• International Journal of Concrete Structures and Materials
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• v.5 no.1
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• pp.57-64
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• 2011

An extensive database has been constructed of reinforced concrete (RC) beam-column connection tests subjected to cyclic lateral loading. All cases within the database experienced joint shear failure, either in conjunction with or without yielding of longitudinal beam reinforcement. Using the experimental database, envelope curves of joint shear stress vs. joint shear strain behavior have been created by connecting key points such as cracking, yielding, and peak loading. Various prediction approaches for RC joint shear behavior are discussed using the constructed experimental database. RC joint shear strength and deformation models are first presented using the database in conjunction with a Bayesian parameter estimation method, and then a complete model applicable to the full range of RC joint shear behavior is suggested. An RC joint shear prediction model following a U.S. standard is next summarized and evaluated. Finally, a particular joint shear prediction model using basic joint shear resistance mechanisms is described and for the first time critically assessed.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.377-384
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• 2000

The characteristics and prediction model of the shear strength for unsaturated residual soils was studied. In order to investigate the influence of the initial water content on the shear strength, unsaturated triaxial tests were carried out varying the initial water content, and the applicability of existing prediction models for the unsaturated shear strength was testified. It was shown that the soil - water characteristic curve and the shear strength of the unsaturated soil varied with the change of the initial water content. A sample compacted in the lower initial water content needs a higher suction to get the same degree of saturation while the shear strength of a sample with the lower initial water content displays a lower value. In order to apply the existing prediction models of the unsaturated shear strength to granite residual soils, a correction coefficient, α, on the internal friction angle, ø'was added.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.139-146
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• 2002

The characteristics and prediction model for the shear strength of unsaturated residual soils was studied. In order to investigate the influence of the net normal stress on the shear strength, unsaturated triaxial tests and SWCC tests were carried out varying the net normal stress, and the experimental data for unsaturated shear strength tests were compared with predicted shear strength envelopes using existing prediction models. It was shown that the soil - water characteristic curve and the shear strength of the unsaturated soil varied with the change of the net normal stress. Therefore, to achieve a truly descriptive shear strength envelope for unsaturated soils, tile effect of the normal stress on the contribution of matric suction to the shear strength has to be taken into consideration. In this paper, a modified prediction model for the unsaturated shear strength was proposed.

• Steel and Composite Structures
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• v.36 no.5
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• pp.493-506
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• 2020

The load-slip relationship of the shear connection is an important parameter in design and analysis of composite structures. In this paper, a load-slip curve prediction method of the shear connection based on the artificial neural networks (ANNs) is proposed. The factors which are significantly related to the structural and deformation performance of the connection are selected, and the shear stiffness of shear connections and the transverse coordinate slip value of the load-slip curve are taken as the input parameters of the network. Load values corresponding to the slip values are used as the output parameter. A twolayer hidden layer network with 15 nodes and 10 nodes is designed. The test data of two different forms of shear connections, the stud shear connection and the perforated shear connection with flange heads, are collected from the previous literatures, and the data of six specimens are selected as the two prediction data sets, while the data of other specimens are used to train the neural networks. Two trained networks are used to predict the load-slip curves of their corresponding prediction data sets, and the ratio method is used to study the proximity between the prediction loads and the test loads. Results show that the load-slip curves predicted by the networks agree well with the test curves.

• Steel and Composite Structures
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• v.28 no.2
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• pp.251-266
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• 2018

Compared to conventional flat web I-beams, the prediction of shear buckling stress of corrugated web steel beams (CWSBs) is not straightforward. But the CWSBs combined advantages of lightweight large spans with low-depth high load-bearing capacities justify dealing with such difficulties. This work investigates experimentally and analytically the shear strength of trapezoidal CWSBs. A set of large scale CWSBs are manufactured and tested to failure in shear. The results are compared with widely accepted CWSBs shear strength prediction models. Confirmed by the experimental results, the linear buckling analyses of trapezoidal corrugated webs demonstrated that the local shear buckling occurs only in the flat plane folds of the web, while the global shear buckling occurs over multiple folds of the web. New analytical prediction model accounting for the interaction between the local and global shear buckling of CWSBs is proposed. Experimental results from the current work and previous studies are compared with the proposed analytical prediction model. The predictions of the proposed model are significantly better than all other studied models. In light of the dispersion of test data, accuracy, consistency, and economical aspects of the prediction models, the authors recommend their proposed model for the design of CWSBs over the rest of the models.

• Steel and Composite Structures
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• v.27 no.3
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• pp.355-370
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• 2018

In steel-concrete composite beams, longitudinal shear forces are transferred across steel flange-concrete slab interface by means of shear connectors. The connector behavior is highly non-linear and involves several complex mechanisms. The design resistance and stiffness of composite beams depends on the shear connection behavior and the accuracy in the connector resistance prediction is essential. However determining the stud shear resistance is not an easy process: analytical methods do not give an adequate response to this problem and it is therefore necessary to use experimental methods. This paper present a summary of the main procedures to predict the resistance of the stud shear connectors embedded in solid slab, and stud shear connectors in composite slab using profiled steel sheeting with rib perpendicular to steel beam. A large number of experimental studies on the behavior of stud shear connectors and reported in the literature are also summarized. A comparison of the stud shear resistance prediction using six reference codes (AISC, AASHTO, Eurocode-4, GB50017, JSCE and AS2327.1) and other procedures reported in the literature against experimental results is presented. From this exercise, it is concluded that there are still inaccuracies in the prediction of stud shear resistance in all analysed procedures and that improvements are needed.

• Structural Engineering and Mechanics
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• v.74 no.4
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• pp.503-514
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• 2020

This study proposes prediction models for the shear strength of steel fiber reinforced concrete (SFRC) and ultra-high-performance fiber reinforced concrete (UHPC) beams using a Bayesian parameter estimation approach and a collected experimental database. Previous researchers had already proposed shear strength prediction models for SFRC and UHPC beams, but their performances were limited in terms of their prediction accuracies and the applicability to UHPC beams. Therefore, this study adopted a statistical approach based on a collected database to develop prediction models. In the database, 89 and 37 experimental data for SFRC and UHPC beams without stirrups were collected, respectively, and the proposed equations were developed using the Bayesian parameter estimation approach. The proposed models have a simplified form with important parameters, and in comparison to the existing prediction models, provide unbiased high prediction accuracy.

• Smart Structures and Systems
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• v.14 no.5
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• pp.785-809
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• 2014

In this paper, an Adaptive nerou-based inference system (ANFIS) is being used for the prediction of shear strength of high strength concrete (HSC) beams without stirrups. The input parameters comprise of tensile reinforcement ratio, concrete compressive strength and shear span to depth ratio. Additionally, 122 experimental datasets were extracted from the literature review on the HSC beams with some comparable cross sectional dimensions and loading conditions. A comparative analysis has been carried out on the predicted shear strength of HSC beams without stirrups via the ANFIS method with those from the CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94 codes of design. The shear strength prediction with ANFIS is discovered to be superior to CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94. The predictions obtained from the ANFIS are harmonious with the test results not accounting for the shear span to depth ratio, tensile reinforcement ratio and concrete compressive strength; the data of the average, variance, correlation coefficient and coefficient of variation (CV) of the ratio between the shear strength predicted using the ANFIS method and the real shear strength are 0.995, 0.014, 0.969 and 11.97%, respectively. Taking a look at the CV index, the shear strength prediction shows better in nonlinear iterations such as the ANFIS for shear strength prediction of HSC beams without stirrups.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.59-70
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• 2023

In order to predict low-level wind shear at Incheon International Airport (RKSI), a Low-Level Wind Shear prediction system (KMAP-LLWS) along the runway take-off and landing route at RKSI was established using Korea Meteorological Administration Post-Processing (KMAP). For the performance evaluation, the case of low-level wind shear cases calculated from Aircraft Meteorological Data Relay (AMDAR) from July 2021 to June 2022 was used. As a result of verification using the performance evaluation index, POD, FAR, CSI, and TSS were 0.5, 0.85, 0.13, and 0.34, respectively, and the prediction performance was improved by POD, CSI, and TSS compared to the Low-Level Wind Shear prediction system (LDPS-LLWS) calculated using the Korea Meteorological Administration's Local Data Assimilation and Prediction System (LDAPS). This means that the use of high-resolution numerical models improves the predictability of wind changes. In addition, to improve the high FAR of KMAP-LLWS, the threshold for low-level wind shear strength was adjusted. As a result, the most effective low-level wind shear threshold at 8.5 knot/100 ft was derived. This study suggests that it is possible to predict and respond to low-level wind shear at RKSI. In addition, it will be possible to predict low-level wind shear at other airports without wind shear observation equipment by applying the KMAP-LLWS.

• Computers and Concrete
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• v.22 no.2
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• pp.197-207
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• 2018

In the present study, group method of data handling networks (GMDH) are adopted and evaluated for shear strength prediction of both FRP-reinforced concrete members with and without stirrups. Input parameters considered for the GMDH are altogether 12 influential geometrical and mechanical parameters. Two available and very recently collected comprehensive datasets containing 112 and 175 data samples are used to develop new models for two cases with and without shear reinforcement, respectively. The proposed GMDH models are compared with several codes of practice. An artificial neural network (ANN) model and an ANFIS based model are also developed using the same databases to further assessment of GMDH. The accuracy of the developed models is evaluated by statistical error parameters. The results show that the GMDH outperforms other models and successfully can be used as a practical and effective tool for shear strength prediction of members without stirrups ($R^2=0.94$) and with stirrups ($R^2=0.95$). Furthermore, the relative importance and influence of input parameters in the prediction of shear capacity of reinforced concrete members are evaluated through parametric and sensitivity analyses.