• Magazine of the Korea Concrete Institute
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• v.1 no.1
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• pp.87-94
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• 1989

철근콘크리트 뼈대구조와 같이 설계변수가 과다하고, 제약조건식이 복잡한 구조물의 최적화를 위하여는 구조물을 여러개의 부분구조물로 분할하여 최적해를 구하는 분할법이 많이 사용되고 있다. 그러나 기존의 분할법에 의한 최적화는 구조해석과정과 고정된 부재력에대한 단면설계변수의 부분최적화 과정만으로 이루어지기 때문에, 최적해를 구하려면 반복적인 재해석과정만을 수행하지 않으면 안된다. 따라서 본 연구에서는 다단계분할법에 의하여 철근콘크리트 뼈대구조의 최적화 문제를 3단계로 형성하고, 분할된 부분최적화문제의 최적화시 전체구조의 강성 및 부재력 변화가 반영되어 부분 구조물의 결합을 유지시킬 수 있는 최적화 알고리즘을 제안하였다. 최적화 문제에서 설계변수로는 단면의 크기, 철근량, 모멘트 재분배율등을 취하고,목적함수는 경비함수, 제약조건으로는 강도설계법에 의한 부재강도, 시방서의 요구사항등을 고려하여 문제를 형성하였다. 본 연구에서 개발한 다단계 최적화과정의 첫째 단계에서는 탄성해석에 의하여 재분배모멘트의 설계공간을 형성한다. 이 때 부재력변화량추정(forece approximation technique)에 의하여 단면치수의 변화에 따른 부재력의 변화를 제약조건식 내에 포함시킬 수 있도록 하였다. 둘째 단면에서는 첫째 단계에서 구한 부재력변화량추정이 포함된 제약조건식 내에서 무제약최소화기법에 의하여 단면치수를 최적화하도록 하였다. 셋째 단계에서는 재분배 모멘트를 최적화하였으며, 이 때 재분배모멘트의 변화에 따른 단면설계 변수의 변화는 둘째 단계에서 구한 설계민감도(design sensitivity)를 이용하여 반영시키도록 하였다. 제안된 알고리즘을 1층 2경간 및 2층 1경간 뼈대구조에 적용하여 알고리즘의 타당성과 효율성을 입증하였다. 따라서 본 연구의 알고리즘은 철근 콘크리트 뼈대구조의 최적설계에 안정성있게 적용할 수 있을 것으로 판단된다.

• Magazine of the Korea Concrete Institute
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• v.9 no.1
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• pp.133-141
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• 1997

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. To overcome difficulties arising from the presence of two materials in one element(concrete and steel) , the principle of divided parameters is adopted. The design variable parameters are divided into two groups - external and internal. The optimization is also divided into external and internal procedure. Several scarxh algorithms are tested to verify their accuracy for the external optimization. This work proposes a new search method, a modified pattern search, and sample problems prove its accuracy and uscf'ulness. The design obtained by this method is an optimum and in full accord with ACI Building Code Ftequirements(ACI'318-89).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.3
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• pp.265-274
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• 2017

This study presents a sustainable design method to optimize the embodied energy and $CO_2$ emission complying with the design code for reinforced concrete column. The sustainable design method effectively achieves the minimization of the environmental load and energy consumption whereas the conventional design method has been mostly focused on the cost saving. Failure of reinforced concrete column exhibits compressive or tensile failure mode against an external force such as flexure and compression; thus, optimization analyses are conducted for both failure modes. For the given sections and reinforcement ratios, the optimized sections are determined by optimizing cost, embodied energy, and $CO_2$ emission and various aspects of the sections are thoroughly investigated. The optimization analysis results show that 25% embodied energy and 55% $CO_2$ emission can be approximately reduced by 10% increase in cost. In particular, the embodied energy and $CO_2$ emission were more effectively reduced in the tensile failure mode rather than in the compressive failure mode. Consequently, it was proved that the sustainable design method effectively implements the concept of sustainable development in the design of reinforced concrete structure by optimizing embodied energy consumption and $CO_2$ emission.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1053-1063
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• 2014

This study presents a sustainable design method that optimizes the embodied energy of concrete beam based on the concept of sustainable development that effectively utilizes natural resource and energy within the range that our succeeding generation can afford to utilize. In order to get the flexural strength carrying the ultimate load, concrete beam sections are designed by optimization that consists of the embodied energy as a objective function and the requirements of design code as constrained conditions. The sustainable design can be used to minimize the embodied energy consumed in material production, construction, operation, demolition of the infrastructure. As a result of comparison of the cost and the embodied energy optimizations based on practical beam sections, it is shown that 20% embodied energy saving and 35% $CO_2$ emission saving are achieved by sacrificing 10% cost increase. The sustainable design method provides a new effective methodology that manages the strength design concept based on cost minimization together with economic feasibility and sustainability. In addition, the method is expected to be applied to more various structural design practices.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.5
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• pp.429-436
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• 2016

In this study, the genetic algorithm based optimal structural design method is proposed. The objective functions are to minimize the cost and $CO_2$ emissions, simultaneously. The cost and $CO_2$ emissions are calculated based on the cross-sectional dimensions, length, material strength, and reinforcement ratio of beam and column members. Thus, the cost and $CO_2$ emissions are evaluated by using the amounts of concrete and reinforcement used to construct a building. In this study, the cost and $CO_2$ emissions calculated at the phases of material transportation, construction, and building operation are excluded. The constraint conditions on the strength of beam and column members and the inter-story drift ratio are considered. The linear static analysis by using OpenSees is automatically conducted in the proposed method. The genetic algorithm is employed to solve the formulated problem. The proposed method is validated by applying it to the 4-story reinforced concrete moment frame example.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.4
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• pp.275-281
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• 2013

In this paper, determination of the scalability of the cluster composed common personal computer was performed when optimization of reinforced concrete structure using genetic algorithm. The goal of this research is watching the potential of multi-core-PC cluster for optimization of seismic design of reinforced-concrete structures. By increasing the number of core-processer of cluster, decreasing of computation time per each generation of genetic algorithm was observed. After classifying the components in singular personal computer, the estimation of the expected bottle-neck phenomenon and comparison with wall-clock time and Amdahl's law equation was performed. So we could obseved the scalability of the cluster appear complex tendency. For separating the bottle-neck phenomenon of physical and algorithm, the different size of population was selected for genetic algorithm cases. When using 64 core-processor, the efficiency of cluster is low as 31.2% compared with Amdahl's law efficiency.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.3
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• pp.319-328
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• 2011

This paper introduces the construction of Strut-Tie model based on the Evolutionary Structural Optimization(ESO) method. Differently from conventional ESO method which uses plane stress elements, the introduced approach adopts the use of truss elements with the fact that the optimum topology of structures by ESO method is open a truss-like structure. Several examples are provided to demonstrate the capability of the proposed method in finding the best Strut-Tie models. In advance, it is shown that the introduced method is supported through the correlation studies between two-dimensional plane stress analysis and Strut-Tie models, and can be used effectively in practice, especially in shear design of complex reinforced concrete members where no previous experience is available.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.501-509
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• 2019

The construction of foundation piles for buildings and bridges is changing from pile driving to an injected precast pile method. The goal is to minimize environmental damage, noise pollution, and complaints from neighboring residents. However, it is necessary to develop economic piles that are optimized for precasting by a centrifugal method in terms of both the material and structural system. A reinforced joint method is proposed for reinforced concrete piles (RC piles) manufactured by centrifugal casting. A previous study concluded that the structural performance of the current joint system for RC piles could be improved by using a reinforced joint composed of extended circular band plates and studs. In this study, the structural performance of such a joint was validated experimentally by bending and shear strength measurements. The proposed joint reinforcement method showed adequate structural performance in terms of bending and shear strength. The overall load-deflection behavior is close to that of a structure without joints, so it is expected that the behavior and performance of the design can be reliably reflected in site structures.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.219-224
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• 1999

In this study New design automation method of R/C structure based on the finite element method and the analogy evolution ary procedure was developed . This system is the efficient tool to support Reinforcement Arrangement of R/C structure. The anology evolutionary procecure is similar to the evolutionary procedure proposed by Xie and Steven.

• Computational Structural Engineering
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• v.7 no.1
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• pp.117-124
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• 1994

Multi-level Multi-objective optimization(MLMO) for reinforced concrete framed structure is performed, and compared with the results of single-level single-objective optimization. MLMO method allows flexibility to meet the design needs such as deflection and cost of structures using weighting factors. Using Multi-level formulation, the numbers of constraints and variables are reduced at each levels, and the optimization formulation becomes simplified. The force approximation method is used to reflect the variation in design variables between the substructures, and thus coupling is maintained. And the linear approximated constraints and objective function are used to reduce the number of structural analysis in optimization process. It is shown that the developed algorithm with move limit can converge effectively to optimal solution.