Reliability assessment of robustness for reinforced concrete moment resisting frames

A strain-based 5-step procedure is illustrated for the probabilistic robustness assessment of 2D reinforced concrete moment resisting frames. Considering the central column removal as failure scenario, this study compares three frames, including a code-conforming design ( frame 1 ) and two enhanced designs ( frame 2 and frame 3 ). For the three frames, non-linear finite-element (NLFE) models have been defined including properly calibrated translational springs. By sampling from materials and loads, 300 displacement-controlled pushdown NLFE global analyses have been conducted to determine energy-based dynamic amplification factors (1.02 - 1.75). Next, 300 probabilistic static-equivalent NLFE global analyses, performed by removing the column and amplifying loads, permitted to monitor the aleatory peak strains in any material and point of the frames. This allowed to compute the failure probabilities with respect to the ultimate limit state. Robustness improvements lead to much lower failure probabilities (10 -7 - 10 -3 ) in any element with a reduction of damage propagation. • Robustness response of three RC MR frames is compared for a failure scenario; • 5-step strain-based global procedure is used to assess structural reliability at ULS; • Probabilistic pushdown NLFE analyses are useful to define aleatory capacity curves; • Energy-based DAFs are evaluated for probabilistic static-equivalent NLFE analyses; • Failure probabilities are assessed to estimate safety level and damage propagation.

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Publication Details

Journal
Developments in the Built Environment
Published
2025-03-01
DOI
https://doi.org/10.1016/j.dibe.2025.100639
Citations
13
Primary Topic
Structural Response to Dynamic Loads
Type
article
Field-Weighted Citation Impact
12.39
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article

Reliability assessment of robustness for reinforced concrete moment resisting frames

Diego Gino, Paolo Castaldo, Elena Miceli
13 citations
Developments in the Built Environment
Structural Response to Dynamic Loads
12.39
article

Reliability assessment of robustness for reinforced concrete moment resisting frames

Diego Gino, Paolo Castaldo, Elena Miceli
article en
13 citations

Abstract

A strain-based 5-step procedure is illustrated for the probabilistic robustness assessment of 2D reinforced concrete moment resisting frames. Considering the central column removal as failure scenario, this study compares three frames, including a code-conforming design ( frame 1 ) and two enhanced designs ( frame 2 and frame 3 ). For the three frames, non-linear finite-element (NLFE) models have been defined including properly calibrated translational springs. By sampling from materials and loads, 300 displacement-controlled pushdown NLFE global analyses have been conducted to determine energy-based dynamic amplification factors (1.02 - 1.75). Next, 300 probabilistic static-equivalent NLFE global analyses, performed by removing the column and amplifying loads, permitted to monitor the aleatory peak strains in any material and point of the frames. This allowed to compute the failure probabilities with respect to the ultimate limit state. Robustness improvements lead to much lower failure probabilities (10 -7 - 10 -3 ) in any element with a reduction of damage propagation. • Robustness response of three RC MR frames is compared for a failure scenario; • 5-step strain-based global procedure is used to assess structural reliability at ULS; • Probabilistic pushdown NLFE analyses are useful to define aleatory capacity curves; • Energy-based DAFs are evaluated for probabilistic static-equivalent NLFE analyses; • Failure probabilities are assessed to estimate safety level and damage propagation.

Developments in the Built EnvironmentVol. 21
Politecnico di Torino (IT)
Sustainable cities and communities
Openalex Percentile: Top 1%
Structural Response to Dynamic Loads
12.39
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Reliability assessment of robustness for reinforced concrete moment resisting frames — Diego Gino, Paolo Castaldo, et al. · Developments in the Built Environment (2025) | TGRS Research Map | TGRS