• Title/Summary/Keyword: Parameter study

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A Study on the Regeneration Performance of DPF using Lumped Parameter Model (총괄 변수 모델을 이용한 DPF 재생 성능에 관한 연구)

  • Chon, Mun Soo
    • Journal of Institute of Convergence Technology
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    • v.1 no.1
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    • pp.41-47
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    • 2011
  • With the world-wide demand on the emission minimization, the needs on the diesel aftertreatment devices with high efficiency are also increasing. In order to effectively develop or design a high-performance diesel particulate filter, a clear understanding on the deposition and regeneration mechanism is required. In the present study, a theory on the lumped parameter model for wall-flow type diesel particulate filters is described focusing on the deposition efficiency, pressure drop inside the filter. The fourth order explicit Runge-Kutta method is utilized for the mass flow rate computation. Engine operation modes with controlled and uncontrolled regeneration options are selected. The computational lumped parameter model is validated by comparing the computed results with the measured data.

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Hull Form Optimization Based on From Parameter Design (Form Parameter Design 을 이용한 선형최적화)

  • Lee, Yeon-Seung;Choi, Young-Bok
    • Journal of the Society of Naval Architects of Korea
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    • v.46 no.6
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    • pp.562-568
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    • 2009
  • Hull form generation and variation methods to be mainly discussed in this study are based on the fairness optimized B-Spline form parameter curves (FOBFC). These curves can be used both as indirect modification function for variation and as geometric entities for hull form generation. The flexibility and functionality of geometric control technique play the most important role for the success of hull form optimization. This study shows the hydrodynamic optimization process and the characteristics of optimum design hull forms of a 14,000TEU containership and 60K LPG carrier. SHIPFLOW has been used as a CFD solver and FS-Framework as a geometric modeler and optimizer.

ESTIMATION ALGORITHM FOR PHYSICAL PARAMETERS IN A SHALLOW ARCH

  • Gutman, Semion;Ha, Junhong;Shon, Sudeok
    • Journal of the Korean Mathematical Society
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    • v.58 no.3
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    • pp.723-740
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    • 2021
  • Design and maintenance of large span roof structures require an analysis of their static and dynamic behavior depending on the physical parameters defining the structures. Therefore, it is highly desirable to estimate the parameters from observations of the system. In this paper we study the parameter estimation problem for damped shallow arches. We discuss both symmetric and non-symmetric shapes and loads, and provide theoretical and numerical studies of the model behavior. Our study of the behavior of such structures shows that it is greatly affected by the existence of critical parameters. A small change in such parameters causes a significant change in the model behavior. The presence of the critical parameters makes it challenging to obtain good estimation. We overcome this difficulty by presenting the Parameter Estimation Algorithm that identifies the unknown parameters sequentially. It is shown numerically that the algorithm achieves a successful parameter estimation for models defined by arbitrary parameters, including the critical ones.

Study on the Prediction Technique of Vehicle Performance using Parameter Analysis (파라미터 해석을 통한 차량 성능 예측 기법 연구)

  • Kim, Ki-Chang;Kim, Chan-Mook;Kim, Jin-Taek
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2009.10a
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    • pp.647-653
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    • 2009
  • Taguchi parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used SN (Signal to Noise) ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. This paper describes the prediction technique of vehicle performance using parameter analysis to reduce man hour and test development period as well as to achieve stable NVH performance. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce the time needed to develop better vehicles.

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Bayesian Estimation of Shape Parameter of Pareto Income Distribution Using LINEX Loss Function

  • Saxena, Sharad;Singh, Housila P.
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.33-55
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    • 2007
  • The economic world is full of patterns, many of which exert a profound influence over society and business. One of the most contentious is the distribution of wealth. Way back in 1897, an Italian engineer-turned-economist named Vilfredo Pareto discovered a pattern in the distribution of wealth that appears to be every bit as universal as the laws of thermodynamics or chemistry. The present paper proposes some Bayes estimators of shape parameter of Pareto income distribution in censored sampling. Asymmetric LINEX loss function has been considered to study the effects of overestimation and underestimation. For the prior distribution of the parameter involved a number of priors including one and two-parameter exponential, truncated Erlang and doubly truncated gamma have been contemplated to express the belief of the experimenter s/he has regarding the parameter. The estimators thus obtained have been compared theoretically and empirically with the corresponding estimators under squared error loss function, some of which were reported by Bhattacharya et al. (1999).

Inference about Measure of Agreement in the General Mixture Model via Parameter Orthogonalization

  • Um, Jongseok
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.341-352
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    • 2003
  • Collecting data through experiment, the observers are an import source of measurement error and the inference on the measure of agreement, say kappa, is necessary. The models commonly used are complicated general mixture model, which have many nuisance parameters. Orthogonalization of parameters reduce the effect of nuisance parameter. Orthogonalization of estimating function gives the same effect as the parameter orthogonalization. In this study, the method for orthogonalization of estimating equation is studied and applied to the Beta-binomial model to examine the properties of the estimate of kappa. As a result, the likelihood function is insensitive to the change of the nuisance parameter and bias is smaller than the result of m.1.e. when kappa has extreme values

A development off displacement pump performance evaluation method by using dimensionless parameter (무차원계수를 이용한 왕복펌프의 성능평가 방법 개발)

  • 조희근;윤진하;전종길;김경원;이인복
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.05a
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    • pp.731-734
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    • 2002
  • There have been no obvious design criteria of high efficient displacement pump using a dimensionless parameter which can represent many physical aspect of displacement pump could be very useful to estimate displacement pump performance. Many dimensionless analysis methods have been developed in fluid dynamics, machine design and so on. In this study a new dimensionless parameter is developed for estimate displacement pump performance and efficiency, until now to evaluate the performance of displacement pumps which are widely used in industry field, primarily experimental methods have been used. The dimensionless parameter contains many physical information about pump design. For example, they are the relation between flow rate and power, displacement operation displacement and size, inlet and outlet valve size. And the developed dimensionless functions are induced from numerical method.

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Bayesian Estimation of the Two-Parameter Kappa Distribution

  • Oh, Mi-Ra;Kim, Sun-Worl;Park, Jeong-Soo;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • v.14 no.2
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    • pp.355-363
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    • 2007
  • In this paper a Bayesian estimation of the two-parameter kappa distribution was discussed under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape parameter and scale parameter in the Gibbs sampler is implemented using the adaptive rejection Metropolis sampling algorithm of Gilks et al. (1995). A Monte Carlo study showed that the Bayesian estimators proposed outperform other estimators in the sense of mean squared error.