• Earthquakes and Structures
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• 제7권3호
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• pp.271-294
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• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• Tribology and Lubricants
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• 제39권3호
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• 대한조선학회논문집
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• 제60권5호
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• pp.332-340
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• 2023

The present study established hull form optimization for small catamaran based on variations of knuckle lines. Four knuckle lines below the free surface were employed as design variables. Knuckle lines were independently transformed within remaining the main dimensions of the existing hull. For the hull form optimization, the SHERPA algorithm of HEEDS was utilized. Computational fluid dynamics was employed to estimate the resistance performance. The optimal hull showed the improvement of resistance performance of 9.3% than that of existing hull. The improvement of wave and pressure distributions for optimal hull was confirmed. Throughout the present study, it is expected that established optimization method can be applied for various small vessels such as fishing and leisure boats.

• 전자공학회논문지
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• 제53권8호
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• pp.59-65
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• 2016

본 논문은 대량의 stream data를 처리하는 어플리케이션에서 하드웨어 가속기들이 접근하는 메모리가 non-cacheable에서 cacheable으로 변경됨에 따라 발생할 수 있는 데이터 일관성 문제를 고려하여 시스템 최적화를 진행하였다. 이를 위해 상위 수준 시뮬레이션을 통한 프로파일링 결과를 토대로 분석식을 만들어 활용하였다. 실험한 결과 여러 이미지 크기에서 메모리가 cacheable로 변경됨에 따라 평균 1.40배의 성능 향상을 보였다. 분석식의 주요 파라미터 최적화를 통해 최종적으로 3.88배의 성능 이득이 발생했으며, 항상 메모리가 cacheable인 경우의 성능이 항상 우월한 것은 아님을 확인할 수 있었다.

• Steel and Composite Structures
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• 제47권3호
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• pp.339-353
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• 2023

The primary objective of the current study is to optimize and evaluate the seismic performance of steel momentresisting frame (MRF) structures considering soil-structure interaction (SSI) effects. The structural optimization is implemented in the context of performance-based design in accordance with FEMA-350 at different confidence levels from 50% to 90% by taking into account fixed- and flexible-base conditions using an efficient metaheuristic algorithm. Nonlinear response-history analysis (NRHA) is conducted to evaluate the seismic response of structures, and the beam-on-nonlinear Winkler foundation (BNWF) model is used to simulate the soil-foundation interaction under the MRFs. The seismic performance of optimally designed fixed- and flexible-base steel MRFs are compared in terms of overall damage index, seismic collapse safety, and interstory drift ratios at different performance levels. Two illustrative examples of 6- and 12-story steel MRFs are presented. The results show that the consideration of SSI in the optimization process of 6- and 12-story steel MRFs results in an increase of 1.0 to 9.0 % and 0.5 to 5.0 % in structural weight and a slight decrease in structural seismic safety at different confidence levels.

• Steel and Composite Structures
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• 제27권5호
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• pp.613-622
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• 2018

The requirement to safe and economical buildings caused to the exploitation of nonlinear capacity structures and optimization of them. This requirement leads to forming seismic design method based on performance. In this study, concentrically braced frames (CBFs) have been optimized at the immediate occupancy (IO) and collapse prevention (CP) levels. Minimizing structural weight is taken as objective function subjected to performance constraints on inter-story drift ratios at various performance levels. In order to evaluate the seismic capacity of the CBFs, pushover analysis is conducted, and the process of optimization has been done by using Bee Algorithm. Results indicate that performance based design caused to have minimum structural weight and due to increase capacity of CBFs.

• ETRI Journal
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• 제29권1호
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• pp.50-58
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• 2007

Robust adaptive beamforming based on worst-case performance optimization is investigated in this paper. It improves robustness against steering vector mismatches by the approach of diagonal loading. A closed-form solution to optimal loading is derived after some approximations. Besides reducing the computational complexity, it shows how different factors affect the optimal loading. Based on this solution, a performance analysis of the beamformer is carried out. As a consequence, approximated closed-form expressions of the source-of-interest power estimation and the output signalto-interference-plus-noise ratio are presented in order to predict its performance. Numerical examples show that the proposed closed-form expressions are very close to their actual values.

• Industrial Engineering and Management Systems
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• 제13권4호
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• pp.442-448
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• 2014

Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.9-11
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• 2006

This paper presents JPEG quantization table design using RD optimization and neural network. Using R-D optimization, quantization table with good performance can be obtained. However, it is time-consuming and difficult to adopt to embedded systems. In this paper, a new quantization table design method is proposed using R-D optimization and neural network. Neural network learns the quantization table obtained from R-D optimization and produces a quantization table for the Images. The proposed system is applied to Yale face data. From the simulation results, it has been shown that the proposed codec has better performance than JPEG.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.711-722
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• 2020

An optimization framework using genetic algorithms has been developed towards an automated parametric optimization of the Octabuoy semi-submersible design. Compared with deep draft production units, the design of the shallow draught Octabuoy semi-submersible provides a floating system with improved motion characteristics, being less susceptible to vortex induced motions in loop currents. The relatively large water plane area results in a decreased natural heave period, which locates the floater in the wave period range with more wave energy. Considering this, the hull design of Octabuoy semi-submersible has been optimized to improve the floater's motion performance. The optimization has been conducted with optimized parameters of the pontoon's rectangular cross section area, the cone shaped section's height and diameter. Through numerical evaluations of both the 1st-order and 2nd-order hydrodynamics, the optimization through genetic algorithms has been proven to provide improved hydrodynamic performance, in terms of heave and pitch motions. This work presents a meaningful framework as a reference in the process of floating system's design.