• 제목/요약/키워드: Approximate Optimal Design

검색결과 154건 처리시간 0.022초

승용차 A-Pillar Trim의 치수설계를 위한 소프트컴퓨팅기반 반응표면기법의 응용 (Application of Soft Computing Based Response Surface Techniques in Sizing of A-Pillar Trim with Rib Structures)

  • 김승진;김형곤;이종수;강신일
    • 대한기계학회논문집A
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    • 제25권3호
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    • pp.537-547
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    • 2001
  • The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

액체 추진 로켓의 최적 연료 바이어스 산정 및 추진제 잔류량 분석 (Optimal Selection of Fuel Bias and Propellant Residual Analysis of a Liquid Rocket)

  • 송은정;조상범;노웅래
    • 한국항공우주학회지
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    • 제43권1호
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    • pp.88-95
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    • 2015
  • 본 논문에서는 액체 엔진의 혼합비 오차와 추진제 탑재 오차가 성능에 미치는 영향에 대해서 분석하였다. 75톤급 엔진 4개를 클러스터링하는 발사체 모델에 대해 이런 오차에 의해 발생하는 추진제 잔류량을 확률적인 Monte-Carlo 방법을 사용하여 계산하고 잔류량을 최소화할 수 있는 최적 연료 바이어스를 도출하였다. 다른 발사체에 사용된 근사식을 사용한 해석적인 방법과 비교함으로써 얻어진 결과의 타당성을 검토하였다.

제조 시스템의 최적 신뢰도 및 보전도 할당 (Allocation of the Optimal Reliability and Maintainability in Manufacturing Systems)

  • 이상철
    • 산업경영시스템학회지
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    • 제22권50호
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    • pp.23-32
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    • 1999
  • Reliability and maintainability allocation in the analysis of the system's design, with the objective of planning and installing the individual components in such a way that the system performance is achieved. This paper has been made to solve an important task in reliability management of manufacturing systems within the general objective being to increase productivity while maintaining costs low. Thus, the purpose of this paper is to provide an analytical approach to determine an optimal reliability and maintainability allocation, trading off among system performance and parts investment costs. Two important considerations will be addressed in this regard : (ⅰ) determine the reliability and maintainability allocation of parts which maximizes a given production index, having fixed the total cost of investments ; and (ⅱ) determine the reliability and maintainability allocation which minimizes the total cost of investments, having fixed a minimum acceptable level of productivity. The procedure proposed in this paper is able to provide to managers and designers useful indications on the reliability and maintainability characteristics of parts in series -parallel systems. And this heuristic model is a decision support tool for contractors who are involved in large scale design projects such as ship and aircraft design. Numerical examples prove that an approximate expression of the average throughput rate is sufficiently accurate to be used in a numerical optimization method.

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Optimization approach applied to nonlinear analysis of raft-pile foundations

  • Tandjiria, V.;Valliappan, S.;Khalili, N.
    • Structural Engineering and Mechanics
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    • 제7권6호
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    • pp.533-550
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    • 1999
  • Optimal design of raft-pile foundations is examined by combining finite element technique and the optimization approach. The piles and soil medium are modeled by three dimensional solid elements while the raft is modelled by shell elements. Drucker-Prager criterion is adopted for the soil medium while the raft and the piles are assumed to be linear elastic. For the optimization process, the approximate semi-analytical method is used for calculating constraint sensitivities and a constraint approximation method which is a combination of the extended Bi-point approximation and Lagrangian polynomial approximation is used for predicting the behaviour of the constraints. The objective function of the problem is the volume of materials of the foundation while the design variables are raft thickness, pile length and pile spacing. The generalized reduced gradient algorithm is chosen for solving the optimization process. It is demonstrated that the method proposed in this study is promising for obtaining optimal design of raft-pile foundations without carrying out a large number of analyses. The results are also compared with those obtained from the previous study in which linear analysis was carried out.

A Methodology of Optimal Design for Solar Heating and Cooling System Using Simulation Tool

  • Lee, Dongkyu;Nam, Hyunmin;Lee, Byoungdoo
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.540-543
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    • 2015
  • Solar energy is one of the most important alternative energy sources which have been shown to meet high levels of heating and cooling demands in buildings. However, the efficiencies to satisfy these demands using solar energy significantly vary based on the characteristics of individual building. Therefore, this paper is focused on developing the methodology which can help to design optimal solar system for heating and cooling to be in cooperated within the existing buildings according to their load profiles. This research has established the Solar Heating and Cooling (SHC) system which is composed of collectors, absorption chiller, boiler and heat storage tank. Each component of SHC system is analyzed and made by means of Modelica Language and Pistache tool is verified the results. Sequential approximate optimization (SAO) and meta-models determined to 15 design parameters to optimize SHC system. Finally, total coefficient of performance (COP) of the entire SHC system is improved approximately 7.3% points compared to total COP of the base model of the SHC system.

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Design method of computer-generated controller for linear time-periodic systems

  • Jo, Jang-Hyen
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.225-228
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    • 1992
  • The purpose of this project is the presentation of new method for selection of a scalar control of linear time-periodic system. The approach has been proposed by Radziszewski and Zaleski [4] and utilizes the quadratic form of Lyapunov function. The system under consideration is assigned either in closed-loop state or in modal variables as in Calico, Wiesel [1]. The case of scalar control is considered, the gain matrix being assumed to be at worst periodic with the system period T, each element being represented by a Fourier series. As the optimal gain matrix we consider the matrix ensuring the minimum value of the larger real part of the two Poincare exponents of the system. The method, based on two-step optimization procedure, allows to find the approximate optimal gain matrix. At present state of art determination of the gain matrix for this case has been done by systematic numerical search procedure, at each step of which the Floquet solution must be found.

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Enhanced Genetic Programming Approach for a Ship Design

  • Lee, Kyung-Ho;Han, Young-Soo;Lee, Jae-Joon
    • Journal of Ship and Ocean Technology
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    • 제11권4호
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    • pp.21-28
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    • 2007
  • Recently the importance of the utilization of engineering data is gradually increasing. Engineering data contains the experiences and know-how of experts. Data mining technique is useful to extract knowledge or information from the accumulated existing data. This paper deals with generating optimal polynomials using genetic programming (GP) as the module of Data Mining system. Low order Taylor series are used to approximate the polynomial easily as a nonlinear function to fit the accumulated data. The overfitting problem is unavoidable because in real applications, the size of learning samples is minimal. This problem can be handled with the extended data set and function node stabilization method. The Data Mining system for the ship design based on polynomial genetic programming is presented.

전역-부분 근사화에 의한 부구조화 기반 구조재해석 (Substructuring-Based Structural Reanalysis by Global-Local Approximations)

  • 서상구;김경일;황충열;황진하
    • 전산구조공학
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    • 제9권1호
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    • pp.141-149
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    • 1996
  • 부구조화에 근거한 대형 구조의 효율적 근사재해석방법을 제시한다. 대형 구조시스템의 설계최적하에 있어서 가장 큰 문제는 반복되는 해석과 설계시에 드는 많은 계산비용 및 시간이다. 따라서 본 연구에서는 설계 최적화문제의 주요한 도구의 하나인 근사화기법에 근거한 몇가지 재해석방법을 비교.분석하여 효율적 구조재해석 방법을 제시하였다. 대형 구조에 대한 효율적 해석 방법의 하나인 부구조화의 틀에 테일러급수전개와 차원축소방법을 결합한 이 재해석기법은 반복되는 거동해석에 효율적일 뿐아니라, 설계민감도 벡터를 이용하기 때문에 최적설계에도 많은 잇점을 제공한다. 본 알고리즘을 트러스 구조에 적용하여 효율적 및 타당성을 검증하였다.

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비동기 DS/CDMA 시스템을 위한 연판정 다단 검출기의 최적 설계 (On optimal design of soft-decision multistage detectors for asynchronous DS/CDMA systems)

  • 고정훈;주정석;이용훈
    • 한국통신학회논문지
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    • 제22권9호
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    • pp.2035-2042
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    • 1997
  • 비동기 부호 분할 다중 접속(Code Division Multiple Access: CDMA) 시스템을 위한 다단(mutistage) 간섭 제거 검출기의 매 단에서 기존에 사용되어 온 경판정(hard decision)을 대신할 수 있는 연판정(soft decision) 함수의 설계를 고려한다. 특히, 평균 제곱 오류(mean square error: MSE)의 관점에서 최적인 시그모이드(sigmoid) 함수와 구현시 복잡도를 줄이면서 시그모이드 함수를 가장 잘 근사화하는 다단계 양자화기(multu-level quantizer)들을 유도한다. 다단 검출기의 매 단에서 이들 판정 함수들의 변수는 산출된 입력 특성에 의해 조정된다. 컴퓨터 모의 실험을 통하여 이들 연판정 함수를 갖는 다단 검출기가 경판정을 사용하는 경우보다 현저하게 성능을 향상시킴을 보인다.

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A response surface modelling approach for multi-objective optimization of composite plates

  • Kalita, Kanak;Dey, Partha;Joshi, Milan;Haldar, Salil
    • Steel and Composite Structures
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    • 제32권4호
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    • pp.455-466
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    • 2019
  • Despite the rapid advancement in computing resources, many real-life design and optimization problems in structural engineering involve huge computation costs. To counter such challenges, approximate models are often used as surrogates for the highly accurate but time intensive finite element models. In this paper, surrogates for first-order shear deformation based finite element models are built using a polynomial regression approach. Using statistical techniques like Box-Cox transformation and ANOVA, the effectiveness of the surrogates is enhanced. The accuracy of the surrogate models is evaluated using statistical metrics like $R^2$, $R^2{_{adj}}$, $R^2{_{pred}}$ and $Q^2{_{F3}}$. By combining these surrogates with nature-inspired multi-criteria decision-making algorithms, namely multi-objective genetic algorithm (MOGA) and multi-objective particle swarm optimization (MOPSO), the optimal combination of various design variables to simultaneously maximize fundamental frequency and frequency separation is predicted. It is seen that the proposed approach is simple, effective and good at inexpensively producing a host of optimal solutions.