이 연구는 지속가능한 수자원 이용 및 관리대책을 수립하는 데에 필요한 수문학적 자료를 제공할 목적으로 2017~2020년 홍수기 (6~9월)에 발생한 총 59회의 강우 사상에 대한 강우-유출 특성을 파악하였다. 그 결과, 강우량은 5.0~400.8 mm, 유출고는 0.1~176.5 mm, 유출률은 0.1~242.9%의 범위로 나타났다. 그리고 유출수문곡선에서 직접유출과 기저유출을 분리한 결과, 홍수기의 총 유출일 대비 기저유출 (139.3일)이 직접유출 (78.3일)보다 유출기간이 길었지만, 총 유출고에 대한 기여도는 직접유출 (54.2%)이 기저유출 (45.8%)보다 높게 나타났다. 또한, 유출에 영향을 미치는 강우조건을 분석한 결과, 직접 유출과 기저유출의 유출고 및 첨두유출고에 높은 유의성 (p<0.05)을 보이는 강우조건은 강우량과 강우지속시간으로 나타났다. 특히, 유출고와 첨두유출고의 강우량은 각각 5.0~200.4, 10.5~110.5 mm의 범위에서는 기저유출이 우세한 강우사상이 나타났지만, 유출고와 첨두유출고의 강우량이 각각 267.4~400.8, 169.0~400.8 mm의 범위에서는 직접유출이 우세한 강우사상이 나타났다. 앞으로 극한 기후현상에 따른 물 부족이 심화할 것으로 예상되는 가운 데, 산지계류의 직접유출 및 기저유출에 대한 장기적이고도 지속적인 분석이 이루어진다면 지표수-지하수의 이용 및 관리 측면에서의 활용과 자료의 신뢰성을 높일 수 있을 것으로 판단된다.

PURPOSES : The cooling characteristics of the asphalt mixture in a moving dump truck were analyzed using a numerical simulation method. The cooling characteristic can be used to determine the optimum transport path for minimizing the temperature drop of the asphalt mixture. METHODS : In this research, a coupled analysis of the discrete element method (DEM) with computational fluid dynamics (CFD) was applied for cooling characteristic analysis of asphalt mixtures in transit. Two different transit speeds, 30 km/h and 60 km/h, were considered to evaluate the effect of speed on the temperature drop of the asphalt mixture. Velocity, pressure, and temperature contours were plotted and temperature variations were compared. RESULTS : Most of the temperature drops in the asphalt mixture were observed in the middle of the dump box in the longitudinal direction. It was confirmed that a faster speed causes a greater temperature drop for the same travel time and a slower speed causes the more temperature to reach the same travel distance as expected. CONCLUSIONS : It is concluded that the coupled analysis method can be used to quantitatively evaluate the effect of vehicle speed on temperature drop in asphalt mixtures. In addition, the method can be used to determine the optimum travel path considering environmental conditions and traffic congestion.

A seasonal characteristic of fish assemblages in the coastal waters of Gapa-do was determined using samples collected by a trammel net from 2015 to 2019. Annual mean temperature and salinity were 18.9℃, 33.6 psu (2015), 19.5℃, 33.6 psu (2016), 18.9℃, 33.8 psu (2017), 18.8℃, 34.5 psu (2018) and 19.5℃, 33.7 psu (2019), which show a stable water mass. During the survey period, a total of 50 species (30 families and 8 orders) of fishes were identified, including Scorpaeniformes (3 families and 9 species) and Perciformes (18 families and 29 species) that accounted for 68% of the total number. The number of species was higher in summer than in winter, showing the peak in the summer by 35 species and the low in the winter by 20 species. The number of individuals and the biomass peaked in the summer by 690 individuals and 151.4 kg, and were the lowest in the autumn by 336 individuals and 76.6 kg. The annual diversity index, evenness index and richness index were appeared to be 2.54-2.75, 0.68-0.76 and 5.32-6.65 at each stations. The dominance index was appeared to be the highest in 2018 and the lowest in 2015. Marbled rockfish (Sebastiscus marmoratus), rock fish (Sebastes inermis), filefish (Stephanolepis cirrhifer), rabbit fish (Siganus fuscescens), porcupine fish (Diodon holocanthus) and smallscale blackfish (Girella melanichthys) were dominant species, which occurred abundantly during the entire survey period. Subtropical fishes were identified as a total of 24 species (48.0%) and the number of species was higher in 2019 by 20 (60.6%) species and lower in 2015 by 13 (44.8%) species. The dominant species of the subtropical fishes were appeared to be rabbit fish, porcupine fish, smallscale blackfish, flag fish (Goniistius zonatus), stripey (Microcanthus strigatus), grunter (Parapristipoma trilineatum), and bluestriped angelfish (Chaetodontoplus septentrionalis) at the study sites.

The increased turbidity in rivers during flood events has various effects on water environmental management, including drinking water supply systems. Thus, prediction of turbid water is essential for water environmental management. Recently, various advanced machine learning algorithms have been increasingly used in water environmental management. Ensemble machine learning algorithms such as random forest (RF) and gradient boosting decision tree (GBDT) are some of the most popular machine learning algorithms used for water environmental management, along with deep learning algorithms such as recurrent neural networks. In this study GBDT, an ensemble machine learning algorithm, and gated recurrent unit (GRU), a recurrent neural networks algorithm, are used for model development to predict turbidity in a river. The observation frequencies of input data used for the model were 2, 4, 8, 24, 48, 120 and 168 h. The root-mean-square error-observations standard deviation ratio (RSR) of GRU and GBDT ranges between 0.182~0.766 and 0.400~0.683, respectively. Both models show similar prediction accuracy with RSR of 0.682 for GRU and 0.683 for GBDT. The GRU shows better prediction accuracy when the observation frequency is relatively short (i.e., 2, 4, and 8 h) where GBDT shows better prediction accuracy when the observation frequency is relatively long (i.e. 48, 120, 160 h). The results suggest that the characteristics of input data should be considered to develop an appropriate model to predict turbidity.

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

2020년 7월에 도시계획시설(공원) 실효제가 시행됨에 따라, 본 논문에서는 서울시 근린공원 중 시민의 이용과 사유지가 많은 미집행 근린공원 35개소를 대상으로 공원이 실효되기 전 보상 및 관리방안을 마련하기 위한 연구를 진행하였다. 선행연구 분석, 현장조사, GIS분석 및 전문가의 자문 등을 통해 공원 특성에 따른 장·단기적 대응지 분류기준 및 공원보상 우선순위 기준 마 련하였다. 연구내용은 실효시기를 기준으로 장·단기적 대응지를 구분하여 단기적 대응지는 ‘접근성, 이용성, 관리성’에 따라 3가지의 순위로 구분하였으며, 장기적 대응지는 국공유지, 중 복규제지, 접근성 취약지, 공원기능 상실지로 구분하였다. 연구결과 대부분의 근린공원은 필지 별로 특성이 상이하여 공원 내 장·단기적 대응지가 혼재하여 분포하고 있는 것으로 확인되었 으며, 특히 까치산, 염창, 영축산, 고덕 등은 단기적 대응지의 보상필요면적의 20% 이상이므로 집행이 시급한 것으로 나타났다. 또한 장기적 대응지 중 국공유지의 비율이 80% 이상인 낙산, 청량, 배봉산, 계남, 노량진, 불광, 와룡과 중복규제지의 비율이 공원 내 50% 이상인 세곡, 광 평, 고덕의 경우 해당 항목의 분포 비율이 높으므로 각 규제에 따라 공원별 통합 관리가 가능할 것으로 사료된다.

Expensive PCBN or ceramic cutting tools are used for the processing of difficult-to-cut materials such as Ti and Ni alloy materials. These tools have a problem of breaking easily due to their high hardness but low fracture toughness. To solve this problem, cutting tools that form various coating layers are used in low-cost WC-Co hard material tools, and researches on various tool materials are being conducted. In this study, WC-5, 10, and 15 wt%Ni hard materials for difficult-to-cut cutting materials are densified using horizontal ball milled WC-Ni powders and pulsed current activated sintering method (PCAS method). Each PCASed WC–Ni hard materials are almost completely dense, with a relative density of up to 99.7 ~ 99.9 %, after the simultaneous application of pressure of 60 MPa and electric current for 2 min; process involves almost no change in the grain size. The average grain sizes of WC and Ni for WC-5, 10, and 15 wt%Ni hard materials are about 1.09 ~ 1.29 and 0.31 ~ 0.51 μm, respectively. Vickers hardness and fracture toughness of WC-5, 10, and 15 wt%Ni hard materials are about 1,923 ~ 1,788 kg/mm2 and 13.2 ~ 14.3 MPa.m1/2, respectively. Microstructure and phase analyses of PCASed WC-Ni hard materials are performed.

The Municipal Building of Busan was the first western-style building of Korea in 1879. It was also the predecessor of Busan Metropolitan City Hall. On the other hand, the Municipal Building of Busan was a symbolic structure that shows the history of Busan. The Municipal Building of Busan has inherited the construction location and site, including the speciality of Choryangwaegwan, and is a good example of the process of inheriting the authority of the former space through the appropriation of the building. The Municipal Building of Busan was relocated to the edge of the coast in 1934 because a small and dilapidated building failed to function properly. The relocation of the Municipal Building of Busan in 1934 was the origin of changing the coastal space in downtown. As a result, landfill sites along the coast were in the limelight and developed into the downtown area of Busan after Korea's liberation.

In this study, the effects of heat-moisture treatment (boiling or steaming for 45 min) prior to hot air drying (70 o C for 8 h) on water activity (Aw), moisture (MC), Brix, color, and texture of dried sweet potato slices were investigated to identify the best pretreatment condition for producing dried sweet potato with the best eating quality. Dried sweet potato slices pretreated by boiling (BL) showed significantly lower Aw, MC, and hardness while Brix was significantly higher than with steaming (ST) treatment. There were no significant differences for the color, springiness, cohesiveness, gumminess, and brittleness indexes. At 8 h drying, the Aw, MC, Brix, and hardness of the BL and ST samples were 0.81 and 0.82, 19.71% and 25.53%, 53.80% and 49.40%, and 20.49 kg/cm 2 and 31.98 kg/ cm 2 , respectively. This information will be useful for manufacturers in the production of dried sweet potato slices. These findings provide evidence of the feasibility of heat-moisture treatments in the production of dried sweet potato.

PURPOSES : This study analyzes the characteristics of generated fine particulate matter (PM2.5) and nitrogen oxide (NOX) at roadsides using a statistical method, namely, a generalized linear model (GLM). The study also investigates the applicability and capability of a machine learning methods such as a generalized regression neural network (GRNN) for predicting PM2.5 and NOX generations. METHODS : To analyze the characteristics of PM2.5 and NOX generations at roadsides, data acquisition was conducted in a specific segment of roads, and PM2.5 and NOX prediction models were estimated using GLM. In addition, to investigate the applicability and capability of a machine learning methods, PM2.5 and NOX prediction models were estimated using a GRNN and were compared with models employing previously estimated GLMs using r-square, mean absolute deviation (MAD), mean absolute percentage error (MAPE), and root mean square error (RMSE) as parameters. RESULTS : Results revealed that relative humidity, wind speed, and traffic volume were significant for both PM2.5 and NOX prediction models based on estimated models from a GLM. In addition, to compare the applicability and capability of the GLM and GRNN models (i.e., PM2.5 and NOX prediction models), the GRNN model of PM2.5 and NOX prediction was found to yield better statistical significance for r-square, MAD, MAPE, and RMSE as compared with the same parameters used in the GLM. CONCLUSIONS : Analytical results indicated that a higher relative humidity and traffic volume could lead to higher PM2.5 and NOX concentrations. By contrast, lower wind speed could affect higher PM2.5 and NOX concentrations at roadsides. In addition, based on a comparison of two statistical methods (i.e., GLM and GRNN models used to estimate PM2.5 and NOX), GRNN model yielded better statistical significance as compared with GLM.