• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.77-84
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• 2003

It is an aim of this study to perform extensive numerical study for analyzing the anisotropic turbulence effects on spatial and temporal behaviors of diesel sprays after wall impingement. The turbulence model of Durbin is used for comparisons with the $k-\varepsilon$ model. The turbulence-induced dispersions of droplets are considered to describe the anisotropy of turbulence effectively and the spray/wall interactions are simulated using the model of Lee and Ryou. The present study investigates the internal structures of impinging diesel sprays such as Sauter mean diameter (SMD), loca1 droplet velocities, and local gas velocities and also compares the results predicted by two turbulence models with the experimental data. The Durbin's model considering the anisotropy of turbulence predicts both gas and droplet tangential velocities better than the$k-\varepsilon$ model does. It is concluded that the anisotropy of turbulence should be considered in simulating impinging diesel sprays.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.131-141
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• 1998

Video data occurred in multimedia documents consist of a large scale of irregular data including audio-visual, spatial-temporal, and semantic information. In general, it is difficult to grasp the exact meaning of such a video information because video data apparently consist of unmeaningful symbols and numerics. In order to relieve these difficulties, it is necessary to develop an integrated manager for complex structures of video data and provide users of video digital libraries with easy, systematic access mechanisms to video informations. This paper proposes a generic integrated video information model(GIVIM) based on an extended Dublin Core metadata system to effectively store and retrieve video documents in digital libraries. The GIVIM is an integrated mo이 of a video metadata model(VMN) and a video architecture information model(VAIM). We also present design and implementation results of a video document management system(VDMS) based on the GIVIM.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1996.11a
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• pp.107-116
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• 1996

Numerical simulations have been conducted to characterize unsteady flow structures in an axisymmetric supersonic inlet diffuser with sinusoidal pressure oscillations at the diffuser exit. The formulation is based on the unsteady Navier-Stokes equations and turbulence closure is achieved using a two-layer model with a too-Reynolds-number scheme for the near-wall treatment. The governing equations are formulated in an integral form, and are discretized by the four-stage Runge-Kutta scheme for temporal terms and the Harten-Yee upwind TVD scheme for convective terms. Results indicated that the inlet shock characteristics are significantly modified by acoustic oscillations originating from the combustor. The characteristics of shock/boundarv-layer interactions (such as the size of separation bubble, terminal shock shape, and vorticity intensity) are also greatly iufluenced by the shock oscillation due to acoustic waves.

• Wind and Structures
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• v.13 no.2
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• pp.191-206
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• 2010

Windborne debris is a major cause of structural damage during severe windstorms and hurricanes owing to its direct impact on building envelopes as well as to the 'chain reaction' failure mechanism it induces by interacting with wind pressure damage. Estimation of debris risk is an important component in evaluating wind damage risk to residential developments. A debris risk model developed by the authors enables one to analytically aggregate damage threats to a building from different types of debris originating from neighboring buildings. This model is extended herein to a general debris risk analysis methodology that is then incorporated into a vulnerability model accounting for the temporal evolution of the interaction between pressure damage and debris damage during storm passage. The current paper (Part I) introduces the debris risk analysis methodology, establishing the mathematical modeling framework. Stochastic models are proposed to estimate the probability distributions of debris trajectory parameters used in the method. It is shown that model statistics can be estimated from available information from wind-tunnel experiments and post-damage surveys. The incorporation of the methodology into vulnerability modeling is described in Part II.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.237-251
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• 2003

In this paper, we propose a video retrieval system to search logical structure and semantic contents of video data efficiently. The proposed system employs a layered modelling method that orBanifes video data in raw data layer, content layer and key frame layer. The layered modelling of the proposed system represents logical structures and semantic contents of video data in content layer. Also, the proposed system supports various types of searches such as text search, visual feature based similarity search, spatio-temporal relationship based similarity search and semantic contents search.

• Steel and Composite Structures
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• v.20 no.5
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• pp.1119-1131
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• 2016

As a first attempt, an inverse hybrid numerical method for small scale parameter estimation of functionally graded (FG) nanobeams using measured frequencies is presented. The governing equations are obtained with the Eringen's nonlocal elasticity assumptions and the first-order shear deformation theory (FSDT). The equations are discretized by using the differential quadrature method (DQM). The discretized equations are transferred from temporal domain to frequency domain and frequencies of the nanobeam are obtained. By applying random error to these frequencies, measured frequencies are generated. The measured frequencies are considered as input data and inversely, the small scale parameter of the beam is obtained by minimizing a defined functional. The functional is defined as root mean square error between the measured frequencies and calculated frequencies by the DQM. Then, the conjugate gradient (CG) optimization method is employed to minimize the functional and the small scale parameter is obtained. Efficiency, convergence and accuracy of the presented hybrid method for small scale parameter estimation of the beams for different applied random error, boundary conditions, length-to-thickness ratio and volume fraction coefficients are demonstrated.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.2
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• pp.232-240
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• 2013

This paper presents recent advances in damage visualization algorithms of laser generated ultrasonic propagation imaging(UPI) system. An effective damage evaluation method is required to extract correct information from raw data to properly characterize anomalies present in structure. A temporal-reference free imaging system provides easy and rapid defect inspection capability with less computational complexity. In this paper a number of methods such as ultrasonic wave propagation imaging(UWPI), anomalous wave propagation imaging(AWPI), ultrasonic spectral imaging(USI), wavelet ultrasonic propagation imaging(WUPI), variable time window amplitude mapping(VTWAM), time point adjustment(TPA), time of flight and amplitude mapping(ToF&Amp) and ultrasonic wavenumber imaging(UWI) are discussed with instances of successful implementation on various structures.

• Smart Structures and Systems
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• v.19 no.4
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• pp.383-391
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• 2017

In this paper, we investigate the impacts of network topology on the performance of a distributed estimation algorithm, namely combine-then-adaptive (CTA) diffusion LMS, based on the data with or without the assumptions of temporal and spatial independence with noisy links. The study covers different network models, including the regular, small-world, random and scale-free whose the performance is analyzed according to the mean stability, mean-square errors, communication cost (link density) and robustness. Simulation results show that the noisy links do not cause divergence in the networks. Also, among the networks, the scale free network (heterogeneous) has the best performance in the steady state of the mean square deviation (MSD) while the regular is the worst case. The robustness of the networks against the issues like node failure and noisier node conditions is discussed as well as providing some guidelines on the design of a network in real condition such that the qualities of estimations are optimized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.1
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• pp.193-204
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• 1997

In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.