• Proceedings of the KIEE Conference
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• 1997.07d
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• pp.1443-1445
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• 1997

This paper presents an analysing method to find out an optimum metal shape for insulation strength of SCI(Silicone Composite Insulator). Using finite element method, the interested parameters of the configuration such as a aspect of metal/silicone composite and a material properties are investigated and derived a thread of optimum design parameters.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.335-342
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• 2016

When dynamics changes occurred in an existing Bayesian Network (BN), the related parameters embedding on the BN have to be updated to new parameters adapting to changed patterns. In this case, these parameters have to be updated with the consideration of the causalities in the BN. This research suggests a framework for updating parameters dynamically using Expectation Maximization (EM) algorithm and Harmony Search (HS) algorithm among several Meta-Heuristics techniques. While EM is an effective algorithm for estimating hidden parameters, it has a limitation that the generated solution converges a local optimum in usual. In order to overcome the limitation, this paper applies HS for tracking the global optimum values of Maximum Likelihood Estimators (MLE) of parameters. The proposed method suggests a learning and propagation framework of BN with dynamic changes for overcoming disadvantages of EM algorithm and converging a global optimum value of MLE of parameters.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.79-93
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• 1999

The common accelerated life test(ALT) consists of test methods applying a constant stress, higher than the use condition stress, to items. There we, however, situations for which a progressive stress ALT, in which the stress on a test item is continuously increased with time, Is more convenient to perform testing and simpler in analyzing data than a constant stress ALT. When a product under constant stress s follows a Weibull distribution with parameters $\theta$(5) and $\beta$, maximum likelihood(ML) estimators of parameters involved in the model are obtained and their asymptotic distributions are derived under stress bounded ramp tests in which the stress is increased linearly from use condition stress to the stress upper bound. The optimum test plans are also found which minimize the asymptotic variance of the ML estimator of the log mean life at design constant stress. For selected values of the design parameters, tables useful for finding optimal test plans are given. The effect of the pre-estimates of design parameters is studied.

• Journal of the Korean Ceramic Society
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• v.24 no.2
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• pp.170-178
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• 1987

Changes of the properties of PECVD-SiN film with the variation of deposition process parameters were investigated and optimum process parameters were determined. The refractive index of the film increased with increasing substrate temperature and pressure, and decreasing rf-power, NH3/SiH4 gas ratio and total gas flow. BHF etch rate and deposition rate show a decreasing tendency with increasing refractive index. The step coverage of the film was not affected much by deposition rate and pressure, but improved apparently with increasing rf-power and NH3/SiH4 gas ratio. Also the optimum process parameters were determined by considering the characteristic properties as well as thickness uniformity of films. The refractive index of the film deposited under this condition was 2.06.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.123-128
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• 2002

The machining parameters for the wire electrical discharge machining(WEDM), including no load voltage, pulse-on time, pulse-off time, wire tension, water flow rata offset etc. should be chosen properly so that a better performance can be obtained An optimum selection of machining parameters relies heavily on the operators technologies and experience. This study presents a method by means of Taguchi method to select optimal machining parameter combination for an cutting speed or surface roughness. Experimental results demonstrate that the machining models are appropriate and the derived machining parameters satisfy the real requirements in notice.

• Communications for Statistical Applications and Methods
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• v.20 no.2
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• pp.137-145
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• 2013

The use of pooled standard deviation can reduce the efficiency loss in optimum allocation when strata standard deviations are estimated and several of them are equal. Also shown is that the pooled standard deviation is useful in optimum allocation under a multivariate setting. In addition to theoretical development, we provide the result of simulation study to support the theory.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.378-385
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• 2004

Viscous-driven pumping is a very promising type in microscale applications. However, there exist a few disadvantages such as low efficiency and small volume flow rate. In the present study, a pump with tandem rotating cylinders and its optimum synthesis are proposed fur enhancing pumping performance. First, using an unstructured grid CFD method, we investigate the effects of geometrical parameters and then the performance of the pump with tandem cylinders is evaluated. Next, an optimum design synthesis tool is constructed by combining the aforementioned CFD analysis model with the mathematical optimization model, namely, Modified Method of Feasible Directions (MMFD). This technique is used to optimize the geometrical parameters of the pump, fur maximizing pumping efficiency. From the optimization results, it is believed that the present optimum synthesis is robust and has a potential fur other microfluidic device design.

• Advances in nano research
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• v.14 no.2
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• pp.155-164
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• 2023

Grain size in sheet metals in one of the main parameters in determining formability. Grain size control in industry requires delicate process control and equipment. In the present study, effects of grain size on the formability of steel sheets is investigated. Experimental investigation of effect of grain size is a cumbersome method which due to existence of many other effective parameters are not conclusive in some cases. On the other hand, since the average grain size of a crystalline material is a statistical parameter, using traditional methods are not sufficient for find the optimum grain size to maximize formability. Therefore, design of experiment (DoE) and artificial intelligence (AI) methods are coupled together in this study to find the optimum conditions for formability in terms of grain size and to predict forming limits of sheet metals under bi-stretch loading conditions. In this regard, a set of experiment is conducted to provide initial data for training and testing DoE and AI. Afterwards, the using response surface method (RSM) optimum grain size is calculated. Moreover, trained neural network is used to predict formability in the calculated optimum condition and the results compared to the experimental results. The findings of the present study show that DoE and AI could be a great aid in the design, determination and prediction of optimum grain size for maximizing sheet formability.

• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.147-160
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• 2017

In this study, the optimum parameters of Tuned Mass Dampers (TMDs) are proposed using Gravity Search Algorithm (GSA) and Particle Swarm Optimization (PSO) to reduce the responses of the structures. A MATLAB program is developed to apply the new approach to the benchmark 10 and 40-story structures. The obtained results are compared to those of other optimization methods used in the literature to verify the developed code. To show the efficiency and accuracy of the proposed methods, nine far-field and near-field worldwide earthquakes are applied to the structures. The results reveal that in the 40-story structure, GSA algorithm can reduce the Relative Displacement (RD) and Absolute Acceleration (AA) up to 43% and 21%, respectively while the PSO decreases them by 50% and 25%, respectively. In contrast, both GSA and PSO algorithms reduce the RD and AA about 29% and 21% for the 10-story structure. Furthermore, using the proposed approach the required TMD parameters reduce by 47% and 63% in the 40 and 10-story buildings in comparison with the referenced ones. Result evaluation and related comparison indicate that these methods are more effective even by using smaller TMD parameters resulting in the reduction of acting force from TMD, having smaller stiffness and damping factors while being more cost effective due to its decreased parameters. In other words, the TMD with optimum parameters can play a positive role in both tall and typical structures.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.12 s.243
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• pp.1629-1637
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• 2005

Optimum sensitivity analysis (OSA) is the process to find the sensitivity of optimum solution with respect to the parameter in the optimization problem. The prevalent OSA methods calculate the optimum sensitivity as a post-processing. In this research, a simple technique is proposed to obtain optimum sensitivity as a result of the original optimization problem, provided that the optimum sensitivity of objective function is required. The parameters are considered as additional design variables in the original optimization problem. And then, it is endowed with equality constraints to penalize the additional variables. When the optimization problem is solved, the optimum sensitivity of objective function is simultaneously obtained as Lagrange multiplier. Several mathematical and engineering examples are solved to show the applicability and efficiency of the method compared to other OSA ones.