• Interaction and multiscale mechanics
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• v.4 no.1
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• pp.17-34
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• 2011

This paper deals with the modeling of the plane frame structure-foundation-soil system. The superstructure along with the foundation beam is idealized as beam bending elements. The soil medium near the foundation beam with stress concentrated is idealized by isoparametric finite elements, and infinite elements are used to represent the far field of the soil media. This paper presents the modeling of shear wall structure-foundation and soil system using the optimal membrane triangular, super and conventional finite elements. Particularly, an alternative formulation is presented for the optimal triangular elements aimed at reducing the programming effort and computational cost. The proposed model is applied to a plane frame-combined footing-soil system. It is shown that the total settlement obtained from the non-linear interactive analysis is about 1.3 to 1.4 times that of the non-interactive analysis. Furthermore, the proposed model was found to be efficient in simulating the shear wall-foundation-soil system, being able to yield results that are similar to those obtained by the conventional finite element method.

• Journal of Korean Association for Spatial Structures
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• v.24 no.2
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• pp.83-90
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• 2024

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

• Computers and Concrete
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• v.12 no.3
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• pp.351-375
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• 2013

Post-punching resistance of a flat slab can help redistribute the gravity loads and resist progressive collapse of a structure following initial damage. One important difficulty with accounting for the post-punching strength of a slab is the discontinuity that develops following punching shear. A numerical simulation technique is proposed here to model and evaluate post-punching resistance of flat slabs. It is demonstrated that the simulation results of punching shear and post-punching response of the model of a slab on a single column are in good agreement with corresponding experimental data. It is also shown that progressive collapse due to a column removal (explosion) can lead to punching failure over an adjacent column. Such failure can propagate throughout the structure leading to the progressive collapse of the structure. Through post-punching modeling of the slab and accounting for the associated discontinuity, it is also demonstrated that the presence of an adequate amount of integrity reinforcement can provide an alternative load path and help resist progressive collapse.

• Journal of Power System Engineering
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• v.7 no.1
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• pp.60-67
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• 2003

This paper introduces basic study how to restrain the vibration of a four story shear structure. We have modeled a four story shear structure mathematically and have identified each parameters by experiment. We have gotten a reduced nominal model through modal analyzing method and the $H_{\infty}$ control theory is used in the control system design to get the robust controller. It's shown that the desirable performances is confirmed through the mathematical simulation. And a designed controller applying the $H_{\infty}$ control theory shows the good performance for the impulse disturbance through the simulation results. That is, the robustness of this control system is confirmed for the ability of disturbance rejection and modeling error.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.315-329
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• 2003

As shear occurs along a soil-structure interface, a localized zone with a thickness of several grain diameters will develop in soil along the interface, forming an interfacial layer. In this paper, the behaviour of a soil-structure interface is studied numerically by modelling the plane shear of a granular layer bounded by rigid plates. The mechanical behaviour of the granular material is described with a micro-polar hypoplastic continuum model. Numerical results are presented to show the development of shear localization along the interface for shearing under conditions of constant normal pressure and constant volume, respectively. Evolution of the resistance on the surface of the bounding plate is considered with respect to the influences of grain rotation.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.04a
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• pp.357-362
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• 2000

This Paper presents dynamic analysis of underground R/C Subway Structure, subjected to seismic actions. Earthquakes brought serious damage to RC subway Structure. Foe studying the collapse mechanism of underground RC Subway, seismic of a subway station is simulated in using FEM program ASP2000 of two-dimension based on the path dependent RC elastic model, soil foundation and interfacial models. The shear failure of intermediate vertical columns is founds to be the major cause of the structural collapse. According to FEM simulation of the failure mechanism, it is considered that the RC column would lose axial load carrying capacity after the occurrence of the localized diagonal shear cracks , and sudden failure of the outer frame would be followed. Specially, the shear stress in the middle slab reaches maximum shear capacity. So, the Structure would fail in the middle slab as a result of erasing the vertical ground motion computation.

• Nuclear Engineering and Technology
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• v.30 no.5
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• pp.387-395
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• 1998

In general, the laminated rubber bearing (LRB), a composite structure laminated with the elastic rubber and steel plates, has a complex hysteretic nonlinear characteristics in relationships between the restoring force and shear deflection. The representative nonlinear characteristics of LRB include the change of hysteresis loop with cyclic shear deflections and the hardening effects at large shear deflection regions. Changes of the hysteresis loop of LRB with cyclic shear deflections affect the horizontal stiffness and the damping characteristics. The hardening behavior of LRB in large shear deflection region results in an increased horizontal stiffness and therefore, has a great impacton the seismic responses. In this paper, the seismic response analysis is carried out using the modified hysteretic bi-linear model of LRB, which takes into account the hysteresis loop change and the hardening behavior with cyclic shear deflection. The results on seismic responses are compared with those obtained using the widely used hysteretic hi-linear model. The new model is found to reveal the greater amount of peak acceleration response.

• Structural Engineering and Mechanics
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• v.57 no.4
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• pp.657-680
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• 2016

Reinforced concrete (RC) deep beams are structural members that predominantly fail in shear. Therefore, determining the shear strength of these types of beams is very important. The strut-and-tie method is commonly used to design deep beams, and this method has been adopted in many building codes (ACI318-14, Eurocode 2-2004, CSA A23.3-2004). In this study, the efficiency of artificial neural networks (ANNs) in predicting the shear strength of RC deep beams is investigated as a different approach to the strut-and-tie method. An ANN model was developed using experimental data for 214 normal and high-strength concrete deep beams from an existing literature database. Seven different input parameters affecting the shear strength of the RC deep beams were selected to create the ANN structure. Each parameter was arranged as an input vector and a corresponding output vector that includes the shear strength of the RC deep beam. The ANN model was trained and tested using a multi-layered back-propagation method. The most convenient ANN algorithm was determined as trainGDX. Additionally, the results in the existing literature and the accuracy of the strut-and-tie model in ACI318-14 in predicting the shear strength of the RC deep beams were investigated using the same test data. The study shows that the ANN model provides acceptable predictions of the ultimate shear strength of RC deep beams (maximum $R^2{\approx}0.97$). Additionally, the ANN model is shown to provide more accurate predictions of the shear capacity than all the other computed methods in this study. The ACI318-14-STM method was very conservative, as expected. Moreover, the study shows that the proposed ANN model predicts the shear strengths of RC deep beams better than does the strut-and-tie model approaches.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.291-296
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• 2000

In this paper a relatively simple and reliable wall models are investigated, which are suitable to be efficiently incorporated in a practical nonlinear seismic analysis of reinforced concrete shear wall structural systems. Four types of analogous frames have been selected for the elastic stress analysis. Three types of macro-elements model which include wide-column model, truss model and Kabeyasawa model, are chosen for the use in nonlinear analysis. A numerical analysis is carried out for six stories plane coupled wall structure. Analysis results indicate that macro-elements wall model is effective and suitable for simulating stress in elastic analysis. In inelastic analysis, the yielding strength have little effect on different wall model, and the effect on post-yielding stiffness in story shear-drift relationship depend on force-deformation properties of macro-elements.

• Smart Structures and Systems
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• v.15 no.5
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• pp.1215-1232
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• 2015

In the present paper, a method for identifying damage in a multi storeyed shear building structure is presented using minimum number of modal parameters of the structure. A damage at any level of the structure may lead to a major failure if the damage is not attended at appropriate time. Hence an early detection of damage is essential. The proposed identification methodology requires experimentally determined sparse modal data of any particular mode as input to detect the location and extent of damage in the structure. Here, the first natural frequency and corresponding partial mode shape values are used as input to the model and results are compared by changing the sensor placement locations at different floors to conclude the best location of sensors for accurate damage identification. Initially experimental data are simulated numerically by solving eigen value problem of the damaged structure with inclusion of random noise on the vibration characteristics. Reliability of the procedure has been demonstrated through a few examples of multi storeyed shear structure with different damage scenarios and various noise levels. Validation of the methodology has also been done using dynamic data obtained through experiment conducted on a laboratory scale steel structure.