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상하수도학회지 update

Journal of the Korean Society of Water and Wastewater

  • : 대한상하수도학회
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수록정보
수록범위 : 1권1호(1987)~35권1호(2021) |수록논문 수 : 2,001
상하수도학회지
35권1호(2021년 02월) 수록논문
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1대한상하수도학회지 목차

저자 : 대한상하수도학회

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 1-2 (2 pages)

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2파일럿 플랜트 규모에서 일체형 침전부상공정(SeDAF)의 설계인자 및 운전특성에 대한 실증적 평가

저자 : 장여주 ( Yeoju Jang ) , 정진홍 ( Jinhong Jung ) , 임현만 ( Hyunman Lim ) , 김원재 ( Weonjae Kim )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 1-14 (14 pages)

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Eutrophication and algal blooms can lead to increase of taste and odor compounds and health problems by cyanobacterial toxins. To cope with these eco-social issues, Ministry of Environment in Korea has been reinforcing the effluent standards of wastewater treatment facilities. As a result, various advanced phosphorus removal processes have been adopted in each wastewater treatment plant nation-widely. However, a lot of existing advanced wastewater treatment processes have been facing the problems of expensive cost in operation and excessive sludge production caused by high dosage of coagulant. In this study, the sedimentation and dissolved air flotation (SeDAF) process integrated with sedimentation and flotation has been developed for enhanced phosphorus removal in wastewater treatment facilities. Design and operating parameters of the SeDAF process with the capacity of 100 m3/d were determined, and a demonstration plant has been installed and operated at I wastewater treatment facility (located in Gyeonggi-do) for the verification of field applicability. Several empirical evaluations for the SeDAF process were performed at demonstration-plant scale, and the results showed clearly that T-P and turbidity values of treated water were to satisfy the highest effluent standards below 0.2 mg/L and 2.0 NTU stably for all of operation cases.

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3주입 압력파의 웨이블릿 일관성 분석을 사용한 저수조-관로-밸브 시스템에서의 누수탐지모형 연구

저자 : 고동원 ( Dongwon Ko ) , 이정섭 ( Jeongseop Lee ) , 김진원 ( Jinwon Kim ) , 김상현 ( Sanghyun Kim )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 15-25 (11 pages)

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In this study, a method of leakage detection was proposed to locate leak position for a reservoir pipeline valve system using wavelet coherence analysis for an injected pressure wave. An unsteady flow analyzer handled nonlinear valve maneuver and corresponding experimental result were compared. Time series of pressure head were analyzed through wavelet coherence analysis both for no leak and leak conditions. The leak information can be obtained through either time domain reflectometry or the difference in wavelet coherence level, which provide predictions in terms of leak location. The reconstructed pressure signal facilitates the identification of leak presence comparing with existing wavelet coherence analysis.

KCI등재

4Ferrate(VI)를 이용한 다양한 수중 환경에서의 tetracycline의 분해 특성 및 반응 경로 연구

저자 : 박경덕 ( Kyeong-deok Park ) , 김일규 ( Il-kyu Kim )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 27-37 (11 pages)

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Tetracycline is one of the most commonly used as antibiotics for the livestock industry and it is still widely used nowadays. Tetracycline and its metabolites are excreted with excrement, which is difficult to completely removed with conventional sewage treatment, therefore it is apprehended that the tetracycline-resistant bacteria occurs. In this study, the oxidant named ferrate(VI) was used to degrade the tetracycline and investigate the reaction between ferrate(VI) and tetracycline under various aqueous conditions. The highest degradation efficiency of tetracycline occurred in basic condition (pH 10.1 ± 0.1) because of the pKa values of tetracycline and ferrate(VI). The results also showed the effect of water temperature on the degradation of tetracycline was not significant. In addition, the dosage of ferrate(VI) was higher, the degradation of tetracycline and the self-degradation of ferrate(VI) also higher, finally the efficiency of ferrate(VI) was lower. The results said that the various mechanisms effects the reaction of ferrate(VI) oxidation, it required the consideration of the characteristics of the target compound for optimal degradation efficiency. Additionally, intermediate products were detected with LC/MS/MS and three degradation pathways were proposed.

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5계량서지적 분석을 활용한 핵심 담수화 기술의 연구 동향

저자 : 이경훈 ( Gyeonghun Lee ) , 김혜원 ( Hye-won Kim ) , 부찬희 ( Chanhee Boo ) , 백영빈 ( Youngbin Beak ) , 곽노균 ( Rhokyun Kwak ) , 김춘수 ( Choonsoo Kim ) , 정성필 ( Seongpil Jeong )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 39-52 (14 pages)

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The global water shortage is getting more attention by global climate change. And water demand rapidly increases due to industrialization and population growth. Desalination technology is being expected as an alternative water supply method. Desalination technology requires low energy or maintenance costs, making it a competible next generation technology, with examples such as forward osmosis (FO), membrane distillation (MD), capacitive deionization (CDI), and electrodialysis (ED) to compete with reverse osmosis (RO). In order to identify recent research trends in desalination technologies (FO, MD, RO, CDI, and ED) between 2000-2020, a bibliometric analysis was conducted in the current study. The number of published papers in desalination technology have increased in Desalination and Journal of Membrane Science mainly. Moreover, it was found that FO, MD, RO, CDI, and ED technologies have been applied in various research areas including electrochemical, food processing and carbon-based material synthesis. Recent research topics according to the desalination technologies were also identified.

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6하수처리시설의 자연 재해 영향 정량화 지수 개발 연구

저자 : 박정수 ( Jungsu Park ) , 박재형 ( Jae-hyeoung Park ) , 최준석 ( June-seok Choi ) , 허태영 ( Tae-young Heo )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 53-61 (9 pages)

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The quantified analysis of damages to wastewater treatment plants by natural disasters is essential to maintain the stability of wastewater treatment systems. However, studies on the quantified analysis of natural disaster effects on wastewater treatment systems are very rare. In this study, a total disaster index (DI) was developed to quantify the various damages to wastewater treatment systems from natural disasters using two statistical methods (i.e., AHP: analytic hierarchy process and PCA: principal component analysis). Typhoons, heavy rain, and earthquakes are considered as three major natural disasters for the development of the DI. A total of 15 input variables from public open-source data (e.g., statistical yearbook of wastewater treatment system, meteorological data and financial status in local governments) were used for the development of a DI for 199 wastewater treatment plants in Korea. The total DI was calculated from the weighted sum of the disaster indices of the three natural disasters (i.e., TI for typhoon, RI for heavy rain, and EI for earthquake). The three disaster indices of each natural disaster were determined from four components, such as possibility of occurrence and expected damages. The relative weights of the four components to calculate the disaster indices (TI, RI and EI) for each of the three natural disasters were also determined from AHP. PCA was used to determine the relative weights of the input variables to calculate the four components. The relative weights of TI, RI and EI to calculate total DI were determined as 0.547, 0.306, and 0.147 respectively.

KCI등재

7미세조류 분리/회수를 위한 세포외 고분자물질 생물 응집제 활용

저자 : 최오경 ( Ohkyung Choi ) , Dandan Dong , 김종락 ( Jongrack Kim ) , 맹승규 ( Sung Kyu Maeng ) , 김극태 ( Keugtae Kim ) , 이재우 ( Jae Woo Lee )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 63-69 (7 pages)

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Microalgae are primary producers of aquatic ecosystems, securing biodiversity and health of the ecosystem and contributing to reducing the impact of climate change through carbon dioxide fixation. Also, they are useful biomass that can be used as biological resources for producing valuable industrial products. However, harvesting process, which is the separation of microalgal biomass from mixed liquor, is an important bottleneck in use of valorization of microalgae as a bioresource accounting for 20 to 30% of the total production cost. This study investigates the applicability of sewage sludge-derived extracellular polymeric substance (EPS) as bioflucculant for harvesting microalgae. We compared the flocculation characteristics of microalgae using EPSs extracted from sewage sludge by three methods. The flocculation efficiency of microalgae is closely related to the carbohydrate and protein concentrations of EPS. Heat-extracted EPS contains the highest carbohydrate and protein concentrations and can be a best-suited bioflocculant for microalgae recovery with 87.2% flocculation efficiency. Injection of bioflocculant improved the flocculation efficiency of all three different algal strains, Chlorella Vulgaris, Chlamydomonas Asymmetrica, Scenedesmus sp., however the improvement was more significant when it was used for flocculation of Chlamydomonas Asymmetrica with flagella.

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8MAP 결정화 적용을 위한 잉여슬러지의 인 및 암모니아의 거동 특성

저자 : 오경수 ( Kyungsu Oh ) , 김장호 ( Jangho Kim ) , 박기태 ( Kitae Park ) , 박대원 ( Daewon Park ) , 김형수 ( Hyungsoo Kim )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 71-81 (11 pages)

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Phosphorus is a vital resource for sustaining agriculture and nutrition, but a limited non-renewable resource. This paper aimed to derive the behavioral characteristics of phosphate, ammonia and metals of waste activated sludge (WAS) by process of activated sludge for application of magnesium ammonium phosphate (MAP) crystallization system. WAS used in the experiment was obtained in each activated sludge process, such as A2O, MLE (Modified Ludzack Ettinger), and oxidation ditch. WAS was analyzed for the behavior of phosphate ammonia and metallic materials according to pH and microwave conditions. As a result of evaluating the phosphate, nitrogen, and metal material behavior of each WAS according to the microwave and pH conditions, the release path of the polyphosphate contained in the cells into the phosphate form by analyzing the phosphorus release rate of the excess sludge of various microbial community structures was confirmed. These results are believed to be able to estimate the origin of the released phosphate. In addition, the evaluation of the behavior of phosphate, nitrogen, and metal substances according to microwave heating and pH for each activated sludge process was carried out in a batch test, and the amount of phosphate released was in the order of A2O, MLE, and oxidation dich processes. These results confirmed that phosphate emission was closely related to the dominance of polyphosphate-accumulating microorganisms, whereas in the case of ammonia, it was found that the composition of extracellular polymers and the characteristics of influent water were more affected than the dominance of specific microorganisms. The amount of metal released had a direct effect on the reaction pH condition, and the amount of metal ions released from the WAS released under alkaline conditions formed a metal compound with phosphate and ammonia, resulting in less release.

KCI등재

9딥러닝과 앙상블 머신러닝 모형의 하천 탁도 예측 특성 비교 연구

저자 : 박정수 ( Jungsu Park )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 83-91 (9 pages)

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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.

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10딥러닝을 이용한 정삼투 막모듈의 플럭스 예측

저자 : 김재윤 ( Jaeyoon Kim ) , 전종민 ( Jongmin Jeon ) , 김누리 ( Noori Kim ) , 김수한 ( Suhan Kim )

발행기관 : 대한상하수도학회 간행물 : 상하수도학회지 35권 1호 발행 연도 : 2021 페이지 : pp. 93-100 (8 pages)

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Forward osmosis (FO) process is a chemical potential driven process, where highly concentrated draw solution (DS) is used to take water through semi-permeable membrane from feed solution (FS) with lower concentration. Recently, commercial FO membrane modules have been developed so that full-scale FO process can be applied to seawater desalination or water reuse. In order to design a real-scale FO plant, the performance prediction of FO membrane modules installed in the plant is essential. Especially, the flux prediction is the most important task because the amount of diluted draw solution and concentrate solution flowing out of FO modules can be expected from the flux. Through a previous study, a theoretical based FO module model to predict flux was developed. However it needs an intensive numerical calculation work and a fitting process to reflect a complex module geometry. The idea of this work is to introduce deep learning to predict flux of FO membrane modules using 116 experimental data set, which include six input variables (flow rate, pressure, and ion concentration of DS and FS) and one output variable (flux). The procedure of optimizing a deep learning model to minimize prediction error and overfitting problem was developed and tested. The optimized deep learning model (error of 3.87%) was found to predict flux better than the theoretical based FO module model (error of 10.13%) in the data set which were not used in machine learning.

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1연안해역에서 석유오염물질의 세균학적 분해에 관한 연구

(2006)홍길동 외 1명심리학41회 피인용

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(2006)홍길동심리학41회 피인용

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