Reliability-based modeling of punching shear capacity of FRP-reinforced two-way slabs

Kurtoğlu, Ahmet Emin; Çevik, Abdülkadir; Albegmprli, Hasan M.; Gülşan, Mehmet Eren; Bilgehan, Mahmut

doi:10.12989/cac.2016.17.1.087

Cited by 8 publications

(3 citation statements)

References 18 publications

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“…Additionally, as learning data increases, the machine learning ( ML)-based models' efficiency may be enhanced progressively, keeping them current with the strict precision demands for complicated engineering challenges [25][26][27][28][29][30]. Numerous studies have shown how well ML-based models work in solving issues associated to civil engineering, such as forecasting the mechanical characteristics (compressive/ tensile strength/shear) of hardened concrete [31][32][33][34], the ultimate bond strength of corroded reinforcement and surrounding concrete [35,36], the bearing capability of piles [37,38], the pulling capability of ground anchors [39][40][41], and others.…”

Section: Introductionmentioning

confidence: 99%

Bearing capacity prediction of the concrete pile using tunned ANFIS system

Gu,

Liao,

Cheng

2024

J. Eng. Appl. Sci.

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The design process for pile foundations necessitates meticulous deliberation of the calculation pertaining to the bearing capacity of the piles. The primary objective of this work was to investigate the potential use of Coot bird optimization ($${\text{CBO}}$$ CBO ) techniques in predicting the load-bearing capacity of concrete-driven piles. Despite the availability of several suggested models, the investigation of Coot bird optimization ($${\text{CBO}}$$ CBO ) for estimating the pile-carrying capacity has been somewhat neglected in this research. This work presents and validates a unique approach that combines the Coot bird optimization ($${\text{CBO}}$$ CBO ) model with the Multi-layered perceptron ($${\text{MLP}}$$ MLP ) neural network and adaptive neuro-fuzzy inference system ($${\text{ANFIS}}$$ ANFIS ). The findings of 472 different driven pile static load tests were put in a database. The proposed framework's building, validation, and testing stages were each accomplished utilizing the training set (70%), validation set (15%), and testing set (15%) of the dataset, respectively. According to the findings, $${{\text{MLP}}}_{{\text{CBO}}}$$ MLP CBO and $${{\text{ANFIS}}}_{{\text{CBO}}}$$ ANFIS CBO both offer remarkable possibilities for accurately predicting the pile-bearing capacity of a given structure. The $${R}^{2}$$ R 2 values for $${{\text{ANFIS}}}_{{\text{CBO}}}$$ ANFIS CBO during the training stage were 0.9874, while during the validating stage, they were 0.9785, and during the testing stage they were 0.987. After considering various kinds of performance studies and contrasting them with existing literature, it has been concluded that the $${{\text{ANFIS}}}_{{\text{CBO}}}$$ ANFIS CBO model provides a more appropriate calculation of the bearing capacity of concrete-driven piles.

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Section: Introductionmentioning

confidence: 99%

Bearing capacity prediction of the concrete pile using tunned ANFIS system

Gu,

Liao,

Cheng

2024

J. Eng. Appl. Sci.

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“…Corbels can be provided to support rails that transfer heavy loads from moving cranes in heavy-duty factory workshops. Corbels are also provided at the cantilevered end of the girders in double cantilever balanced reinforced concrete bridges to support the end spans of the bridge [2].…”

Section: Introductionmentioning

confidence: 99%

“…The addition of steel fibers to the concrete substantially increases the shear strength. The effectiveness of fiber reinforcement to increase shear resistance is dependent on several factors, including matrix properties, fiber properties (material properties, aspect ratio, and shape), fiber content, and bond stress versus slip response of fibers [2]. The most common fibers used in corbels are steel, glass, and carbon fibers.…”

Section: Introductionmentioning

confidence: 99%

Shear Resistance of Fibrous Reinforced Concrete Corbels - A Critical Review

Mahmood

Karim

2022

construction

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Reinforced concrete corbels have become a frequent attribute in building construction, with precast high-strength concrete increasing use. Corbels are short-hunched cantilevers that project from the inner face of columns or walls to support heavy concentrated loads or beam reactions. They are essential structural elements for supporting precast beams, girders, cranes, and other precast structure systems. This paper reviews the effect of fiber, shear span to depth ratio, concrete strength, and reinforcement ratio on the reinforced fibrous high strength concrete corbel's shear resistance in previous research. The results show that the shear resistance of corbels enhances with increasing main reinforcement, compressive strength, and the volume fraction of fibers, whereas it decreases with the improvement of the shear span-to-effective depth ratio of the corbel. In addition, using fibers in high-strength reinforced concrete corbel increases the ductility and thus defines the mode of failure of the corbels, depending on the fiber parameters.

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