• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.37.1-37.1
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• 2017

Since the seminal work of Perrin, physicists have understood in the context of kinetic theory how ink slowly diffuses in a glass of water. The fluctuations of the stochastic forces acting on water molecules drive the diffusion of the ink in the fluid. This is the archetype of a process described by the so-called fluctuation-dissipation theorem, which universally relates the rate of diffusion to the power spectrum of the fluctuating forces. For stars in galaxies, a similar process occurs but with two significant differences, due to the long-range nature of the gravitational interaction: (i) for the diffusion to be effective, stars need to resonate, i.e. present commensurable frequencies, otherwise they only follow the orbit imposed by their mean field; (ii) the amplitudes of the induced fluctuating forces are significantly boosted by collective effects, i.e. by the fact that, because of self-gravity, each star generates a wake in its neighbours. In the expanding universe, an overdense perturbation passing a critical threshold will collapse onto itself and, through violent relaxation and mergers, rapidly converge towards a stationary, phase-mixed and highly symmetric state, with a partially frozen orbital structure. The object is then locked in a quasi-stationary state imposed by its mean gravitational field. Of particular interests are strongly responsive colder systems which, given time and kicks, find the opportunity to significantly reshuffle their orbital structure towards more likely configurations. This presentation aims to explain this long-term reshuffling called gravity-driven secular evolution on cosmic timescales, described by extended kinetic theory. I will illustrate this with radial migration, disc thickening and the stellar cluster in the galactic centre.

• Journal of The Korean Astronomical Society
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• v.36 no.2
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• pp.67-72
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• 2003

The basic objective of helioseismology is to determine the structure and the dynamics of the Sun by analysing the frequency spectrum of the solar oscillations. Accurate frequency measurements provide information that enables us to probe the solar interior structure and the dynamics. Therefore the frequency of the solar oscillation is the most fundamental and important information to be extracted from the solar oscillation observation. This is why many efforts have been put into the development of accurate data analysis techniques, as well as observational efforts. To test one's data analysis method, a realistic artificial data set is essential because the newly suggested method is calibrated with a set of artificial data with predetermined parameters. Therefore, unless test data sets reflect the real solar oscillation data correctly, such a calibration is likely incomplete and a unwanted systematic bias may result in. Unfortunately, however, commonly used artificial data generation algorithms insufficiently accommodate physical properties of the stochastic excitation mechanism. One of reason for this is that it is computaionally very expensive to solve the governing equation directly. In this paper we discuss the nature of solar oscillation excitation and suggest an efficient algorithm to generate the artificial solar oscillation data. We also briefly discuss how the results of this work can be applied in the future studies.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.12
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• pp.1132-1139
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• 2008

The aim of this study is to apply shape optimization technique for the repair of aging airframe components, which may extend fatigue life substantially. Free-form optimum shapes of a cracked part to be reworked or replaced are investigated with the objective to minimize the peak local stress concentration or fatigue-damage. Iterative non-gradient method, which is based on an analogy with biological growth, is employed by incorporating the robust optimization method to take account of the stochastic nature of the loading conditions. Numerical examples of optimal hole shape in a flat plate are presented to validate the proposed method. The method is then applied to determine the reworked or replacement shape for the repair of a cracked rib in the rear assembly wing body of aircraft.

• Tribology and Lubricants
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• v.11 no.5
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• pp.99-107
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• 1995

This paper reported research results to develop an algorithm of on-lin evaluation of surface profiles and roughness generated by turning. The developed module consisted of computer simulation of surface profiles using mechanism of cutting mark formation and cutting vibrations, and online measurement of cutting vibrations. The relative cutting vibrations between tool and worpkiece were measured through an inductance pickup at the rate of one sample per rotation of the workpiece. The sampling process was monitored using an encoder to avoid conceling out the phase lag between waves. The digital cutting signals from the Analog-to-Digital converter were transferred to the simulation module of surface profile where the surface profiles were generated. The developed algorithm or surface generation in a hard turning was analyzed through computer simulations to consider the stochastic and dynamic nature of cutting process. Cutting tests were performed using AISI 304 Stainless Steel and carbide inserts in practical range of cutting conditions. Experimental results showed good correlation between the surface profiles and roughness obtained using the developed algorithm and the surface texture measured using a surface profilemeter. The research provided the feasibility to monitor surface characteristics during tribelogical tests considering wear effect on surface texture in machining.

• BMB Reports
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• v.46 no.4
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• pp.219-224
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• 2013

The cell-fate specification of the anchor cell (AC) and a ventral uterine precursor cell (VU) in Caenorhabditis elegans is initiated by a stochastic interaction between LIN-12/Notch receptor and LAG-2/Delta ligand in two neighboring Z1.ppp and Z4.aaa cells. Both cells express lin-12 and lag-2 before specification, and a small difference in LIN-12 activity leads to the exclusive expressions of lin-12 in VU and lag-2 in the AC, through a feedback mechanism of unknown nature. Here we show that the expression pattern of lag-1/CSL, a transcriptional repressor itself that turns into an activator upon binding of the intracellular domain of Notch, overlaps with that of lin-12. Site-directed mutagenesis of LAG-1 binding sites in lag-1 maintains its expression in the AC, and eliminates it in the VU. Thus, AC/VU cell-fate specification appears to involve direct regulation of lag-1 expression by the LAG-1 protein, activating its transcription in VU cells, but repressing it in the AC.

• Wind and Structures
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• v.30 no.4
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• pp.379-392
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• 2020

The paper presents a Life-Cycle Cost-based optimization framework for wind-excited tall buildings equipped with Tuned Mass Dampers (TMDs). The objective is to minimize the Life-Cycle Cost that comprises initial costs of the structure, the control system and costs related to repair, maintenance and downtime over the building's lifetime. The integrated optimization of structural sections and mass ratio of the TMDs is carried out, leading to a set of Pareto optimal solutions. The main advantage of the proposed methodology is that, differently from the traditional optimal design approach, it allows to perform the unified design of both the structure and the control system in a Life Cycle Cost Analysis framework. The procedure quantifies wind-induced losses, related to structural and nonstructural damage, considering the stochastic nature of the loads (wind velocity and direction), the specificity of the structural modeling (e.g., non-shear-type vibration modes and torsional effects) and the presence of the TMDs. Both serviceability and ultimate limit states related to the structure and the TMDs' damage are adopted for the computation of repair costs. The application to a case study tall building allows to demonstrate the efficiency of the procedure for the integrated design of the structure and the control system.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1801-1806
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• 2004

Stochastic nature of subgrid-scale stress causes the predictability problem in large eddy simulation (LES) by which the LES solution field decorrelates with field from filtered directnumerical simulation (DNS). In order to evaluate the predictability limit in a priori sense, the information on the interplay between resolved scale and subgrid-scale (SGS) is required. In this study, the analysis on the inter-scale interaction is performed by applying tophat and cutoff filters to DNS database of flow over a circular cylinder at Reynolds number of 3900. The effect of filter shape is investigated on the interpretation of correlation between scales. A critique is given on the use of tophat filter for SGS analysis using DNS database. It is shown that correlations between Karman vortex and SGS kinetic energy drastically decrease when the cutoff filter is used, which implies that the small scale universality holds even in the presence of the large scale coherent structure.

• Journal of the Korean Geotechnical Society
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• v.19 no.2
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• pp.123-133
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• 2003

A practical statistical approach that can be used to model various sources of uncertainty systematically is presented in the context of reliability analysis of slope stability. New expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. The stochastic nature of seismic loading is studied by generating a large series of hazard-compatible artificial motions, and by using them in subsequent response analyses. The analyses indicate that in a seismically less active region such as the Korean Peninsular, a moderate variability in soil properties has an effect as large as the characterization of earthquake hazard on the computed risk of slope failure and excessive slope deformations.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.151-151
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• 2019

Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.

• Design & Manufacturing
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• v.16 no.3
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• pp.50-57
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• 2022

The qualities of the products produced by injection molding are strongly influenced by the process variables of the injection molding machine set by the engineer. It is very difficult to predict the qualities of the injection molded product considering the stochastic nature of the manufacturing process, since the processing conditions have a complex impact on the quality of the injection molded product. It is recognized that the artificial neural network(ANN) is capable of mapping the intricate relationship between the input and output variables very accurately, therefore, many studies are being conducted to predict the relationship between the results of the product and the process variables using ANN. However in the condition of a small number of data sets, the predicting performance and robustness of the ANN model could be reduced due to too many input variables. In the present study, the ANN model that predicts the length of the injection molded product for multiple combinations of process variables was developed. And the accuracy of each ANN model was compared for 8 process variables and 4 important process inputs that were determined by the feature selection. Based on the comparison, it was verified that the performance of the ANN model increased when only 4 important variables were applied.