Particle and aerosol research (한국입자에어로졸학회지)

Korean Association for Particle and Aerosol Research (한국입자에어로졸학회)
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Prediction of collection performance for a granular bed filter filled with various shapes of packing material

다양한 형상의 충전물로 채워진 충전층 집진기의 집진성능 예측

  • Jae-Hyun Park (Department of Integrated Particulate Matter Management, Kangwon National University) ;
  • Myong-Hwa Lee (Department of Integrated Particulate Matter Management, Kangwon National University)
  • 박재현 (강원대학교 미세먼지통합관리학과) ;
  • 이명화 (강원대학교 미세먼지통합관리학과)
  • Received : 2023.10.10
  • Accepted : 2023.11.25
  • Published : 2023.12.31
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Abstract

Granular bed filters are widely used to remove particulate matter in flue gas and are filled with various shapes of packing material. The packing material plays an important role in determining the overall collection performance, such as pressure drop and collection efficiency. The pressure drop of a granular bed filter has been calculated using the Ergun equation, while the collection efficiency has been predicted using the log-penetration equation based on the single sphere theory. However, a prediction equation of collection efficiency for a granular bed filter filled with non-spherical packing materials has not been suggested yet. Therefore, in this study, three different shapes of packing materials (sphere, cylinder, and irregular) were prepared to propose a prediction equation. The pressure drop and collection efficiency in a granular bed filter filled with each shape of packing material were measured experimentally and compared with theoretically predicted values. We found that experimentally measured pressure drops matched well with values theoretically predicted using the Ergun equation considering the shape factor. However, experimental collection efficiencies were higher than theoretical ones predicted by the log-penetration equation using the single sphere theory. We modified the log-penetration equation by employing a shape factor and found a good relationship between experimental and theoretical collection efficiencies.

Keywords

Acknowledgement

이 성과는 정부(환경부)의 재원으로 한국환경산업기술원의 사업장미세먼지지능형최적저감·관리기술개발사업(연구개발과제번호 : RS-2023-0219242)과 미세먼지관리 특성화대학원사업의 지원을 받아 수행되었습니다.

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