利用壓力擾動訊號來界定B類粒子快速流體化流域

Abstract

本實驗使用高7m與內徑0.108m循環式流體化床，以平均粒徑155μm、密度為2615kg/m3之砂為床體粒子。以氣體速度和固體流量兩個操作變數，來界定循環式流體化床中快速流體化區域的操作範圍。以壓力探針測量上升床中之局部壓力及壓差擾動訊號，並經統計方法得到的標準偏差和冪次頻譜密度函數來討論不同流態的特徵。 在固定固體循環量下，漸漸減低氣速，由稀相輸送流態進入快速流體化流態之流域轉變，以床中各段之壓力梯度約相等的氣體流速Uc2作為稀相輸送流態和快速流體化流態之轉換速度。而繼續減低氣速，床中壓降呈現遞增趨勢，當流態由快速流體化進入紊流流態時，其固體循環量無法穩定維持，此時氣體速度Uc1作為快速流體化和紊流流態之轉換速度。 對Geldart B類粒子而言，軸向平均空隙度分佈是隨著表面氣體速度與粒子循環量的變化而變；低固體循環量及高氣體速度下表現單一平均空隙度的分佈，而高固體循環量及低氣體速度下則表現出底部空隙度小頂部空隙度大的單調指數分佈。 以床中兩點間的壓差擾動訊號經冪次頻譜密度函數分析發現，床底所得的頻譜圖隨著流態的不同有明顯能量上的差距，故可以區分在快速流體化、紊流流態及稀相輸送的差別。

The flow characteristics of Geldart group B powder (sand; =155 μm) in fast fluidization bed were investigated by instantaneous pressure signals in a circulating fluidized bed (0.108 m i.d. and 7m height) by using non-mechanical valve (L-vale) to control the flow rate of solid particles. It was found that for the transition from dilute phase convey to fast fluidization, the transition point was determined by plotting pressure gradients measured both at the top and the bottom of the riser. As the gas velocity is gradually reduced at the fixed solid flux, a critical gas velocity （Uc2）would be reached at which two distinct regions in the riser appear. Further reduction of the gas velocity below Uc2 at the same constant solid flux, a point （Uc1）will eventually be reached when steady operation at the given solid flux becomes impossible. The transition between fast fluidization and turbulent occurred at transition velocity Uc1. For Geldart group B particles, the axial bed average voidage distribution in the solid riser changes with superficial gas velocity and solid circulation rates. Dilute phase convey appears for low solid circulation rates or high superficial gas velocity, fast fluidization appears for high solid circulation rates or low superficial velocities. At fast fluidization, the power spectrum density function of differential pressure fluctuation signals in the bottom region of dense phase was well defined. So the region transition from turbulent to dilute phase convey was determined by the power spectrum density function of differential pressure fluctuation signals.