• Title/Summary/Keyword: Prediction of effluent

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Application and evaluation for effluent water quality prediction using artificial intelligence model (방류수질 예측을 위한 AI 모델 적용 및 평가)

  • Mincheol Kim;Youngho Park;Kwangtae You;Jongrack Kim
    • Journal of Korean Society of Water and Wastewater
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    • v.38 no.1
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    • pp.1-15
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    • 2024
  • Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

Improvement Plan of Ocean Physics Assessment Technique for Power Plant Thermal Effluent (발전소 온배수에 의한 해양물리학적 평가기법 개선방안 연구)

  • Kim, Myeong-Won;Jo, Gwang-Woo;Maeng, Jun-Ho;Kang, Tae-Soon;Kim, Jongkyu
    • Journal of Ocean Engineering and Technology
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    • v.28 no.3
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    • pp.245-253
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    • 2014
  • This research analyzed the current situation and problems with an environmental impact assessment to provide a rational ocean physics assessment technique for power plant thermal effluent. This research also tried to create an improvement plan for heated effluent diffusion impact assessment by examining the reporting regulations for environmental impact assessment, national and international evaluation guidelines, etc. In the case of evaluating the oceanographic impact of heated effluent discharged from power plants, a pre-investigation is necessary before a full-scale presentence investigation, to accurately predict and minimize power plant construction effects on the surrounding environments. Before this presentence investigation, moreover, an integrated presentence plan, which agrees with the business plan, effect prediction, and post-investigation, needs to be established. A sufficient summit investigation must be made, which considers climate changes, and new and additional power plant construction. For accurate long-term oceanic environmental change prediction, the credibility of effect prediction must be elevated by presenting an evaluation method that is categorized by numerical organization models, verification methods, result presentation, and other things. Furthermore, unproductive conflicts between the people involved in heated effluent evaluation should be reduced by these improvement plans.

Prediction of Effluent Concentration for Contaminated Stream Purification using UFBR (상향류식 고정생물막조를 이용한 오염소하천 정화에 있어서 유출수 농도 예측)

  • Park, Young-Seek;Moon, Jung-Hynu;Ahn, Kab-Hwan
    • Journal of Wetlands Research
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    • v.4 no.1
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    • pp.87-95
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    • 2002
  • The objective of this study is to treat contaminated stream by using a UFBR(upflow fixed biofilm reactor) packed with waste-concrete media. This system was tested from June 1999 to January 2000. Over $20.0^{\circ}C$, $COD_{cr}$ removal efficiency did not affected with organic loading rate while, $COD_{cr}$ removal efficiency decreased about 7% with decrease of temperature from $27.0^{\circ}C$ to $8.7^{\circ}C$. Under $16^{\circ}C$, TKN removal efficiency was affected with TKN loading rate. The proposed model apply to mass balance equation of fixed biofilm reactor for predicting effluent was well satisfied with measured value($R^2=0.94$).

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A Study on the Influence of a Sewage Treatment Plant's Operational Parameters using the Multiple Regression Analysis Model

  • Lee, Seung-Pil;Min, Sang-Yun;Kim, Jin-Sik;Park, Jong-Un;Kim, Man-Soo
    • Environmental Engineering Research
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    • v.19 no.1
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    • pp.31-36
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    • 2014
  • In this study, the influence of the control and operational parameters within a sewage treatment plant were reviewed by performing multiple regression analysis on the effluent quality of the sewage treatment. The data used for this review are based on the actual data from a sewage treatment plant using the media process within the year 2012. The prediction models of chemical oxygen demand ($COD_{Mn}$) and total nitrogen (T-N) within the effluent of the 2nd settling tank based on the multiple regression analysis yielded the prediction accuracy measurements of 0.93 and 0.84, respectively; and it was concluded that the model was accurately predicting the variances of the actual observed values. If the data on the energy spent on each operating condition can be collected, then the operating parameter that conserves energy without violating the effluent quality standards of COD and T-N can be determined using the regression model and the standardized regression coefficients. These results can provide appropriate operation guidelines to conserve energy to the operators at sewage treatment plants that consume a lot of energy.

A Numerical Prediction for Water Quality at the Developing Region of Deep Sea Water in the East Sea Using Ecological Model (생태계모델을 이용한 동해 심층수 개발해역의 수질환경 변화예측)

  • Lee, In-Cheol;Yoon, Seok-Jin;Kim, Hyeon-Ju
    • Journal of Ocean Engineering and Technology
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    • v.22 no.2
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    • pp.34-41
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    • 2008
  • As a basic study for developing a forecasting/estimating system that predicts water quality changes when Deep Sea Water (DSW) drains to the ocean after using it, this study was carried out as follows: 1) numerical simulation of the present state at DSW developing region in the East sea using SWEM, 2) numerical prediction of water quality changes by effluent DSW, 3) analysis of influence degree 'With defined DEI (DSW effect index) at F station. On the whole, when DSW drained to the ocean, Chl-a, COD and water-temperature were decreased and DIN, DIP and DO were increased by effluent DSW, and Salinity was steady. According to analysis of influence degree, the influence degree of DIN was the highest and it was high in order of Chl-a, COD, Water-temperature, DO, DIP and Salinity. The influence degree classified by DSW effluent position was predicted that suiface outflow was lower than bottom outflow. Ad When DSW discharge increased 10 times, the influence degree increased about $5{\sim}14$ times.

Development and Validation of Multiple Regression Models for the Prediction of Effluent Concentration in a Sewage Treatment Process (하수처리장 방류수 수질예측을 위한 다중회귀분석 모델 개발 및 검증)

  • Min, Sang-Yun;Lee, Seung-Pil;Kim, Jin-Sik;Park, Jong-Un;Kim, Man-Soo
    • Journal of Korean Society of Environmental Engineers
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    • v.34 no.5
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    • pp.312-315
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    • 2012
  • In this study, the model which can predict the quality of effluent has been implemented through multiple regression analysis to use operation data of a sewage treatment plant, to which a media process is applied. Multiple regression analysis were carried out by cases according to variable selection method, removal of outliers and log transformation of variables, with using data of one year of 2011. By reviewing the results of predictable models, the accuracy of prediction for $COD_{Mn}$ of treated water of secondary clarifiers was over 0.87 and for T-N was over 0.81. Using this model, it is expected to set the range of operating conditions that do not exceed the standards of effluent quality. In conclusion, the proper guidance on the effluent quality and energy costs within the operating range is expected to be provided to operators.

Design Model of Constructed Wetlands for Water Quality Management of Non-point Source Pollution in Rural Watersheds (농촌유역의 비점원 오염 수질관리를 위한 인공습지 설계모형)

  • 최인욱;권순국
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.5
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    • pp.96-105
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    • 2002
  • As an useful water purification system for non-point source pollution in rural watersheds, interests in constructed wetlands are growing at home and abroad. It is well known that constructed wetlands are easily installed, no special managemental needs, and more flexible at fluctuating influent loads. They have a capacity for purification against nutrient materials such as phosphorus and nitrogen causing eutrophication of lentic water bodies. The Constructed Wetland Design Model (CWDM), developed through this study is consisted mainly of Database System, Runoff-discharge Prediction Submodel, Water Quality Prediction Submodel, and Area Assessment Submodel. The Database System includes data of watershed, discharge, water quality, pollution source, and design factors for the constructed wetland. It supplies data when predicting water quality and calculating the required areas of constructed wetlands. For the assessment of design flow, the GWLF (Generalized Watershed Loading Function) is used, and for water quality prediction in streams estimating influent pollutant load, Water Quality Prediction Submodel, that is a submodel of DSS-WQMRA model developed by previous works is amended. The calculation of the required areas of constructed wetlands is achieved using effluent target concentrations and area calculation equations that developed from the monitoring results in the United States. The CWDM is applied to Bokha watershed to appraise its application by assessing design flow and predicting water quality. Its application is performed through two calculations: one is to achieve each target effluent concentrations of BOD, SS, T-N and T-P, the other is to achieve overall target effluent concentrations. To prove the validity of the model, a comparison of unit removal rates between the calculated one from this study and the monitoring result from existing wetlands in Korea, Japan and United States was made. As a result, the CWDM could be very useful design tool for the constructed wetland in rural watersheds and for the non-point source pollution management.

Model Experiments on Prediction of Effluent Concentration of Suspended Solid in Containment of Dumping Dredged Soil (준설투기장내 부유물질 유출농도 예측에 관한 모형실험)

  • Lee, Dongwon;Jun, Sanghyun;Yoo, Kunsun;Yoo, Namjae
    • Journal of the Korean GEO-environmental Society
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    • v.12 no.6
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    • pp.35-42
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    • 2011
  • In this paper, model experiments in the laboratory were carried out to predict the effluent concentrations of suspended solid in containment of dumping dredged soils and test results were compared with results estimated by the currently used design method. Model tests of simulating dumping the dredged soils with a pump dredger in field were performed with changing the influent concentration and the length of containment and effluent concentration of suspended solid with time were measured during tests. As results of comparing test results about effluent concentration with those estimated from the design method by US Army COE(1987), they were confirmed to be in relatively good agreements.

Artificial Neural Network Modeling and Prediction Based on Hydraulic Characteristics in a Full-scale Wastewater Treatment Plant (실규모 하수처리공정에서 동력학적 동특성에 기반한 인공지능 모델링 및 예측기법)

  • Kim, Min-Han;Yoo, Chang-Kyoo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.555-561
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    • 2009
  • The established mathematical modeling methods have limitation to know the hydraulic characteristics at the wastewater treatment plant which are complex and nonlinear systems. So, an artificial neural network (ANN) model based on hydraulic characteristics is applied for modeling wastewater quality of a full-scale wastewater treatment plant using DNR (Daewoo nutrient removal) process. ANN was trained using data which are influents (TSS, BOD, COD, TN, TP) and effluents (COD, TN, TP) components in a year, and predicted the effluent results based on the training. To raise the efficiency of prediction, inputs of ANN are added the influent and effluent information that are in yesterday and the day before yesterday. The results of training data tend to have high accuracy between real value and predicted value, but test data tend to have lower accuracy. However, the more hydraulic characteristics are considered, the results become more accuracy.

A Comparison of Substrate Removal Kinetics of Anaerobic Reactor systems treating Palm Oil Mill Effluent (Palm Oil Mill Effluent 처리 시 Anaerobic Hybrid Reactor의 기질 제거 Kinetics 비교)

  • Oh, Dae-Yang;Shin, Chang-Ha;Kim, Tae-Hoon;Park, Joo-Yang
    • Journal of Korean Society of Water and Wastewater
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    • v.25 no.6
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    • pp.971-979
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    • 2011
  • Palm Oil Mill Effluent (POME) is the mixed organic wastewater generated from palm oil industry. In this study, kinetic analysis with treating POME in an anaerobic hybrid reactor (AHR) was performed. Therefore, the AHR was monitored for its performances with respect to the changes of COD concentrations and hydraulic retention time (HRT). Batch tests were performed to find out the substrate removal kinetics by granular sludge from POME. Modified Stover Kincannon, First-order, Monod, Grau second-order kinetic models were used to analyze the performance of reactor. The results from the batch test indicate that the substrate removal kinetics of granular sludge is corresponds to follow Monod's theory. However, Grau second-order model were the most appropriate models for the continuous test in the AHR. The second order kinetic constant, saturation value constant, maximum substrate removal rate, and first-order kinetic constant were 2.60/day, 41.905 g/L-day, 39.683 g/L-day, and 1.25/day respectively. And the most appropriate model was Grau second-order kinetic model comparing the model prediction values and measured COD concentrations of effluent, whereas modified Stover-Kincannon model showed the lowest correlation.