• 제목/요약/키워드: Prediction of effluent

검색결과 47건 처리시간 0.037초

유기탄소 실시간 모니터링을 위한 분광학적 특성인자 분석 (Analysis of Optical Properties of Organic Carbon for Real-time Monitoring)

  • 유영민;박종관;이병준;이승윤
    • 한국물환경학회지
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    • 제37권5호
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    • pp.344-354
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    • 2021
  • Optical methods such as UV and fluorescence spectrophotometers can be applied not only in the qualitative analysis of dissolved organic matter (DOM), but also in real-time quantitative DOM monitoring for wastewater and natural water. In this study, we measure the UV254 and fluorescence excitation emission spectra for a sewage treatment plant influent and effluent, and river water before and after sewage effluent flows into the river to examine the composition and origin of DOM. In addition, a correlation analysis between quantified DOM characteristics and dissolved organic carbon (DOC) was conducted. Based on the fluorescence excitation emission spectra analysis, it was confirmed that the protein-type tryptophan-like DOM was the dominant substance in the influent, and that the organic matter exhibited relatively more humic properties after biological treatment. However, DOM in river water showed the fluorescence characteristics of terrestrial humic-like and algal tyrosine-like (protein-like) organic matter. In addition, a correlation analysis was conducted between the DOC and optical indices such as UV254, the fluorescence intensity of protein-like and humic-like organic matter, then DOC prediction models were suggested for wastewater and river monitoring during non-rainfall and rainfall events. This study provides basic information that can improve the understanding of the contribution of DOC concentration by DOM components, and can be used for organic carbon concentration management in wastewater and natural water.

생활오수 처리를 위한 인공습지의 처리수 수질 추정식에 관한 연구 (Study on the Estimation Equation of Effluent Concentration from Constructed Wetland for Domestic Wastewater Treatment)

  • 윤춘경;권순국;전지흥
    • 한국물환경학회지
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    • 제16권4호
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    • pp.491-499
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    • 2000
  • Effluent concentration estimation equations for treatment wetland were reviewed with 3 -year experimental data. Four equations from USEPA, WPCF, Kadlec and Knight, and this study were applied to the over 100 data points of 1996 to 1999 study at the pilot plant in Konkuk University. The system was a subsurface flow type and consisted of 60cm depth of sand and reeds, and it worked continuously including winter with domestic sewage from school building. Generally, all the equations demonstrated reasonable agreement with experimental data and they could be used for design process if selected carefully. Among them, the equation from this study showed the best fit for the data. The reason might be not only the equation was derived from the experimental data, but also it included plant coverage parameter in the equation while others did not Plant coverage was proved to be an important parameter in the prediction of the treatment wetland system, and its inclusion in the estimation equation could improve the accuracy. Although existing equations could be used in the wetland design, pilot plant experiment for the anticipated condition and subsequent equation development can provide more reliable equation. It takes time to obtain meaningful data from wetland system. Therefore, timely onset of well organized study is recommended before large scale application of treatment wetland system to either point or nonpoint source pollution abatement.

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활성슬러지 모델을 이용한 A2O공법 영양염류 제거 및 미생물 거동 (Nutrients removal and microbial activity for A2O Process Using Activated Sludge Models)

  • 윤현식;김덕진;최봉호;김문일
    • 상하수도학회지
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    • 제26권6호
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    • pp.889-896
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    • 2012
  • In this study, simulation results of nitrogen and phosphorus removals and microbial activities for an $A_2O$ process in wastewater treatment plant are presented by using Activated Sludge Models (ASMs). Simulations were performed using pre-calibrated model and layout implemented in GPS-X simulation software. The models were used to investigate variations of SRT, water temperature, DO and C/N ratio effect on nutrients removal and microbial activity. According to the simulated results, the successful nitrification required SRT higher than 10.3 days, whereas increase of $NO_3$-N loading in the anaerobic reactor caused phosphorus release by PAOs; the effluent $NH_4$-N showed rapid change between $12^{\circ}C$(21.7 mg/L) and $13^{\circ}C$(3.2 mg/L); the effluent phosphorus was increased up to 1.9 mg/L at water temperature of $25^{\circ}C$; the DO increase was positive for heterotrophs and autotrophs growths but negative for PAOs growth; the PAOs showed low activity when C/N ratio was lower than 2.5. The experimental results indicated that the calibrated models can assure the prediction quality of the ASMs and can be used to optimize the $A_2O$ process.

하수처리수를 이용한 소수력발전소 설계 및 성능예측 (Design and Performance Prediction of Small Hydropower Plant Using Treated Effluent in Wastewater Treatment Plant)

  • 이철형;박완순;김원경;김정연;채규정
    • 한국태양에너지학회 논문집
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    • 제33권2호
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    • pp.78-83
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    • 2013
  • A methodology to predict the output performance of small hydro power plant using treated effluent in waste water treatment plant has been studied. Existing waste water treatment plant located in Kyunggi-Do were selected and the output performance characteristics for these plants were analyzed. .Based on the models developed in this study, the hydrologic performance characteristics for SHP sites have been analyzed. The results show that the flow duration characteristics of small hydropower plant for waste water treatment plant have quite differences compared with small hydropower plant for the river. As a result, it was found that the developed model in this study can be used to analyze the output characteristics for small hydro power in waste water treatment plant. Additionally, primary design specifications such as design flowrate, capacity, operational rate and annual electricity production were estimated and discussed. It was found that the models developed in this study can be used to decide the design performance of small hydropower plant for waste water treatment plant effectively.

뜰개 이동 예측을 위한 신경망 및 통계 기반 기계학습 기법의 성능 비교 (Performance Comparison of Machine Learning Based on Neural Networks and Statistical Methods for Prediction of Drifter Movement)

  • 이찬재;김경도;김용혁
    • 한국융합학회논문지
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    • 제8권10호
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    • pp.45-52
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    • 2017
  • 뜰개는 해양에서 해수의 특성 및 흐름을 관측하기 위한 장비로서, 해수의 흐름 관측을 이용해 유출유 확산 예측을 위해 사용될 수 있다. 본 논문에서는 관측기관에서 사용하는 뜰개가 특정 시간 간격으로 관측한 바람 및 해수의 특성과 이동경로를 기계학습 기법들을 이용하여 학습시키고 예측하는 모델을 제안한다. 서포트벡터 회귀, 방사기저함수 네트워크, 가우시안 프로세스, 다층 퍼셉트론, 순환신경망을 이용하여 뜰개의 이동경로 예측 방법을 제시한다. 기존 MOHID 수치모델과 비교하여 각 기법별로 4 개의 사례중 3 개에서 성능이 개선되었으며, 가장 좋은 개선율을 보인 기법은 LSTM으로 평균 47.59% 개선되었다. 추후 연구에서는 배깅과 부스팅을 이용하여 가중치를 부여하여 정확도를 개선할 예정이다.

첨단 전자산업 폐수처리시설의 Water Digital Twin(II): e-ASM 모델 보정, 수질 예측, 공정 선택과 설계 (Water Digital Twin for High-tech Electronics Industrial Wastewater Treatment System (II): e-ASM Calibration, Effluent Prediction, Process selection, and Design)

  • 허성구;정찬혁;이나희;심예림;우태용;김정인;유창규
    • 청정기술
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    • 제28권1호
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    • pp.79-93
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    • 2022
  • 본 연구에서는 Part I에서 제안한 첨단 전자산업 폐수처리시설 특화 Water Digital Twin모델인 e-ASM을 이용하여 랩-파일럿 처리장 데이터를 바탕으로 모델 보정(Calibration), 유입 성상에 따른 제거 효율, 유출수 예측 및 최적 공법 선정을 수행하였다. 첨단 전자산업 폐수처리시설의 특화 모델링을 위하여, 민감도 분석을 통해 e-ASM 모델의 정합성과 상관성이 높은 동역학적 파라미터를 선정하였고, 다중반응표면분석법 (Multiple response surface methodology, MRS)을 이용하여 동역학적 파라미터를 보정하였다. e-ASM 모델의 보정 결과, Lab-scale, Pilot-scale 단위의 실험데이터와 90% 이상의 높은 정합성을 보였다. 그리고 4가지 유기폐수 처리처리공법인 MLE, A2/O, 4-stage MLE-MBR, Bardenpho-MBR을 제안한 Water Digital Twin으로 구현하여 유입 폐수의 성상별 운전조건에 따라 제거효율을 분석하였으며, Bardenpho-MBR이 C/N ratio 변화에서도 안정적으로 COD (Chemical oxygen demand)를 90% 이상 제거하며 높은 총 질소 제거 효율을 보였다. 그리고 유입 폐수의 조건별 Bardenpho-MBR공정의 수리학적 체류시간(Hydraulic retention time, HRT)이 3일 이상일 때 1,800 mg L-1의 고농도 TMAH 폐수를 98% 이상 제거할 수 있음을 확인할 수 있었다. 이와 같이, 본 연구에서 개발한 e-ASM은 전자산업 제조시설별, 유입 폐수의 성상별 특화 모델링을 통해 높은 정합성을 가진 전자산업 폐수처리공정의 Water Digital Twin를 구현할 수 있고, 최적운전, Water AI, 최적가용기법 선정 등의 응용 가능성을 바탕으로 지속 가능한 첨단전자 산업을 위해 활용될 수 있을 것으로 사료된다.

소수력 발전소 건설에 의한 삼천포 화력발전소 방류수로 흐름변화 예측 (Prediction of the Flow Pattern Changes using FLOW-3D Model in the Effluent Region of the Samcheonpo Thermal Power Plant (TPP))

  • 조홍연;정신택;김정대;강금석
    • 한국해안해양공학회지
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    • 제18권4호
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    • pp.338-347
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    • 2006
  • 삼천포 화력발전소에서는 냉각수로 이용되고 방류되는 해수를 이용한 소수력 발전소가 건설되고 있다. 소수력 발전소는 발전량을 최대화하기 위해서는 규모를 크게 하는 것이 바람직하나, 소수력 발전소가 방류수로의 기능을 저해하지는 않는 범위에서 결정하여야 하기 때문에 적정규모를 결정하기 위해서는 수리학적인 고려가 필요하다. 본 연구에서는 현재 방류수로의 흐름특성 자료를 이용하여 3차원 흐름모형인 FLOW3D모형을 구축하고, 구축된 모형을 이용하여 소수력 발전소의 규모에 따른 방류수로 상류 지점의 수위 증가 양상을 예측하였으며, 발전소 건설에 따른 흐름변화 양상도 분석하였다 삼천포 소수력발전소 건설은 상류의 수위증가를 유발하며, 설계유량 156톤/초, 발전소 가동보 높이 3.8 m 기준에 대한 방류수로 Weir 상류지점의 수위는 4.97 m로 현 상태 4.32 m 보다 65 cm 정도 증가하는 것으로 파악되었다.

인공 신경망(ANN)에 의한 하수처리장의 유입 유량 및 유입 성분 농도의 예측 (Prediction of Influent Flow Rate and Influent Components using Artificial Neural Network (ANN))

  • 문태섭;최재훈;김성희;차재환;염훈식;김창원
    • 한국물환경학회지
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    • 제24권1호
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    • pp.91-98
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    • 2008
  • This work was performed to develop a model possible to predict the influent flow and influent components, which are one of main disturbances causing process problems at the operation of municipal wastewater treatment plant. In this study, artificial neural network (ANN) was used in order to develop a model that was able to predict the influent flow, $COD_{Mn}$, SS, TN 1 day-ahead, 2day-ahead and 3 day ahead. Multi-layer feed-forward back-propagation network was chosen as neural network type, and tanh-sigmoid function was used as activation function to transport signal at the neural network. And Levenberg-Marquart (LM) algorithm was used as learning algorithm to train neural network. Among 420 data sets except missing data, which were collected between 2005 and 2006 at field plant, 210 data sets were used for training, and other 210 data sets were used for validation. As result of it, ANN model for predicting the influent flow and components 1-3day ahead could be developed successfully. It is expected that this developed model can be practically used as follows: Detecting the fault related to effluent concentration that can be happened in the future by combining with other models to predict process performance in advance, and minimization of the process fault through the establishment of various control strategies based on the detection result.

Kinetic Analysis and Mathematical Modeling of Cr(VI) Removal in a Differential Reactor Packed with Ecklonia Biomass

  • Park, Dong-Hee;Yun, Yeoung-Sang;Lim, Seong-Rin;Park, Jong-Moon
    • Journal of Microbiology and Biotechnology
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    • 제16권11호
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    • pp.1720-1727
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    • 2006
  • To set up a kinetic model that can provide a theoretical basis for developing a new mathematical model of the Cr(VI) biosorption column using brown seaweed Ecklonia biomass, a differential reactor system was used in this study. Based on the fact that the removal process followed a redox reaction between Cr(VI) and the biomass, with no dispersion effect in the differential reactor, a new mathematical model was proposed to describe the removal of Cr(VI) from a liquid stream passing through the differential reactor. The reduction model of Cr(VI) by the differential reactor was zero order with respect to influent Cr(IlI) concentration, and first order with respect to both the biomass and influent Cr(VI) concentrations. The developed model described well the dynamics of Cr(VI) in the effluent. In conclusion, the developed model may be used for the design and performance prediction of the biosorption column process for Cr(VI) detoxification.

제지공정 폐수 전처리 수질예측을 위한 실험적 모델과 통계적 모델 개발 (Development of Empirical and Statistical Models for Prediction of Water Quality of Pretreated Wastewater in Pulp and Paper Industry)

  • 손진식;한지희;이상호
    • 상하수도학회지
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    • 제31권4호
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    • pp.289-296
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    • 2017
  • Pulp and paper industry produces large volumes of wastewater and residual sludge waste, resulting in many issues in relation to wastewater treatment and sludge disposal. Contaminants in pulp and paper wastewater include effluent solids, sediments, chemical oxygen demand (COD), and biological oxygen demand (BOD), which should be treated by wastewater treatment processes such as coagulation and biological treatment. However, few works have been attempted to predict the treatment efficiency of pulp and paper wastewater. Accordingly, this study presented empirical models based on experimental data in laboratory-scale coagulation tests and compared them with statistical models such as artificial neural network (ANN). Results showed that the water quality parameters such as turbidity, suspended solids, COD, and UVA can be predicted using either linear or expoential regression models. Nevertheless, the accuracies for turbidity and UVA predictions were relatively lower than those for SS and COD. On the other hand, ANN showed higher accuracies than the emprical models for all water parameters. However, it seems that two kinds of models should be used together to provide more accurate information on the treatment efficiency of pulp and paper wastewater.