• Title/Summary/Keyword: performance-based optimization

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Design Optimization of a Channel Roughened by Dimples Using Weighted Average Surrogate Model (가중평균 대리모델을 사용한 딤플 유로의 최적설계)

  • Lee, Ki-Don;Kim, Kwang-Yong
    • The KSFM Journal of Fluid Machinery
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    • v.11 no.1
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    • pp.52-60
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    • 2008
  • Staggered dimples printed on opposite walls of an internal cooling channel are formulated numerically and optimized to enhance heat transfer performance. Nusselt number and friction factor based objectives are considered and a weighted average surrogate model is used to approximate the data generated by numerical simulation. The dimpled channel shape is defined by three geometric design variables, and the design point within design space are selected using Latin hypercube sampling. A weighted-sum method for multi-objective optimization is applied to integrate multiple objectives into a single objective. By the optimization, the objective function value is improved largely and heat transfer rate is increase much higher than pressure loss increase due to shape deformation. Channel with vertically non-symmetric optimum dimples is tested and found that the best appears if dimples on opposite wall are displaced by one quarter of dimple spacing.

Multicriteria Optimization of Spindle Units

  • Lim Sang-Heon;Lee Choon-Man;Zverev Igor Aexeevich
    • International Journal of Precision Engineering and Manufacturing
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    • v.7 no.4
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    • pp.57-62
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    • 2006
  • The quality of precision spindle units (S/Us) running on rolling bearings depends strongly on their structural parameters, such as the configuration and geometry of the S/U elements and bearing preloads. When S/Us are designed, their parameters should be optimized to improve the performance characteristics. However, it is practically impossible to state perfectly a general criterion function for S/U quality. Therefore, we propose to use a multicriteria optimization based on the parameter space investigation (PSI) method We demonstrate the efficiency of the proposed method using the optimization results of high-speed S/Us.

Robust design of liquid column vibration absorber in seismic vibration mitigation considering random system parameter

  • Debbarma, Rama;Chakraborty, Subrata
    • Structural Engineering and Mechanics
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    • v.53 no.6
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    • pp.1127-1141
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    • 2015
  • The optimum design of liquid column dampers in seismic vibration control considering system parameter uncertainty is usually performed by minimizing the unconditional response of a structure without any consideration to the variation of damper performance due to uncertainty. However, the system so designed may be sensitive to the variations of input system parameters due to uncertainty. The present study is concerned with robust design optimization (RDO) of liquid column vibration absorber (LCVA) considering random system parameters characterizing the primary structure and ground motion model. The RDO is obtained by minimizing the weighted sum of the mean value of the root mean square displacement of the primary structure as well as its standard deviation. A numerical study elucidates the importance of the RDO procedure for design of LCVA system by comparing the RDO results with the results obtained by the conventional stochastic structural optimization procedure and the unconditional response based optimization.

A Biologically Inspired Intelligent PID Controller Tuning for AVR Systems

  • Kim Dong-Hwa;Cho Jae-Hoon
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.624-636
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    • 2006
  • This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

Robust Predictive Feedback Control for Constrained Systems

  • Giovanini, Leonardo;Grimble, Michael
    • International Journal of Control, Automation, and Systems
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    • v.2 no.4
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    • pp.407-422
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    • 2004
  • A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

Optical Misalignment Cancellation via Online L1 Optimization (온라인 L1 최적화를 통한 탐색기 비정렬 효과 제거 기법)

  • Kim, Jong-Han;Han, Yudeog;Whang, Ick Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.7
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    • pp.1078-1082
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    • 2017
  • This paper presents an L1 optimization based filtering technique which effectively eliminates the optical misalignment effects encountered in the squint guidance mode with strapdown seekers. We formulated a series of L1 optimization problems in order to separate the bias and the gradient components from the measured data, and solved them via the alternating direction method of multipliers (ADMM) and sparse matrix decomposition techniques. The proposed technique was able to rapidly detect arbitrary discontinuities and gradient changes from the measured signals, and was shown to effectively cancel the undesirable effects coming from the seeker misalignment angles. The technique was implemented on embedded flight computers and the real-time operational performance was verified via the hardware-in-the-loop simulation (HILS) tests in parallel with the automatic target recognition algorithms and the intra-red synthetic target images.

Numerical Optimization of the Turbine Blade Leaning Angle Using the Parallel Genetic Algorithm

  • Lee, Eun-Seok;Jeong, Yong-Hyun;Park, Soon-Young
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.686-689
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    • 2008
  • The leaning angle optimization of turbine blade using the genetic algorithm was conducted in this paper. The calculation CFD technique was based upon the Diagonalized Alternating Directional Implicit scheme(DADI) with algebraic turbulence modeling. The leaning angle of VKI turbine blade was represented using B-spline curve. The control points are the design variable. Genetic algorithm was taken into account as an optimization tool. The objective was to minimize the total pressure loss. The optimized final geometry shows the better aerodynamic performance compared with the initial turbine blade.

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Analysis and optimal design of fiber-reinforced composite structures: sail against the wind

  • Nascimbene, R.
    • Wind and Structures
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    • v.16 no.6
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    • pp.541-560
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    • 2013
  • The aim of the paper is to use optimization and advanced numerical computation of a sail fiber-reinforced composite model to increase the performance of a yacht under wind action. Designing a composite-shell system against the wind is a very complex problem, which only in the last two decades has been approached by advanced modeling, optimization and computer fluid dynamics (CFDs) based methods. A sail is a tensile structure hoisted on the rig of a yacht, inflated by wind pressure. Our objective is the multiple criteria optimization of a sail, the engine of a yacht, in order to obtain the maximum thrust force for a given load distribution. We will compute the best possible yarn thickness orientation and distribution in order to minimize the total fiber volume with some displacement constraints and in order to leave the most uniform stress distribution over the whole structure. In this paper our attention will be focused on computer simulation, modeling and optimization of a sail-shape mathematical model in different regatta and wind conditions, with the purpose of improving maneuverability and speed made good.

An Algorithm for Bit Error Rate Monitoring and Adaptive Decision Threshold Optimization Based on Pseudo-error Counting Scheme

  • Kim, Sung-Man
    • Journal of the Optical Society of Korea
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    • v.14 no.1
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    • pp.22-27
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    • 2010
  • Bit error rate (BER) monitoring is the ultimate goal of performance monitoring in all digital transmission systems as well as optical fiber transmission systems. To achieve this goal, optimization of the decision threshold must also be considered because BER is dependent on the level of decision threshold. In this paper, we analyze a pseudo-error counting scheme and propose an algorithm to achieve both BER monitoring and adaptive decision threshold optimization in optical fiber transmission systems. To verify the effectiveness of the proposed algorithm, we conduct computer simulations in both Gaussian and non-Gaussian distribution cases. According to the simulation results, BER and the optimum decision threshold can be estimated with the errors of < 20% and < 10 mV, respectively, within 0.1-s processing time in > 40-Gb/s transmission systems.

Hyper-parameter Optimization for Monte Carlo Tree Search using Self-play

  • Lee, Jin-Seon;Oh, Il-Seok
    • Smart Media Journal
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    • v.9 no.4
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    • pp.36-43
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    • 2020
  • The Monte Carlo tree search (MCTS) is a popular method for implementing an intelligent game program. It has several hyper-parameters that require an optimization for showing the best performance. Due to the stochastic nature of the MCTS, the hyper-parameter optimization is difficult to solve. This paper uses the self-playing capability of the MCTS-based game program for optimizing the hyper-parameters. It seeks a winner path over the hyper-parameter space while performing the self-play. The top-q longest winners in the winner path compete for the final winner. The experiment using the 15-15-5 game (Omok in Korean name) showed a promising result.