for Reinforced Concrete Columns Retrofitted with Fiber-Reinforced Polymer Jackets — Eyitayo A. Opabola, Héctor García Matamoros · Journal of Composites for Construction (2025) | TGRS Research Map | TGRS