• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.93-96
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• 2004

Since a ductile coupled shear wall system is the primary seismic load resisting systems of many structures, a coupling beams of these system must exhibit excellent ductility and energy absorption capacity. In this paper, the seismic response of coupled shear wall system is discussed. The cyclic response of steel coupling beams embedded into reinforced concrete boundary elements was studied. Three half-scale subassemblies representing a portion of a prototype structure were designed. constructed, and tested. The main test variables were the connection details of hybrid coupled shear wall. These efforts have resulted in details for increasing the seismic capacity of steel coupling beam in the seismic behavior of buildings.

• Structural Engineering and Mechanics
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• v.72 no.4
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• pp.443-454
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• 2019

In order to reduce the residual drift of a structure in structural engineering field, a combined structural system (dual) consisting of steel buckling-restrained braced frame (BRBF) along with shear wall is proposed. In this paper, BRBFs are used with special reinforced concrete shear walls as combined systems. Some prototype models of the proposed combined systems as well as steel BRBF-only systems (without walls) are designed according to the code recommendations. Then, the nonlinear model of the systems is prepared using fiber elements for the reinforced concrete wall and appropriate elements for the BRBs. Seismic responses of the combined systems subjected to ground motions at maximum considered earthquake level are investigated and compared to those obtained from BRBFs. Results showed that the maximum residual inter-story drift from the combined systems is, on average, less than half of the corresponding value of the BRBFs. In this research, mean of absolute values of the maximum inter-story drift ratio demand obtained from combined systems is less than the 3% limitation, while this criterion has not been fulfilled by BRBF systems.

• Journal of the Korean Wood Science and Technology
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• v.35 no.6
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• pp.1-12
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• 2007

For the purpose of effective utilization of domestic second-grown larch as structural members, post and beam construction applying traditional construction to Japanese larch glulam members was adopted with processing by machine pre-cut method. In general, horizontal shear test by KS F 2154 is conducted to assess the horizontal shear properties of the wooden structure by post and beam construction. The frame was consisted of post and beam member with appropriate fasteners, and members have their own processed parts (notch, hole, etc.) that can be well-connected each other. The shear wall was consisted of the frame with screw-nail sheathed panel (OSB). The results of horizontal shear loading tests without vertical loads conducted on the frame and the shear wall structures, the maximum strengths were about 1.9 kN/m and about 9.7 kN/m, the shear rigidities were about 167 kN/rad, 8198 kN/rad, respectively. The strength proportion of the frame specimen was about 20% of the wall's and about 2% in initial stiffness. Nail failures are remarkable on the shear wall specimen with punching shears and shear failures. The shear load factor for the shear wall specimen by the method of Architectural Institute of Japan was 1.5, which was obtained by the bi-linear method. Loading method should be considered to obtain smooth load-deformation relationship. For the better shear performance of the structures, column base and post and beam connections and sheathed panel should be further examined as well.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.455-462
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• 2013

The effects of earthquakes can be devastating especially to existing structures that are not based on earthquake resistant design. This study proposes a steel grid shear wall that can provide a sufficient lateral resistance and can be used as a seismic retrofit method. The pushover analysis was performed on RC structure with and without the proposed steel grid shear wall. Obtain the performance point that the target structure for seismic loads applied to evaluate the response and performance levels. The capacity spectrum at performance point is nearly elastic range, so satisfied the performance objectives(LS level). And response modification factor(R factor) were calculated from the pushover analysis. The R factor approach is currently implemented to reflect inelastic ductile behavior of the structures and to reduce elastic spectral demands from earthquakes to the design level. The R factor increases from 2.17 to 3.25 was higher than the design criteria. As a result, according to reinforcement by steel grid shear wall, strength, stiffness, and ductility of the low-rise RC structure has been appropriately improved.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.6 s.40
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• pp.55-66
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• 2004

Recently, many high-rise apartment buildings using the box system, composed of only reinforced concrete walls and slabs, have been constructed. In residential buildings such as apartments, vibrations occur from various sources and these vibrations transfer to neighboring residential units through walls and slabs. It is necessary to use a refined finite element model for an accurate vibration analysis of shear wall building structures. But it would take significant amount of computational time and memory if the entire building structure were subdivided into a finer mesh. Therefore, an efficient analytical method, which has only translational DOFs perpendicular to walls or slabs by the matrix condensation technique, is proposed in this study to obtain accurate results in significantly reduced computational time. If all of the DOFs except those perpendicular to walls or slabs in the shear wall structure eliminated using the matrix condensation technique at a time, the computational time for the matrix condensation would be significant. Thus, the modeling technique using super elements and substructuring technique is proposed to reduce the computational time for the matrix condensation. Dynamic analysis of 3-story and 5-story shear wall example structures were performed to verify the efficiency and accuracy of the proposed method. It was confirmed that the proposed method can provide the results with outstanding accuracy requiring significantly reduced computational time and memory.

• Computers and Concrete
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• v.32 no.3
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• pp.313-326
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• 2023

The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.53-61
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• 2004

Recently, most of residential-commercial buildings and apartment houses which are being constructed in the downtown area mainly adopt hybrid structural systems to compose various spaces. Especially, column-supported wall system which is one of the hybrid systems includes shear wall and rigid frame structure and these structures are connected by the transfer floor. But this system is very disadvantageous from the viewpoint of structural safety and is difficult to find out the stress distribution at the transfer floor. Therefore, this study analyzes the behavior and stress distribution according to the shear wall layout of transfer girder system subject to vertical and static lateral loads. Also, this study recognizes load paths and stress concentration based on the analysis results nearby the transfer floor and presents guidelines for the effective design of wall and transfer girder.

• Structural Engineering and Mechanics
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• v.22 no.3
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• pp.371-399
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• 2006

The theoretical background and capabilities of the developed program, SAR-CWF, for stochastic analysis of 3D reinforced-concrete shear wall-frame structures subject to seismic excitations is presented. Incremental stiffness and strength properties of system members are modeled by extended Roufaiel-Meyer hysteretic relation for bending while shear deformations for walls by Origin-Oriented hysteretic model. For the critical height of shear-walls, division to sub-elements is performed. Different yield capacities with respect to positive and negative bending, finite extensions of plastic hinges and P-${\delta}$ effects are considered while strength deterioration is controlled by accumulated hysteretic energy. Simulated strong motions are obtained from a Gaussian white-noise filtered through Kanai-Tajimi filter. Dynamic equations of motion for the system are formed according to constitutive and compatibility relations and then inserted into equivalent It$\hat{o}$-Stratonovich stochastic differential equations. A system reduction scheme based on the series expansion of eigen-modes of the undamaged structure is implemented. Time histories of seismic response statistics are obtained by utilizing the computer programs developed for different types of structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.27 no.2
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• pp.91-99
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• 2023

Structural vibration induced by earthquake hazards is one of the most significant concerns in structure performance-based design. Structural hazards evoked from seismic events must be properly identified to make buildings resilient enough to withstand extreme earthquake loadings. To investigate the effects of combined earthquake-resistant systems, shear walls and five types of dampers are incorporated in nineteen structural models by altering their arrangements. All the building models were developed as per ACI 318-14 and ASCE 7-16. Seismic fragility curves were developed from the incremental dynamic analyses (IDA) performed by using seven sets of ground motions, and eventually, by following FEMA P695 provisions, the collapse margin ratio (CMR) was computed from the collapse curves. It is evident from the results that the seismic performance of the proposed combined shear wall-damper system is significantly better than the models equipped with shear walls only. The scrutinized dual seismic resisting system is expected to be applied practically to ensure a multi-level shield for tall structures in high seismic risk zones.

• Advances in Computational Design
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• v.8 no.1
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• pp.37-59
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• 2023

Squat reinforced concrete (SRC) shear walls are a critical part of the structure for both office/residential buildings and nuclear structures due to their significant role in withstanding seismic loads. Despite this, empirical formulae in current design standards and published studies demonstrate a considerable disparity in predicting SRC wall shear strength. The goal of this research is to develop and evaluate hybrid and ensemble artificial neural network (ANN) models. State-of-the-art population-based algorithms are used in this research for hybrid intelligence algorithms. Six models are developed, including Honey Badger Algorithm (HBA) with ANN (HBA-ANN), Hunger Games Search with ANN (HGS-ANN), fitness-distance balance coyote optimization algorithm (FDB-COA) with ANN (FDB-COA-ANN), Averaging Ensemble (AE) neural network, Snapshot Ensemble (SE) neural network, and Stacked Generalization (SG) ensemble neural network. A total of 434 test results of SRC walls is utilized to train and assess the models. The results reveal that the SG model not only minimizes prediction variance but also produces predictions (with R²= 0.99) that are superior to other models.