Prediction of spontaneous imbibition in fractal porous media based on modified porosity correlation

 Spontaneous imbibition plays a significant role in different technical applications, and several analytical models have been proposed for predicting the fluid imbibition mass into porous media based on the fractal theory. Herein, these previous models are reconsidered in view of the obvious difference between the effective porosity and the areal porosity of porous media. Firstly, an implicit equation for fractal tortuosity is proposed and a modified correlation for the areal porosity is presented; then, a semi-analytical prediction model for fluid imbibition mass with gravity pressure is derived; finally, comparisons of predictions among several previous models with the present model are carried out. The modeling results show consistency with the experimental data published in the literature.Cited as: Li, Y., Yu, D., Niu, B. Prediction of spontaneous imbibition in fractal porous media based on modified porosity correlation. Capillarity, 2021, 4(1): 13-22, doi: 10.46690/capi.2021.01.02

Modeling Analysis of DC Magnetic Bias of Iron Core Reactor of APF

As one of the main power devices of active power filter (APF), iron core reactor DC magnetic bias would affect the performance of APF. Based on the study of DC magnetic bias mechanism of APF iron core reactor, the data model was established in this paper. The performance of APF device impacted by iron core reactor DC magnetic bias was analysed through the simulation in different DC current conditions, and optimization scheme was proposed to reduce DC magnetic bias to improve working performance of APF. To reduce DC magnetic bias, main circuit parameters and control characteristics were uniform, and reluctance of iron core was increased. Results of the simulations and experiments validated that the improved method could restrain reactor DC magnetic bias to reduce even harmonic current in APF output current, which could greatly optimize APF performance

Highly enhanced catalytic stability of copper by the synergistic effect of porous hierarchy and alloying for selective hydrogenation reaction

Supported copper has a great potential for replacing the commercial palladium-based catalysts in the field of selective alkynes/alkadienes hydrogenation due to its excellent alkene selectivity and relatively high activity. However, fatally, it has a low catalytic stability owing to the rapid oligomerization of alkenes on the copper surface. In this study, 2.5 wt% Cu catalysts with various Cu:Zn ratios and supported on hierarchically porous alumina (HA) were designed and synthesized by deposition–precipitation with urea. Macropores (with diameters of 1 μm) and mesopores (with diameters of 3.5 nm) were introduced by the hydrolysis of metal alkoxides. After in situ activation at 350 °C, the catalytic stability of Cu was highly enhanced, with a limited effect on the catalytic activity and alkene selectivity. The time needed for losing 10% butadiene conversion for Cu1Zn3/HA was ~40 h, which is 20 times higher than that found for Cu/HA (~2 h), and 160 times higher than that found for Cu/bulky alumina (0.25 h). It was found that this type of enhancement in catalytic stability was mainly due to the rapid mass transportation in hierarchically porous structure (i.e., four times higher than that in bulky commercial alumina) and the well-dispersed copper active site modified by Zn, with identification by STEM–HAADF coupled with EDX. This study offers a universal way to optimize the catalytic stability of selective hydrogenation reactions