• 산업기술연구
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• 제20권A호
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• pp.73-82
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• 2000

This study was implemented to find an optimal model for wastewater treatment processes using PHOENICS(Parabolic, hyperbolic or Elliptic Numerical Integration Code Series) and ASM(Activated Sludge Model). PHOENICS is a general software based upon the laws of physics and chemistry which govern the motion of fluids, the stresses and strains in solids, heat flow, diffusion, and chemical reaction. The wastewater flow and removal efficiency of particle in two phase system of a grit chamber in wastewater treatment plant were analyzed to inquire the predictive aspect of the operational model. ASM was developed for a biokinetic model based upon material balance in complex activated sludge systems, which can demonstrate dynamic and spatial behavior of biological treatment system. This model was applied to aeration tank and settling chamber in Choonchun city, and the modeling result shows dynamic transport in aeration tank. PHOENCS and ASM could be contributed for the optimal operation of wastewater treatment plant.

• 한국물환경학회지
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• 제23권1호
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• pp.131-137
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• 2007

Industrial wastewater management guideline and evaluation model of Best Available Technologies for the leather tanning and finishing industry was developed as an economical evaluation model using evaluation of BAT including economical evaluation combined with cost analysis model and cost annualization model in considering of economical factors and non-water environmental factors. It was verified that approximately 10% will be increased annually to modify conventional treatment process ($3,700m^3/d$) of J leather wastewater treatment plant to advanced process of K leather wastewater treatment plant.

• 상하수도학회지
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• 제11권3호
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• pp.87-95
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• 1997

A river water quality management model was made by Dynamic programming. This model optimizes the wastewater treatment cost of the application area, and computed water quality with it must meet the water quality standard. And this model takes into consideration tributary input, wastewater treatment plant effluent, withdrawls for several purposes. Modified Streeter-Phelps equation was used to calculate BOD and DO. Optimization problem was solved with particular exceedance probability flow, and the water quality of each point was calculated with the decided treatment efficiencies. At that time, the probability satisfying the water quality standard of constraints to the exceedance probability of the flow. The developed model was applied to the lower part of the Han-River. The reliability to meet the water quality standard is 70 % when 4 wastewater treatment plants of Seoul City are operated by activated sludge system at autumn of the year 2001. Treatment cost of this case is 121.288 billion won per year.

• 상하수도학회지
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• 제30권4호
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• pp.369-379
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• 2016

It was confirmed that the extreme value distribution model applies to probability of exceeding more than once a day monthly the facility capacities using data of daily maximum inflow rate for 7 wastewater treatment plant. The result of applying the extreme value model, A, D, E wastewater treatment plant has a problem compared to B, C, F, G wastewater treatment plant. but all the wastewater treatment plant has a problem except C, F wastewater treatment plant based 80% of facility capacity. In conclusion, if you make a standard in statistical aspects probability exceeding more than once a day monthly can be 'exceed day is less than a few times annually' or 'probability of exceeding more than once a day monthly is less than what percent'.

• 상하수도학회지
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• 제21권6호
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• pp.701-707
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• 2007

The information on the incoming load to wastewater treatment plants is not often available to apply to evaluate effects of control actions on the field plant. In this study, a time series model was developed to forecast influent flow rate, BOD, COD, SS, TN and TP concentrations using field operating data. The developed time series model could predict 1 day ahead forecasting results accurately. The coefficient of determination between measured data and 1 day ahead forecasting results has a range from 0.8898 to 0.9971. So, the corelation is relatively high. We made forecasting program based on the time series model developed and hope that the program will assist the operators in the stable operation in wastewater treatment plants.

• 한국산학기술학회논문지
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• 제15권3호
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• pp.1795-1800
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• 2014

본 논문은 생물학적 활성오니 폐수처리공정의 열전달 모델식을 제시하여 공정의 온도를 예측하였다. 열전달 모델은 폐수처리공정에 들어오고 나가는 모든 열을 고려하였다. 공정에 들어오는 열은 태양 복사열과 포기조 impeller의 기계적 에너지의 변환열, 포기조 내의 생화학 반응열이다. 공정에서 나가는 열은 폐수 자체의 복사열, 포기작용에 의한 증발열과 포기조 표면으로 나가는 전도열, 바람에 의한 대류열, 포기조와 지표면과의 전도열을 고려하였다. 들어오고 나가는 모든 열은 기존의 열전달 경험식을 적용하였다. 적용된 경험식으로 폐수처리장 공정의 열전달 모델식을 제시하였다. 모델식으로 실제 폐수처리공정의 온도를 예측하였으며, 모델식 예측치와 실제값이 $1.0^{\circ}C$ 이내로 일치하였다.

• 상하수도학회지
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• 제21권4호
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• pp.409-420
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• 2007

ASM No. 1 is a very useful model to analyze wastewater treatment system removing organic carbon and nitrogen material. But it isn't adequate to control the wastewater treatment system with real time since it has many material divisions and parameters. So, the purpose of this study is the simplification of ASM No. 1 to control the wastewater treatment system. ASM No. 1 was changed with the model which has 3 material divisions(COD, $NH_4{^+}$, $NO_3{^-}$) and two phases(Aerobic and Anoxic condition). SBR was running with two phases(Phase I and II). Phase II running 20 minutes with aerobic time was used for deciding model parameters and Phase I running 12 minutes with aerobic time was used for proving the simplified model. The simplified model was compared with ASM No. 1 using data of Phase I and II. As a result of model comparison, the simplified model has enough ability to express the variation of $NH_4{^+}$ compound.

• 상하수도학회지
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• 제38권1호
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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.

• 한국수소및신에너지학회논문집
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• 제33권5호
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• pp.583-590
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• 2022

In this paper, the performance characteristics of the 2 vane pump for wastewater treatment were investigated using response surface method(RSM) with commercial computation fluid dynamics(CFD) software. Design variables of wastewater treatment pump were defined with the meridional plane of the 2 vane pump impeller. The objective functions were defined as the total head and the efficiency at the design flow rate. The hydraulic performance of optimum model was verified by numerical analysis and the reliability of the model was retained by comparison of numerical analysis and comparative analysis with the reference model.

• 상하수도학회지
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• 제29권3호
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• pp.427-436
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• 2015

Developing two process models to simulate wastewater treatment process is needed to draw a comparison between measured BOD data and estimated process model data: a mathematical model based on the process mass-balance and an ANN (artificial neural network) model. Those two types of simulator can fit well in terms of effluent BOD data, which models are formulated based on the distinctive five parameters: influent flow rate, effluent flow rate, influent BOD concentration, biomass concentration, and returned sludge percentage. The structuralized mass-balance model and ANN modeI with seasonal periods can estimate data set more precisely, and changing optimization algorithm for the penalty could be a useful option to tune up the process behavior estimations. An complex model such as ANN model coupled with mass-balance equation will be required to simulate process dynamics more accurately.