• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.231-239
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• 2003

A Digital Wave Tank simulation technique based on a finite-difference method and a modified marker-and-cell (MAC) algorithm is applied to investigate the characteristics of nonlinear Tsunami propagations and their interactions with a 2D sloping beach and Ohkushiri island, and to predict maximum wave run-up around the island. The Navier-Stokes (NS) and continuity equation are governed in the computational domain and the boundary values updated at each time step by a finite-difference time-marching scheme in the frame of rectangular coordinate system. The fully nonlinear kinematic free-surface condition is satisfied by the modified marker-density function technique. The Nearshore Tsunami is assumed to be a solitary wave and generated from the numerical wavemaker in the developed Digital Wave Tank. The simulation results are compared with the experiments and other numerical methods based on the shallow-water wave theory.

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.114-122
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• 2024

Irradiation-induced defects and the precipitates in the wrapper material of the Indian Fast Breeder Test Reactor (FBTR), SS 316 are analyzed using the synchrotron source-based Angle Dispersive X-Ray Diffraction (ADXRD) technique with X-rays of energy 17.185 keV (wavelength ~0.72146 Å). The differences and similarities in the high displacement damage samples as a function of dpa (displacement per atom) and dpa rate in the range of 2.9 × 10^-7- 9 × 10^-7 dpa/s are studied. Ferrite and M₂₃C₆ are commonly observed in the present set of high displacement damage 40-74 dpa SS 316 samples irradiated at temperatures in the range of 400-483 ℃. Also, the dislocation density has increased as a function of the irradiation dose. The X-ray diffraction peak profile parameters quantified such as peak shift and asymmetry show that the irradiation-induced defects are sensitive to the dpa rate-irradiation temperature combinations. The increase in yield strength as a function of displacement damage is also correlated to the dislocation density.

• 한국농공학회논문집
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• 제55권5호
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• pp.49-58
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• 2013

Appropriate random variables and probability density functions based on statistical analysis should be defined to execute reliability analysis. Most studies have focused on only normal distributions or assumed that the variables showing non-normal characteristics follow the normal distributions. In this study, the reliability problem with non-normal probability distribution was dealt with using the convolution method in the case that the integration domains of variables are limited to a finite range. The results were compared with the traditional method (linear transformation of normal distribution) and Monte Carlo simulation method to verify that the application was in good agreement with the characteristics of probability density functions with peak shapes. However it was observed that the reproducibility was slightly reduced down in the tail parts of density function.

• 전자공학회논문지A
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• 제30A권2호
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• pp.46-52
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• 1993

The estimation of yield for semiconductor devices requires not only establishment of critical area but also a new parameter of process defect density that contains inspection mean defect density related cleanness of manufacure process line, minimum feature size and the total number of mask process. We estimate the repaired yield of memory devide, leads the semiconductor technique, repaired by redundancy scheme in relation with defect density distribution function, and we confirm the repaired yield for different devices as this model. This shows the possibility of the yield estimation as statistical analysis for the condition of device related cleanness of manufacture process line, design and manufacture process.

• 천문학회지
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• 제33권3호
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• pp.151-158
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• 2000

We conducted a deep CCD observations in V band to obtain stellar density distribution and to determine the distances toward two molecular clouds with anomalous velocity in the Galactic anti-center region. Star count method based on the linear programming technique was applied to the CCD photometric data. We found two prominent peaks at distances of around 1.4 and 2.7 kpc. It is found that the first peak coincides well with stellar density enhancement of B8-A0 stars and the second one with the outer Perseus arm. The effect of the choice of the luminosity function is discussed. The stellar number density distribution is used to derive the distances to the molecular clouds and the visual extinctions caused by the clouds. We found that two molecular clouds are located almost at the same distance of about 1.1 $\pm$ 0.1 kpc, and the peak extinctions caused by the clouds are about 2.2 $\pm$ 0.3 mag in V band.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제4B권3호
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• pp.108-113
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• 2004

This paper presents methods to improve performance of the power supply system in a NASA deep space explorer. In the Stirling engine driven reciprocating Brushless DC (BLDC) generator, the accurate position information of the prime mover is important to diagnose the performance of the engine and prevent distortion of the output power. Since sensors to detect the position are fragile and unreliable, and conventional sensorless techniques have drawbacks in the low speed region, a novel sensorless position detection technique for the prime mover has been proposed and verified. Another major issue of the generator for the spacecraft is power density maximization. The mass of the power system is important to the mass of the satellite. Therefore, the components of the spacecraft should be lightweight. Conventional rectification methods cannot achieve the maximum power possible due to non-optimal current waveforms. The optimal current waveform for maximizing power density and minimizing machine size and weight in a nonsinusoidal power supply system has been derived, incorporated in a control system, and verified by simulation work.

• Structural Engineering and Mechanics
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• 제78권2호
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• pp.145-161
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• 2021

Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

• Computers and Concrete
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• 제23권6호
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• pp.421-431
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• 2019

The alarming rate of depletion of natural stone based coarse aggregates is a cause of great concern. The coarse aggregates occupy nearly 60-70% by volume of concrete being produced. Research efforts are on to look for alternatives to stone based coarse aggregates from sustainability point of view. Response surface methodology (RSM) is adopted to study and address the effect of ferrochrome slag (FCS) replacement to coarse aggregate replacement in the ordinary Portland cement (OPC) based concretes. RSM involves three different factors (ground granulated blast furnace slag (GGBS) as binder, flyash (FA) as binder, and FCS as coarse aggregate), with three different levels (GGBS (0, 15, and 30%), FA (0, 15, and 30%) and FCS (0, 50, and 100%)). Experiments were carried out to measure the responses like, workability, density, and compressive strength of FCS based concretes. In order to optimize FCS replacement in the OPC based concretes, three different traditional optimization techniques were used (grey relational analysis (GRA), technique for order of preference by similarity (TOPSIS), and desirability function approach (DFA)). Traditional optimization techniques were accompanied with principal component analysis (PCA) to calculate the weightage of responses measured to arrive at the final ranking of replacement levels of GGBS, FA, and FCS in OPC based concretes. Hybrid combination of PCA-TOPSIS technique is found to be significant when compared to other techniques used. 30% GGBS and 50% FCS replacement in OPC based concrete was arrived at, to be optimal.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.657-666
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• 2020

A reliable and cost-effective technique for the development of corrosion damage model is introduced to predict nonlinear time-dependent corrosion wastage of steel structures. A detailed explanation on how to propose a generalised mathematical formulation of the corrosion model is investigated in this paper (Part I), and verification and application of the developed method are covered in the following paper (Part II) by adopting corrosion data of a ship's ballast tank structure. In this study, probabilistic approaches including statistical analysis were applied to select the best fit probability density function (PDF) for the measured corrosion data. The sub-parameters of selected PDF, e.g., the largest extreme value distribution consisting of scale, and shape parameters, can be formulated as a function of time using curve fitting method. The proposed technique to formulate the refined time-dependent corrosion wastage model (TDCWM) will be useful for engineers as it provides an easy and accurate prediction of the 1) starting time of corrosion, 2) remaining life of the structure, and 3) nonlinear corrosion damage amount over time. In addition, the obtained outcome can be utilised for the development of simplified engineering software shown in Appendix B.

• Journal of applied mathematics & informatics
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• 제41권6호
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• pp.1341-1364
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• 2023

This article introduces a method for estimating the conditional hazard function of a real-valued response variable based on a functional variable. The method uses local linear estimation of the conditional density and cumulative distribution function and is applied to a functional stationary ergodic process where the explanatory variable is in a semi-metric space and the response is a scalar value. We also examine the uniform almost complete convergence of this estimation technique.