• 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.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.577-582
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• 2000

This study is aimed to evaluate the shear strength of reinforced concrete deep beams subject to concentrated loads, using a simplified strut-tie model. For the shear strength prediction of deep beams, it is prerequisite to evaluate the effective width of strut and to verify the efficiency factors proposed by MacGregor et al.. The results analyzed by truss models have been compared with those calculated by domestic code for the existing data of 90 deep beam specimens. The shear strength of deep beams were reviewed with respect to concrete strength, the shear span-depth ratio, and the ratio of web reinforcements. The results showed that the shear strength of the proposed model gave a better agreement than the domestic code approach.

• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1132-1142
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• 2001

The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

• Computers and Concrete
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• v.9 no.3
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• pp.227-244
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• 2012

A theoretical model for shear strength evaluation of fibrous concrete beams reinforced with stirrups is proposed. The formulation is founded on the theory of plasticity and the stress field concepts, generalizing a known plastic model for calculating the bearing capacity of reinforced concrete beams, to the case of fibrous concrete. The beneficial effect of steel fibres is estimated taking into account the residual tensile strength of fibrous concrete, by modifying an analytical constitutive law which presents a plastic plateau as a post-peak branch. Around fifty results of experimental tests carried out on steel fibrous concrete beams available in the literature were collected, and a comparison of shear strength estimation provided by other semi-empirical models is performed, proving that the numerical values obtained with the proposed model are in very good agreement with the experimental results.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.896-901
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• 2003

This paper describes a model on shear strength of RC columns strengthened with FRP sheets. In this study, we propose a confined concrete strength model of RC columns confined by transverse reinforcement as well as FRP sheet by introducing corresponding effective confinement coefficient for each confined concrete area. Then, a shear strength model of the confined RC columns is proposed by lower and upper bound limit analysis which are based on the truss-arch model theory and shear band failure theory, respectively. Along with shear test data obtained from strengthened column specimens, the developed analytical models are verified. The comparison shows that the proposed model can be used effectively for the prediction of both ultimate strength and required amount of strengthening in retrofit design for RC columns.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.245-248
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• 2006

The development of offshore structures have been increased spectacularly, especially in oil rig structures. This study concerns with the effects of heave motion of spar platform that attached the helical fin. There are three models, namely, cylinder, cylinder-truss and cylinder-cell with different geometrical dimensions are examined. Finally, the interaction between structure and fluid is closely considered. As the results, it can be seen that the existence of helical fin does not influence on surging but it affects a little on heaving of spar platform.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.362-369
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• 1998

The computational environment in which engineers perform their designs has been rapidly evolved from coarse serial machines to massively parallel machines. Although the recent development of high-performance computers are available for a number of years, only limited successful applications of the new computational environments in computational structural engineering field has been reported due to its limited availability and large cost associated with high-performance computing. As a new computational model for high-performance engineering computing without cost and availability problems, parallel structural analysis models for large scale structures on a network of personal computers (PCs) are presented in this paper. In structural analysis solving routine for the linear system of equations is the most time consuming part. Thus, the focus is on the development of efficient preconditioned conjugate gradient (PCG) solvers on the proposed computational model. Two parallel PCG solvers, PPCG-I and PPCG-II, are developed and applied to analysis of large scale space truss structures.

• Computational Structural Engineering
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• v.5 no.2
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• pp.93-104
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• 1992

The final objective of optimization methods is to find global optimum accurately and efficiently. The optmization processes by simulated annealing and genetic algorithm which have stochastic search process are examined and are applied to several mathematical models and truss, beam structures. Then the robustnesses of these two methods are studied and compared with the results of deterministic optimization methods from the viewpoints of reliability and running time in obtaining the global optimum.

• Proceedings of the Korea Concrete Institute Conference
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• 2005.05a
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• pp.143-146
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• 2005

최근 들어 90도 표준갈고리의 대안으로 정착판을 지니는 헤드 철근(headed bar)에 대한 관심이 높아지고 있다. 헤드 철근의 정착내력은, 정착판의 지압력과 위험단면에서 헤드까지 정착길이의 부착력으로 발현된다. 실제 구조물에서는 정착되는 부재의 재료 및 기하학적 물성에 의해 다양한 파괴가 발생된다. 따라서 헤드 철근의 정착내력은 단순히 지압력과 부착력의 합으로 산정될 수 없으며, 발생 가능한 모든 파괴양상을 고려한 최소 내력으로 결정되어야 한다. 헤드 철근의 정착내력을 산정하기 위한 기본적인 해석모델로, CCT 절점에 정착된 헤드 철근의 트러스 모델을 제안하였다. 제안된 트러스 모델의 파괴는 부착파괴와 콘크리트의 압축파괴로 구분되며, 재료 및 기하학적 물성에 의해 파괴 양상이 결정된다. 이러한 트러스 모델은 외부 보-기둥 접합부와 같이 보다 복잡한 부위에 정착된 헤드철근의 정착 기구를 설명하는데 활용될 수 있다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.119-126
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• 1996

In this paper, a method of substructural identification is presented for the estimation of localized structural parameters. for this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for the substructure to process the measurement data impaired by noises. The sequential prediction error method is used fer the estimation of unknown localized parameters. Using the substructural method, the number of unknown parameters can be reduced and the convergence and accuracy of estimation can be improved. For some substructures, the effect of the input excitation is expressed in terms of the responses at the inferences with the main structure, and substructural identification may be carried out without measuring the actual input excitation to the whole structure. Example analysis is carried out for idealized structural models of a multistory building and a truss bridge. The results indicate that the present method is effective and efficient for local damage estimation of complex structures.