• 한국생산제조학회지
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• 제20권4호
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• pp.412-418
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• 2011

Reliability-based Topology optimization(RBTO) is to get an optimal design satisfying uncertainties of design variables. Although RBTO based on homogenization and density distribution method has been done, RBTO based on BESO has not been reported yet. This study presents a reliability-based topology optimization(RBTO) using bi-directional evolutionary structural optimization(BESO). Topology optimization is formulated as volume minimization problem with probabilistic displacement constraint. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., RIA, PMA, SLSV and ADL(adaptive-loop), are used. Reliability-based topology optimization design process is conducted to obtain optimal topology satisfying allowable displacement and target reliability index with the above four methods, and then each result is compared with respect to numerical stability and computing time. The results of this study show that the RBTO based on BESO using the four methods can effectively be applied for topology optimization. And it was confirmed that DLSV and ADL had better numerical efficiency than SLSV. ADL and SLSV had better time cost than DLSV. Consequently, ADL method showed the best time efficiency and good numerical stability.

• 한국자동차공학회논문집
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• 제6권6호
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• pp.276-284
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• 1998

Optimum design of bumper beam is investigated using nonlinear CAE structural analysis techniques.In order to minimize its weight, while enhancing structural performances, bumper beam structural analyses were carried out to produce optimum section. Model is composed of bumper beam and stay. First, considering FMVSS safety standard, static strength and energy absorbing capability were estimated for several competitive bumpers through pendulum static analysis, and most promising section was chosen. Next, to ensure dynamic crashworthinesss performance for center pole impact was evaluated for the bumper beam with chosen section through pendulum static analysis, referring to DHS bumper dynamic impact standard. Finally, 2.5 mph bumper beam was designed and its structural performance was estimated. Through this investigation, an optimized bumper beam section with less weight of 20% while maintaining almost equal carshworthiness, compared with a conventional bumper beam section which proved its impact crashworthiness by experiments, was developed.

• 국제초고층학회논문집
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• 제2권4호
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• pp.345-354
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• 2013

This paper presents an advanced engineering technique using finite element analysis to improve structural silicone glazing (SSG) design in high-performance curtain wall systems for building facade. High wind pressures often result in bulky SSG aluminum extrusion profile dimensions. Architectural desire for aesthetically slender curtain wall sight-lines and reduction in aluminum usage led to optimization of structural silicone bite geometry for improved stress distribution through use of finite element analysis of the hyperelastic silicone models. This advanced design technique compared to traditional SSG design highlights differences in stress distribution contours in the silicone sealant. Simplified structural engineering per the traditional SSG design method lacks accurate forecasting of material and stress optimization, as shown in the advanced analysis and design. Full scale physical specimens were tested to verify design capacity in addition to correlate physical test results with the theoretical simulation to provide confidence of the model. This design technique will introduce significant engineering advancement to the curtain wall industry and building facade.

• Structural Engineering and Mechanics
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• 제55권3호
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• pp.535-554
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• 2015

Dolphin echolocation (DE) optimization algorithm is a recently developed meta-heuristic in which echolocation behavior of Dolphins is utilized for seeking a design space. The computational performance of meta-heuristic algorithms is highly dependent to its internal parameters. But the computational time of adjusting these parameters is usually extensive. The DE is an efficient optimization algorithm as it includes few internal parameters compared with other meta-heuristics. In the present paper a modified Dolphin echolocation (MDE) algorithm is proposed for optimization of steel frame structures. In the MDE the step locations are determined using one-dimensional chaotic maps and this improves the convergence behavior of the algorithm. The effectiveness of the proposed MDE algorithm is illustrated in three benchmark steel frame optimization test examples. Results demonstrate the efficiency of the proposed MDE algorithm in finding better solutions compared to standard DE and other existing algorithms.

• 대한기계학회논문집A
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• 제27권1호
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• pp.158-166
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• 2003

The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.

• Wind and Structures
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• 제18권5호
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• pp.497-510
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• 2014

Seismic and wind load performances of buildings are commonly improved by using bracing systems. In practice, standard bracing systems, such as X, Y, V, and K types are used. To determine the appropriate bracing type, the designer uses trial & error method among the standard bracings to obtain better results. However, using topology optimization yields more efficient bracing systems or new bracing can be developed depending on building and loading types. Determination of optimum bracing type for minimum deformation on a building under the effect of wind load is given in this study. A new bracing system is developed by using topology optimization. Element removal method is used to determine and remove the comparatively inefficient materials. Optimized bracing is compared with proposed bracing types available in the related literature. Maximum deformation value of building is used as performance indicator to compare effectiveness of different bracings to resist wind loads. The proposed bracing, yielded 99%, deformation reduction compared to the unbraced building.

• 한국유체기계학회 논문집
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• 제13권6호
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• pp.19-24
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• 2010

The demands for small, high performance and high loaded aircraft compressor are increased in the world. But the design requirements become increasingly complex to design these high technical engines, the requirement of the design optimization become increased. The optimal design result of several disciplines show different tendencies and nonlinear characteristics of the compressor design, the multidisciplinary design optimization method must be considered in compressor design. Therefore, the artificial Neural Net method is adapted to make the approximation model of 3-stage axial compressor design optimization for considering the nonlinear characteristic. At last, the optimal result of this study is compared to that of previous study.

• Steel and Composite Structures
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• 제16권4호
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• pp.357-374
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• 2014

The design basis is being shifted from strength to deformation in modern performance-based design codes. This paper presents a practical method for optimization of eccentrically braced steel frames, based on the concept of uniform deformation theory (UDT). This is done by gradually shifting inefficient material from strong parts of the structure to the weak areas until a state of uniform deformation is achieved. In the first part of this paper, UDT is implemented on 3, 5 and 10 story eccentrically braced frames (EBF) subjected to 12 earthquake records representing the design spectrum of ASCE/SEI 7-10. Subsequently, the optimum strength-distribution patterns corresponding to these excitations are determined, and compared with four other loading patterns. Since the optimized frames have uniform distribution of deformation, they undergo less damage in comparison with code-based designed structures while having minimum structural weight. For further investigation, the 10 story EBF is redesigned using four different loading patterns and subjected to 12 earthquake excitations. Then a comparison is made between link rotations of each model and those belonging to the optimized one which revealed that the optimized EBF behaves generally better than those designed by other loading patterns. Finally, efficiency of each loading pattern is evaluated and the best one is determined.

• 한국전산구조공학회논문집
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• 제23권5호
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• pp.535-541
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• 2010

본 연구에서는 정상상태의 비선형 열탄성 문제에 대하여 탄성 계수 및 열전도 계수에 대해서 보조변수법을 이용한 연속체 기반의 설계민감도 방정식을 유도하였고, 온도와 변위장이 연성된 보조방정식을 정의하여 효율적으로 설계민감도 해석을 수행하여 위상 최적설계에 적용하였다. 수치 예제를 통하여 열탄성 문제에서 위상 최적설계가 갖는 요소망 의존성을 살펴보았다. 또한 열 하중이 지배적인 경우와 기계적 하중이 지배적인 경우를 비교하여 다중 물리 연성문제에서 위상 최적설계가 갖는 하중에 대한 의존성을 고찰하였다.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권8호
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• pp.551-560
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• 2004

In this paper, we propose a new architecture of Self-Organizing Fuzzy Polynomial Neural Networks (SOFPNN) that is based on a genetically optimized multilayer perceptron with fuzzy polynomial neurons (FPNs) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially genetic algorithms (GAs). The proposed SOFPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional SOFPNNs. The design procedure applied in the construction of each layer of a SOFPNN deals with its structural optimization involving the selection of preferred nodes (or FPNs) with specific local characteristics (such as the number of input variables, the order of the polynomial of the consequent part of fuzzy rules, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. Through the consecutive process of such structural and parametric optimization, an optimized and flexible fuzzy neural network is generated in a dynamic fashion. To evaluate the performance of the genetically optimized SOFPNN, the model is experimented with using two time series data(gas furnace and chaotic time series), A comparative analysis reveals that the proposed SOFPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literatures.