• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3855-3863
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• 2022

An evaluation of the radiation shielding performance of high-Z-particle-loaded polylactic acid (PLA) composite materials was pursued. Specimens were produced via fused deposition modeling (FDM) using copper-PLA, steel-PLA, and BaSO₄-PLA composite filaments containing 82.7, 75.2, and 44.6 wt% particulate phase contents, respectively, and were tested under broad-band flash x-ray conditions at the Sandia National Laboratories HERMES III facility. The experimental results for the mass attenuation coefficients of the composites were found to be in good agreement with GEANT4 simulations carried out using the same exposure conditions and an atomistic mixture as a model for the composite materials. Further simulation studies, focusing on the Cu-PLA composite system, were used to explore a shield design parameter space (in this case, defined by Cu-particle loading and shield areal density) to assess performance under both high-energy photon and electron fluxes over an incident energy range of 0.5-15 MeV. Based on these results, a method is proposed that can assist in the visualization and isolation of shield parameter coordinate sets that optimize performance under targeted radiation characteristics (type, energy). For electron flux shielding, an empirical relationship was found between areal density (AD), electron energy (E), composition and performance. In cases where ${\frac{E}{AD}}{\geq}2MeV{\bullet}cm{\bullet}g^{-1}$, a shield composed of >85 wt% Cu results in optimal performance. In contrast, a shield composed of <10 wt% Cu is anticipated to perform best against electron irradiation when ${\frac{E}{AD}}<2MeV{\bullet}cm{\bullet}g^{-1}$.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• Korean Journal of Materials Research
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• v.34 no.5
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• pp.223-234
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• 2024

This review explores the potential of pillared bentonite materials as solid acid catalysts for synthesizing diethyl ether, a promising renewable energy source. Diethyl ether offers numerous environmental benefits over fossil fuels, such as lower emissions of nitrogen oxides (NO_x) and carbon oxides (CO_x) gases and enhanced fuel properties, like high volatility and low flash point. Generally, the synthesis of diethyl ether employs homogeneous acid catalysts, which pose environmental impacts and operational challenges. This review discusses bentonite, a naturally occurring alumina silicate, as a heterogeneous acid catalyst due to its significant cation exchange capacity, porosity, and ability to undergo modifications such as pillarization. Pillarization involves intercalating polyhydroxy cations into the bentonite structure, enhancing surface area, acidity, and thermal stability. Despite the potential advantages, challenges remain in optimizing the yield and selectivity of diethyl ether production using pillared bentonite. The review highlights the need for further research using various metal oxides in the pillarization process to enhance surface properties and acidity characteristics, thereby improving the catalytic performance of bentonite for the synthesis of diethyl ether. This development could lead to more efficient, environmentally friendly synthesis processes, aligning with sustainable energy goals.

• Fire Science and Engineering
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• v.26 no.5
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• pp.21-27
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• 2012

A real A real scale fire test was performed in accordance with KS F ISO 9705 test method to investigate the combustion characteristics of glass wool sandwich panels. To do this, six kinds of specimens having different density and thickness were examined. The glass sandwich panels were installed inside the room, which had internal dimensions of 2.4 m wide${\times}3.6m$ deep${\times}2.4m$ high. also, combustion characteristic are determined through the exposure of specimens to flame by the propane gas burner has a capacity of 100 kW (10 minutes) and 300 kW (10 minutes) for total 25 minutes of test time. Results of the real sale fire test, it was found that maximum HRR of each specimen was 333.2~365.5 kW, maximum heat flux was 12.4~12.9 kW/$m^2$ And, maximum internal temperature for all specimens was not over $500^{\circ}C$. During the real scale fire test, flash-over didn't occur and the difference by density and thickness of specimen was not found from the results of HRR, heat flux, and internal temperature measurement.

• Korean Journal of Plant Resources
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• v.29 no.1
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• pp.128-135
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• 2016

This study examined radiation damage and the optimal gamma-ray dose for mutation breeding in oat (Avena sativa L. cv. Samhan). The seed germination rate decreased as the dose increased over 500 Gy. The median lethal dose (LD₅₀) was approximately 392 Gy. The median reduction dose (RD₅₀) for plant height, tiller number, root length, and flash weight was 411, 403, 394, and 411 Gy, respectively. The optimal dose of gamma irradiation for inducing oat mutation appears to be in the range 300-400 Gy. We performed the comet assay to observe nuclear DNA damage induced by gamma-ray irradiation. This assay showed a clear difference with gamma-ray treatments. DNA damage increased temporarily 7 days after treatment depending on the dose, while no significant difference was identified in response to 300 Gy 30 days after the gamma-ray treatments. The growth characteristics of the M₂ generation decreased as the dose increased over 400 Gy.

• The KIPS Transactions:PartA
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• v.16A no.5
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• pp.357-368
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• 2009

Mobile IP storage has been proposed to overcome storage limitation in the flash memory and hard disks. It provides almost capacity-free space for mobile devices over wireless IP networks. However, battery lifetime of the mobile devices is reduced rapidly because of power consumption with continuous use of a WLAN device when multimedia contents are being streamed through the mobile IP storage. This paper proposes an energy-efficient WLAN device power control technique for streaming multimedia contents with the mobile IP storage. The proposed technique consists of a prefetch buffer input/output module, a WLAN device power control module, and a reconfigurable prefetch buffer module. Besides, it adaptively determines the size of the prefetch buffer according to a quality of the multimedia contents, and it dynamically controls the power mode of the WLAN device on the basis of power on-off operations while streaming the multimedia contents. We evaluate the performance of the proposed technique on a PXA270-based mobile device that employs the embedded linux 2.6.11, Intel iSCSI reference codes, and a WLAN device. Extensive experiments reveal that the proposed technique can save the energy consumption of the WLAN device up to 8.5 times with QVGA multimedia contents, as compared with no power control.

• Journal of Radiation Industry
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• v.8 no.2
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• pp.89-95
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• 2014

This study was conducted to determine the optimal dose of gamma-ray on the growth and nucleus DNA damage for mutation breeding in licorice. Gamma-rays irradiated to dry seeds with various doses (0 to 1000 Gy). Significant decreases in germination rate (%), survival rate (%) and growth characteristics (plant height, number of leaves, root length and fresh weight) were observed by dose of increased. $LD_{50}$ (lethal dose) was approximately 400 Gy to 500 Gy. Also, reduction doses ($RD_{50}$) of plant height, number of leaves, root length and flash weight were 428 Gy, 760 Gy, 363 Gy and 334 Gy, respectively. It is supplest that the optimal dose of gamma irradiation for licorice mutation induction might be about 400 Gy in this study. We also conducted comet assay to observe nucleus DNA damage due to gamma irradiation. In comet assay, a clear difference was identified over 300 Gy treatments. With increasing doses of gamma-ray in the range of 100 to 1000 Gy, the rate of head DNA was decreased significantly from 92.88% to 73.09%. Tail length(${\mu}m$) was increased as the dose of increased over 300 Gy. Growth characteristics (Germination rate, Survival rate, plant height, number of leaves, root length and fresh weight) were highly negatively ($P{\leq}0.01$) correlated with dose. While the tail length was highly positively ($P{\leq}0.01$) correlated with dose.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.75-85
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• 2009

This work proposes a 13b 100MS/s 0.13um CMOS ADC for 3G communication systems such as two-carrier W-CDMA applications simultaneously requiring high resolution, low power, and small size at high speed. The proposed ADC employs a four-step pipeline architecture to optimize power consumption and chip area at the target resolution and sampling rate. Area-efficient high-speed high-resolution gate-bootstrapping circuits are implemented at the sampling switches of the input SHA to maintain signal linearity over the Nyquist rate even at a 1.0V supply operation. The cascode compensation technique on a low-impedance path implemented in the two-stage amplifiers of the SHA and MDAC simultaneously achieves the required operation speed and phase margin with more reduced power consumption than the Miller compensation technique. Low-glitch dynamic latches in sub-ranging flash ADCs reduce kickback-noise referred to the differential input stage of the comparator by isolating the input stage from output nodes to improve system accuracy. The proposed low-noise current and voltage references based on triple negative T.C. circuits are employed on chip with optional off-chip reference voltages. The prototype ADC in a 0.13um 1P8M CMOS technology demonstrates the measured DNL and INL within 0.70LSB and 1.79LSB, respectively. The ADC shows a maximum SNDR of 64.5dB and a maximum SFDR of 78.0dB at 100MS/s, respectively. The ABC with an active die area of $1.22mm^2$ consumes 42.0mW at 100MS/s and a 1.2V supply, corresponding to a FOM of 0.31pJ/conv-step.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Energy Engineering
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• v.22 no.2
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• pp.237-244
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• 2013

The engine oil is used for lubrication of various internal combustion engines. Recently, the vehicle and engine oil manufacture usually guarantee for oil change over 15000~20000 km mileage, but the most of driver usually change engine oil every 5000 km driving in korea. It can cause to raise environmental contamination by used engine oil and increase the cost of driving by frequently oil change. In this study, we investigate the various physical properties such as flash point, pour point, kinematic viscosity, cold cranking simulator characteristics, total acid number, four-ball test and concentration of metal component for fresh engine oil and used engine oil after real vehicle driving (5000 km, 10000 km). The result showed that the total acid number, wear scar diameter by four-ball test, Fe and Cu had increased than fresh engine oil, but 2 kind of used oil (5000 km and 10000km) had similar physical values and concentration of metal component.