Numerical study of microscopic particle arrangement of suspension flow in a narrow channel for the estimation of macroscopic rheological properties

In a narrow channel, the apparent relative viscosity of a suspension with finite-size particles is strongly dependent on its microscopic particle arrangement. Relative viscosity increases when suspended particles flow near the channel wall; thus, a suspension in a narrow channel does not always exhibit the same rheological properties even if the concentration is the same. In this study, we focus on the inertia and concentration of particles in a narrow channel and consider their effects on the microscopic particle arrangement and macroscopic suspension rheology. Two-dimensional pressure-driven suspension flow simulations were performed using a two-way coupling scheme, and normalized particle density distribution (PDD) were implemented to consider their particle arrangements. The results demonstrated that the velocity profiles for the particle suspension were changed by the Reynolds number and particle concentration because of the interactions between particles according to the power-law index. These changes affected the particle equilibrium positions in the channel, and the subsequent changes in solvent layer thickness caused changes in the macroscopic apparent viscosity. The behavior of microscopic particles played important roles in determining macroscopic rheology. Thus, we have confirmed that a normalized PDD can be used to estimate and assess the macroscopic rheology of a suspension.     

A review of thin film electrolytes fabricated by physical vapor deposition for solid oxide fuel cells

The ohmic resistance in solid oxide fuel cells (SOFCs) mainly comes from the electrolyte, which can be reduced by developing novel electrolyte materials with higher ionic conductivity and/or fabricating thin-film electrolytes. Among various kinds of thin-film fabrication technology, the physical vapor deposition (PVD) method can reduce the electrolyte thickness to a few micrometers and mitigate the issues associated with high-temperature sintering, which is necessary for wet ceramic methods. This review summarizes recent development progress in thin-film electrolytes fabricated by the PVD method, especially pulsed laser deposition (PLD) and magnetron sputtering. At first, the importance of the substrate surface morphology for the quality of the film is emphasized. After that, the fabrication of thin-film doped-zirconia and doped-ceria electrolytes is presented, then we provide a brief summary of the works on other types of electrolytes prepared by PVD. Finally, we have come to the summary and made perspectives.     

One-step to prepare high-performance gas diffusion layer (GDL) with three different functional layers for proton exchange membrane fuel cells (PEMFCs)

Gas diffusion layer (GDL) is one of the most important components of fuel cells. In order to improve the fuel cell performance, GDL has developed from single layer to dual layers, and then to multiple layers. However, dual or multi layers in GDL are usually prepared by layer-by-layer methods, which cost too much time, energy, and resources. In this work, we successfully developed a facile one-step method to prepare a GDL with three functional layers by utilizing the different sedimentation rates and filtration rates of short carbon fiber (CF) and carbon nanotube (CNT). The treatment temperature for this GDL is much lower than that of traditional method. The thickness of the GDL can be effectively controlled from as thin as 50 μm to more than 200 μm by simply adjusting the content of CF. The GDL with high flexibility is suitable to develop high performance flexible electronics. The fuel cell with the GDL has the maximum power density 1021 mW cm^?2, which shows 19% improvement comparing to the conventional one. Therefore, this work breaks the traditional concept that GDL for fuel cells only can be prepared by very complex and high-cost procedure.     

Nonsimilar solution of a boundary layer flow of a Reiner–Philippoff fluid with nonlinear thermal convection

The thermodynamics modeling of a Reiner–Philippoff-type fluid is essential because it is a complex fluid with three distinct probable modifications. This fluid model can be modified to describe a shear-thinning, Newtonian, or shear-thickening fluid under varied viscoelastic conditions. This study constructs a mathematical model that describes a boundary layer flow of a Reiner–Philippoff fluid with nonlinear radiative heat flux and temperature- and concentration-induced buoyancy force. The dynamical model follows the usual conservation laws and is reduced through a nonsimilar group of transformations. The resulting equations are solved using a spectral-based local linearization method, and the accuracy of the numerical results is validated through the grid dependence and convergence tests. Detailed analyses of the effects of specific thermophysical parameters are presented through tables and graphs. The study reveals, among other results, that the buoyancy force, solute and thermal expansion coefficients, and thermal radiation increase the overall wall drag, heat, and mass fluxes. Furthermore, the study shows that amplifying the space and temperature-dependent heat source parameters allows fluid particles to lose their cohesive force and, consequently, maximize flow and heat transfer.     

基于改进灰狼优化算法的服务功能链映射算法

随着工业互联网、车联网、元宇宙等新型互联网应用的兴起，网络的低时延、可靠性、安全性、确定性等方面的需求正面临严峻挑战。采用网络功能虚拟化技术在虚拟网络部署过程中，存在服务功能链映射效率低与部署资源开销大等问题，联合考虑节点激活成本、实例化开销，以最小化平均部署网络成本为优化目标建立了整数线性规划模型，提出基于改进灰狼优化算法的服务功能链映射（improved grey wolf optimization based service function chain mapping，IMGWO-SFCM）算法。该算法在标准灰狼优化算法基础上添加了基于无环K最短路径（K shortest path，KSP）问题算法的映射方案搜索、映射方案编码以及基于反向学习与非线性收敛改进三大策略，较好地平衡了其全局搜索及局部搜索能力，实现服务功能链映射方案的快速确定。仿真结果显示，该算法在保证更高的服务功能链请求接受率下，相较于对比算法降低了11.86%的平均部署网络成本。     

An optimal configuration for hybrid SOFC,gas turbine,and Proton Exchange Membrane Electrolyzer using a developed Aquila Optimizer

In this research, a technical, economic and environmental analysis has been proposed to a Hybrid Solid Oxide Fuel Cell (SOFC) system-based hybrid system including biomass, gas turbine, and Proton Exchange Membrane Electrolyzer. A multi-objective optimization technique has been utilized to improve the overall product cost and the exergy effectiveness based on a developed version of Aquila Optimizer (DAO). The main idea of using the developed version is to improve the accuracy and the precision of the original Aquila optimizer. The system is then authenticated in terms of energy/exergy effectiveness, and energy-economic efficiency. The achievements indicate that employing the optimization algorithm for different configurations provided satisfying results for the system.     

Automated prediction system of household energy consumption in cities using web crawler and optimized artificial intelligence

The supply of electrical energy is critical to convenient and comfortable living. However, people consume a large amount of energy, contributing to an energy crisis and global warming, and damaging some ecological cycles. Residential electricity consumption has greater elasticity than industrial and business consumption; it therefore has high energy-saving potential. This work establishes an automated platform, which provides information about residential electricity consumption in each city in Taiwan. Machine learning was used to forecast future residential electricity demand. A nature-inspired optimization method was applied to enhance the accuracy of the best machine learner, yielding an even better hybrid ensemble model. Performance measures indicate that the resulting model is accurate and provides effective information for reference. An automatic web-based system based on the model was combined with a web crawler and scheduled to run automatically to provide information on monthly residential electricity consumption in each county and city. By providing energy consumption information across the country, power providers and government can discuss policy and set different goals for energy use. The results of this study can facilitate the early implementation of energy-saving and carbon emission-reducing in cities and aid utility companies in establishing energy conservation guidelines.     

红心火龙果发酵液喷雾干燥工艺优化及红心火龙果籽油的研究

以红心火龙果发酵液作为研究对象,通过优化喷雾干燥工艺制备粉剂,最佳工艺条件为:20%麦芽糊精,进液量:10mL/min,进口温度为120℃,出口温度为65℃;得到的粉剂为紫红色粉末,益生菌含量达到108cfu/g以上,口感酸甜。将发酵后的火龙果籽进行提取,得到的火龙果籽油含有丰富的十六酸、亚油酸和油酸。     

Antibacterial activity of V- doped rod-like MgO crystals decorated with nanoflake layer

In present study, we report a V doping fabrication method for obtaining rod-like MgO crystals decorated with a nanoflake layer. This novel structure has only been minimally reported in literature. Pure MgO and Mg₂V₂O₇–MgO composite materials were obtained by precipitation and impregnation methods, with vanadium added concentrations of 0–9%. The influence of V doping on crystal structure and particle morphology of MgO was investigated by scanning electron microscopy (SEM). X-ray diffraction (XRD) analysis demonstrated that MgO has a cubic structure, while X-ray photoelectron spectroscopy (XPS) revealed that V⁵⁺ exists on the surface of MgO. The specific surface areas and pore sizes of MgO composites were calculated by BET and BJH analysis. These techniques revealed that specific surface area and pore size of MgO increased due to vanadium doping. The antibacterial effects of Mg₂V₂O₇–MgO composite materials against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were assessed using a bacterial killing/colony-forming unit (CFU) assay and bacteriostatic ring method. Our results demonstrate that V doping dramatically improved antimicrobial properties of MgO, with 7 mol% doping inducing the best antibacterial activity. The antibacterial mechanisms of Mg₂V₂O₇–MgO composite material were also proposed.