• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.34.1-34.1
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• 2009

After SNIa and WMAP observations during the last decade, the discovery of the accelerated expansion of the universe is a major challenge to particle physics and cosmology. There are currently three candidates for the dark energy which results in this accelerated expansion: $\cdot$ a non-zero cosmological constant, $\cdot$ a dynamical cosmological constant (quintessence scalar field), $\cdot$ modifications of Einstein's theory of gravity. The scalar field model like quintessence is a simple model with time-dependent w, which is generally larger than -w1. Because the different w lead to a different expansion history of the universe, the geometrical measurements of cosmic expansion through observations of SNIa, CMB and baryon acoustic oscillations (BAO) can give us tight constraints on w. One of the interesting ways to study the scalar field dark-energy models is to investigate the coupling between the dark energy and the other matter fields. In fact, a number of models which realize the interaction between dark energy and dark matter, or even visible matter, have been proposed so far. Observations of the effects of these interactions will offer an unique opportunity to detect a cosmological scalar field. In this talk, after briefly reviewing the main idea of the three possible candidates for dark energy and their cosmological phenomena, we discuss the interactinng dark-energy model, paying particular attention to the interacting mechanism between dark energy with a hot dark matter (neutrinos). In this so-called mass-varying neutrino (MVN) model, we calculate explicitly the cosmic microwave background (CMB) radiation and large-scale structure (LSS) within cosmological perturbation theory. The evolution of the mass of neutrinos is determined by the quintessence scalar field, which is responsible for the cosmic acceleration today.

• Korean Journal of Construction Engineering and Management
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• v.17 no.4
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• pp.20-27
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• 2016

Emergency and evacuation planning is critical to reduce potential loss of life from flooding. In order to develop evacuation plans, emergency managers and decision makers require estimates of probable inundation areas and times of inundation. In this paper, we present an agent-based modeling approach that incorporates in a hydrodynamic model to estimate both of these properties. A case study is conducted modeling the failure of a dam located in Andong, South Korea. We estimate flood travel times for Manning's roughness coefficients and discharge using a coupling of the continuity equation and Manning's equation. Using the output from the hydrodynamic model and the flood travel times, the agent-based model produces flood inundation maps at each time interval. The model estimates that for two-thirds of the Andong region the time of inundation is estimated to be slightly less than three minutes. The results of this study can be used to in the development of emergency and evacuation planning for the region.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.58-74
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• 2022

Deterministic accident analysis plays a central role in the nuclear power plant (NPP) safety evaluation and licensing process. Traditionally the conservative approach opted for the point kinetics model, expressing the reactor core parameters in the form of reactivity and power tables. However, with the current advances in computational power, high fidelity multi-physics simulations using real-time code coupling, can provide more detailed core behavior and hence more realistic plant's response. This is particularly relevant for transients where the core is undergoing reactivity anomalies and uneven power distributions with strong feedback mechanisms, such as reactivity initiated accidents (RIAs). This work addresses a RIA, specifically a control element assembly (CEA) withdrawal at power, using the multi-physics analysis tool RELAP5/MOD 3.4/3DKIN. The thermal-hydraulics (TH) code, RELAP5, is internally coupled with the nodal kinetics (NK) code, 3DKIN, and both codes exchange relevant data to model the nuclear power plant (NPP) response as the CEA is withdrawn from the core. The coupled model is more representative of the complex interactions between the thermal-hydraulics and neutronics; therefore the results obtained using a multi-physics simulation provide a larger safety margin and hence more operational flexibility compared to those of the point kinetics model reported in the safety analysis report for APR1400. The systems engineering approach is used to guide the development of the work ensuring a systematic and more efficient execution.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Steel and Composite Structures
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• v.52 no.2
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• pp.237-248
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• 2024

In order to make the dynamic analysis and design of improved composite beam with corrugated steel web (CBGSCC) bridge more efficient and economical, the parametric self-cyclic analysis model (SCAM) was written in Python on Anaconda platform. The SCAM can call ABAQUS finite element software to realize automatic modeling and dynamic analysis. For the CBGSCC bridge, parameters were set according to the general value range of CBGSCC bridge parameters in actual engineering, the SCAM was used to calculate the large sample model generated by parameter coupling, the optimal value range of each parameter was determined, and the sensitivity of the parameters was analyzed. The number of diaphragms effects weakly on the dynamic characteristics. The deck thickness has the greatest influence on frequency, which decreases as the deck thickness increases, and the deck thickness should be 20-25 cm. The vibration frequency increases with the increase of the bottom plate thickness, the web thickness, and the web height, the bottom plate thickness should be 17-23mm, the web thickness should be 13-17 mm, and the web height should be 1.65-1.7 5 m. Web inclination and Skew Angle should not exceed 30°, and the number of diaphragms should be 3-5 pieces. This method can be used as a new method for structural dynamic analysis, and the importance degree and optimal value range of each parameter of CBGSCC bridge can be used as a reference in the design process.

• The Journal of the Acoustical Society of Korea
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• v.43 no.5
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• pp.547-556
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• 2024

To predict the response of dynamic systems through analysis, it is essential to accurately estimate the system's stiffness and apply it to the analytical model. However, directly measuring the stiffness of actual mechanical systems is challenging. Many existing methods involve decomposing the system into components, obtaining the frequency response for each component, and then reassembling them to determine the overall system response. This process can be cumbersome, and variations in coupling conditions between components can increase errors. In this study, a new method is proposed to estimate system stiffness indirectly through experiments without decomposing the system into components. The approach combines response measurements from the entire system with a theoretical model for analysis. It simplifies the stiffness source into a lumped mass model and constructs the equations of motion based on a reduced-order model of the entire system. Subsequently, the stiffness is quantified by calculating the interface forces between the stiffness source and the receiver using vibration measurements obtained at arbitrary positions through experimentation.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.308-308
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• 2017

The low and unstable yield of soybean has been a major problem in Japan. Excess soil moisture conditions are one of the major factors to restrict soybean productivity. More than 80 % of soybean crops are cultivated in converted paddy fields which often have poor drainage. In central and eastern regions of Japan, the early vegetative growth of soybean tends to be restricted by the flooding damage because the early growth period is overlapped with the rainy season. Field observation shows that induced excess water stress in early vegetative stage reduces dry matter production by decreasing intercepted radiation by leaf and radiation use efficiency (RUE) (Bajgain et al., 2015). Therefore, it is necessary to evaluate the responses of soybean growth for excess water conditions to assess these effects on soybean productions. In this study, we aim to modify the soybean crop model (Sinclair et al., 2003) by adding the components of the restriction of leaf area development and RUE for adaptable to excess water conditions. This model was consist of five components, phenological model, leaf area development model, dry matter production model, plant nitrogen model and soil water balance model. The model structures and parameters were estimated from the data obtained from the field experiment in Tsukuba. The excess water effects on the leaf area development were modeled with consideration of decrease of blanch emergence and individual leaf expansion as a function of temperature and ground water level from pot experiments. The nitrogen fixation and nitrogen absorption from soil were assumed to be inhibited by excess water stress and the RUE was assumed to be decreasing according to the decline of leaf nitrogen concentration. The results of the modified model were better agreement with the field observations of the induced excess water stress in paddy field. By coupling the crop model and the ground water level model, it may be possible to assess the impact of excess water conditions for soybean production quantitatively.

• Journal of the Korean Institute of Gas
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• v.22 no.4
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• pp.39-48
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• 2018

This study presents optimal design of gas lift considering composition of reservoir oil and injected gas which can affect gas lift performance in offshore oil reservoir. Reservoir simulation was conducted by using reservoir models which were built in accordance with API gravity of oil. The results of simulation reveal that oil production rate is considerably increased by gas lift when the reservoir productivity decrease. As a results of response curve analysis for gas lift using well models, gas injection rate to improve the production rate increases as the API gravity of oil decreases and the specific gravity of injected gas increases. The optimal design of gas lift was carried out using multiple lift valves. Consequently, gas lift can be operated at relatively low injection pressure because of decrease in injection depth in comparison to the single lift valve design. The improved oil production rates were analyzed by coupling between reservoir model and well model. As a results of the coupling, it is expected that natural gas injection in the heavy oil reservoir is the most efficient method for improving oil production by gas lift.

• Journal of the Korean Magnetics Society
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• v.13 no.3
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• pp.97-102
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• 2003

Synthetic ferrimagnetic layer (SyFL) with structure NiFe/Ru/NiFe which can be applied high density TMR device in free layer were prepared by an inductively coupled plasma (ICP) helicon-sputter. We proposed a model of predicting coercivity (H$\_$c/), spin-flopping field (H$\_$sf/), and saturation field (H$\_$s/) as a function of Ru thicknesses, from the equilibrium state of energies of Zeeman, exchange, and uniaxial anisotropy. We fabricated the samples of Ta(50 ${\AA}$)/NiFe(50${\AA}$)nu(4∼20${\AA}$)NiFe(30 ${\AA}$)/Ta(50${\AA}$), and measured the M-H loops with a superconduction quantum interference device (SQUID) applying the external field up to ${\pm}$ 15 kOe. The result was well agreed with the proposed model, and reveal K$\_$u = 1000 erg/㎤, J$\_$ex/ =0.7 erg/$\textrm{cm}^2$. We report that H$\_$c/ below 10 Oe is available, and R$\_$u/ thickness range should be in 4-10 ${\AA}$ for MRAM application. Our result implies that permalloy layers may lead to considerable magnetostriction effect in SyFL and intermixing in NiFe/Ru interfaces.

• Journal of the Korean Magnetics Society
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• v.24 no.5
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• pp.140-145
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• 2014

We analyzed the MnIr thickness dependence of torque signals measured in exchange coupled CoFe/MnIr ($t_{AF}$) bilayers. The measured torque signals were compared with calculated ones by Stoner-Wohlfarth model. The exchange coupling anisotropy $J_c$ was considered for the model calculation between ferromagnetic (F) and antiferromagnetic (AF) layers with uniaxial anisotropy constant of $K_F$ and $K_{AF}$, respectively. The rotational losses were appeared in the range of $0.5t_c$ < $t_{AF}$ < $t_c$ ($=J_c/K_{AF}$) by the unpinned AF layer. While, the unidirectional anisotropy ($J_k$) was caused by the pinned AF layer at $t_{AF}$ > $t_c$. The critical thickness of MnIr layer was $t_c$ = 3.4 nm in CoFe/MnIr bilayers. The rotational losses behavior as shown in $t_{AF}$ = 3 nm sample were explained by the random orientation of the easy axis of AF grains. The unidirectional anisotropy obtained from torque signal of $t_{AF}$ = 10 nm sample was $J_k=0.63J_c$. Thus, the unidirectional anisotropy can be enhanced up to $J_k=J_c$ by aligning the AF easy axis.