• Korean Journal of Soil Science and Fertilizer
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• v.44 no.3
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• pp.337-343
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• 2011

A particular empirical equation for rainfall kinetic energy is needed to compute rainfall erosivity, calculated by the annual sum of the product of total rainfall energy and maximum 30-min rainfall intensity. If rainfall kinetic energy equation was different, rainfall erosivity will be produced differently. However, the previous studies in Korea had little concern about rainfall kinetic energy equation and it was not clear which rainfall kinetic energy is suitable for Korea. The purpose of this study is to analyze and evaluate the difference of the rainfall erosivity based on different rainfall kinetic energy equations obtained from previous studies. This study introduced new rainfall erosivity factors based on rainfall kinetic energy equation of Noe and Kwon (1984) that is only regression model developed in Korea. Data of annual rainfall erosivity for 21 weather stations in 1980~1999 were used in this study. The result showed that rainfall erosivity factors by the previous equations had been about 10~20% overestimated than rainfall erosivity by Noe and Kwon (1984)'s equation in Korea.

• Bulletin of the Korean Chemical Society
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• v.10 no.2
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• pp.167-171
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• 1989

Kinetic energy release in the fragmentation of tert-butylbenzene molecular ion was investigated using mass-analyzed ion kinetic energy spectrometry. Method to estimate kinetic energy release distribution (KERD) from experimental peak shape has been explained. Experimental KERD was in good agreement with the calculated result using phase space theory. Effect of dynamical constraint was found to be important.

• Journal of the Korean institute of surface engineering
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• v.41 no.6
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• pp.301-307
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• 2008

In this paper, nanocrystallization of CuNiTiZr bulk metallic glass (BMG) subjecting to a kinetic spraying, dependent on impact velocity, was investigated by numerical and experimental approaches. The crystallization fraction and nucleation activation energy of initial feedstock and as-deposited coating were estimated by DSC and Kissinger method, respectively. The results of numerical modeling and experiment showed that the crystalline fraction and nucleation activation energy in BMG coatings were depended on kinetic energy of incident particle. Upon impact, the conversion of particle kinetic energy leads to not only decreasing free energy barrier but also increasing the driving force for an amorphous to crystalline phase transformation. The nanocrystallization of BMGs is associated with the strain energy delivered by a plastic deformation with a high strain rate.

• Journal of Environmental Science International
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• v.6 no.4
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• pp.313-322
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• 1997

In order to study the seasonal variation of kinetic and potential energy of residual flow field In Suyoung Bay of Korea, we calculated Its energy budget and compared It with the tidal energy there. The potential energy shows the large value In winter and spring and the small one In summer and early autumn when the density stratification Is developed. The kinetic energy of residual flow varies seasonally and the seasonally averaged kinetic energy of residual flow per unit area is 6.4$\times$$10^{-4}ergs s^{-1}cm^{-}2$. It Is mainly governed by the density-driven current with the exception of that In November when the kinetic energy of tide-induced residual current is larger than those of density-driven current and wind-driven current. An averaged traction of the kinetic energy of tide-Induced residual current, wind-driven current and density-driven current, which are the major components of residual flow, is 29.1%, 3.4%, 67.5%, respectively, to the kinetic energy of residual flow, The fraction of kinetic energy of residual flow, potential energy and tidal energy per unit area is 1.0 : 6.7$\times$$10^3$: 8.2$\times$$10^4$ respectively.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1788-1793
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• 2008

Classical molecular dynamics simulations (MDS) were conducted to simulate nano-sized cluster collisions with a weakly attractive static surface. Energy exchanges associated with the cluster collision and the adhesion probability are discussed. Routes of the energy exchanges and the kinetic energy loss are vastly altered in their mode according to the cluster incident velocity. In the elastic collision regime ($V_0$<0.1), most incident kinetic energy is recovered into the rebounding kinetic energy, but a little loss in the incident kinetic energy causes the cluster adhesion. Dissipated kinetic energy is converted into the rotational energy. In the weakly plastic collision regime (0.1<$V_0$<0.3), the transition from elastic to plastic collision occurs, and a large part of the released potential energy is converted into rebounding translational energy. For strongly plastic collisions ($V_0$>0.3), permanent cluster deformation occurs with extensive collapse of the lattice structure inducing a solid-to-solid phase transition; moreover, most of the cluster kinetic energy is converted into cluster potential and thermal energy.

• Journal of the Korean Society of Visualization
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• v.9 no.4
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• pp.16-21
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• 2011

The effects of stroke change on turbulent kinetic energy for the in-cylinder flow of a four-valve SI engine were studied. For this study, the same intake manifold, head, cylinder, and the piston were used to examine turbulence characteristics in two different strokes. In-cylinder flow measurements were conducted using three dimensional LDV system. The measurement method, which simultaneously collects 3-D velocity data, allowed a evaluation of turbulent kinetic energy inside a cylinder. High levels of turbulent kinetic energy were found in regions of high shear flow, attributed to the collisions of intake flows. These specific results support the more general conclusion that the inlet conditions play the dominant role in the generation of the turbulence fields during the intake stroke. However, in the absence of two counter rotating vortices, this intake generated turbulent kinetic energy continues to decrease but at a much faster rate.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.1-18
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• 1987

Prediction performances by Einstein's equation of diffusivity, Peskin's model, Three-Equation model, Four-Equation model and Algebraic Stress Model, have been compared by analyzing twophase (air-solid) turbulent jet flow. Turbulent kinetic energy equation of dispersed phase was solved to investigate effects of turbulent kinetic energy on turbulent diffusivity. Turbulent kinetic energy dissipation rate of particles has been considered by solving turbulent kinetic energy dissipation rate equation of dispesed phase and applying it to turbulent diffusivity of dispersed phase. Results show that turbulent diffusivity of dispersed phase can be expressed by turbulent kinetic energy ratio between phases and prediction of turbulent kinetic energy was improved by considering turbulent kinetic energy dissipation rate of dispersed phase for modelling turbulent diffusivity. This investigation also show that Algebraic Stress Model is the most promising method in analyzing gas-solid two phaes turbulent flow.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.1
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• pp.1-7
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• 1988

Prediction performances by Einstein's equation of diffusivity, Peskin's model, Three-Equation model, Four-Equation model and Algebraic Stress Model, have been compared by analyzing twophase (air-solid) turbulent jet flow. Turbulent kinetic energy equation of dispersed phase was solved to investigate effects of turbulent kinetic energy on turbulent diffusivity. Turbulent kinetic energy dissipation rate of particles has been considered by solving turbulent kinetic energy dissipation rate equation of dispersed phase and applying it to turbulent diffusivity of dispersed phase. Results show that turbulent diffusivity of dispersed phase can be expressed by turbulent kinetic energy ratio between phases and prediction of turbulent kinetic energy was improved by considering turbulent kinetic energy dissipation rate of dispersed phase for modelling turbulent diffusivity. This investigation also show that Algebraic Stress Model is the most promising method in analyzing gas-solid two phases turbulent flow.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.136-144
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• 2006

Vehicles usually have 3 types of speed pattern like acceleration, travel, and deceleration. It requires much driving energy from engine while accelerating, preserves much kinetic energy by inertia moment at travel speed, and releases the kinetic energy to the air while decelerating by the break system. If we accumulate the kinetic energy while decelerating and reuse the energy at the accelerating stage, then it can elevate the fuel efficiency, reduce the emission and improve the motive power. This paper proposes a hydraulic type energy regenerative system which converts the kinetic energy into hydraulic energy at the stage of deceleration and reuses it at the starting and accelerating stage of vehicles. The test equipment which has the field condition of city bus was prepared to evaluate the performance for energy regeneration. The test results show that both energy regeneration efficiency and fuel efficiency are improved significantly and the emission is reduced notably.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.79-84
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• 2011

The purpose of this study was to investigate the relevance of the prediction equations derived from the relationship between metabolic energy expenditure and kinetic energy, for different speeds of walking and running over the treadmill. Seven male subjects participated in this study. A tri-axial accelerometer was attached on between the left and right posterior superior iliac spines. Kinetic energy was calculated by the integration of acceleration data and compared with the metabolic energy measured by a gas analyzer. Correlation coefficients were determined to find a relationship between the kinetic energy and the metabolic energy expenditure. Also, the difference between measured and predicted values was used to find the relevance for individual and group equations. Results showed a relatively good correlation between the measured metabolic energy and the calculated kinetic energy. In addition, a dramatic increase in kinetic energy was observed at the transition speed of walking and running (6 km/h). There was no difference in how to predict the kinetic energy expenditure for individual and group even though people have different physical characteristics. This study would be useful to predict metabolic energy expenditures by the regression analysis with acceleration data.