Catalytic combustion synthesis of CNTs/MgO composite powders and the influences on the thermal shock resistance of low-carbon Al2O3–C refractories

Using MgC₂O₄, Mg powders as raw materials and Ni(NO₃)₂?6H₂O as a catalyst, CNTs/MgO composite powders were prepared by a catalytic combustion synthesis method. The CNTs/MgO composite powders were characterized by XRD, Raman spectroscopy, FESEM/EDS and HRTEM. The effects of catalyst content on the degree of graphitization and aspect ratio of the CNTs in composite powders were investigated. Moreover, the thermal shock resistance of low-carbon Al₂O₃–C refractories after adding the composite powder was investigated. The results indicated that the CNTs prepared with 1 wt% Ni(NO₃)₂?6H₂O addition had a higher degree of graphitization and aspect ratio. In particular, the aspect ratio could reach approximately 200. The growth mechanism of hollow bamboo-like CNTs in the composite powders was proven to be a V-L-S mechanism. The thermal shock resistance of Al₂O₃–C samples could be improved significantly after adding CNTs/MgO composite powders. In particular, compared with CM0, the residual strength ratio of Al₂O₃–C samples with added 2.5 wt% composite powders could be increased 63.9%.     

Robust optimal operation of continuous catalytic reforming process under feedstock uncertainty

The continuous catalytic regenerative (CCR) reforming process is one of the most significant sources of hydrogen production in the petroleum refining process. However, the fluctuations in feedstock composition and flow rate could significantly affect both product distribution and energy consumption. In this study, a robust deviation criterion based multi-objective optimization approach is proposed to perform the optimal operation of CCR reformer under feedstock uncertainty, with simultaneous maximization of product yields and minimization of energy consumption. Minimax approach is adopted to handle these uncertain objectives, and the Latin hypercube sampling method is then used to calculate these robust deviation criteria. Multi-objective surrogate-based optimization methods are next introduced to effectively solve the robust operational problem with high computational cost. The level diagram method is finally utilized to assist in multi-criteria decision-making. Two robust operational optimization problems with different objectives are solved to demonstrate the effectiveness of the proposed method for robust optimal operation of the CCR reforming process under feedstock uncertainty.     

Tabular data: Deep learning is not all you need

A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone.     

Development of high pressure membraneless alkaline electrolyzer

A technology for cyclic generation of hydrogen and oxygen using electrodes made of variable valency material that does not need the use of separating ion-exchange membranes is presented. The technological solution enables to fabricate electrolyzers for uninterrupted producing high-pressure hydrogen with reduced energy intensity of the production. The total work for compressing 1 m³ of hydrogen and 0.5 m³ of oxygen has been estimated. Results of investigation of influence of discrete supply of DC current to the electrolysis cell, in order to improve the processes of gas evolution and to simplify the power systems of the electrolysis plant, have been considered. There is also considered an electrolysis installation equipped with a thermosorption compressor in which LaNi₅ is used as a hydride-forming compound. The comparative characteristics of the developed electrolyzer and the currently used hydrogen generators are given.     

Optimization of flow in additively manufactured porous columns with graded permeability

Chemical engineering systems often involve a functional porous medium, such as in catalyzed reactive flows, fluid purifiers, and chromatographic separations. Ideally, the flow rates throughout the porous medium are uniform, and all portions of the medium contribute efficiently to its function. The permeability is a property of a porous medium that depends on pore geometry and relates flow rate to pressure drop. Additive manufacturing techniques raise the possibilities that permeability can be arbitrarily specified in three dimensions, and that a broader range of permeabilities can be achieved than by traditional manufacturing methods. Using numerical optimization methods, we show that designs with spatially varying permeability can achieve greater flow uniformity than designs with uniform permeability. We consider geometries involving hemispherical regions that distribute flow, as in many glass chromatography columns. By several measures, significant improvements in flow uniformity can be obtained by modifying permeability only near the inlet and outlet.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Preparation of Pt/Ce–Zr–Y mixed oxide/anodized aluminium oxide catalysts for hydrogen passive autocatalytic recombination

The use of a Pt-based catalyst was evaluated for autocatalytic hydrogen recombination. The Pt was supported on a mixture of Ce-, Zr- and Y-oxides (CZY) to yield nanosized Pt particles. The Pt/CZY/AAO catalyst was then prepared by the spray-deposition of the Pt/CZY intermediate onto an anodized aluminium oxide (AAO) layer on a metallic aluminum core. The Pt/CZY/AAO catalyst (3 × 1 cm) was evaluated for hydrogen combustion (1–8 vol% hydrogen in the air) in a recombiner section testing station. The thermal distribution throughout the catalyst surface was investigated using an infrared camera. The maximum temperature gradient (ΔT) for the examined hydrogen concentrations did not exceed 36 °C. The Pt/CZY/AAO catalyst was also evaluated for prolonged hydrogen combustion duration to assess its durability. An average combustion temperature of 239.0 ± 10.0 °C was maintained for 53 days of catalytic hydrogen combustion, suggesting that there was limited, or no, catalyst deactivation. Finally, a Pt/CZY/AAO catalytic plate (14.0 × 4.5 cm) was prepared to investigate the thermal distribution. An average surface temperature of 212.5 °C and a maximum ΔT of 5.4 °C was obtained throughout the catalyst surface at a 3 vol% hydrogen concentration.     

Topology optimization of flexure hinges with a prescribed compliance matrix based on the adaptive spring model and stress constraint

This paper focuses on the configuration design of flexure hinges with a prescribed compliance matrix and preset rotational center position. A new method for the topology optimization of flexure hinges is proposed based on the adaptive spring model and stress constraint. The hinge optimization model is formulated by maximizing the bending displacement with a spring while optimizing the compliance matrix to a prescribed value. To avoid numerical instability, an artificial spring is used as an auxiliary calculation, and a new strategy is developed for adaptively adjusting the spring stiffness according to the prescribed compliance matrix. The maximum stress of flexure hinge is limited by using a normalized P-norm of the effective von Mises stress, and a position constraint of rotational center is proposed to predetermine the position of the rotational center. In addition, to reduce the error of the stress measurement, a simple but effective filtering method is presented to obtain a complete black-and-white design. Numerical examples are used to verify the proposed method. Topology results show that the obtained flexure hinges have the prescribed compliance matrix and preset rotational center position while also meeting the stress requirements.     

Effect of heat loss on the syngas production by fuel-rich combustion in a divergent two-layer burner

The effect of heat loss on the syngas production from partial combustion of fuel-rich in a divergent two-layer burner is numerically studied using two-dimensional model with detailed kinetics GRI-Mech 1.2. Both the radiation and wall heat losses to the surrounding are considered in the computations. It is shown that two types heat losses have different effects on the syngas production. The radiation heat loss has significant effect on the syngas temperature and the syngas temperature is dropped as radiation heat loss is increased, but it has neglected effect on the reforming efficiency and methane conversion efficiency. The wall heat loss has a comprehensive effect on the syngas production. The wall heat loss not only reduces the conversion efficiency, but also significantly decreases the syngas temperature. The effect of wall heat loss becomes weak as the equivalence is increased. The reforming efficiency drops from 0.440 to 0.424 for equivalence ratio of 2 and mixture velocity of 0.17 m/s for the predictions between adiabatic wall and non-adiabatic conditions.     

低分子量聚丙烯酸钾的合成及其应用

采用水溶液聚合法制备了低分子量聚丙烯酸钾（PAAK），并作为新型消焰剂加入单基发射药中。通过火焰原子吸收光谱法测试了PAAK中钾的含量；用乌氏黏度计测定了特性黏度；采用DSC法研究不同pH值的PAAK与硝化棉（NC）的相容性；利用充氮氧弹法对添加PAAK、硝酸钾KNO₃、硫酸钾K₂SO₄的单基发射药的燃烧残渣进行了对比研究。结果表明，合成的PAAK中，钾的质量分数为15.21%，相对分子量在3 000左右，有利于和NC均匀混合，且在中性或微碱性（pH＝7.0~7.5）的情况与NC相容性良好。与传统的KNO₃、K₂SO₄消焰剂相比，PAAK能够和NC均匀混合，制备均质透明的单基发射药；PAAK发射药的燃烧残渣最少，占发射药质量的0.18%。