Clean Technology (청정기술)

The Korean Society of Clean Technology (한국청정기술학회)
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Water Digital Twin for High-tech Electronics Industrial Wastewater Treatment System (II): e-ASM Calibration, Effluent Prediction, Process selection, and Design

첨단 전자산업 폐수처리시설의 Water Digital Twin(II): e-ASM 모델 보정, 수질 예측, 공정 선택과 설계

  • Heo, SungKu (Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Jeong, Chanhyeok (Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Lee, Nahui (Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Shim, Yerim (Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Woo, TaeYong (Integrated engineering, Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Kim, JeongIn (Integrated engineering, Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University) ;
  • Yoo, ChangKyoo (Department. of Environmental Science and Engineering College of Engineering, Kyung Hee University)
  • 허성구 (경희대학교 공과대학 환경학 및 환경공학과) ;
  • 정찬혁 (경희대학교 공과대학 환경학 및 환경공학과) ;
  • 이나희 (경희대학교 공과대학 환경학 및 환경공학과) ;
  • 심예림 (경희대학교 공과대학 환경학 및 환경공학과) ;
  • 우태용 (경희대학교 공과대학 환경학 및 환경공학과 융합공학전공) ;
  • 김정인 (경희대학교 공과대학 환경학 및 환경공학과 융합공학전공) ;
  • 유창규 (경희대학교 공과대학 환경학 및 환경공학과)
  • Received : 2021.12.01
  • Accepted : 2021.01.12
  • Published : 2022.03.31
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Abstract

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.

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.

Keywords

Acknowledgement

이 논문은 2021년도 과학기술정보통신부의 재원으로 한국연구재단의 지원을 받아 수행된 연구로 이에 감사를 드립니다 (No. 2021R1A2C2007838).

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