Seismic Retrofitting Methods Newly Developed for Railway Concrete Structures

Ishibashi, Toshiyuki; Tsuyoshi, Takeshi; Kobayashi, Kaoru

doi:10.3151/jact.2.65

Cited by 9 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As dynamic tests of timber infill walls had not previously been performed, new insight is provided into their performance as a seismic retrofit, parallel to the rapidly expanding timber construction industry (Woodworks, 2022). Finally, the dataset quantifies the dynamic response of frames with active external confinement of columns, a retrofit that has been field-deployed in Japan (Ishibashi et al, 2004). Retrofit performance can be compared for pristine or damaged RC frames, providing a relative sense of retrofit performance without extrapolation.…”

Section: Introductionmentioning

confidence: 99%

Earthquake response of reinforced concrete frames with infill and active external confinement: Tests and dataset

Kerby,

Monical,

Pujol

2023

Earthquake Spectra

View full text Add to dashboard Cite

One option to retrofit reinforced concrete (RC) frames is the construction of infill walls. Infill increases lateral strength and stiffness but tends to reduce drift capacity relative to bare frames. Few studies have quantified the reductions in drift demand attributable to infills prior to failure. This report summarizes data from experiments designed to compare drift demands of frames with and without infill. Included data come from two experimental programs completed at Purdue University which focused on the in-plane dynamic response of reduced-scale, non-ductile RC frames to uniaxial simulated earthquake ground motions. 254 dynamic tests were conducted on bare frames, frames with masonry infill walls, and frames with timber infill walls. In 11 of 14 test series, active confinement was applied to columns using external post-tensioned reinforcement. The complete dataset is open-access online on Zenodo, DOI: 10.5281/zenodo.6954967.

show abstract

Section: Introductionmentioning

confidence: 99%

Earthquake response of reinforced concrete frames with infill and active external confinement: Tests and dataset

Kerby,

Monical,

Pujol

2023

Earthquake Spectra

View full text Add to dashboard Cite

show abstract

“…The purpose of these anchor bars is to improve the flexure and shear capacity of the concrete structures. Many techniques employ post-installed anchor bars for the retrofitting process [1,2], and among them, the most common is the technique of concrete jacketing. Traditionally, the anchor bar is attached to the structural member by drilling a hole and injecting infill material known as epoxy resin to hold the anchor bar in place.…”

Section: Introductionmentioning

confidence: 99%

Cyclic Pull-Out Push-In Shear-Lag Model for Post-installed Anchor-Infill Assembly

Saleem

2014

Arab J Sci Eng

View full text Add to dashboard Cite

A cyclic piecewise linear shear-lag material model representing the local bond behavior of the postinstalled anchor-infill assembly used for simulating its cyclic pull-out push-in response is presented. The anchor-infill assembly is such that used in various strengthening techniques to strengthen reinforced concrete structures. The properties of the infill material used for installing post-installed anchor-infill assembly are characterized by a nonlinear interface between the surrounding concrete and the anchor. A new type of anchor-infill assembly is introduced in which the infill material is divided into two layers for the purpose of providing a larger failure path length resulting in increase of the energy absorption capacity. The cyclic response is divided into two categories, namely the one with indentation and the one without indentation, where indentation represents concrete crushing at the base of drilled hole used for installing anchor bar. Each cycle is further subdivided into six paths of elastic loading followed by de-bonding in pull-out direction, unloading, reloading, de-bonding in pushin direction and unloading again. The stiffness degradation upon de-bonding and stiffness recovery upon reloading due to the lateral pressure effect and Poisson's effect is incorporated in the form of stiffness and constant shear force update at the beginning of each loading path. Rules are formulated to plot the cyclic response, by a trial and error approach, to suit the presented material model. The sequential conceptual diagram showing the development of global cyclic loaddisplacement response of the anchor-infill assembly is also presented. Finally, the response of the anchor-infill assembly is plotted using thefinite element method under three dif- M. Saleem (B) ferent support conditions and comparisons are made with the results of numerical rules and good agreement is found. The effectiveness of the proposed two-layer model is also confirmed by comparing its cyclic pull-out push-in response with that of single-interface model, and it is found that the energy absorption capacity increases by 24 % and the failure path length increases by 80 %.Keywords Post-installed anchor-infill assembly · Local bond behavior · Cyclic shear-lag model · Pull-out · Push-in · Lateral pressure · Indentation 123 8538 Arab J Sci Eng (2014) 39:8537-8547

show abstract

Using artificial neural network and non‐destructive test for crack detection in concrete surrounding the embedded steel reinforcement

Saleem

Gutiérrez

2021

Structural Concrete

View full text Add to dashboard Cite

Bond between steel and concrete is one of the key aspects of structural design and its performance evaluation. In the past much research work has been focused on understanding bond deterioration owing to corrosion of reinforcement, however, there exists no nondestructive method to access the bond condition. In this regard, the presented experimental research work details the development of a nondestructive testing method to estimate the crack condition of concrete surrounding the steel reinforced by using ultrasonic pulse velocity test. In addition, a multilayer feedforward back propagation perceptron artificial neural network (ANN) is developed in order to avoid simplification assumptions for developing models to predict the cracking, owing to the nonlinear complex stress distribution at the steel-concrete interface. The ANN is used to predict the crack width and to conduct sensitivity analysis of the various factors influencing the bond deterioration. A high accuracy level is achieved between the predicted and the experimental values with R 2 of 0.97 and the most influential parameter is highlighted.

show abstract

Seismic Retrofitting Methods Newly Developed for Railway Concrete Structures

Cited by 9 publications

References 0 publications

Earthquake response of reinforced concrete frames with infill and active external confinement: Tests and dataset

Earthquake response of reinforced concrete frames with infill and active external confinement: Tests and dataset

Cyclic Pull-Out Push-In Shear-Lag Model for Post-installed Anchor-Infill Assembly

Using artificial neural network and non‐destructive test for crack detection in concrete surrounding the embedded steel reinforcement

Contact Info

Product

Resources

About