• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.1
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• pp.37-44
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• 1998

In this study a new hybrid method is developed for solving flow-dominated transport problems accurately and effectively. The method takes the forward-tracking particle method for advection. However, differently from the random-walk Lagrangian approach it solves the diffusion process on the fixed Eulerian grids. Therefore, neither any interpolating algorithm nor a large enough number of particles is required. The method was successfully examined for both cases of instantaneous and continuous sources released at a point. Comparison with a surrounding 5-point Hermite polynomial method (Eulerian-Lagrangian method) and the random-walk pure Lagrangian method shows that the present method is superior in result accuracy and time-saving ability.

• Journal of Mechanical Science and Technology
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• v.19 no.12
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• pp.2312-2320
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• 2005

The aerodynamic effects of leading-edge accretion can raise important safety concerns since the formulation of ice causes severe degradation in aerodynamic performance as compared with the clean airfoil. The objective of this study is to develop a numerical simulation strategy for predicting the particle trajectory around an MS-0317 airfoil in the test section of the NASA Glenn Icing Research Tunnel and to investigate the impingement characteristics of droplets on the airfoil surface. In particular, predictions of the mean velocity and turbulence diffusion using turbulent flow solver and Continuous Random Walk method were desired throughout this flow domain in order to investigate droplet dispersion. The collection efficiency distributions over the airfoil surface in simulations with different numbers of droplets, various integration time-steps and particle sizes were compared with experimental data. The large droplet impingement data indicated the trends in impingement characteristics with respect to particle size ; the maximum collection efficiency located at the upper surface near the leading edge, and the maximum value and total collection efficiency were increased as the particle size was increased. The extent of the area impinged on by particles also increased with the increment of the particle size, which is similar as compared with experimental data.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.104-116
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• 2022

The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm²) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (D_m) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean D_m, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for D_m, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.09a
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• pp.27-30
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• 2001

Flow and transport at fracture intersections, and their effects on network scale transport, are investigated in three-dimensional random fracture networks. Fracture intersection mixing rules complete mixing and streamline routing are defined in terms of fluxes normal to the intersection line between two fractures. By analyzing flow statistics and particle transfer probabilities distributed along fracture intersections, it is shown that for various network structures with power law size distributions of fractures, the choice of intersection mixing rule makes comparatively little difference in the overall simulated solute migration patterns. The occurrence and effects of local flows around an intersection (local flow cells) are emphasized. Transport simulations at fracture intersections indicate that local flow circulations can arise from variability within the hydraulic head distribution along intersections, and from the internal no flow condition along fracture boundaries. These local flow cells act as an effective mechanism to enhance the nondiffusive breakthrough tailing often observed in discrete fracture networks. It is shown that such non-Fickian (anomalous) solute transport can be accounted for by considering only advective transport, in the framework of a continuous time random walk model. To clarify the effect of forest environmental changes (forest type difference and clearcut) on water storage capacity in soil and stream flow, watershed had been investigated.

• Journal of the Korean Institute of Navigation
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• v.16 no.1
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• pp.94-97
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• 1992

In this paper, the individual number of the future has depended not only upon the present individual number but upon the present individual age, considering the stochastic process model of individual number when the life span of each individual number and the individual age as a set, this becomes a Markovian. Therefore, in this paper the individual is treated as invariable, without depending upon the whole record of each individual since its birth. As a result, suppose {N(t), t>0} be a counting process and also suppose $Z_n$ denote the life span between the (n-1)st and the nth event of this process, (n{$geq}1$) : that is, when the first individual is established at n=1(time, 0), the Z$Z_n$ at time nth individual breaks, down. Random walk $Z_n$ is $Z_n=X_1+X_2+{\cdots}{\cdots}+X_A, Z_0=0$ So, fixed time t, the stochastic model is made up as follows ; A) Recurrence (Regeneration)number between(0.t) $N_t=max{n ; Z_n{\leq}t}$ B) Forwardrecurrence time(Excess life) $T^-I_t=Z_{Nt+1}-t$ C) Backward recurrence time(Current life) $T^-_t=t-Z_{Nt}$