• 제목/요약/키워드: reliability-based optimization

검색결과 479건 처리시간 0.027초

분산컴퓨팅 환경에서 공력 설계최적화의 효율성 연구 (A STUDY ON THE EFFICIENCY OF AERODYNAMIC DESIGN OPTIMIZATION IN DISTRIBUTED COMPUTING ENVIRONMENT)

  • 김양준;정현주;김태승;손창호;조창열
    • 한국전산유체공학회지
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    • 제11권2호
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    • pp.19-24
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    • 2006
  • A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

Cancer Prediction Based on Radical Basis Function Neural Network with Particle Swarm Optimization

  • Yan, Xiao-Bo;Xiong, Wei-Qing;Hu, Liang;Zhao, Kuo
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권18호
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    • pp.7775-7780
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    • 2014
  • This paper addresses cancer prediction based on radial basis function neural network optimized by particle swarm optimization. Today, cancer hazard to people is increasing, and it is often difficult to cure cancer. The occurrence of cancer can be predicted by the method of the computer so that people can take timely and effective measures to prevent the occurrence of cancer. In this paper, the occurrence of cancer is predicted by the means of Radial Basis Function Neural Network Optimized by Particle Swarm Optimization. The neural network parameters to be optimized include the weight vector between network hidden layer and output layer, and the threshold of output layer neurons. The experimental data were obtained from the Wisconsin breast cancer database. A total of 12 experiments were done by setting 12 different sets of experimental result reliability. The findings show that the method can improve the accuracy, reliability and stability of cancer prediction greatly and effectively.

복합재 미익 구조의 신뢰성 기반 확률론적 구조해석 (The Reliability-Based Probabilistic Structural Analysis for the Composite Tail Plane Structures)

  • 이석제;김인걸
    • 한국군사과학기술학회지
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    • 제15권1호
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    • pp.93-100
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    • 2012
  • In this paper, the deterministic optimal design for the tail plane made of composite materials is conducted under the deterministic loading condition and compared with that of the metallic materials. Next, the reliability analysis with five random variables such as loading and material properties of unidirectional prepreg is conducted to examine the probability of failure for the deterministic optimal design results. The MATLAB programing is used for reliability analysis combined with FEA S/W(COMSOL) for structural analysis. The laminated composite is assumed to the equivalent orthotropic material using classical laminated plate theory. The response surface methodology and importance sampling technique are adopted to reduce computational cost with satisfying the accuracy in reliability analysis. As a result, structural weight of composite materials is lighter than that of metals in deterministic optimal design. However, the probability of failure for the deterministic optimal design of the tail plane structures is too high to be neglected. The sensitivity of each variable is also estimated using probabilistic sensitivity analysis to figure out which variables are sensitive to failure. The computational cost is considerably reduced when response surface methodology and importance sampling technique are used. The study of the computationally inexpensive method for reliability-based design optimization will be necessary in further work.

레이저 스캔 모델의 설계 프로세스 개발 (Development of the Design Process for Laser Scanned Model)

  • 김좌일;왕세명;강의철;이관행
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2004년도 춘계학술대회
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    • pp.1029-1034
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    • 2004
  • Recent engineering process requires fast development and manufacturing of the products. This paper mainly discusses the process of rapid product development (RPD) from the reverse engineering to the optimal design. A laser scanning system scans a product and the efficient data processing method reduces the scanned point data. The reduced (scanned) points model is transformed to a finite element model without the construction of a CAD model. Since CAD modeling is a time-consuming work, skipping this step can save much time. This FE model is updated from the result based on the structural characteristics from modal test of the real model. For FE model updating, Response Surface Method is adopted. Finally, the updated FE model is optimized using the reliability-based topology optimization, which is developed recently. All these processes are applied to the design of an upper part model of a cellular phone.

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크리깅 근사모델을 이용한 전역적 강건최적설계 (A Global Robust Optimization Using the Kriging Based Approximation Model)

  • 박경진;이권희
    • 대한기계학회논문집A
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    • 제29권9호
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    • pp.1243-1252
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    • 2005
  • A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

배전계통에서 GA를 이용한 접속변경 순서 결정 방법 (Study of Connection Process in Distribution systems using Genetic Algorithm)

  • 오선;서정갑
    • 한국위성정보통신학회논문지
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    • 제6권1호
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    • pp.6-11
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    • 2011
  • 본 논문에서는 전기 배전시스템에서 부하단의 실시간 변화에 따른 배전시스템의 안정적인 운용을 가능하게 하기 위해서 유전자 알고리즘 방법을 사용한 방법에 대해서 연구하였다 배전시스템의 안정적인 운용은 각각의 배전 구역에서의 안정성을 향상시킨다는 중요한 장점을 가지고 있다 본 논문에서는 배전계통에서 가장 어려운 것으로 평가되는 접속절차에 대한 접근을 기반의 신뢰성 모델에 기초하여 수행하였다 유전자 알고리즘은 일반적인 생물계에서의 생존을 위한 진화의 과정을 구현한 것으로서 본 논문에서는 개의 노드와 개의 배전영역을 갖는 배전시스템을 대상으로 유전자 알고리즘을 적용한 배전시스템 최적화를 구현하였다.

Robust Person Identification Using Optimal Reliability in Audio-Visual Information Fusion

  • Tariquzzaman, Md.;Kim, Jin-Young;Na, Seung-You;Choi, Seung-Ho
    • The Journal of the Acoustical Society of Korea
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    • 제28권3E호
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    • pp.109-117
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    • 2009
  • Identity recognition in real environment with a reliable mode is a key issue in human computer interaction (HCI). In this paper, we present a robust person identification system considering score-based optimal reliability measure of audio-visual modalities. We propose an extension of the modified reliability function by introducing optimizing parameters for both of audio and visual modalities. For degradation of visual signals, we have applied JPEG compression to test images. In addition, for creating mismatch in between enrollment and test session, acoustic Babble noises and artificial illumination have been added to test audio and visual signals, respectively. Local PCA has been used on both modalities to reduce the dimension of feature vector. We have applied a swarm intelligence algorithm, i.e., particle swarm optimization for optimizing the modified convection function's optimizing parameters. The overall person identification experiments are performed using VidTimit DB. Experimental results show that our proposed optimal reliability measures have effectively enhanced the identification accuracy of 7.73% and 8.18% at different illumination direction to visual signal and consequent Babble noises to audio signal, respectively, in comparison with the best classifier system in the fusion system and maintained the modality reliability statistics in terms of its performance; it thus verified the consistency of the proposed extension.

Cross Layer Optimal Design with Guaranteed Reliability under Rayleigh block fading channels

  • Chen, Xue;Hu, Yanling;Liu, Anfeng;Chen, Zhigang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제7권12호
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    • pp.3071-3095
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    • 2013
  • Configuring optimization of wireless sensor networks, which can improve the network performance such as utilization efficiency and network lifetime with minimal energy, has received considerable attention in recent years. In this paper, a cross layer optimal approach is proposed for multi-source linear network and grid network under Rayleigh block-fading channels, which not only achieves an optimal utility but also guarantees the end-to-end reliability. Specifically, in this paper, we first strictly present the optimization method for optimal nodal number $N^*$, nodal placement $d^*$ and nodal transmission structure $p^*$ under constraints of minimum total energy consumption and minimum unit data transmitting energy consumption. Then, based on the facts that nodal energy consumption is higher for those nodes near the sink and those nodes far from the sink may have remaining energy, a cross layer optimal design is proposed to achieve balanced network energy consumption. The design adopts lower reliability requirement and shorter transmission distance for nodes near the sink, and adopts higher reliability requirement and farther transmission distance for nodes far from the sink, the solvability conditions is given as well. In the end, both the theoretical analysis and experimental results for performance evaluation show that the optimal design indeed can improve the network lifetime by 20-50%, network utility by 20% and guarantee desire level of reliability.

해상풍력발전기 자켓 지지구조물의 최적설계 및 신뢰성해석 (Design Optimization and Reliability Analysis of Jacket Support Structure for 5-MW Offshore Wind Turbine)

  • 이지현;김수영;김명현;신성철;이연승
    • 한국해양공학회지
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    • 제28권3호
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    • pp.218-226
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    • 2014
  • Since the support structure of an offshore wind turbine has to withstand severe environmental loads such as wind, wave, and seismic loads during its entire service life, the need for a robust and reliable design increases, along with the need for a cost effective design. In addition, a robust and reliable support structure contributes to the high availability of a wind turbine and low maintenance costs. From this point of view, this paper presents a design process that includes design optimization and reliability analysis. First, the jacket structure of the NREL 5-MW offshore wind turbine is optimized to minimize the weight and stresses, while satisfying the design requirements. Second, the reliability of the optimum design is evaluated and compared with that of the initial design. Although the present study results in a new optimum shape for a jacket support structure with reduced weight and increased reliability, the authors suggest that the optimum design has to be accompanied by a reliability analysis during the design process, as well as reliability based design optimization if needed.

The smooth topology optimization for bi-dimensional functionally graded structures using level set-based radial basis functions

  • Wonsik Jung;Thanh T. Banh;Nam G. Luu;Dongkyu Lee
    • Steel and Composite Structures
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    • 제47권5호
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    • pp.569-585
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    • 2023
  • This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.