• Title/Summary/Keyword: optimization of experiments

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Parameters identification of fractional models of viscoelastic dampers and fluids

  • Lewandowski, Roman;Slowik, Mieczyslaw;Przychodzki, Maciej
    • Structural Engineering and Mechanics
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    • v.63 no.2
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    • pp.181-193
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    • 2017
  • An identification method for determination of the parameters of the rheological models of dampers made of viscoelastic material is presented. The models have two, three or four parameters and the model equations of motion contain derivatives of the fractional order. The results of dynamical experiments are approximated using the trigonometric function in the first part of the procedure while the model parameters are determined as the solution to an appropriately defined optimization problem. The particle swarm optimization method is used to solve the optimization problem. The validity and effectiveness of the suggested identification method have been tested using artificial data and a set of real experimental data describing the dynamic behavior of damper and a fluid frequently used in dampers. The influence of a range of excitation frequencies used in experiments on results of identification is also discussed.

High-velocity powder compaction: An experimental investigation, modelling, and optimization

  • Mostofi, Tohid Mirzababaie;Sayah-Badkhor, Mostafa;Rezasefat, Mohammad;Babaei, Hashem;Ozbakkaloglu, Togay
    • Structural Engineering and Mechanics
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    • v.78 no.2
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    • pp.145-161
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    • 2021
  • Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

The Optimization Analysis for the Selection of Cutting Parameters in Turning Operation

  • Hong, Min-Sung;Lian, Zhe-Man
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.10 no.3
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    • pp.97-103
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    • 2001
  • This paper has focused on the Optimization of the cutting parameters for urning operation based on the Taguchi method. Four cutting parameters. nemely, cutting speed, feed depth of cut and nose radius are optimized with consideration of the surface roughness. The design and analysis of experiments are conducted to study the performance characteristic. The effects of these parameters on the surface roughness have been investigated using signal-to-noise(S/N) ratio and analy-sis of variance(ANOVA). The experiments have been performed using coated tungsten carbide inserts without any cutting fluid. Experimental results illustrate the effectiveness of this approach.

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Robust Optimization of Automotive Seat by Using Constraint Response Surface Model (제한조건 반응표면모델에 의한 자동차 시트의 강건최적설계)

  • 이태희;이광기;구자겸;이광순
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.04b
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    • pp.168-173
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    • 2000
  • Design of experiments is utilized for exploring the design space and for building response surface models in order to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient means to rapidly model the trade-off among many conflicting goals. In robust design, it is important not only to achieve robust design objectives but also to maintain the robustness of design feasibility under the effects of variations, called uncertainties. However, the evaluation of feasibility robustness often needs a computationally intensive process. To reduce the computational burden associated with the probabilistic feasibility evaluation, the first-order Taylor series expansions are used to derive individual mean and variance of constraints. For robust design applications, these constraint response surface models are used efficiently and effectively to calculate variances of constraints due to uncertainties. Robust optimization of automotive seat is used to illustrate the approach.

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Optimization of Lactic Acid Production in SSF by Lactobacillus amylovorus NRRL B-4542 Using Taguchi Methodology

  • Nagarijun Pyde Acharya;Rao Ravella Sreenivas;Rajesham Swargam;Rao Linga Venkateswar
    • Journal of Microbiology
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    • v.43 no.1
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    • pp.38-43
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    • 2005
  • Lactic acid production parameter optimization using Lactobacillus amylovorus NRRL B-4542 was performed using the design of experiments (DOE) available in the form of an orthogonal array and a software for automatic design and analysis of the experiments, both based on Taguchi protocol. Optimal levels of physical parameters and key media components namely temperature, pH, inoculum size, moisture, yeast extract, $MgSO_4{\cdot}7H_20$, Tween 80, and corn steep liquor (CSL) were determined. Among the physical parameters, temperature contributed higher influence, and among media components, yeast extract, $MgSO_4{\cdot}7H_20$, and Tween 80 played important roles in the conversion of starch to lactic acid. The expected yield of lactic acid under these optimal conditions was 95.80% and the actual yield at optimum conditions was 93.50%.

The Study for Construction of the Improved Optimization Algorithm by the Response Surface Method (반응표면법의 향상된 최적화 알고리즘 구성에 관한 연구)

  • Park, J.S.;Lee, D.J.;Im, J.B.
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.13 no.3
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    • pp.22-33
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    • 2005
  • Response Surface Method (RSM) constructs approximate response surfaces using sample data from experiments or simulations and finds optimum levels of process variables within the fitted response surfaces of the interest region. It will be necessary to get the most suitable response surface for the accuracy of the optimization. The application of RSM plan experimental designs. The RSM is used in the sequential optimization process. The first goal of this study is to improve the plan of central composite designs of experiments with various locations of axial points. The second is to increase the optimal efficiency applying a modified method to update interest regions.

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Optimization of a Gate Valve using Orthogonal Array and Kriging Model (직교배열표와 크리깅모델을 이용한 게이트밸브의 최적설계)

  • Kang Jin;Lee Jong-Mun;Kang Jung-Ho;Park Hee-Chun;Park Young-Chul
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.8 s.185
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    • pp.119-126
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    • 2006
  • Kriging model is widely used as design DACE(analysis and computer experiments) model in the field of engineering design to accomplish computationally feasible design optimization. In this paper, the optimization of gate valve was performed using Kriging based approximation model. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. In addition, we describe the definition, the prediction function and the algorithm of Kriging method and examine the accuracy of Kriging by using validation method.

The optimization of suspension system for high performance of Korean Tilling Train (한국형 틸팅 열차의 성능 향상을 위한 현가장치 최적화)

  • Lee, Su-In;Park, Tae-Won;Yoon, Ji-Won
    • Proceedings of the KSR Conference
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    • 2009.05a
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    • pp.1224-1228
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    • 2009
  • The korean tilting train can increase the whole operating speed at a curved railroad, reducing the lateral acceleration with the tilting mechanism unlike the train developed before. However, increasing operating speed on the curved section, may cause safety problem of train travel. In general, a suspension system has important effects on driving safety. Therefore, optimization of suspension system is necessary to secure the safety of the tilting train. In this study, the tilting train suspension system has been optimized using Design of Experiments (DOE). First, the design parameter is selected using sensitivity analysis. A lateral acceleration which affects on the driving safety is chosen as the objective function. And the Design of Experiments (DOE) is used for optimization. As a result, new design parameters which show better performance than the existing suspension system has been suggested.

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A Clustering Tool Using Particle Swarm Optimization for DNA Chip Data

  • Han, Xiaoyue;Lee, Min-Soo
    • Genomics & Informatics
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    • v.9 no.2
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    • pp.89-91
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    • 2011
  • DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.

Numerical Experiments for the Optimization of the Flow Path through a Cross-Flow Fan (횡류팬 유로최적화를 위한 수치실험)

  • Jun, Yong-Du;Lee, Jong-Soo
    • 유체기계공업학회:학술대회논문집
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    • 2002.12a
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    • pp.147-151
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    • 2002
  • Cross flow fan system is widely used for various applications, especially for the air-moving device of heaters, air-conditioners, and air-curtains. Although there are efforts for the optimization of cross-flow fan flow path with different methods of approach, it is still being investigated by many researchers through experimentally and/or theoretically, because the flow pattern of the cross flow fan is not stereotyped. This paper presents some results from numerical experiments for the optimization of the flow path through a cross-flow fan to be applied to indoor wall-mounted room heater. Two dimensional analysis has been applied to a specific fan system including inlet and diffuser outlet. Flow characteristics art presented and discussed for two different flow path at three different operating conditions represented by rotational speed(800, 1,000, 1,200 rpm) of the In. According to the simulated results for the specific fan system under consideration, it could be found that the flow pattern resembles each other at different rotational speed (to say from 800 rpm to 1,200 rpm) for a fixed flow path, while the secondary flows mostly absorbs the speed effects. By changing the flow path significant increase in volume flow rate is estimated upto 2.65 at the same rotational speed. According to the present experience, fan flow path design can be performed more efficiently by incorporating this type of numerical experiments combined with the model tests.

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