Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles
The acoustic agglomeration model of suspended PM 2.5 subjected to a standing-wave sound field is established based on the direct simulation Monte Carlo (DSMC) method. The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate...
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| creator | Fan Fengxian Chen Houtao Yuan Zhulin |
| description | The acoustic agglomeration model of suspended PM 2.5 subjected to a standing-wave sound field is established based on the direct simulation Monte Carlo (DSMC) method. The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate the agglomeration model and the algorithm. The results show that the dynamic behaviors of sub micron particles and micron particles under the effect of sound field are very different, and that the removal efficiency of PM 2.5 by acoustic agglomeration can be greatly improved by adding large particles into the gas stream. In a typical case, the PM 2.5 removal efficiency can be increased from 21.5% to 47.4% with additional particles. |
| doi_str_mv | 10.1109/CDCIEM.2011.579 |
| format | Conference Proceeding |
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The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate the agglomeration model and the algorithm. The results show that the dynamic behaviors of sub micron particles and micron particles under the effect of sound field are very different, and that the removal efficiency of PM 2.5 by acoustic agglomeration can be greatly improved by adding large particles into the gas stream. In a typical case, the PM 2.5 removal efficiency can be increased from 21.5% to 47.4% with additional particles.</description><identifier>ISBN: 161284278X</identifier><identifier>ISBN: 9781612842783</identifier><identifier>EISBN: 0769543502</identifier><identifier>EISBN: 9780769543505</identifier><identifier>DOI: 10.1109/CDCIEM.2011.579</identifier><language>eng</language><publisher>IEEE</publisher><subject>acoustic agglomeration ; Acoustics ; Computational modeling ; Equations ; fine particles (PM2.5) ; Mathematical model ; Monte Carlo method ; Numerical models ; removal efficiency ; sound field ; Trajectory ; Vibrations</subject><ispartof>2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring, 2011, p.1038-1041</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5747991$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5747991$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Fan Fengxian</creatorcontrib><creatorcontrib>Chen Houtao</creatorcontrib><creatorcontrib>Yuan Zhulin</creatorcontrib><title>Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles</title><title>2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring</title><addtitle>cdciem</addtitle><description>The acoustic agglomeration model of suspended PM 2.5 subjected to a standing-wave sound field is established based on the direct simulation Monte Carlo (DSMC) method. The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate the agglomeration model and the algorithm. The results show that the dynamic behaviors of sub micron particles and micron particles under the effect of sound field are very different, and that the removal efficiency of PM 2.5 by acoustic agglomeration can be greatly improved by adding large particles into the gas stream. In a typical case, the PM 2.5 removal efficiency can be increased from 21.5% to 47.4% with additional particles.</description><subject>acoustic agglomeration</subject><subject>Acoustics</subject><subject>Computational modeling</subject><subject>Equations</subject><subject>fine particles (PM2.5)</subject><subject>Mathematical model</subject><subject>Monte Carlo method</subject><subject>Numerical models</subject><subject>removal efficiency</subject><subject>sound field</subject><subject>Trajectory</subject><subject>Vibrations</subject><isbn>161284278X</isbn><isbn>9781612842783</isbn><isbn>0769543502</isbn><isbn>9780769543505</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjLtOw0AUBRchJEhITUGzP2Czd5_eDssYiJSIFCnoout9hEWOjWxT5O8xgtNMMZpDyB2wHIDZh-qpWtfbnDOAXBl7QRbMaKukUIxfkgVo4IXkpni_Jqtx_GTztC4sEzfksXT99zglR8vjse1PYcAp9R3tI91tea5o3X1g54KnzZmW3qdfiy3d4TBHbRhvyVXEdgyrfy7J_rneV6_Z5u1lXZWbLFk2ZaExutE2qsYEaQTH6GQjAJ3xChWLMTrgjoeIzvoorXIatHeGaZwb5cWS3P_dphDC4WtIJxzOB2WksRbED0WlSc4</recordid><startdate>201102</startdate><enddate>201102</enddate><creator>Fan Fengxian</creator><creator>Chen Houtao</creator><creator>Yuan Zhulin</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201102</creationdate><title>Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles</title><author>Fan Fengxian ; Chen Houtao ; Yuan Zhulin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-eb76b69f5b7e4732afc4b31ac7d5a50fffc12c2efac9df495c616dc706af5b5d3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>acoustic agglomeration</topic><topic>Acoustics</topic><topic>Computational modeling</topic><topic>Equations</topic><topic>fine particles (PM2.5)</topic><topic>Mathematical model</topic><topic>Monte Carlo method</topic><topic>Numerical models</topic><topic>removal efficiency</topic><topic>sound field</topic><topic>Trajectory</topic><topic>Vibrations</topic><toplevel>online_resources</toplevel><creatorcontrib>Fan Fengxian</creatorcontrib><creatorcontrib>Chen Houtao</creatorcontrib><creatorcontrib>Yuan Zhulin</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fan Fengxian</au><au>Chen Houtao</au><au>Yuan Zhulin</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles</atitle><btitle>2011 International Conference on Computer Distributed Control and Intelligent Environmental Monitoring</btitle><stitle>cdciem</stitle><date>2011-02</date><risdate>2011</risdate><spage>1038</spage><epage>1041</epage><pages>1038-1041</pages><isbn>161284278X</isbn><isbn>9781612842783</isbn><eisbn>0769543502</eisbn><eisbn>9780769543505</eisbn><abstract>The acoustic agglomeration model of suspended PM 2.5 subjected to a standing-wave sound field is established based on the direct simulation Monte Carlo (DSMC) method. The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate the agglomeration model and the algorithm. The results show that the dynamic behaviors of sub micron particles and micron particles under the effect of sound field are very different, and that the removal efficiency of PM 2.5 by acoustic agglomeration can be greatly improved by adding large particles into the gas stream. In a typical case, the PM 2.5 removal efficiency can be increased from 21.5% to 47.4% with additional particles.</abstract><pub>IEEE</pub><doi>10.1109/CDCIEM.2011.579</doi><tpages>4</tpages></addata></record> |
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| subjects | acoustic agglomeration Acoustics Computational modeling Equations fine particles (PM2.5) Mathematical model Monte Carlo method Numerical models removal efficiency sound field Trajectory Vibrations |
| title | Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles |
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