• 한국공작기계학회논문집
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• 제12권6호
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• pp.36-43
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• 2003

In machining of ceramic materials, they are very difficult-to cut materials because of there high strength and hardness. Machining of ceramics are characterized by cracking and brittle fracture. Generally, ceramics are machined using conventional method such as finding and polishing. However these processes are generally costly and have low MRR(material removal rate). This paper focuses on determining the optimal levels of process parameters for products with CNC machining center. For this purpose, the optimization of cutting parameters is performed based on experimental design method. A design and analysis of experiments is conducted to study the effects of these parameters on the surface roughness by using the S/N ratio, analysis of ANOVA and F-test. Cutting parameters, namely, cutting speed, feed and depth of cut are optimized with consideration of the surface roughness.

• 한국정밀공학회지
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• 제26권6호
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• pp.122-130
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• 2009

The analysis of human movement requires the knowledge of the Hill type muscle parameters, the muscle-tendon and moment arm length change as a function of joint angles. However, values of a subject's muscle parameters are very difficult to identify. It turns out from a sensitivity analysis that the tendon slack length and maximum muscle force are the two critical parameters among the Hill-type muscle model. Therefore, it could be claimed that the variation of the tendon slack length and maximum muscle force from the Delp's reference data will change the muscle characteristics of a subject remarkably. A numeric optimization method to search these tendon parameters specific to a subject is proposed, and the accuracy of the developed algorithm is evaluated through a numerical simulation.

• International Journal of Fluid Machinery and Systems
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• 제2권4호
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• pp.278-285
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• 2009

Operational modal analysis (OMA) allows modal parameters, such as natural frequencies and damping, to be estimated solely from data collected during operation. However, a main shortcoming of these methods resides in the evaluation of the accuracy of the results. This paper will explore the uncertainty and possible variations in the estimates of modal parameters for different operating conditions. Two algorithms based on the Least Square Complex Exponential (LSCE) method will be used to estimate the modal parameters. The uncertainties will be calculated using a Monte-Carlo approach with the hypothesis of constant modal parameters at a given operating condition. In collaboration with Andritz-Hydro Ltd, data collected on two different stay vanes from an Andritz-Hydro Ltd Francis turbine will be used. This paper will present an overview of the procedure and the results obtained.

• Journal of the Korean Statistical Society
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• 제31권1호
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• pp.63-75
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• 2002

Most attempts at Bayesian analysis of neural networks involve hierarchical modeling. We believe that similar results can be obtained with simpler models that require less computational effort, as long as appropriate restrictions are placed on parameters in order to ensure propriety of posterior distributions. In particular, we adopt a model first introduced by Lee (1999) that utilizes an improper prior for all parameters. Straightforward Gibbs sampling is possible, with the exception of the bias parameters, which are embedded in nonlinear sigmoidal functions. In addition to the problems posed by nonlinearity, direct sampling from the posterior distributions of the bias parameters is compounded due to the duplication of hidden nodes, which is a source of multimodality. In this regard, we focus on sampling from the marginal posterior distribution of the bias parameters with Markov chain Monte Carlo methods that combine traditional Metropolis sampling with a slice sampler described by Neal (1997, 2001). The methods are illustrated with data examples that are largely confined to the analysis of nonparametric regression models.

• 소성∙가공
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• 제31권2호
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• pp.81-88
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• 2022

Numerical analysis and dynamic material properties are required to analyze the behavior of workpiece during an electrohydraulic forming (EHF) process. In this study, EHF experiments were conducted under three conditions (6, 7, 8 kV). Dynamic material properties of Al 5052-H34 were inversely estimated through an ANN (Artificial Neural Network) model constructed based on LS-Dyna analysis results. Parameters of Cowper-Symonds constitutive equation, C and p, were used to implement dynamic material properties. By comparing experimental results of three conditions with ANN model results, optimized parameters were obtained. To determine the reliability of the derived parameters, experimental results, LS-Dyna analysis results, and ANN results of three conditions were compared using MSE and SMAPE. Valid parameters were obtained because values of indicators were within confidence intervals.

• Structural Engineering and Mechanics
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• 제21권2호
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• pp.185-204
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• 2005

Variations in system parameters due to uncertainties may result in system performance deterioration. Uncertainties in modeling of structures are often considered to ensure that control system is robust with respect to response errors. Hence, the uncertain concept plays an important role in vibration control of the engineering structures. The paper discusses the robustness of the stability of vibration control systems with uncertain parameters. The vibration control problem of an uncertain system is approximated by a deterministic one. The uncertain parameters are described by interval variables. The uncertain state matrix is constructed directly using system physical parameters and avoided to use bounds in Euclidean norm. The feedback gain matrix is determined based on the deterministic systems, and then it is applied to the actual uncertain systems. A method to calculate the upper and lower bounds of eigenvalues of the close-loop system with uncertain parameters is presented. The lower bounds of eigenvalues can be used to estimate the robustness of the stability the controlled system with uncertain parameters. Two numerical examples are given to illustrate the applications of the present approach.

• Nuclear Engineering and Technology
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• 제33권4호
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• pp.409-422
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• 2001

The dynamic character of a system of the governing differential equations for the one- dimensional two-fluid model, where the momentum flux parameters are employed to consider the velocity and void fraction distribution in a flow channel, is investigated. In response to a perturbation in the form of a＇traveling wave, a linear stability analysis is peformed for the governing differential equations. The expression for the growth factor as a function of wave number and various flow parameters is analytically derived. It provides the necessary and sufficient conditions for the stability of the one-dimensional two-fluid model in terms of momentum flux parameters. It is demonstrated that the one-dimensional two-fluid model employing the physical momentum flux parameters for the whole range of dispersed flow regime, which are determined from the simplified velocity and void fraction profiles constructed from the available experimental data and $C_{o}$ correlation, is stable to the linear perturbations in all wave-lengths. As the basic form of the governing differential equations for the conventional one-dimensional two-fluid model is mathematically ill posed, it is suggested that the velocity and void distributions should be properly accounted for in the one-dimensional two-fluid model by use of momentum flux parameters.s.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 춘계학술대회 논문집
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• pp.285-288
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• 2007

The use of commercial finite element analysis software to perform the entire process analysis and springback analysis has increased fast for last decade. Pamstamp2G is one of commercial software to be used widely in the world but it has still not been perfected in the springback prediction accuracy. We must select the combination of input parameters for the highest springback prediction accuracy in Pamstamp2G because springback prediction accuracy is sensitive to input parameters. Then we study the affect of input parameters to use member part for acquiring high springback prediction accuracy in Pamstamp2G. First, we choose important four parameters which are adaptive mesh level at drawing stage and cam flange stage, Gauss integration point number through the thickness and cam offset on basis of experiment. Second, we make a orthogonal array table L82[(7)] which is consist of 8 cases to be combined 4 input parameters, compare to tryout result and select main factors after analyzing affect factors of input parameters by Taguchi's method in 6 sigma. Third, we simulate after changing more detail the conditions of parameters to have big affect. At last, we find the best combination of input parameters for the highest springback prediction accuracy in Pamstamp2G. The results of the study provide the selection of input parameters to Pamstamp2G users who want to Increase the springback prediction accuracy.

• 한국항공우주학회지
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• 제38권2호
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• pp.188-194
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• 2010

본 연구에서는 영상레이다 (SAR)의 영상품질 분석 변수 및 확장 보간법, 배경레벨 제거 기법 등의 분석 기법을 정의하고 이를 바탕으로 SAR 영상품질 분석 툴을 개발하였다. 개발된 SAR 영상품질 분석 툴은 크게 점 표적 분석 (PTA) 모듈, 분산 표적 분석 (DTA) 모듈, 모호성 분석 (AMA) 모듈, NESZ 분석 (NESZA) 모듈, 총 4개의 주요 모듈로 구성된다. 개발 툴은 SAR 제품 파일 포맷에서 다양한 시스템 파라미터 추출하고, 이를 바탕으로 임펄스 응답 특성, 방사 성능, 모호성 등의 SAR 영상 품질 변수를 계산한다.

• 한국화재소방학회논문지
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• 제26권2호
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• pp.40-52
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• 2012

본 논문에서는 원자력발전소의 모터제어반 스위치기어실 화재 모델링에 대한 입력변수 불확실성 분석을 수행하였다. 화재모델링은 FDS 5.5를 사용하였고 FDS 입력변수 램던 샘플링은 라틴하이퍼쿠브 몬테칼로 방법을 이용하였다. 본 연구에서 수행한 입력변수 불확실성 분석 결과를 비교하기 위해 NUREG-1934의 화재모델링 결정론적 불확실성 분석과 민감도 분석 방법을 이용한 분석도 수행하였다. 분석결과, 본 연구의 모터제어반 스위치 기어룸 화재 모델링에 대한 입력변수 불확실성 분석방법이 NUREG-1934의 방법보다 보수적인 결과를 얻을 수 있음을 확인하였다.