• 한국공간구조학회논문집
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• 제22권2호
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• pp.47-55
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• 2022

In this study, we focus on the feasibility of structural topology optimization for a steel-timber composite beam design of optimally allocating glue-laminated timbers into a web with openings under the condition of given steel flanges. The motivation of this study is to topologically take maximal stiffness harmonizing both tension and compression performance of the steel-timber composite beam and become the eco-frandly timber design for buidling members. As a result of this study, the key web-openings allocation becomes triangle spaces, i.e., empty or no materials, of optimal topologies of both a pure timber plate and a steel flange-web timber plate without web-openings. Several applicable examples verify the effectiveness of topology optimization for steel-timber beams with web-openings.

• 전기학회논문지
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• 제57권3호
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• pp.466-472
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• 2008

The paper concerns Fuzzy C-Means clustering based fuzzy neural networks (FCM-FNN) and the optimization of the network is carried out by means of hierarchal fair competition-based parallel genetic algorithm (HFCPGA). FCM-FNN is the extended architecture of Radial Basis Function Neural Network (RBFNN). FCM algorithm is used to determine centers and widths of RBFs. In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM-FNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Since the performance of FCM-FNN is affected by some parameters of FCM-FNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the HFCPGA which is a kind of multipopulation-based parallel genetic algorithms(PGA) is exploited to carry out the structural optimization of FCM-FNN. Moreover the HFCPGA is taken into consideration to avoid a premature convergence related to the optimization problems. The proposed model is demonstrated with the use of two representative numerical examples.

• Structural Engineering and Mechanics
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• 제86권1호
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2000년도 봄 학술발표회논문집
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• pp.458-465
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• 2000

In the field of structural optimization simulated annealing (SA) algorithm has widely been adopted as an optimizer with the positive features of SA such as simplicity of the algorithm and possibility of finding global solution However, annealing process of SA algorithm based on random generator with the zeroth order structural information requires a large of number of iterations highly depending on cooling schedules and stopping criteria. In this paper, MSA algorithm is presented in the form of two phase annealing process with the effective cooling schedule and stopping criteria. With the application to optimal seismic design of steel structures, the performance of the proposed MSA algorithm has been demonstrated with respect to stability and global convergence of the algorithm

• Steel and Composite Structures
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• 제42권1호
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• pp.139-149
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• 2022

To simplify the design and reduce the construction cost of traditional multi-girder structural systems, twin I-girder structures are widely used in many countries in recent years. Due to the concern on post-fracture redundancy, however, twin girder bridges are currently classified as fracture critical structures in AASHTO specifications for highway bridges. To investigate the after-fracture behavior of such structures, a composite steel and concrete twin girder specimen was built and an artificial fracture through the web and the bottom flange was created on one main girder. The static loading test was performed to investigate its mechanical performance after a severe fracture occurred on the main girder. Applied load and vertical displacement curves, and the applied load versus strain relationships at key sections were measured. To investigate the load distribution and transfer capacities between two steel girders, the normal strain development on crossbeams was also measured during the loading test. In addition, both shear and normal strains of studs were also measured in the loading test to explore the behavior of shear connectors in such bridges. The functions and structural performance of structural members and possible load transfer paths after main girder fractures in such bridges were also discussed. The test results indicate in this study that a typical twin I-girder can resist a general fracture on one of its two main girders. The presented results can provide references for post-fracture performance and optimization for the design of twin I-girder bridges and similar structures.

• 한국공간구조학회논문집
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• 제24권2호
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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.

• 한국안전학회지
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• 제27권6호
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• pp.115-121
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• 2012

This paper, being the second in a two-part series, presents the robust performance of the proposed design method which can enhance a reliability-based design optimization(RBDO) under the uncertainties of probabilistic models. The robust performances of the solutions obtained by the proposed method, described in the Part 1, are investigated through the parametric studies. A 10-bar truss example is considered, and the uncertain parameters include the number of data observed, and the variations of applied loadings and allowable stresses. The numerical results show that the proposed method can produce a consistent result despite of the large variations in the parameters. Especially, even with the relatively small data set, the analysis results show that the exact probabilistic model can be successfully predicted with optimized design sections. This consistency of estimating appropriate probability model is also observed in the case of the variations of other parameters, which verifies the robustness of the proposed method.

• Earthquakes and Structures
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• 제16권2호
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• pp.165-175
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• 2019

Incremental dynamic analysis (IDA), as an accurate method to evaluate the parameters of structural performance levels, requires many non-linear time history analyses, using a set of ground motion records which are scaled to different intensity levels. Therefore, this method is very computationally demanding. In this study, a new method is presented to estimate the summarized (16%, 50%, and 84% fractiles) IDA curves of a first-mode dominated structure using discrete wavelet transform and bees optimization algorithm. This method reduces the number of required ground motion records for the prediction of the summarized IDA curves. At first, a subset of first list ground motion records is decomposed by means of discrete wavelet transform which have a low dispersion estimating the summarized IDA curves of equivalent SDOF system of the main structure. Then, the bees algorithm optimizes a series of factors for each level of detail coefficients in discrete wavelet transform. The applied factors change the frequency content of original ground motion records which the generated ground motions records can be utilized to reliably estimate the summarized IDA curves of the main structure. At the end, to evaluate the efficiency of the proposed method, the seismic behavior of a typical 3-story special steel moment frame, subjected to a set of twenty ground motion records is compared with this method.

• 한국공간구조학회논문집
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• 제21권3호
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• pp.43-50
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• 2021

A tilted tall building is actively constructed as landmark structures around world to date. Because lateral displacement responses of a tilted tall building occurs even by its self-weight, reduction of seismic responses is very important to ensure structural safety. In this study, a smart tuned mass damper (STMD) was applied to the example tilted tall building and its seismic response control performance was investigated. The STMD was composed of magnetorheological (MR) damper and it was installed on the top floor of the example building. Control performance of the STMD mainly depends on the control algorithn. Fuzzy logic controller (FLC) was selected as a control algorithm for the STMD. Because composing fuzzy rules and tuning membership functions of FLC are difficult task, evolutionary optimization algorithm (EOA) was used to develop the FLC. After numerical simulations, it has been seen that the STMD controlled by the EOA-optimized FLC can effectively reduce seismic responses fo the tilted tall building.

• Composites Research
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• 제22권3호
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• pp.66-73
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• 2009

적층 두께, 면밀도, 질량관성모우멘트는 소재의 구조-역학적 특성을 나타내는 중요한 인자들이다. 본 연구에서는 이와 같은 인자들이 다층-복합재료구조의 내충격 성능에 미치는 영향을 고찰하기 위해 높은 충격자 속도 하에서 탄자한계속도기 최대가 되는 재료-구조 최적화를 수행하였다. 세라믹복합재료, 고무, 알루미늄 그리고 알루미늄 폼으로 구성된 다층-복합재료구조의 최적화를 위해 Florence 모델과 Awerbuch-Bonder 모델을 연계한 통합 모델을 개발하였으며, 구속 조건으로써 적층 두께, 면밀도, 질량관성모우멘트를 함께 사용하였다. 결과에서 알 수 있듯이, 제안된 통합 모델을 통해 계산된 탄자한계속도는 유한표소해석에서의 탄자한계속도와 거의 유사함을 확인하였다. 통합 모델을 바탕으로 재료-구조 최적화를 통해 설정된 다층구조는 최적화를 수행하지 않은 다층구조에 비해 약 10.8%의 탄자한계속도 및 26.7%의 충격흡수에너지 향상이 나타남을 알 수 있다.