Hydrogen production by silica membrane reactor during dehydrogenation of methylcyclohexane: CFD analysis

A comprehensive computational fluid dynamic model has been developed using COMSOL Multiphysics 5.4 software to predict the behavior of a membrane reactor in dehydrogenation of methylcyclohexane for hydrogen production. A reliable reaction kinetic of dehydrogenation reaction and a permeation mechanism of hydrogen through silica membrane have been used in computational fluid dynamic modeling. For performance comparison, an equivalent traditional fixed bed reactor without hydrogen removal has been also modeled. After model validation, it has been used to evaluate the operating parameters effect on the performance of both the silica membrane reactor and the equivalent traditional reactor as well. The operating temperature ranged between 473 and 553 K, pressure between 1 and 2.5 bar, sweep factor from ?6.22 to 25 and feed flow rate from 1 to 5 × 10^?6 mol/s. The membrane reactor performed better than the equivalent traditional reactor, achieving as best result complete methylcyclohexane conversion and 96% hydrogen recovery.     

旗袍三围规格的优化设计研究

旗袍需要拥有合身的廓形,贴体程度要求高且强调人体曲线美感,而旗袍的松量设计直接影响其外观造型的优美程度及穿着舒适感。文章首先采用正交实验法针对相同款式旗袍设计了9种不同水平组合的三围松量设置方案,并制作成相同款式不同三围规格的旗袍样衣;然后利用心理学标尺,对9件旗袍样衣的静态造型和穿着舒适感分别进行主观评价,并利用直观分析法和方差分析法综合分析主观评价结果;最后对分析结果进行验证,最终找出外观造型优美程度高和穿着舒适感佳的三围松量水平组合,为旗袍三围规格的优化设计提供理论依据。     

Artificial neural networks as alternative tool for minimizing error predictions in manufacturing ultradeformable nanoliposome formulations

This work was aimed at determining the feasibility of artificial neural networks (ANN) by implementing backpropagation algorithms with default settings to generate better predictive models than multiple linear regression (MLR) analysis. The study was hypothesized on timolol-loaded liposomes. As tutorial data for ANN, causal factors were used, which were fed into the computer program. The number of training cycles has been identified in order to optimize the performance of the ANN. The optimization was performed by minimizing the error between the predicted and real response values in the training step. The results showed that training was stopped at 10?000 training cycles with 80% of the pattern values, because at this point the ANN generalizes better. Minimum validation error was achieved at 12 hidden neurons in a single layer. MLR has great prediction ability, with errors between predicted and real values lower than 1% in some of the parameters evaluated. Thus, the performance of this model was compared to that of the MLR using a factorial design. Optimal formulations were identified by minimizing the distance among measured and theoretical parameters, by estimating the prediction errors. Results indicate that the ANN shows much better predictive ability than the MLR model. These findings demonstrate the increased efficiency of the combination of ANN and design of experiments, compared to the conventional MLR modeling techniques.     

Computational Investigation of Effects of Grain Size on Ballistic Performance of Copper

Numerical simulations were conducted to compare ballistic performance and penetration mechanism of copper (Cu) with four representative grain sizes. Ballistic limit velocities for coarse-grained (CG) copper (grain size ≈ 90 µm), regular copper (grain size ≈ 30 µm), fine-grained (FG) copper (grain size ≈ 890 nm), and ultrafine-grained (UG) copper (grain size ≈ 200 nm) were determined for the first time through the simulations. It was found that the copper with reduced grain size would offer higher strength and better ductility, and therefore renders improved ballistic performance than the CG and regular copper. High speed impact and penetration behavior of the FG and UG copper was also compared with the CG coppers strengthened by nanotwinned (NT) regions. The comparison results showed the impact and penetration resistance of UG copper is comparable to the CG copper strengthened by NT regions with the minimum twin spacing. Therefore, besides the NT-strengthened copper, the single phase copper with nanoscale grain size could also be a strong candidate material for better ballistic protection. A computational modeling and simulation framework was proposed for this study, in which Johnson–Cook (JC) constitutive model is used to predict the plastic deformation of Cu; the JC damage model is to capture the penetration and fragmentation behavior of Cu; Bao–Wierzbicki (B-W) failure criterion defines the material's failure mechanisms; and temperature increase during this adiabatic penetration process is given by the Taylor–Quinney method.     

Zero-Sequence Voltage-based Method for Determination and Classification of Unloaded Overhead Line Operating Conditions at the Moment of Energization

Overhead line energization can be performed under normal or faulty conditions. The latter indicates an occurrence of a fault along the line that exists at the moment of energization. This can lead to significant over-voltages that could endanger proper line operation. The issue gets more complex to protective devices when it comes to high-resistance faults, which impair the ability of relays to react promptly and accurately. Consequently, installation of additional detection devices becomes necessary. This paper proposes a novel method that properly detects and classifies line operating conditions at the moment of energization. The method is designed to be useful for utilities and it can be considered as a low-cost, fast, and accurate detection and classification approach, suitable for dealing with both low-resistance and high-resistance faults. Through comprehensive mathematical modeling it was found that both normal and faulty conditions during line energization are accompanied by the zero-sequence voltages of specific characteristics. The differences between zero voltage sequences are reflected in harmonic content, magnitudes of dominant frequencies, and their phase angles in regard to supply voltage. These findings are taken as the method's detection and classification criteria. The validity of the proposed model is verified by simulations and by field measurements.     

FDM用PETG系列耗材的改性研究

对市售聚对苯二甲酸乙二醇酯-1，4-环己烷二甲醇酯（PETG）丝材及原材料进行研究，选用PETG 2012作为制备熔融堆积成型技术（FDM）用PETG丝材的基体树脂。选用聚碳酸酯（PC）对基体PETG进行增韧增强改性，并制成3D打印高分子丝材进行打印测试，探讨了PC含量对PETG耗材及制件性能的影响。结果表明，在低PC含量下，PETG与PC的相容性较好，PETG与PC制件未出现明显的分层，分布比较均匀；共混物的流动性随着PC含量的增加而降低，且打印件的维卡软化温度和热变形温度随着PC用量的增加而增加；此外，PC材料的加入使得PETG打印件的力学性能得到较大改善：打印件的拉伸强度随着PC用量的增加而增大，缺口冲击强度却随着PC用量的增加呈现先增加后减小的趋势； PETG/PC的配比为1∶1时，可制得力学性能优异的3D打印耗材。     

偶联剂对PLA/PBAT/WF复合材料3D打印性能的影响

以聚乳酸（PLA）和聚己二酸/对苯二甲酸丁二酯（PBAT）为基体，杨木粉（WF）为填充增强材料，使用混炼机熔融共混制备PLA/PBAT/WF复合材料，采用熔融沉积成型（FDM）技术制备标准实验试样，通过扫描电子显微镜、红外光谱分析、旋转流变测试以及力学试验等方法，研究不同含量的硅烷偶联剂KH550对PLA/PBAT共混物以及PLA/PBAT/WF的相容性、流变性及力学性能的影响。结果表明，在偶联剂用量为3 %（质量分数，下同）时，拉伸强度提高了136 %；偶联剂KH550与 PLA和PBAT共价键偶联生成接枝聚合物，二者相容性得到提高；同时偶联剂与WF表面羟基发生缩聚反应有效的改善了其与PLA/PBAT的基体相容性，PLA/PBAT/WF复合材料的FDM的制件力学性能得到较大提升；复合材料的黏度随偶联剂含量的增加呈下降的趋势，含量为3 %时线材的综合打印性能及制品质量最佳。