• Tribology and Lubricants
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• v.17 no.4
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• pp.297-306
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• 2001

Under the condition of variable density and specific heat, maximum pressure, maximum temperature, bearing load, friction and side leakage in high-speed journal bearing operation are examined within some degree of Journal misalignment. The results are compared with the calculation results under the conditions of constant density and specific heat, and variable density and constant specific heat. It is found that the condition of variable density and specific heat play important roles in determining friction and load of Journal bearing at high speed operation.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.305-310
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• 2001

Within some degree of journal misalignment, maximum pressure, maximum temperature, bearing load, friction and side leakage in high-speed journal bearing operation are examined under the condition of variable density and specific heat. The results are compared with the calculation results under the conditions of constant density and specific heat, and variable density and constant specific heat. It is found that the effects of variable density and specific heat on shaft misalignment are significant in determining the load capacity of a journal bearing operating at high speed.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.287-292
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• 2001

Under the condition of variable density and specific heat, maximum pressure, maximum temperature, bearing load, friction and side leakage in high-speed journal bearing operation are examined. The results are compared with the calculation results under the conditions of constant density and specific heat, and variable density and constant specific heat. It is found that the condition of variable density and specific heat play important roles in determining friction and load of journal bearing at high speed operation.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.1
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• pp.115-124
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• 2002

The optimum design of auto-catalyst needs a good compromise between the pressure drop and flow distribution in the monolith. One of the effective methods to achieve this goal is to use the concept of radially variable cell density. However, there has been no study of evaluating the usefulness of this method on light-off catalyst. We have computationally investigated the effectiveness of variable cell density technique applied to the light-off catalyst using a three-dimensional integrated CFD model. in which transient chemical reacting calculations are involved. Computed results show that variable cell density technique can reduce the accumulated emissions of CO and HC during the early 100sec of FTP cycle by 86.78 and 80.87%, respectively, The effect of air-gap between the monoliths has been also examined. It is found that air-gap has a beneficial effect on reducing pressure drop and cold-start emissions.

• Korean Journal of Mathematics
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• v.27 no.1
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• pp.193-219
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• 2019

The Navier-Stokes equations with variable density are challenging problems in numerical analysis community. We recently built the 2nd order stabilized Gauge-Uzawa method [SGUM] to solve the Navier-Stokes equations with constant density and have estimated theoretically optimal accuracy. Also we proved that SGUM is unconditionally stable. In this paper, we apply SGUM to the Navier-Stokes equations with nonconstant variable density and find out the stability condition of the algorithms. Because the condition is rather strong to apply to real problems, we consider Allen-Cahn scheme to construct unconditionally stable scheme.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.37-40
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• 1989

When we analyze the magnetostatic problem by the FEM, it is a traditional method to use the magnetic vector potential as an unknown variable.(abbreviated to A Method) Therefore, we should differentiate this magnetic vector potential to get the magnetic flux density. In this procedure of differentiation, the accuracy of the calculation is reduced. In order to overcome this problem, this paper uses the magnetic flux density as an unknown variable.(abbreviated to B Method) The validity of this new method (B Method) to use the magnetic flux density directly as an unknown variable, is ensured as the result of the application example researches.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• Journal of Forest and Environmental Science
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• v.28 no.4
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• pp.205-211
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• 2012

Yield tables are a frequently used data base for regional timber resource forecasting. A normal yield table is based on two independent variables, age and site (species constant), and applies to fully stocked (or normal) stands while empirical yield tables are based on average rather than fully stocked stands. Normal and empirical yield tables essentially have many limitations. The limitations of normal and empirical yield tables led to the development of variable density yield tables. Mathematical models for estimating timber yields are usually developed by fitting a suitable equation to observed data. The model is then used to predict yields for conditions resembling those of the original data set. It may be accurate for the specific conditions, but of unproven accuracy or even entirely useless in other circumstances. Thus, these models tend to be specific rather than general and require validation before applying to other areas. Dalbergia sissoo forms a major portion of irrigated plantations in the hot desert of India and is an important timber tree species where stem wood is primarily used as timber. Variable density yield model is not available for this species which is very crucial in long-term planning for managing the plantations on a sustained basis. Thus, the objective of this study was to develop variable density yield model based on the data collected from 30 sample plots of D. sissoo laid out in IGNP area of Rajasthan State (India) and measured annually for 5 years. The best approximating model was selected based on the fit statistics among the models tested in the study. The model develop was evaluated based on quantitative and qualitative statistical criteria which showed that the model is statistically sound in prediction. The model can be safely applied on D. sissooo plantations in the study area or areas having similar conditions.

• School Mathematics
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• v.4 no.4
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• pp.677-688
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• 2002

The context and intuitive understanding is very important in Statistics Education. Especially, there is a need to mitigate student's difficulty in studying probability density function. One of teaching method this concept is to using relative frequency histogram. But, as using this method, we should know several problems included in that. This study investigate problems in the method for teaching probability density function as gradual meaning of histogram. Also, as alternative approach, this thesis introduce the density curve concept. The application of four methods to teach the concept of the probability density function and analysis of the survey result is done in this research.

• Water Engineering Research
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• v.2 no.1
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• pp.1-10
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• 2001

The frequency analyses for the precipitation data in Korea were performed. We used daily maximum series, monthly maximum series, and annual series. For nonparametric frequency analyses, variable kernel estimators were used. Nonparametric methods do not require assumptions about the underlying populations from which the data are obtained. Therefore, they are better suited for multimodal distributions with the advantage of not requiring a distributional assumption. In order to compare their performance with parametric distributions, we considered several probability density functions. They are Gamma, Gumbel, Log-normal, Log-Pearson type III, Exponential, Generalized logistic, Generalized Pareto, and Wakeby distributions. The variable kernel estimates are comparable and are in the middle of the range of the parametric estimates. The variable kernel estimates show a very small probability in extrapolation beyond the largest observed data in the sample. However, the log-variable kernel estimates remedied these defects with the log-transformed data.