查看更多>>摘要：Water flux of pervaporation (PV) desalination membranes can be increased by reducing thickness of the selective layer and/or reducing the resistance of the support layer. However, low resistant support layer typically has large surface pores that requires a thick selective layer to avoid fracture. To solve this problem, we used poly(acrylic acid-co-2-acrylamido-2-methyl propane sulfonic acid) (P(AA-AMPS)) to crosslink PVA to improve the mechanical property of the coating layer. The PVA layer was deposited on to a highly porous PTFE substrate via spray-coating. By optimizing the spray-coating conditions, a thin and defect-free P(AA-AMPS) crosslinked PVA/PTFE composite membrane with a selective layer thickness of 1.1 mu m was prepared. The water flux of the composite membrane reached to 256.6 +/- 31.3 kg/(m(2) h) at 75 degrees C with a NaCl rejection rate over 99.9% when desalinating a 3.5 wt.% NaCl solution. The membrane flux is higher than all reported PV desalination membranes. (C) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
查看更多>>摘要：In the chemical and food industries the undesired formation of foams in thermal separation processes can lead to considerable losses in performance and efficiency. Existing methods cannot represent the foaming ability of boiling mixtures. Against this background, a novel laboratory-scale method, based on Bikerman's established definition of foamability, is developed to characterise the foamability of evaporation-induced foams. Based on the measured maximum steady-state foam volume and the maximum foam growth rate, a dimensionless number is established, which allows the evaluation of the evaporation-induced foaming ability.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
查看更多>>摘要：Soft sensor technique has become a promising solution to enable real-time estimations of difficult-to-measure quality variables in industrial processes. However, traditional soft sensor models cannot always function well due to two challenging issues. First, labeled data are usually expensive to obtain in many real-world applications, thus leading to unsatisfactory performance for traditional supervised soft sensors. Meanwhile, the information behind abundant unlabeled data is not fully exploited. Second, it is very common for soft sensors to encounter the modeling uncertainty resulting from the diversity of training data, model hyperparameters, and optimization parameters. Therefore, a new soft sensor method called semi-supervised ensemble support vector regression (SSESVR) is proposed by combining semi-supervised learning with ensemble learning. The SSESVR method first formulates the estimation of pseudo-labels as a multi-learner pseudo-labeling optimization problem and then solve it through evolutionary approach, thus extending the labeled training set using satisfactory pseudo-labeled data. Further, by considering multimodal perturbation mechanism, a two-level ensemble architecture is employed to enable efficient cooperation of semi-supervised and ensemble learning framework. Two case studies are conducted to verify the effectiveness and superiority of the proposed SSESVR approach.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
查看更多>>摘要：Accurate prediction of dryout during falling film evaporation is important to ensure good performance as post-dryout heat transfer coefficients are very low. No prediction method verified with a wide range of data is presently available and there has been a need for one. A new correlation is presented for dryout of saturated fluids on plain horizontal tubes. It has been verified with data for seven fluids from eight sources. The fluids are R-11, R-134a, R-236fa, R-410A, isobutane, and propane. Other parameters in the database are: heat flux from 0.2-95 kW m-2, reduced pressures from 0.00164 to 0.15, and liquid Reynolds numbers from 13 to 970. The new correlation predicts the data from single tubes and arrays of tubes with mean absolute deviation (MAD) of 15.8%. The same data were also compared to other correlations and those had much higher deviations. The new correlation and results of comparison with test data are presented and discussed.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
Abbas, Taisir K.Rashid, Khalid T.Alsalhy, Qusay F.
14页
查看更多>>摘要：Isotope cesium-137 (137Cs) is a major fission product that results from nuclear processes. This radioactive material constitutes a hazardous source of contamination to the environment even at low concentrations. Removal of this harmful radioactive isotope is deemed as an intricate challenge to resolve. The present study aims to synthesize a novel NaYzeolite modified Polyethersulfone (PES) membranes for 137Cs removal from real nuclear liquid waste. The zeolite has been synthesized through hydrothermal method on seedless static aging. Various zeolite contents were then impregnated within the PES membrane matrix to modify the membrane characteristics and ion-exchange properties. Besides, the proposed interaction mechanism of the modified NaYzeolite and PES has been illustrated for the first time in this study. The characteristics of the NaY zeolite, neat PES, and modified membranes were characterized comprehensively via X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), fourier-transform infrared spectroscopy (FT-IR), dynamic light scattering (DLS), and contact angle (CA) techniques. Results disclosed that optimum removal rate (90.2%) was obtained by the membrane prepared using 0.15% NaY while the decontamination factor (DF) was 10.2 at pH 7.5. Therefore, a legend agent copper ferrocyanides (CuFC) has been added to the feed solution aiming to promote the removal efficiency of 137Cs and enhance the decontamination factor. As a result, about 99.2% Cesium retention and 121.2 decontamination factor were achieved.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
Thomas, Kiran MathewNyande, Baggie W.Lakerveld, Richard
15页
查看更多>>摘要：Tubular crystallizers are desirable for continuous operations because they can approach plug flow conditions, achieve higher throughputs, and can be easy to control. However, the possible limitations of tubular crystallizers may include settling of crystals, fouling and higher pressure drops at longer residence times. The performance of a tubular crystallizer with gaps between the Kenics type mixing elements is characterized and compared with a standard Kenics static mixer and a hollow tubular crystallizer for the crystallization of lysozyme from solution. The gapped Kenics static mixer crystallizer provides an attractive trade-off between the standard Kenics static mixer and the hollow tubular crystallizer in terms of mixing length, shear rate, residence time distribution, pressure drop and segregation or settling of crystals. Furthermore, the gapped Kenics static mixer crystallizer and the standard Kenics static mixer crystallizer exhibit a similar crystallization performance in terms of desupersaturation profile and mean crystal size at the outlet for different initial lysozyme concentrations and seed loadings. The advantages of the gapped Kenics static mixer crystallizer in terms of pressure drop and minimization of crystal settling allow for lower flow rates and longer residence times under plug flow conditions, which has important practical benefits for continuous crystallization. (c) 2022 Published by Elsevier Ltd on behalf of Institution of Chemical Engineers.
查看更多>>摘要：The analysis of catalytic processes and the development of innovative technologies require a deep comprehension of the complex interplay between the intrinsic functionality of the heterogeneous material and the surrounding environment in the reactor. This is particularly important for multiphase catalytic reactors where complex interactions among the phases distribution, the inter-and intra-phase transport and the catalytic material occur. In this work, a computational framework has been developed to couple the solution of the hydrodynamics of multiphase flow using Computational Fluid Dynamics (CFD) with the detailed description of the surface reactivity through first-principles microkinetic models. In particular, the methodology employs an algebraic Volume-Of-Fluid (VOF) approach for the advection of the phases and takes advantage of the Compressive-Continuous Species Transfer (CST) for the modeling of the species mass interfacial transfer. The heterogeneous chemistry is included as source terms to the mass and energy equations acting at the catalytic surface, while the solution of the mass balance equation employs an operator splitting approach. The numerical framework has been assessed with respect to simple geometries by direct comparison with analytical and fully coupled solutions followed by examples of application in the context of the nitrobenzene hydrogenation to aniline. The envisioned approach is the first step toward the first-principles-based multiscale analysis of multiphase catalytic processes paving the way toward the detailed understanding and development of innovative and intensified technologies.(c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
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