• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.3
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• pp.426-434
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• 2000

This paper deals with a generalized similarity solution for the one-dimensional solidification of ternary or higher-order multicomponent alloys. The present approach not only retains the existing features of binary systems such as temperature- solute coupling, shrinkage-induced flow, solid-liquid property differences, and finite back diffusion, but also is capable of handling a multicomponent alloy without restrictions on the partition coefficient and microsegregation parameter. For an alloy of N-solute species, governing equations in the mushy region reduce to (N+2) nonlinear ordinary differential equations via similarity transformation, which are to be solved along with the closed-form solutions for the solid and liquid regions. A linearized correction scheme adopted in the solution procedure facilitates to determine the solidus and liquidus positions stably. The result for a sample ternary alloy agrees excellently with the numerical prediction as well as the reported similarity solution. Additional calculations are also presented to show the utility of this study. Finally, it is concluded that the present analysis includes the previous analytical approaches as subsets.

• Structural Engineering and Mechanics
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• v.27 no.6
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• pp.697-711
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• 2007

Though extensive research has been carried out for the ultimate strength of steel reinforced concrete (SRC) members under static and cyclic load, there was only limited information on the applied analysis models. Modeling of the inelastic response of SRC members can be accomplished by using a microcosmic model. However, generally used microcosmic model, which usually contains a group of parameters, is too complicated to apply in the nonlinear structural computation for large whole buildings. The intent of this paper is to develop an effective modeling approach for the reliable prediction of the inelastic response of SRC columns. Firstly, five SRC columns were tested under cyclic static load and constant axial force. Based on the experimental results, normalized trilinear skeleton curves were then put forward. Theoretical equation of normalizing point (ultimate strength point) was built up according to the load-bearing mechanism of RC columns and verified by the 5 specimens in this test and 14 SRC columns from parallel tests. Since no obvious strength deterioration and pinch effect were observed from the load-displacement curve, hysteresis rule considering only stiffness degradation was proposed through regression analysis. Compared with the experimental results, the applied analysis model is so reasonable to capture the overall cyclic response of SRC columns that it can be easily used in both static and dynamic analysis of the whole SRC structural systems.

• Computers and Concrete
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• v.21 no.1
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• pp.47-54
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• 2018

Artificial neural network models can be successfully used to simulate the complex behavior of many problems in civil engineering. As compared to conventional computational methods, this popular modeling technique is powerful when the relationship between system parameters is intrinsically nonlinear, or cannot be explicitly identified, as in the case of concrete behavior. In this investigation, an artificial neural network model was developed to assess the residual compressive strength of self-compacted concrete at elevated temperatures ($20-900^{\circ}C$) and various relative humidity conditions (28-99%). A total of 332 experimental datasets, collected from available literature, were used for model calibration and verification. Data used in model development incorporated concrete ingredients, filler and fiber types, and environmental conditions. Based on the feed-forward back propagation algorithm, systematic analyses were performed to improve the accuracy of prediction and determine the most appropriate network topology. Training, testing, and validation results indicated that residual compressive strength of self-compacted concrete, exposed to high temperatures and relative humidity levels, could be estimated precisely with the suggested model. As illustrated by statistical indices, the reliability between experimental and predicted results was excellent. With new ingredients and different environmental conditions, the proposed model is an efficient approach to estimate the residual compressive strength of self-compacted concrete as a substitute for sophisticated laboratory procedures.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.9-20
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• 2002

The purpose of this research is to develop computational procedures for studying nonlinear soil-structure interaction Problems. In orders to study soil-structure interaction behavior, the finite element analysis for the strip footing subjected to both vortical and lateral loads, and foundation layer reinforced with sheet pile are considered, interface elements are used between the footing and the soil to model the interaction behavior The main analyzed results are as follows; 1. For the prediction of settlement and lateral displacement, the result due to interface element was evaluated larger then without interface element. 2. For the determination of ultimate bearing capacity, the value using interface element appeared smaller by 12%, which was safe. 3. The horizontal and vertical displacement of strip footing affected by the presence of interface element.

• Journal of the Earthquake Engineering Society of Korea
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• v.17 no.3
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• pp.133-141
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• 2013

This paper presents the seismic evaluation and prediction of a damaged piloti-type Reinforced Concrete (RC) building before and after post-retrofitting under successive earthquakes. For considering realistic successive earthquakes, the past records measured at the same station were combined. In this study, the damaged RC building due to the first earthquake was retrofitted with a buckling-restrained brace (BRB) before the second earthquake occurred. Nonlinear Time History Analysis (NTHA) was performed under the scaled intensity of the successive ground motions. Based on the extensive structural response data obtained form from the NTHA, the fragility relationships between the ground shaking intensity and the probability of reaching a pre-determined limit state was were derived. In addition, The the fragility curves of the pre-damaged building without and with the BRBs were employed to evaluate the effect of the successive earthquakes and the post-retrofit effect. Through the seismic assessment subjected to the successive records, it was observed that the seismic performance of the pre-damaged building was significantly affected by the severity of the damage from the first earthquake damages and the hysteresis behavior of the retrofit element.

• Earthquakes and Structures
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• v.6 no.6
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• pp.627-646
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• 2014

Adobe is one of the oldest construction materials that is still used in many seismic countries, and different construction techniques are found around the world. The adobe material is characterized as a brittle material; it has acceptable compression strength but it has poor performance under tensile and shear loading conditions. Numerical modelling is an alternative approach for studying the nonlinear behaviour of masonry structures such as adobe. The lack of a comprehensive experimental database on the adobe material properties motivated the study developed here. A set of a reference material parameters for the adobe were obtained from a calibration of numerical models based on a quasi-static cyclic in-plane test on full-scale adobe wall representative of the typical Peruvian adobe constructions. The numerical modelling, within the micro and macro modelling approach, lead to a good prediction of the in-plane seismic capacity and of the damage evolution in the adobe wall considered.

• Computers and Concrete
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• v.20 no.1
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• pp.31-38
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• 2017

In the present study an Artificial Neural Network (ANN) was used to predict the compressive strength of self-compacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in this work. ANN's are considered as nonlinear statistical data modeling tools where complex relationships between inputs and outputs are modeled or patterns are found. In the present ANN model, eight input parameters are used to predict the compressive strength of self-compacting of concrete. These include varying amounts of cement, coarse aggregate, fine aggregate, fly ash, fiber, water, super plasticizer (SP), viscosity modifying admixture (VMA) while the single output parameter is the compressive strength of concrete. The importance of different input parameters for predicting the strengths at various ages using neural network was discussed in the study. There is a perfect correlation between the experimental and prediction of the compressive strength of SCC based on ANN with very low root mean square errors. Also, the efficiency of ANN model is better compared to the multivariable regression analysis (MRA). Hence it can be concluded that the ANN model has more potential compared to MRA model in developing an optimum mix proportion for predicting the compressive strength of concrete without much loss of material and time.

• Steel and Composite Structures
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• v.23 no.1
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• pp.17-29
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• 2017

The seismic performance of steel beam to concrete-encased composite column with unsymmetrical steel section joints is investigated and reported within this paper. Experimental and analytical evaluation were conducted on a total of 8 specimens with T-shaped and L-shaped steel section under lateral cyclic loading and axial compression. The test parameters included concrete strength, stirrup ratio and axial compression ratio. The response of the specimens was presented in terms of their hysterisis loop behavior, stress distribution, joint shear strength, and performance degradation. The experiment indicated good structural behavior and good seismic performance. In addition, a three-dimensional nonlinear finite-element analysis simulating was conducted to simulate their seismic behaviors. The finite-element analysis incorporated both bond-slip relationship and crack interface interaction between steel and concrete. The results were also compared with the test data, and the analytical prediction of joint shear strength was satisfactory for both joints with T-shaped and L-shaped steel section columns. The steel beam to concrete-encased composite column with unsymmetrical steel section joints can develop stable hysteretic response and large energy absorption capacity by providing enough stirrups and decreased spacing of transverse ties in column.

• Smart Structures and Systems
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• v.26 no.5
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• pp.641-656
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• 2020

The finite element solutions of thermal buckling load values of the graded sandwich curved shell structure are reported in this research using a higher-order kinematic model including the shear deformation effect. The numerical buckling temperature has been computed using an in-house specialized code (MATLAB environment) prepared in the framework of the current mathematical formulation. In addition, the mathematical model includes the excess structural distortion under the influence of elevated environment via Green-Lagrange nonlinear strain. The corresponding eigenvalue equation has been solved to predict the critical buckling temperature of the graded sandwich structure. The numerical stability and the accuracy of the current solution have been confirmed by comparing with the available published results. Thereafter, the model is extended to bring out the influences of structural parameters i.e. the curvature ratio, core-face thickness ratio, support conditions, power-law indices and sandwich types on the thermal buckling behavior of graded sandwich curved shell panels.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.359-359
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• 2011

기존 수자원계획에 있어서 수문량 예측은 매우 제한적으로 활용되고 있는 실정으로서 최근 기후변화 및 이상기후로 기인하는 기상학적 불확실성 증가에 대해서 효과적으로 대응 하기가 어렵다. 본 연구에서는 기상인자를 활용한 수문변량 예측기법을 개발하고자 하며 국내에 수문자료가 충분한 지역에 대해서 모형의 적합성과 타당성을 평가하고자 한다. 대부분의 수문변량은 해수면온도, 해수면기압, 바람장 등 Large Scale의 기상학적 특성과 연관성을 가지고 있으며 선행시간을 가지고 수문순환에 영향을 주고 있다. 수문변량과 기상학적 변량사이에는 일반적으로 비선형 관계를 가지고 있는 것으로 알려지고 있으며 이러한 비선형 관계를 효과적으로 예측하기 위해서 본 연구에서는 비선형 예측모형을 개발 하고자 한다. 최근 비선형 예측모형에서 불확실성을 고려한 모형에 대한 연구가 활발히 진행되고 있으며 특히, 다중 모형을 사용한 Ensemble 개념의 예측모형 도입이 이루어지고 있다. 본 연구에서는 국내 다목적댐 유입량 및 강수량에 대해서 최적 기상변량을 도출하고 이를 활용한 비선형 Ensemble 예측모형을 개발하였다. 일반적인 선형 회귀분석 모형에 비해 기상현상과 수문현상에 비선형성을 효과적으로 재현할 수 있는 장점을 확인할 수 있었으며 이와 더불어 예측결과에 대한 불확실성을 제공함으로서 신뢰성 있는 수자원 계획을 위한 기초자료로서 활용이 가능할 것으로 판단된다.