Numerical Modeling of Acoustic Agglomeration of Standard-Size Aerosols

• Main Authors: Shin-Yi Chen, 陳仕怡
• Other Authors: none
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/84717312039640298955

碩士 === 逢甲大學 === 環境工程與科學所 === 92 === In general, conventional particles removal devices are less-efficient to the fine particles between 0.1μm and 1.0 μm, those are easy settling in the respiratory system and cause adverse health effects. The preconditioning techniques should be adopted before fine particles went into the conventional control devices so as to shift their size distribution. The mechanisms of acoustic agglomeration are very complex, including both orthokinetic interaction and hydrodynamic interaction. To simulate the real effects of some exact sized particle in the sound field, modification of Song's AASM model were proceeded and the standard-size particles (the diameters are 0.45μm, 0.9μm and 2.5μm, respectively) were utilized. Various operating conditions(frequency: 900Hz, 2000Hz, 4000Hz, 6000Hz and 8000Hz ;sound pressure level:120dB, 130dB, 140dB, 150dB and 160dB; detention time: 3.0s, 4.5s, 6.0s, 7.5s and 9.0s; number concentration: 107/cm3, 5×107/cm3, 108/cm3) were discussed via sensitivity analysis. The results show that sound pressure level is the most important factor in acoustic agglomeration. General speaking, a least value of 140dB is required. Low frequency / high sound pressure was more efficient in larger particles, while high frequency / high sound pressure was, on the contrary, more efficient in small particles. When detention time increases, the agglomeration index (AI) also increase, but the proper value was normally set between detention time often set between 3.0 and 6.0 seconds because of the cost consideration. For monodisperse particles, the larger particle size, the large AI value. Hydrodynamic interaction is proved to be the major mechanism because the mutual radiation pressure increase as the particles size increase. The number concentration also shows great impact on AI value, AI increase as long as number concentration increase. In polydisperse agglomeration, AI of small particles was greater than those of large particles, this results shows that larger particles act as a sink to mop up the small particles in the agglomeration volume.