Reinforced-Concrete Shear Walls Retrofitted Using Weakening and Self-Centering: Numerical Modeling

Basereh, Sina; Okumus, Pinar; Aaleti, Sriram

doi:10.1061/(asce)st.1943-541x.0002669

Cited by 19 publications

(13 citation statements)

References 26 publications

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“…The failure was assumed to occur when the lateral strength dropped by at least 20%. The experimental data of the SW3 test can be found in Basereh and Okumus (2021).…”

Section: Methodsmentioning

confidence: 99%

A graph‐based method for quantifying crack patterns on reinforced concrete shear walls

Bazrafshan

Basereh

et al. 2023

Computer aided Civil Eng

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This paper presents an innovative method to quantify damage based on surface cracks of reinforced concrete shear walls (RCSWs). The key idea is to use artificial intelligence and convert crack patterns to graphs. In this method, the mathematics of graph theory is used to extract information (graph‐based features) from crack patterns and use them for crack quantification. The proposed graph features are used in linear regression and leave‐one‐out cross‐validation to predict the mechanical features calculated for each RCSW: Park and Ang damage index and the dissipated energy. Among the three general stages of damage, which are safe, questionable, and not safe, this paper focuses on quantifying the second stage. To validate the approach, crack images of three RCSWs are used. The walls had different aspect ratios (0.54, 0.94, and 2.00) and were subject to quasi‐static cyclic loading. Regression results demonstrate low root mean squared errors and high coefficients of determination (R2 scores above 0.845). This proves the ability of the proposed graph‐based method in quantifying damage based on surface crack patterns.

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“…The failure was assumed to occur when the lateral strength dropped by at least 20%. The experimental data of the SW3 test can be found in Basereh and Okumus (2021).…”

Section: Methodsmentioning

confidence: 99%

A graph‐based method for quantifying crack patterns on reinforced concrete shear walls

Bazrafshan

Basereh

et al. 2023

Computer aided Civil Eng

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“…Three different RCSWs namely, SW1, SW2 [11,12], and SW3 [13] are considered to test the proposed method. The walls have different aspect ratios (height to length) of 0.94, 0.54, and 2.00 to account for the flexure and shear behavior of the RCSWs.…”

Section: Methodsmentioning

confidence: 99%

A virtual-reality framework for graph-based damage evaluation of reinforced concrete structures

Bazrafshan

Ebrahimkhanlou

2023

Nondestructive Characterization and Monitoring of Advanced Materials, Aerospace, Civil Infrastructure, and Transportation XVII

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Artificial intelligence (AI) and virtual/augmented reality (VR/AR) are facilitating objective and fast assessment of infrastructures. Computer vision advancements are also transforming traditional methods into automated information modeling and decision support systems. These advancements offer new opportunities to combat growing challenges that threaten infrastructure systems. In particular, climate change, aging structures, and population growth have intensified threats to infrastructure, requiring methods for evaluating infrastructure quickly after a disaster. VR uses cameras and sensors to provide images of the current state of a structural system, including the pattern of concrete cracks. A novel framework for analyzing the degree of damage in cracked reinforced concrete shear walls (RCSWs) is presented in this paper by leveraging virtual reality (VR) technology. An automated and unbiased approach is enabled by converting images of crack patterns on the surface of concrete structures into graphs. It is possible to extract relevant information from graphs, including graph features, to quantify the extent of damage using graph theory. A machine learning algorithm is then trained using these features to predict the extent of the damage. To validate the approach, the framework was applied to data collected from three RCSWs that were subjected to quasi-static cyclic loading. ML was used to predict the secant stiffness and its descending trend during each load cycle in the experimental test. The VR-based approach achieves high R2 scores of 0.90, 0.91, and 0.99 in a machine learning regression, indicating the framework's success.

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“…The debonded rebar length was calculated assuming a maximum lateral drift of 4% (maximum drift used in validation testing described later and conservatively above the one considered by ACI 550. [7][8][9][10][11][12][13][14][15][16][17][18][19] and was 50 in. (1.27 m) and 55 in.…”

Section: Wallmentioning

confidence: 99%

“…13 However, only one study investigated applications to RC shear wall-foundation joints 14 and another investigated only partial cuts at the edges of the shear wall base. 15 Neither of these studies investigated how weakening at this joint impacted seismic fragility functions.…”

Section: Introductionmentioning

confidence: 99%

Lateral load response and collapse probability of reinforced concrete shear walls retrofitted for repairability

Okumus,

Basereh,

Aaleti

2024

Earthq Engng Struct Dyn

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This paper demonstrates the efficacy of a new reinforced concrete shear wall seismic retrofit method through a series of nonlinear static and incremental dynamic analyses. Unlike traditional retrofit methods, the method investigated aims to convert conventional walls into self‐centering walls whose behavior is governed by rocking and flexure. The retrofit involves creating a cold joint at the foundation–wall interface, cutting some reinforcing bars to allow rocking, adding external post‐tensioning to enable self‐centering, and externally confining wall toes to prevent concrete crushing. The retrofit was applied to two building archetypes, each with two different shear wall designs. The four walls were retrofitted by varying retrofit parameters (portion of the vertical reinforcement bars cut, and external post‐tensioning amount). Nonlinear static and nonlinear response history analyses were performed using experimentally validated, computationally efficient models that simulate walls with fiber‐based beam–column elements. Incremental dynamic analysis was used to create collapse fragility functions for pre‐ and post‐retrofit walls. The results show that the retrofit is effective when some vertical reinforcement bars are left uncut across the foundation–wall interface. The retrofit is more effective for walls with vertical reinforcement distributed across cross‐section as compared to walls with reinforcement concentrated near boundary elements and for walls with structurally efficient amounts of reinforcement as compared to walls with higher amounts of reinforcement. This is attributed to the larger amount of reinforcement bars cut in walls with concentrated reinforcement layouts or heavy reinforcement amounts, leading to a larger loss of strength, recovery of which requires larger amounts of post‐tensioning.

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Reinforced-Concrete Shear Walls Retrofitted Using Weakening and Self-Centering: Numerical Modeling

Cited by 19 publications

References 26 publications

A graph‐based method for quantifying crack patterns on reinforced concrete shear walls

A graph‐based method for quantifying crack patterns on reinforced concrete shear walls

A virtual-reality framework for graph-based damage evaluation of reinforced concrete structures

Lateral load response and collapse probability of reinforced concrete shear walls retrofitted for repairability

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