Shear Strength of RC-Composite Beams with Prestressed Concrete and Non-Prestressed Concrete

Kim, Chul-Goo; Park, Hong-Gun; Hong, Geon-Ho; Lee, Hyerin; Suh, Jung-Il

doi:10.14359/51702224

Cited by 8 publications

(3 citation statements)

References 8 publications

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“…Few studies have shown a close approach to those issues, the most important being those by Halicka et al [1,14,15] and Kim et al [9,[16][17][18]. In particular, Halicka et al developed an experimental study about the influence of interface quality on the shear strength of concrete composite beams [1,14,15], in which the possible failure mechanisms in concrete composite beams are described as well as an analytical criterion to predict the failure mechanism.…”

Section: Introductionmentioning

confidence: 99%

“…Halicka points out in [14] there are few research works regarding the influence of the interface cracking on the shear strength of the composite element. Kim et al [9,[16][17][18] ran an extensive experimental programme on the shear strength of rectangular composite beams made of prestressed and non-prestressed concrete, using different strength concretes (high-strength and low-strength concrete) and adding or not steel fibres in the concrete mass. They obtained interesting results about the influence on the shear strength of these different concretes and their location at the precast beam or the slab; however, the influence of the interface was not studied since most of the specimens behaved similarly to monolithic specimens.…”

Section: Introductionmentioning

confidence: 99%

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Towards the Development of a Formulation for Obtaining the Shear Strength of Concrete Composite Beams

Rueda¹,

Bonet²,

Sosa³

et al. 2023

hya

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In the design and assessment of precast concrete beams with a slab cast on top, namely concrete composite beams, engineers still face in practice unsolved shear-related issues, such as the contribution to shear strength of the slab, the concrete strength to be considered in shear formulations or the influence of the interface between concretes in the shear behaviour. In the present research, 69 shear tests were performed on monolithic and composite beams, with rectangular or T-shaped cross-section, with or without transverse reinforcement and with different concrete qualities, to experimentally analyse the issues mentioned above. The study of the shear transfer mechanisms at failure led to formulating a model for explaining the observed results. Based on this model, a shear strength predictive formulation for concrete composite beams with web reinforcement has been developed, which has been verified with the experimental results from this research and 24 additional tests from the literature. This formulation provides accurate predictions compared to the shear strength formulations of current codes EC2, MC-10 and ACI 318-19. The proposed model lays the foundations for the future development of a user-friendly formulation for calculating the shear strength of concrete composite beams.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards the Development of a Formulation for Obtaining the Shear Strength of Concrete Composite Beams

Rueda¹,

Bonet²,

Sosa³

et al. 2023

hya

View full text Add to dashboard Cite

show abstract

“…As a result of pouring, the concrete interior often produces phenomena such as cavities and in-compactness. This will lead to the strength, compactness, frost resistance, anti-permeability, and other properties of concrete being reduced and will also affect the service life of concrete structures to a certain extent, and may even affect the safe operation of buildings [9][10][11][12]. Cement is an important part of concrete, but it will emit a large amount of carbon in the process of production, which will bring a certain burden to the environment [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Design of Construction Materials: A Comparative Study of AI Approaches for Predicting the Strength of Concrete with Blast Furnace Slag

Zhu

Zhou

et al. 2022

Materials

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Concrete production by replacing cement with green materials has been conducted in recent years considering the strategy of sustainable development. This study researched the topic of compressive strength regarding one type of green concrete containing blast furnace slag. Although some researchers have proposed using machine learning models to predict the compressive strength of concrete, few researchers have compared the prediction accuracy of different machine learning models on the compressive strength of concrete. Firstly, the hyperparameters of BP neural network (BPNN), support vector machine (SVM), decision tree (DT), random forest (RF), K-nearest neighbor algorithm (KNN), logistic regression (LR), and multiple linear regression (MLR) are tuned by the beetle antennae search algorithm (BAS). Then, the prediction effects of the above seven machine learning models on the compressive strength of concrete are evaluated and compared. The comparison results show that KNN has higher R values and lower RSME values both in the training set and test set; that is, KNN is the best model for predicting the compressive strength of concrete among the seven machine learning models mentioned above.

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Stochastic modelling and assessment of long-span precast prestressed concrete elements failing in shear

Slowik

Novák

et al. 2021

Engineering Structures

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Shear Strength of RC-Composite Beams with Prestressed Concrete and Non-Prestressed Concrete

Cited by 8 publications

References 8 publications

Towards the Development of a Formulation for Obtaining the Shear Strength of Concrete Composite Beams

Towards the Development of a Formulation for Obtaining the Shear Strength of Concrete Composite Beams

Intelligent Design of Construction Materials: A Comparative Study of AI Approaches for Predicting the Strength of Concrete with Blast Furnace Slag

Stochastic modelling and assessment of long-span precast prestressed concrete elements failing in shear

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