Chemical Engineering & Technology最新文献

In this study, a new ellipse-fitting algorithm is proposed to achieve the reconstruction of bubble shapes in bubbly flow captured by a high-speed camera in the gas–liquid two-phase column reactor. Bubble flow patterns and geometric parameters in the experimental images are recognized and identified successfully, represented by means of the topological parameters. Three logical steps are carried out in detail. First, the area threshold and the circularity factors are established to identify the bubbles whether belonging to a single bubble or not. The overlapping bubbles in images can be separated from single bubbles based on a watershed segmentation algorithm. Second, a single bubble image and an overlapping bubble image are combined into one image. After that, statistical analysis for the size distributions and ellipse area bubbles is performed for further analysis and discussion. The advantage of this algorithm is that it can make use of a set of major and minor axes of an ellipse to capture the ellipse parameters more effectively. Simulation results are well agreed with experimental measurements. Moreover, it can be used to detect many ellipse-like bubbles that are dispersed in high-speed camera images, indicating that it is a better strategy for the recognition and identification of bubbly turbulent flow accurately.

A pressure correction method is proposed considering the influence of a dual factor. The applicability of a pressure correction method coupled with a drag model is discussed along with the accuracy of the simulation results obtained by such a pressure correction method. It is found that the present pressure correction method combined with the DBS (dual bubble size) drag model can accurately reflect the changing trend of gas holdup distribution with pressure. It is also established that results from this model applied to a bubble column match well with the experimental data. Finally, when compared with other pressure correction models, the proposed model shows better robustness in three-dimensional simulations and can predict radial gas holdup distributions with better accuracy.

The innovation of high-performance, stable electrocatalysts for clean energy systems faces significant challenges. Metal-organic frameworks (MOFs), with their porous nature, flexible structures, and homogeneous active site dispersion, have gained interest as unique precursors for carbon-based catalysts. MOFs' properties significantly enhance catalytic performance in fuel cells. This review highlights recent advancements in MOF design for oxygen electrocatalysis in fuel cells, while also discussing perspectives for future material innovations to improve catalytic activity in this emerging field.

Hydrogen liquefaction is essential for the efficient storage and transportation of hydrogen. In the liquefaction process, catalytic ortho-para conversion is crucial to achieve a product with at least 95 % para-hydrogen to reduce boil-off losses. The proposed hydrogen liquefaction process using a catalyst-filled heat exchanger for continuous ortho-para conversion is modeled through steady-state thermal simulations in Aspen HYSYS. Additionally, an ejector is integrated to reliquefy boil-off gas. The proposed design achieves a specific energy consumption (SEC) of 10.50 kWh ($$)⁻¹ and an exergy efficiency (EXE) of 30.1 %, which is 18 % lower in SEC compared to processes with separate converters. The integrated approach enhances energy utilization and offers references for future hydrogen liquefiers.

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