• Journal of Pharmacopuncture
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• v.22 no.2
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• pp.90-94
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• 2019

Objectives: Paclitaxel (PTX) as an anticancer drug used against solid cancers, possesses adverse reactions such as neuropathic pain which has confined its use. PTX-induced neuropathic pain is mediated via activation of oxidative stress. Berberine (BER), an isoquinoline phytochemical found in several plants, exerts strong antioxidant and painkilling properties. In the current study, we aimed to evaluate pain-relieving effect of BER in a mouse model of PTX-induced neuropathic pain. Methods: This study was done using 42 male albino mice that were randomly divided into 6 groups (n = 7) as follow: Sham-operated (not treated with PTX), negative control group (PTX-treated mice receiving normal saline), BER 5, 10, and 20 mg/kg (PTX-treated mice receiving BER) and positive control group (PTX-treated mice receiving imipramine 10 mg/kg). Neuropathic pain was induced by intraperitoneal administration of four doses of PTX (2 mg/kg/day) on days 1, 3, 5 and 7. Then, on day 7, hot plate test was done to assess latency to heat to measure possible anti-neuropathic pain effect of BER. Results: Four doses of PTX 2 mg/kg/day induced neuropathy that was reduced by BER at all time-points (i.e. 0, 30, 60, 90 and 120 min) after injection (P < 0.001 in comparison to control). The statistical analysis of data showed significant differences between groups (P < 0.001 in comparison to negative control), at 30, 60, 90 and 120 min after injection of BER 5, 10 and 20 mg/kg; in other words, 30, 60, 90 and 120 min after BER administration, neuropathic pain was significantly reduced as compared to normal saline-treated mice. Conclusion: Altogether, our results showed that PTX could induce neuropathic pain as reflected by hyperalgesia and BER could alleviate PTX-induced thermal hyperalgesia.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.51-57
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• 2021

The quality of the ceramic sintered coating on a metal surface through laser surface treatment is affected by the laser irradiation pattern. Depending on the laser irradiation pattern, the amount of residual stress and heat applied or accumulated on the surface increases or decreases, affecting the thickness attained in the ceramic sintering area. When the heat energy accumulated in the sintering area is high, the ceramic and the metal alloy melt and sufficiently mix to form a homogeneous and thick bonding interface. In this study, the thermal energy accumulation in the region sintered with zirconia was controlled using four types of laser processing patterns. The thickness of the diffusion region is analyzed by laser-induced breakdown spectroscopy of Mg-ZrO2 generated by laser sintering zirconia powder on the magnesium alloy surface. On the basis of the analysis of the Mg and Zr present in the sintered region through LIBS, the effect of the irradiation pattern on the sintering quality is confirmed by comparing and analyzing the heat and mass transfer tendency of the diffusion layer and the degree of diffusion according to the irradiation pattern. The derived diffusion coefficients differed by up to 9.8 times for each laser scanning pattern.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.2
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• pp.51-57
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• 2021

This paper analyzed the effects of the concentration of nano-silica particles contained in epoxy resin on the thermomechanical properties of the composite materials. The 12nm sized nanoparticles were mixed with epoxy polymer by 5 different weight ratios for the test samples. The glass transition temperature, stress relaxation, and thermal expansion behaviors were measured using dymanic mechanical analyzer (DMA) and thermomechanical analyzer (TMA). It was shown that the nano particle mixing ratios had significant influences on the viscoelastic behaviors of the materials. As the content of the silica particles was increased, the elastic modulus was also increased, while the glass transition temperatures were decreased. Fourier Transform Infrared Spectroscopy (FTIR) results played an important role in determining the causes of the property changes by the filler contents in terms of the molecular structures, enabling the interpretations on the material behaviors based on the chemical structure changes.

• Korean Journal of Metals and Materials
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• v.46 no.10
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• pp.646-651
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• 2008

The electrolytic reduction of spent oxide fuel involves the liberation of oxygen in a molten LiCl electrolyte, which results in a chemically aggressive environment that is too corrosive for typical structural materials. It is essential to choose the optimum material for the process equipment handling molten salt. IN713LC is one of the candidate materials proposed for application in electrolytic reduction process. In this study, yttria-stabilized zirconia (YSZ) top coat was applied to a surface of IN713LC with an aluminized metallic bond coat by an optimized plasma spray process, and were investigated the corrosion behavior at $675^{\circ}C$ for 216 hours in the molten salt $LiCl-Li_2O$ under an oxidizing atmosphere. The as-coated and tested specimens were examined by OM, SEM/EDS and XRD, respectively. The bare superalloy reveals obvious weight loss, and the corrosion layer formed on the surface of the bare superalloy was spalled due to the rapid scale growth and thermal stress. The top coatings showed a much better hot-corrosion resistance in the presence of $LiCl-Li_2O$ molten salt when compared to those of the uncoated superalloy and the aluminized bond coatings. These coatings have been found to be beneficial for increasing to the hot-corrosion resistance of the structural materials for handling high temperature lithium molten salts.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.199-207
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• 2021

This study aimed to improve the performance of the KTX (Korea Train Express) brake system. To develop a braking disc-hub for the high-speed rail, the model performance was analyzed by finite element analysis, and the analysis results were verified using the braking test results. In addition, heat transfer analysis, thermal stress analysis, natural frequency analysis, and static analysis were conducted to examine the mechanical performance of the braking system. By deriving the design factors and conducting parametric analyses according to the shape of the hub, this study derived the optimal specifications that could improve heat dissipation and reduce weight. The cooling efficiency and structural performance of the optimization model were improved during braking compared to the existing model. It is expected that the design verification will be carried out through analyses of the optimal specifications so that it can be used in the development of brakes in railway vehicles and motor vehicles.

• Conservation Science in Museum
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• v.27
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• pp.91-102
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• 2022

Silica-based inorganic fillers for restoration of iron objects have been used for the reduction of thermal expansivity and the improvement of melt flow index. However, the higher the amount of filler is applied, the more degradation of mechanical properties and the yellowing occur, which could cause retreatment of the objects with adding stress to them. Thus, research on not only the quantification of a mixture of resin and filler but also the yellowing should be emphasized. Experiments on mechanical properties were carried out with a silica-based light filler, Micro Shell as a comparison group. The results of the experiment showed Micro Shell reduced the number of occurrences of the yellowing by 34% compared to existing fillers. The value of adhesion and specific gravity was also improved depending on the filler amount. The results of this research indicate the possibility of using Micro Shell as a new filler.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.3
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• pp.159-166
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• 2022

In this study, slender reinforced concrete columns subjected to high temperatures and eccentric axial loads are evaluated by finite element analysis employing Abaqus (a finite element analysis program). Subsequently, the analysis results are compared and assessed. The sequentially coupled thermal stress analysis provided by Abaqus was employed to reflect the condition of an axially loaded column exposed to fire. First, heat transfer analysis was performed on the column cross-section. After verifying the results, another analysis was conducted: the cross-section was transformed into a three-dimensional element and then structural analyzed. In the analysis process, the column was modeled by accounting for the effects of tension stiffening and initial imperfection that could affect convergence and accuracy. The analysis results were compared with 74 experimental records, and an average error of 6% was observed based on the fire exposure and resistance. The foregoing indicates that the fire resistance performance of reinforced concrete columns can be predicted through finite element analysis.

• Composites Research
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• v.34 no.6
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• pp.337-344
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• 2021

In this study, the progressive failure behavior of the composite fan blade dovetail element under tensile loading is numerically investigated through finite element(FE) simulation. The accuracy of prediction by FE simulation is verified through tensile testing. The dovetail element is one of the joints for coupling the fan blade with the disk in a turbofan engine. The dovetail element is usually made of a metal material such as titanium, but the application of composite material is being studied for weight reduction reasons. However, manufacturing defects such as drop-off ply and resin pocket inevitably occur in realizing complex shapes of the fan blade made by composite materials. To investigate the effect of these manufacturing defects on the composite fan blade dovetail element, we performed numerical simulation with FE model to compare the prediction of the FE model and the tensile test results. At this time, the cohesive zone model is used to simulate the delamination behavior. Finally, we found that FE simulation results agree with test results when considering thermal residual stress and through-thickness compression enhancement effect.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.411-434
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• 2022

In deep geological disposal concept for spent nuclear fuel, it is well-known that rock mass at near-field experiences the thermal-hydraulic-mechanical (THM) coupled behavior. The mechanical properties of rock changes during the coupled process, and it is important to consider the changes into the analysis of numerical simulation and in-situ tests for long-term stability evaluation of nuclear waste disposal repository. This report collected the previous studies on indirect coupled behaviors of rock. The effects of water saturation and temperature on some mechanical properties of rock was considered, while the change in hydraulic conductivity of rock due to stress was included in the indirect coupled behavior.

• 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.