• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.261-264
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• 2006

Deformability of RC members in shear after flexural yielding is limited and controlled by governing failure modes and material strength. Shear strength of members in D-regions has been explained by a direct load path (direct strut or arch action) and indirect load path (fan action or truss action). Indirect load path including truss action and fan action rely on bond along tension ties. Generally, superposition of two actions results in total shear strength when shear failure modes control. The ultimate deformation depends on controlling failure modes and thereby, their force transfer patterns. Proposed models are capable of explaining of limited deformability of RC members in D-regions.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.366-369
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• 2006

Deformability of RC members in shear is controlled by governing failure modes and material strength. Shear strength of members in D-regions has been explained by a direct load path (direct strut or arch action) and indirect load path (fan action or truss action). Indirect load path including truss action and fan action rely on bond along tension ties. Generally, superposition of two actions results in total shear strength when shear failure modes control. The ultimate deformation depends on controlling failure modes and thereby, their force transfer patterns. Proposed models are capable of explaining of limited deformability of RC members in D-regions.

• Steel and Composite Structures
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• v.48 no.6
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• pp.667-679
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• 2023

Concrete filled rectangular steel tubular (CFRST) composite truss girder is composed of the CFRST truss and concrete slab. The failure mechanism of the girder was different under bending and shear failure modes. The bending and shear strength of the girder were investigated experimentally. The influences of composite effect and shear to span ratio on failure modes of the girder was studied. Results indicated that the top chord and the joint of the truss were strengthened by the composited effect. The failure modes of the specimens were changed from the joint on top chord to the bottom chord. However, the composite effect had limited effect on the failure modes of the girder with small shear to span ratio. The concrete slab and top chord can be regarded as the composite top chord. In this case, the axial force distribution of the girder was close to the pin-jointed truss model. An approach of strength prediction was proposed which can take the composite effect and shear to span ratio into account. The approach gave accurate predictions on the strength of CFRST composite truss girder under different bending and shear failure modes.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.2
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• pp.113-119
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• 2024

Existing reinforced concrete buildings with seismically deficient column details affect the overall behavior depending on the failure type of column. This study aims to develop and validate a machine learning-based prediction model for the column failure modes (shear, flexure-shear, and flexure failure modes). For this purpose, artificial neural network (ANN), K-nearest neighbor (KNN), decision tree (DT), and random forest (RF) models were used, considering previously collected experimental data. Using four machine learning methodologies, we developed a classification learning model that can predict the column failure modes in terms of the input variables using concrete compressive strength, steel yield strength, axial load ratio, height-to-dept aspect ratio, longitudinal reinforcement ratio, and transverse reinforcement ratio. The performance of each machine learning model was compared and verified by calculating accuracy, precision, recall, F1-Score, and ROC. Based on the performance measurements of the classification model, the RF model represents the highest average value of the classification model performance measurements among the considered learning methods, and it can conservatively predict the shear failure mode. Thus, the RF model can rapidly predict the column failure modes with simple column details.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.11a
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• pp.137-140
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• 2005

This paper focuses on the premature failure of RC beams bonded with FRP. A number of failure modes for RC beams bonded with FRP have been observed in numerous experimental studies during past decade. Particularly, Rip-off failure and Debonding failure were majority failure modes in RC beams bonded with FRP. Rip-off failure occurred at the plate end due to high interfacial shear and normal stresses however Debonding failure was caused by the yielding of reinforcing bar and the increasing of shear deformation in shear span. On the basis of premature failure mechanism in RC beams bonded with FRP, Basic strengthening length and Premature failure criteria were derived

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.337-357
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• 2022

The objective of this study is to present a data-driven machine learning (ML) framework for predicting ultimate shear strength and failure modes of reinforced concrete ledge beams. Experimental tests were collected on these beams with different loading, geometric and material properties. The database was analyzed using different ML algorithms including decision trees, discriminant analysis, support vector machine, logistic regression, nearest neighbors, naïve bayes, ensemble and artificial neural networks to identify the governing and critical parameters of reinforced concrete ledge beams. The results showed that ML framework can effectively identify the failure mode of these beams either web shear failure, flexural failure or ledge failure. ML framework can also derive equations for predicting the ultimate shear strength for each failure mode. A comparison of the ultimate shear strength of ledge failure was conducted between the experimental results and the results from the proposed equations and the design equations used by international codes. These comparisons indicated that the proposed ML equations predict the ultimate shear strength of reinforced concrete ledge beams better than the design equations of AASHTO LRFD-2020 or PCI-2020.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.46-49
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• 2006

In general, the shear behavior mode of URM wall expresses four types of modes such as rocking failure, sliding shear failure, toe crushing failure, and diagonal tension failure. From the comparison of each equation according to the shear behavior modes, the failure modes based on the aspect ratio and vertical axial stress can be expected. The objectives of this study is to find out the shear behavior of URM wall with different aspect ratio. The test results show that the aspect ratio is understood as an important variable.

• Structural Engineering and Mechanics
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• v.84 no.1
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• pp.1-16
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• 2022

An efficient and accurate classification method for failure modes of reinforced concrete (RC) columns was proposed based on key characteristic parameters. The weight coefficients of seven characteristic parameters for failure modes of RC columns were determined first based on the support vector machine-recursive feature elimination. Then key characteristic parameters for classifying flexure, flexure-shear and shear failure modes of RC columns were selected respectively. Subsequently, a support vector machine with key characteristic parameters (SVM-K) was proposed to classify three types of failure modes of RC columns. The optimal parameters of SVM-K were determined by using the ten-fold cross-validation and the grid-search algorithm based on 270 sets of available experimental data. Results indicate that the proposed SVM-K has high overall accuracy, recall and precision (e.g., accuracy>95%, recall>90%, precision>90%), which means that the proposed SVM-K has superior performance for classification of failure modes of RC columns. Based on the selected key characteristic parameters for different types of failure modes of RC columns, the accuracy of SVM-K is improved and the decision function of SVM-K is simplified by reducing the dimensions and number of support vectors.

• Steel and Composite Structures
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• v.23 no.3
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• pp.351-362
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• 2017

This paper presents an experimental study on the behavior of composite floor slab comprised by a new steel sheet and concrete slab. The strength of composite slabs depends mainly on the strength of the connection between the steel sheet and concrete, which is denoted by longitudinal shear strength. The composite slabs have three main failures modes, failure by bending, vertical shear failure and longitudinal shear failure. These modes are based on the load versus deflection curves that are obtained in bending tests. The longitudinal shear failure is brittle due to the mechanical connection was not capable of transferring the shear force until the failure by bending occurs. The vertical shear failure is observed in slabs with short span, large heights and high concentrated loads subjected near the supports. In order to analyze the behavior of the composite slab with a new steel sheet, six bending tests were undertaken aiming to provide information on their longitudinal shear strength, and to assess the failure mechanisms of the proposed connections. Two groups of slabs were tested, one with 3000 mm in length and other with 1500 mm in length. The tested composite slabs showed satisfactory composite behavior and longitudinal shear resistance, as good as well, the analysis confirmed that the developed sheet is suitable for use in composite structures without damage to the global behavior.

• Steel and Composite Structures
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• v.4 no.3
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• pp.247-263
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• 2004

Comparison of behaviour of shear connections by means of shear-connection strips (perfobond and comb-shaped strips) and headed studs under static and repeated loading, possible failure modes of concrete dowels and ways of the quantitative differentiation of some failure modes are described in the paper. The article presents a review of knowledge resulting from the analysis of shear-connection effects based on tests of perfobond and comb-shaped strips carried out in the laboratories of the Faculty of Civil Engineering of the Technical University of Kosice (TU of Kosice) in Slovakia and their comparison with results obtained by other authors.