• Title/Summary/Keyword: optimization approach

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Reliability-Based Design Optimization of Slider Air Bearings

  • Yoon, Sang-Joon;Choi, Dong-Hoon
    • Journal of Mechanical Science and Technology
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    • v.18 no.10
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    • pp.1722-1729
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    • 2004
  • This paper presents a design methodology for determining configurations of slider air bearings considering the randomness of the air-bearing surface (ABS) geometry by using the iSIGHT. A reliability-based design optimization (RBDO) problem is formulated to minimize the variations in the mean values of the flying heights from a target value while satisfying the desired probabilistic constraints keeping the pitch and roll angles within a suitable range. The reliability analysis is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the reliability constraints affected by the random variables. Reliability constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the RBDO are listed in comparison with the values of the initial design and the results of the deterministic optimization, respectively. To show the effectiveness of the proposed approach, the reliability analyses are simply carried out by using the mean value first-order second-moment (MVFO) method. The Monte Carlo simulation of the RBDO's results is also performed to estimate the efficiency of the proposed approach. Those results are demonstrated to satisfy all the desired probabilistic constraints, where the target reliability level for constraints is defined as 0.8.

An Interactive Approach to Multiple Response Optimization (다중반응최적화를 위한 상호교호적 접근법)

  • Lee, Pyoungsoo;Park, K. Sam
    • Journal of the Korean Operations Research and Management Science Society
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    • v.40 no.3
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    • pp.49-61
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    • 2015
  • We study the problem of multiple response optimization (MRO) and focus on the selection of input levels which will produce desirable output quality. We propose an interactive multiple objective optimization approach to the input design. The earlier interactive methods utilized for MRO communicate with the decision maker only using the response variable values, in order to improve the current response values, thereby resulting in the corresponding design solution automatically. In their interaction steps of preference articulation, no account is taken of any active changes in design variable values. On the contrary, our approach permits the decision maker to change the design variable values in its interaction stage, which makes possible the consideration of the preference or economics of the design variable side. Using some typical value functions, we also demonstrate that our method converges reasonably well to the known optimal solutions.

Optimal design of plane frame structures using artificial neural networks and ratio variables

  • Kao, Chin-Sheng;Yeh, I-Cheng
    • Structural Engineering and Mechanics
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    • v.52 no.4
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    • pp.739-753
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    • 2014
  • There have been many packages that can be employed to analyze plane frames. However, because most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we proposed a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integrative environment. The DAMDO methodology employs neural networks to integrate structural analysis package and optimization package so as not to need directly to integrate these two packages. The key problem of the DAMDO approach is how to generate a set of reasonable random designs in the first phase. According to the characteristics of optimized plane frames, we proposed the ratio variable approach to generate them. The empirical results show that the ratio variable approach can greatly improve the accuracy of the neural networks, and the plane frame optimization problems can be solved by the DAMDO methodology.

A Study on Feedrate Optimization System for Cutting Force Optimization (절삭력 최적화를 위한 이송속도 제어 시스템에 관한 연구)

  • 김성진;정영훈;조동우
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.135-140
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    • 2002
  • Studies on the optimization of machining process can be divided into two different approaches: off-line feedrate scheduling and adaptive control. Each approach possesses its respective strong and weak points compared to each other. That is, each system can be complementary to the other. In this regard, a combined system, which is a feedrate control system for cutting force optimization, was proposed in this paper to make the best of each approach. Experimental results show that the proposed system could overcome the weak points of two systems.

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Validation of a Robust Flutter Prediction by Optimization

  • Chung, Chan-Hoon;Shin, Sang-Joon
    • International Journal of Aeronautical and Space Sciences
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    • v.13 no.1
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    • pp.43-57
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    • 2012
  • In a modern aircraft, there are many variations in its mass, stiffness, and aerodynamic characteristics. Recently, an analytical approach was proposed, and this approach uses the idea of uncertainty to find out the most critical flight flutter boundary due to the variations in such aerodynamic characteristics. An analytical method that has been suggested to predict robust stability is the mu method. We previously analyzed the robust flutter boundary by using the mu method, and in that study, aerodynamic variations in the Mach number, atmospheric density, and flight speed were taken into consideration. The authors' previous attempt and the results are currently quoted as varying Mach number mu analysis. In the author's previous method, when the initial flight conditions were located far from the nominal flutter boundary, conservative predictions were obtained. However, relationships among those aerodynamic parameters were not applied. Thus, the varying Mach number mu analysis results required validation. Using an optimization approach, the varying Mach number mu analysis was found out to be capable of capturing a reasonable robust flutter boundary, i.e., with a low percentage difference from boundaries that were obtained by optimization. Regarding the optimization approach, a discrete nominal flutter boundary is to be obtained in advance, and based on that boundary, an interpolated function was established. Thus, the optimization approach required more computational effort for a larger number of uncertainty variables. And, this produced results similar to those from the mu method which had lower computational complexity. Thus, during the estimation of robust aeroelastic stability, the mu method was regarded as more efficient than the optimization method was. The mu method predicts reasonable results when an initial condition is located near the nominal flutter boundary, but it does not consider the relationships that are among the aerodynamic parameters, and its predictions are not very accurate when the initial condition is located far from the nominal flutter boundary. In order to provide predictions that are more accurate, the relationships among the uncertainties should also be included in the mu method.

Economic Power Dispatch with Valve Point Effects Using Bee Optimization Algorithm

  • Kumar, Rajesh;Sharma, Devendra;Kumar, Anupam
    • Journal of Electrical Engineering and Technology
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    • v.4 no.1
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    • pp.19-27
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    • 2009
  • This paper presents a newly developed optimization algorithm, the Bee Optimization Algorithm (BeeOA), to solve the economic power dispatch (EPD) problem. The authors have developed a derivative free and global optimization technique based on the working of the honey bee. The economic power dispatch problem is a nonlinear constrained optimization problem. Classical optimization techniques fail to provide a global solution and evolutionary algorithms provide only a good enough solution. The proposed approach has been examined and tested on two test systems with different objectives. A simple power dispatch problem is tested first on 6 generators and then the algorithm is demonstrated on 13 thermal unit systems whose incremental fuel cost function takes into account the value point loading effect. The results are promising and show the effectiveness and robustness of the proposed approach over recently reported methods.

Multi-Objective Pareto Optimization of Parallel Synthesis of Embedded Computer Systems

  • Drabowski, Mieczyslaw
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.304-310
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    • 2021
  • The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

Shape Optimization of Truss Structures with Multiobjective Function by α -Cut Approach (α -절단법에 의한 다목적함수를 갖는 트러스 구조물의 형상최적화)

  • Yang, Chang Yong;Lee, Gyu Won
    • Journal of Korean Society of Steel Construction
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    • v.9 no.3 s.32
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    • pp.457-465
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    • 1997
  • The Shape optimization makes it possible to reduce the weight of structure and cost then member sizing optimization. A vast amount of imprecise information is existed in constraints of the optimum design. It is very difficult and sometimes confusing to describe and to deal with the several criteria which contain fuzzy degrees of relatives importance. This paper proposed weighting strategies in the multiobjective shape optimization of fuzzy structural system by ${\alpha}$-cut approach. The algorithm in this research is numerically tested for 2-bar truss structure. The result show that. the user can choose the one optimum solution in practices as obtaining the optimum solutions according to the ${\alpha}$-cut approach, weight of volume and displacement.

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Reliability-Based Topology Optimization Using Performance Measure Approach (성능함수법을 이용한 신뢰성기반 위상 최적설계)

  • Ahn, Seung-Ho;Cho, Seon-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.1
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    • pp.37-43
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    • 2010
  • In this paper, a reliability-based design optimization is developed for the topology design of linear structures using a performance measure approach. Spatial domain is discretized using three dimensional Reissner-Mindlin plate elements and design variable is taken as the material property of each element. A continuum based adjoint variable method is employed for the efficient computation of sensitivity with respect to the design and random variables. The performance measure approach of RBDO is employed to evaluate the probabilistic constraints. The topology optimizationproblem is formulated to have probabilistic displacement constraints. The uncertainties such as material property and external loads are considered. Numerical examples show that the developed topology optimization method could effectively yield a reliable design, comparing with the other methods such as deterministic, safety factor, and worst case approaches.

MULTI-STAGE AERODYNAMIC DESIGN OF AIRCRAFT GEOMETRIES BY KRIGING-BASED MODELS AND ADJOINT VARIABLE APPROACH (Kriging 기반 모델과 매개변수(Adjoint Variable)법을 이용한 항공기형상의 2단계 공력최적설계)

  • Yim, J.W.;Lee, B.J.;Kim, C.
    • 한국전산유체공학회:학술대회논문집
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    • 2009.04a
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    • pp.57-65
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    • 2009
  • An efficient and high-fidelity design approach for wing-body shape optimization is presented. Depending on the size of design space and the number of design of variable, aerodynamic shape optimization process is carried out via different optimization strategies at each design stage. In the first stage, global optimization techniques are applied to planform design with a few geometric design variables. In the second stage, local optimization techniques are used for wing surface design with a lot of design variables to maintain a sufficient design space with a high DOF (Degree of Freedom) geometric change. For global optimization, Kriging method in conjunction with Genetic Algorithm (GA) is used. Asearching algorithm of EI (Expected Improvement) points is introduced to enhance the quality of global optimization for the wing-planform design. For local optimization, a discrete adjoint method is adopted. By the successive combination of global and local optimization techniques, drag minimization is performed for a multi-body aircraft configuration while maintaining the baseline lift and the wing weight at the same time. Through the design process, performances of the test models are remarkably improved in comparison with the single stage design approach. The performance of the proposed design framework including wing planform design variables can be efficiently evaluated by the drag decomposition method, which can examine the improvement of various drag components, such as induced drag, wave drag, viscous drag and profile drag.

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