• Journal of the Korea Organic Resources Recycling Association
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• v.17 no.1
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• pp.58-72
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• 2009

In this study, the organic matter and biomass was characterized by using respirometry based on ASM No.2d (Activated Sludge Model No.2d). The activated sludge models are based on the ASM No.2d model, published by the IAWQ(International Association on Water Quality) task group on mathematical modeling for design and operation of biological wastewater treatment processes. For this study, OUR(Oxygen Uptake Rate) measurements were made on filtered as well as non-filtered wastewater. Also, GC-FID and LC analysis were applied for the estimation of VFAs(Volatile Fatty Acids) COD(S_A) in slowly bio-degradable soluble substrates of the ASM No.2d. Therefore, this study was intended to clearly identify slowly bio-degradable dissolved materials(S_S) and particulate materials(X_I). In addition, a method capable of determining the accurate time to measure non-biodegradable COD(S_I), by the change of transition graphs in the process of measuring microbial OUR, was presented in this study. Influent fractionation is a critical step in the model calibrations. From the results of respirometry on filtered wastewater, the fraction of fermentable and readily biodegradable organic matter(S_F), fermentation products(S_A), inert soluble matter(S_I), slowly biodegradable matter(X_S) and inert particular matter(X_I) was 33.2%, 14.1%, 6.9%, 34.7%, 5.8%, respectively. The active heterotrophic biomass fraction(X_H) was about 5.3%.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.140-148
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• 2017

An important factor in determining the design and treatment efficiency of wastewater treatment plants (WWTPs) is the quantity and quality of influent. These detailed and accurate information is essential for process control, diagnosis and operation, as well as the basis in designing the plant, selecting the process and determining the optimal capacity of each bioreactor. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve the design and operation of WWTPs. In this study, the optimal probability distribution of time series influent data was derived for predicting water quantity and quality, and wastewater influent data were generated using the Monte Carlo simulation analysis. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation condition using the generated influent data and activated sludge model, and suggested the alternative that can operate the most effectively. Thus, the influent quantity and quality are highly correlated with the actual operation data, so that the actual WWTPs influent characteristics were well reproduced. Using this will improve the operating conditions of WWTPs, and a proposed improvement plan for the current TMS (Tele Monitoring System) effluent quality standards can be made.

• Journal of Korean Society of Water and Wastewater
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• v.28 no.6
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• pp.735-745
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• 2014

This paper presents PKES(PuKyung -Excel based Simulator) for WWTPs(wastewater treatment plants) by using MS Excel and VBA(Visual Basic for Application). PKES is a user-friendly simulator for the design and optimization of the whole plant including biological and physico-chemical processes for the wastewater and sludge treatment. PKES calculates the performance under steady or dynamic state and allows changing the mathematical model by the user. Mathematical model implemented in PKES is a improved integration model based on ASM2d and ADM1 for simulation of AS(activated sludge) and AD(anaerobic digestion). Gaseous components of $N_2$, $N_2O$, $CO_2$ and $CH_4$ are added for estimation of GHGs(greenhouse gases) emission. The simulation results for comparison between PKES and Aquasim(EAWAG) showed about the same effluent concentrations. As a result of verification using by measured data of BOD, TSS, TN and TP for 2 years of operation, calculated effluent concentrations were similar to measured effluent concentrations. The values of average RMSE(root mean square error) were 1.9, 0.8, 1.6 and 0.2 mg/L for BOD, TSS, TN and TP, respectively. Total GHGs emission of WWTP calculated by PKES was 138.5 ton-$CO_2$/day and GHGs emissions of $N_2O$, $CO_2$ and $CH_4$ were calculated at 21.7, 28.9 and 87.9 ton-$CO_2$/day, respectively. GHGs emission of activated sludge was 32.5 % and that of anaerobic digestion was 67.5 %.

• Clean Technology
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• v.28 no.1
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• pp.63-78
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• 2022

Electronics industrial wastewater treatment facilities release organic wastewaters containing high concentrations of organic pollutants and more than 20 toxic non-biodegradable pollutants. One of the major challenges of the fourth industrial revolution era for the electronics industry is how to treat electronics industrial wastewater efficiently. Therefore, it is necessary to develop an electronics industrial wastewater modeling technique that can evaluate the removal efficiency of organic pollutants, such as chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), and tetramethylammonium hydroxide (TMAH), by digital twinning an electronics industrial organic wastewater treatment facility in a cyber physical system (CPS). In this study, an electronics industrial wastewater activated sludge model (e-ASM) was developed based on the theoretical reaction rates for the removal mechanisms of electronics industrial wastewater considering the growth and decay of micro-organisms. The developed e-ASM can model complex biological removal mechanisms, such as the inhibition of nitrification micro-organisms by non-biodegradable organic pollutants including TMAH, as well as the oxidation, nitrification, and denitrification processes. The proposed e-ASM can be implemented as a Water Digital Twin for real electronics industrial wastewater treatment systems and be utilized for process modeling, effluent quality prediction, process selection, and design efficiency across varying influent characteristics on a CPS.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1400-1404
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• 2006

생물학적 질소, 인 제거 공정(이하 BNR)의 운전에 있어서 최적 유입수의 C/N(COD/TKN)비, SRT 및 온도의 범위 및 정량적 수치 등은 유기물 뿐 만아니라 질소, 인의 처리 효율에 있어서 매우 중요하다. 특히, 외국과 다른 저농도 유기물 특성을 보이는 국내 하수에 대해서는 BNR 공정의 선택과 설계 및 운전인자의 선별이 무엇보다도 중요한 역할을 한다. 본 연구에서는 IAWQ에서 제시한 ASM No.2d를 기초로 하여 만들어진 전산모형인 Envirosim사의 Biowin 프로그램을 시뮬레이션 도구로 활용하여, 국내 하수에 비교적 적용하기 용이한 A2/O 공정과 MUCT 공정에 대한 유기물, 질소 및 인처리 효율을 비교하고 유입수의 C/N와 SRT 및 온도에 따른 질소, 인 처리 특성과 유출수의 거동 등을 파악하였다. 시뮬레이션 결과, 국내 하수에서는 A2/O 보다는 MUCT 공정이 질소, 인 처리효율이 더 크게 나타났다. 온도와 SRT가 일정한 상태에서 C/N비는 7이상에서 TKN과 TP제거효율이 양호하게 나타났고, 온도와 C/N비를 일정한 조건에서는 SRT가 7일을 넘어서면 효율이 급격히 낮아지는 현상을 관찰할 수 있었다. 온도조건 실험에서는 $20^{\circ}C$이하, 특히 국내 하수처리장에 BNR 적용시 설게조건인 $13^{\circ}C$에 근접해서는 TKN의 제거효율은 급격히 떨어지는 반면에 인 제거효율이 상승하는 것으로 나타났다.

• Journal of the Korean GEO-environmental Society
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• v.8 no.4
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• pp.19-25
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• 2007

Process analysis with ASM3 (Activated Sludge Model3) was performed to offer basic data for the optimization of aerated biofilter (ABF) process design and operation. This study was focused on the simulation of the nitrification reaction in ABF which was a part of the advanced nutrient treatment process using bio-adsorption. The ABF process has been developed for the removal of suspended solids and nitrification reaction in sewage. A GPS-X (General Purpose Simualtor-X) was used for the sensitivity analysis and operation assessment. Sensitivity of ASM3 parameters on ABF was analysed and 4 major parameters ($Y_A$, $k_{sto}$, ${\mu}_A$, $K_{A,HN}$) were determined by dynamic simulation using 70 days data from pilot plant operation. The optimized values were 0.14 for $Y_A$, 3.5/d for $k_{sto}$, 2.7/d for ${\mu}_A$ and 1.1 mg/L for $K_{A,HN}$, respectively. Simulation with optimized parameter values were conducted and TN, $NH_4{^+}-N$ and $NO_3{^-}-N$ concentrations were estimated and compared with measured data at the range of 10 min to 4 hrs of hydraulic retention time (HRT). The simulated results showed that optimized parameter values could represent the characteristics of ABF process. Especially, the ABF showed relatively high nitrification rate (60%) under very short HRT of 10 min. As a consequence, the ABF was thought to be successfully used in the site which having high variation of influent loading rate.

• Journal of Korean Society on Water Environment
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• v.21 no.5
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• pp.448-457
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• 2005

The conventional activated sludge processes were operated as a combined organic substrate removal and nitrification. So, it was necessary to provide with oxygen for both carbon and ammonia removal. But, in the BNR processes, nitrification is separated from carbon removal that causes fast ammonia oxidation and reduced oxygen demands. And most of the substrate is utilized by denitrification organisms and phosphorus accumulating organisms. with these appearances, mathematical model for BNR processes different from IWA ASM can be simplified and applied. In this study, it was performed that the existing equations as McKinney model, nitrification model published by U.S. EPA and oxygen demands from stoichiometry and the relationship between NUR and OUR were applied to full-scale BNR processes and the results were compared with the measured. and it is possible to make out the optimum design parameter from those equations.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1706-1709
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• 2010

Sewerage Treatment Plants(STPs) are complexes systems in which a range of physical, chemical and biological processes occur. Since Activated Sludge Model(ASM) No.1 was published, a number of new mathematical models for simulating biological processes have been developed. However, these models have disadvantages in cost and simplicity due to the laboriousness and tediousness of their procedures. One of the major difficulties of these mathematical model based tools is that the field-operators mostly don't have the time or the computer-science skills to handle there models, so it mainly remains on experts or special engineers. In order to solve these situations and help the field-operators, the $KM^2BM$(K-water & More-M Mass Balance Model) based on the dynamic-mass balance model was developed. This paper presents $KM^2BM$ as a simulation tools for STPs design and optimization. This model considers the most important microbial behavioral processes taking place in a STPs to maximize potential applicability without increasing neither model parameter estimation nor wastewater characterization efforts.