• Structural Engineering and Mechanics
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• v.28 no.6
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• pp.677-694
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• 2008

A vibration power minimization model is developed, based on the mobility matrix method, for a vibration isolation system consisting of a vibrating source placed on an elastic support structure through multiple resilient mounts. This model is applied to investigate the design optimization of an X-Y motion stage-based vibration isolation system used in semiconductor wire-bonding equipment. By varying the stiffness coefficients of the resilient mounts while constraining the dynamic displacement amplitudes of the X-Y motion stage, the total power flow from the X-Y motion stage (the vibrating source) to the equipment table (the elastic support structure) is minimized at each frequency interval in the concerned frequency range for different stiffnesses of the equipment table. The results show that when the equipment table is relatively flexible, the optimal design based on the proposed vibration power inimization model gives significantly little power flow than that obtained using a conventional vibration force minimization model at some critical frequencies. When the equipment table is rigid enough, both models provide almost the same predictions on the total power flow.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.958-967
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• 2023

This work studies the defect features in a dilute FeMnNi alloy by an Object Kinetic Monte Carlo (OKMC) model based on the "grey-alloy" method. The dose rate effect is studied at 573 K in a wide range of dose rates from 10^-8 to 10^-4 displacement per atom (dpa)/s and demonstrates that the density of defect clusters rises while the average size of defect clusters decreases with increasing dose rate. However, the dose-rate effect decreases with increasing irradiation dose. The model considered two realistic mechanisms for producing <100>-type self-interstitial atom (SIA) loops and gave reasonable production ratios compared with experimental results. Our simulation shows that the proportion of <100>-type SIA loops could change obviously with the dose rate, influencing hardening prediction for various dose rates irradiation. We also investigated ways to compensate for the dose rate effect. The simulation results verified that about a 100 K temperature shift at a high dose rate of 1×10^-4 dpa/s could produce similar irradiation microstructures to a lower dose rate of 1×10^-7 dpa/s irradiation, including matrix defects and deduced solute migration events. The work brings new insight into the OKMC modeling and the dose rate effect of the Fe-based alloys.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2452-2459
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• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Proceedings of the Korean Magnestics Society Conference
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• 2003.12a
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• pp.113-113
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• 2003

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.966-969
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• 2006

An optical model based on the optical thin-film theory is derived to calculate the output radiance of small molecules organic light-emitting diodes (OLEDs). We have designed the high efficiency OLEDs using the reflectance phase control of dielectric layers. It is found that OLED with a single $TiO_2$ dielectric layer is a good candidate to enhance the outcoupling efficiency and increase the color purity.

• Bulletin of the Korean Mathematical Society
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• v.56 no.5
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• pp.1355-1376
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• 2019

We investigate the valuation of participating life insurance policies with default risk under a geometric regime-switching jump-diffusion process. We derive explicit formula for the Laplace transform of the price of participating contracts by solving integro-differential system and then price them by inverting Laplace transforms.

• Proceedings of the Korean Biophysical Society Conference
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• 1998.06a
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• pp.15-15
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• 1998

Pores can form and grow in biomembranes because of factors such as thermal fluctuation, transmembrane electrical potential, and cellular environment. We propose a new statistical physics model of the pore growth treated as a non-Markovian stochastic process, with a free energy barrier and memory friction from the membrane matrix treated as a quasi-two-dimensional viscoelastic and dielectric fluid continuum.(omitted)

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.64.2-64.2
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• 2016

Optical variability is one way to probe the nature of the central engine of AGN at smaller linear scales and previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. Especially, intra-night variability can be explained through the damped random walk model but small samples and inhomogeneous data have made constraining this model hard. To understand the properties and physical mechanism of optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Test data of KMTNet in the COSMOS field was obtained over 2 separate nights during 2015, in B, V, R, and I bands. Each night was composed of 5 and 9 epochs with ~30 min cadence. To find AGN in the COSMOS field, we applied multi-wavelength selection methods. Different selection methods means we are looking different region in unification model of AGN, and 100~120, 400~500, 50~100 number of AGN are detected in X-ray, mid-infrared, and radio selection of AGN, respectively. We performed image convolution to reflect seeing fluctuation, then differential photometry between the selected AGN and nearby stars to achieve photometric uncertainty ~0.01mag. We employed one of the standard time-series analysis tools to identify variable AGN, chi-square test. Preliminarily results indicate that intra-night variability is found for X-ray selected, Type1 AGN are 23.6%, 26.4%, 21.3% and 20.7% in the B, V, R, and I band, respectively. The majority of the identified variable AGN are classified as Type 1 AGN, with only a handful of Type 2 AGN showing evidence for variability. The work done so far confirms that there are type and wavelength dependence of intra-night optical variability of AGN.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.55.3-55.3
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• 2019

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a (75 h^-1 Mpc)³ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large (1 h^-1 Gpc)³ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1165-1203
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• 2024

In the paper we validate theoretical models of the pulse against experimental data from the Jozef Stefan Institute TRIGA Mark II research reactor. Data from all pulse experiments since 1991 have been collected, analysed and are publicly available. This paper summarizes the validation study, which is focused on the comparison between experimental values, theoretical predictions (Fuchs-Hansen and Nordheim-Fuchs models) and calculation using computational program Improved Pulse Model. The results show that the theoretical models predicts higher maximum power but lower total released energy, full width at half maximum and the time when the maximum power is reached is shorter, compared to Improved Pulse Model. We evaluate the uncertainties in pulse physical parameters (maximum power, total released energy and full width at half maximum) due to uncertainties in reactor physical parameters (inserted reactivity, delayed neutron fraction, prompt neutron lifetime and effective temperature reactivity coefficient of fuel). It is found that taking into account overestimated correlation of reactor physical parameters does not significantly affect the estimated uncertainties of pulse physical parameters. The relative uncertainties of pulse physical parameters decrease with increasing inserted reactivity. If all reactor physical parameters feature an uncorrelated uncertainty of 10 % the estimated total uncertainty in peak pulse power at 3 $ inserted reactivity is 59 %, where significant contributions come from uncertainties in prompt neutron lifetime and effective temperature reactivity coefficient of fuel. In addition we analyse contribution of two physical mechanisms (Doppler broadening of resonances and neutron spectrum shift) that contribute to the temperature reactivity coefficient of fuel. The Doppler effect contributes around 30 %-15 % while the rest is due to the thermal spectrum hardening for a temperature range between 300 K and 800 K.