• Journal of the Korean Applied Science and Technology
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• v.31 no.3
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• pp.446-452
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• 2014

Methanol was directly produced by the partial oxidation of methane with four-component mixed oxide catalysts. Four-component(Mo-Bi-Cr-Si) mixed oxide catalysts were prepared by the co-precipitation and sol-gel methods. The catalyst prepared by the sol-gel method showed about eleven times higher surface area than that prepared by the co-precipitation method. From the $O_2$-TPD experiment of the prepared catalysts, it was proven that there exists two types of oxygen species, and the oxygen species that participates in the partial oxidation reaction is the lattice oxygen desorbing around $750^{\circ}C$. The optimum reaction condition for methanol production was $420^{\circ}C$, 50 bar, flow rate of 115 mL/min, and $CH_4/O_2$ ratio of 10/1.5, providing methane conversion and methanol selectivity of 3.2 and 26.7%, respectively.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.39-47
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• 2017

Precipitation is an important component for hydrological and water control study. In general, AWS data provides more accurate but low dense information for precipitation while radar data gives less accurate but high dense information. The objective of this study is to construct adjusted precipitation field based on hierarchical spatial model combining radar data and AWS data. Here, we consider a Bayesian hierarchical model with spatial structure for hourly accumulated precipitation. In addition, we also consider a redistribution of hourly precipitation to 2.5 minute precipitation. Through real data analysis, it has been shown that the proposed approach provides more reasonable precipitation field.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.41-50
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• 2024

Precipitation is an important component of the hydrological cycle and a key input parameter for many applications in hydrology, climatology, meteorology, and weather forecasting research. Grid-based satellite rainfall products with wide spatial coverage and easy accessibility are well recognized as a supplement to ground-based observations for various hydrological applications. The error properties of satellite rainfall products vary as a function of rainfall intensity, climate region, altitude, and land surface conditions. Therefore, this study aims to evaluate the commonly used new global grid-based satellite rainfall product, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), using data collected at different spatial and temporal scales. Additionally, in this study, grid-based CHIRPS satellite precipitation data were used to evaluate the 2022 extreme drought. CHIRPS provides high-resolution precipitation data at 5 km and offers reliable global data through the correction of ground-based observations. A frequency analysis was performed to determine the precipitation deficit in 2022. As a result of comparing droughts in 2015, 2017, and 2022, it was found that May 2022 had a drought frequency of more than 500 years. The 1-month SPI in May 2022 indicated a severe drought with an average value of -1.8, while the 3-month SPI showed a moderate drought with an average value of 0.6. The extreme drought experienced in South Korea in 2022 was evident in the 1-month SPI. Both CHIRPS precipitation data and observations from weather stations depicted similar trends. Based on these results, it is concluded that CHIRPS can be used as fundamental data for drought evaluation and monitoring in unmeasured areas of precipitation.

• Atmosphere
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• v.33 no.5
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• pp.457-475
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• 2023

Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

• Resources Recycling
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• v.28 no.5
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• pp.42-50
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• 2019

In this study, the precipitation reaction of vanadium and ammonium chloride in aqueous solution was investigated in order to recover vanadium. Ammonium metavanadate having a crystal structure of [$NH_4VO_3$] was precipitated from aqueous solution containing vanadium at pH 9.2 ~ 9.4, and ammonium polyvanadate having a crystal structure of [$(NH_4)_2V_6O_{16}$] was precipitated when the pH of the aqueous solution containing vanadium was adjusted with sulfuric acid. Ammonium polyvanadate [$(NH_4)_2V_6O_{16}$] precipitated at a temperature of $80{\sim}90^{\circ}C$ and pH 2, and at a temperature of $40^{\circ}C$ and pH 6 ~ 8 of aqueous solution. In the acidic region of aqueous solution pH 2, the vanadium content of the aqueous solution should be at least 3,000 mg/L and the precipitation temperature should be maintained at $80^{\circ}C$ or higher in order to obtain a precipitation ratio of 99% or more. When the ammonium vanadate was precipitated in the alkaline region, the vanadium content was more than 10,000 mg/L and the precipitation temperature was maintained at $40^{\circ}C$ to increase the precipitation ratio. Aluminum was not precipitated regardless of the vanadium content and pH of the aqueous solution. However, the iron component reacts with ammonium chloride to precipitate into ammonium jarosite. Therefore, Fe component must be preferentially removed in order to increase the recovery of vanadium.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Journal of Environmental Science International
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• v.6 no.5
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• pp.461-472
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• 1997

This study was carried out to investigate the characteristics of chemical components and precipitation at Kimhae area from March, 1992 to June, 1994. The pH values, concentration of soluble ions($Cl^-$, $NO_2^-}$ $NO_3^-}$, $NO_4^{2-}$-, $PO_4^{3-}$. $F^-$, $Mg^{2+}$, $Ca^{2+}$, $Mn^{2+}$, $K^+) and non-soluble metals(Cr.Si. Zn, Pb, Cu, Fe, Mn, Mg, Ad. V. Cal were measured by pH meter, IC (ion Chromatography) and ICP(Inductively Coupled Plasma). The data were analyzed by the dally. hourly distribution characteristics of acidity and chemical components, as well as the correlation between them. The results are as follows. 1. The pH range of precipitation was from 3.45 to 6.80 in Kimhae area. and average value was pH 4.62 and main chemical components were $SO_4^{2-}$, $Cl^-$, $NO_3^-$. The highest pH value and concentration appeared in initial rain, which might result from urbanlzation and industrialization in this area and long term transportation from China. 2. The hourly correction distribution of main anions related to pH value In the rainwater showed $SO_4^{2-}$ > $NO_3^-$ > $Cl^-$. Hourly concentration of heavy metal and each ion was highly correlated with pH in the precipitation.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.6
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• pp.589-598
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• 1998

This study was conducted to investigate the chemical characteristics of Precipitation at Seoul, Yangpyong, Hongchon and Inje in the central part of Korean peninsula during the period from March 1994 to November 1997. The precipitation samples were collected by automatic wet-only sampler. The samples were analyzed for major anions (SO42-, NO3-, Cl-, F-) and cations(NH4+, Ca2+, Mg+, Na+, K+), in addition to acidity and electrical conductivity. The analytical instrument for water soluble ionic components was ion chromatography. The volume - weighted mean PH were 4.73, 4.87, 4.89 and 4.81 at Seoul, Yangpyong, Hongchon and Inje, respectively. The sums of cation concentrations was slightly greater than the sums of anion concentrations. Also, the highest ion component was SO42- in anions and NH4+ in cations. The mean equivalent ratios of SO42- to NO3- were found by 2.96, 2.71, 2.43 and 2.25 at Seoul, Yangpyong, Hongchon and Inje, respectively. The factor analysis was conducted in order to make the large and diverse data set as manageable levels and to qualitatively examine the relationship between the variables. It showed that major sources of pollutants in precipitation were from the anthropogenic in Seoul, the natural in Hongchon, and the anthropogenic and natural in Yangpyong and Inje.

• Journal of the Korean Applied Science and Technology
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• v.30 no.4
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• pp.649-655
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• 2013

Methanol was directly produced by the partial oxidation of methane with perovskite and mixed oxide catalysts. Perovskite ($ABO_3$) catalysts were prepared by the malic acid method with changing A and B site components. Three-component mixed oxide catalysts that have Mo and Bi as a main component were prepared by the co-precipitation method. Among the perovskite catalysts, $SrCrO_3$ showed the highest methanol selectivity of 11% at $400^{\circ}C$. For the three-component mixed oxide catalysts, there were no remarkable changes in methane conversion. Among the mixed oxide catalysts, Mo-Bi-Cr mixed oxide catalyst showed the highest methanol selectivity of 15.3% at $400^{\circ}C$. The catalytic activity and methanol selectivity of the three-component mixed oxide catalysts were directly proportional to the surface area of the catalysts.

• Journal of the Korean Society for Heat Treatment
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• v.35 no.6
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• pp.303-313
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• 2022

The purpose of this study was to test and analyze the effects of the mechanical properties and structural changes of the austenitized and tempered martensite STS 410 stainless steel containing 11.5~13%Cr and 0.10%C on its temper embrittlement. The STS 410 stainless steel test pieces for each 3 hours at 960℃, 1000℃ and then, tempered them for 2 hours at 300℃, 350℃, 400℃, 450℃, 500℃, 550℃, 600℃, 650℃ and 700℃ known as the intervals vulnerable to temper embrittlement to observe the changes of their structures and mechanical properties. In case autenitizing was insufficient due to lower temperature of thermal treatment for solution, unsolved carbides and ferrites remained in the structure after quenching, which meant that the parts could wear out and corrode to embrittle at the room temperature. Elongation and impact energy changes with Tempering conditions showed minimum results in range of 400~500℃. The decrease in elongation and impact energy at 400~500℃ was the hardening effect of the subgrain due to the precipitation of many M₃C or M₇C₃, M₂₃C₆. And STS 410 stainless steel corrosion tested in 10% NaCl solution at 30℃ after tempering treatment. The degree of corrosion sensitization showed increasing tendency with increase of tempering temperature and Cr carbide precipitation were observed in grain boundary.