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An Algorithm for predicting the Hydrodynamic and Mass Transfer Parameters in Slurry Bubble Column Reactors for Fischer-Tropsch Synthesis

机译:一种预测浆料泡沫柱反应器中流体动力学和传质参数的算法

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A large number of experimental data points obtained in our laboratory as well as from the literature, covering wide ranges of reactor geometry (column diameter, gas distributor type/open area), physicochemical properties (liquid and gas densities and molecular weights, liquid viscosity and surface tension, gas diffusivity, solid particles size/density), and operating variables (superficial gas velocity, temperature and pressure, solid loading, impurities concentration, mixtures) were used to develop empirical as well as Back-Propagation Neural Network (BPNN) correlations in order to predict the hydrodynamic and mass transfer parameters in slurry bubble column reactors (SBCRs). The empirical and BPNN correlations developed were incorporated in an algorithm for predicting gas holdups (epsilon_G, epsilon_(G-Small), epsilon_(G-Large)); volumetric mass transfer coefficients (k_La, k_(La-Small), k_La_(-Large)); Sauter mean bubble diameters (d_S, d_(S-Small), d_(S-Large)); gas-liquid interfacial areas (a, a_(Small), a_(Large)); and liquid-side mass transfer coefficients (k_L, k_(L-Small), k_(L-Large)) for total, small and large gas bubbles in SBCRs. The developed algorithm was used to predict the effects of reactor diameter and solid (alumina) loading on the hydrodynamic and mass transfer parameters in the Fisher-Tropsch (F-T) synthesis for the hydrogenation of carbon monoxide in a SBCR. The predictions showed that increasing the reactor diameter from 0.1 to 7.0 m and/or increasing the alumina loading from 25 to 50 wt. percent significantly decreased epsilon_G, k_La_(H2) and k_La_(CO) and increased d_S. The decrease of the total gas holdup was found to be controlled by the holdup of small gas bubbles. The increase of the Sauter mean bubble diameter increased both k_(LH2) and k_(LCO), however, the decrease of the total gas holdup coupled with the increase of d_S resulted in a dramatic decrease of the gas-liquid area, a and subsequently kLaH2 and k_La_(CO). Thus, in the churn-turbulent flow regime, the hydrodynamic and mass transfer behaviors of the F-T SBCR were controlled by the holdup of small gas bubbles and the gas-liquid interfacial area, a.
机译:在我们的实验室以及从文献中获得的大量实验数据点,覆盖宽范围的反应器几何形状(柱直径,气体分配器类型/开放区域),物理化学性质(液体和气体密度和分子量,液体粘度和液体粘度和表面张力,气体扩散,固体颗粒尺寸/密度)和操作变量(浅表气体速度,温度和压力,固体载荷,杂质浓度,混合物)用于开发经验以及反向传播神经网络(BPNN)相关性为了预测浆料泡柱反应器(SBCRS)中的流体动力学和传质参数。经验和BPNN相关性纳入预测气体持有的算法(EPSILON_G,EPSILON_(G-SMALL),EPSILON_(G-LAY));体积传质系数(K_LA,K_(LA-Small),K_LA _( - 大));落实的平均泡沫直径(d_s,d_(s-small),d_(s-mand));气液界面区域(A,A_(小),A_(大));和SBCR中的总,小型和大型气泡的液体侧传质系数(K_L,K_(L-Small),K_(L-LAML))。发育算法用于预测反应器直径和固体(氧化铝)负荷对饲料中的捕获量(F-T)合成中的水动力和传质参数的影响,用于SBCR中的一氧化碳氢化。预测显示,将反应器直径增加到0.1至7.0μm和/或增加25至50重量的氧化铝。百分比显着降低,epsilon_g,k_la_(h2)和k_la_(co)和增加d_s。发现总气体夹持的降低是由小气泡的持有控制的。燃烧器平均气泡直径的增加增加了K_(LH2)和K_(LCO),然而,与D_的增加相结合的总气体储存导致气液区域,A和随后的剧烈降低导致急剧下降KLAH2和K_LA_(CO)。因此,在流失湍流的流动状态下,通过储存小气泡和气液界面区域,控制F-T SBCR的流体动力学和传质行为。

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