Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

Effects of an inhomogeneous electron density distribution on the hydrogen distribution in TiZrTaNbAl multi-principal element alloys

A body-centered cubic equiatomic TiZrTaNbAl multi-principal element alloy (MPEA) with elemental fluctuations was investigated to further understand the relationship between the microstructure and hydrogen distribution. In this study, a composition dependence of the hydrogen distribution was observed in the TiZrTaNbAl MPEA. An inhomogeneous electron density distribution of the MPEA was revealed by advanced differential phase-contrast scanning electron microscopy (DPC-STEM) for the first time. The results showed that the electron density has a significant effect on the hydrogen distribution in TiZrTaNbAl MPEAs. This work provides new insight into the design of materials with high hydrogen storage capacity and high hydrogen embrittlement resistance.     

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.     

西藏燕麦主要种植区灌溉定额空间分布及影响因素

燕麦为西藏自治区典型牧草之一,由于种植区地域辽阔,灌溉试验结果受限,西藏燕麦主要种植区的灌溉定额尚不明确。本文在西藏燕麦主要种植区内选取28个典型站点进行资料收集,遵循农业气候相似原则进行区域划分,基于水量平衡法揭示了西藏燕麦主要种植区灌溉定额的空间分布特征,并根据统计学原理分析了其影响因素。研究表明:燕麦主要种植区的灌溉定额呈由西藏中部至东部呈现先递增后递减的趋势,50%水文年下的燕麦灌溉定额在56~265 mm之间变化。降雨量是影响研究区内燕麦灌溉定额的主要因素(R²为0.515),ET₀次之(R²为0.152);其它气象因素中,日照时数对研究区燕麦灌溉定额影响较大(R²为0.462),且呈正相关关系;相对湿度对燕麦灌溉定额影响较小。西藏燕麦主要种植区的灌溉定额及其空间分布可为西藏自治区灌溉用水管理提供支撑。     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Statistical Piezotronic Effect in Nanocrystal Bulk by Anisotropic Geometry Control

Utilizing inner-crystal piezoelectric polarization charges to control carrier transport across a metal-semiconductor or semiconductor–semiconductor interface, piezotronic effect has great potential applications in smart micro/nano-electromechanical system (MEMS/NEMS), human-machine interfacing, and nanorobotics. However, current research on piezotronics has mainly focused on systems with only one or rather limited interfaces. Here, the statistical piezotronic effect is reported in ZnO bulk composited of nanoplatelets, of which the strain/stress-induced piezo-potential at the crystals’ interfaces can effectively gate the electrical transport of ZnO bulk. It is a statistical phenomenon of piezotronic modification of large numbers of interfaces, and the crystal orientation of inner ZnO nanoplatelets strongly influence the transport property of ZnO bulk. With optimum preferred orientation of ZnO nanoplatelets, the bulk exhibits an increased conductivity with decreasing stress at a high pressure range of 200–400 MPa, which has not been observed previously in bulk. A maximum sensitivity of 1.149 µS m⁻¹ MPa⁻¹ and a corresponding gauge factor of 467–589 have been achieved. As a statistical phenomenon of many piezotronic interfaces modulation, the proposed statistical piezotronic effect extends the connotation of piezotronics and promotes its practical applications in intelligent sensing.     

Influence of SiC microstructure on its corrosion behavior in molten FLiNaK salt

The influence of the microstructure on the corrosion rate of three monolithic SiC samples in FLiNaK salt at 900 °C for 250 h was studied. The SiC samples, labeled as SiC-1, SiC-2, and SiC-3, had corrosion rates of 0.137, 0.020, and 0.043 mg/cm²h, respectively. Compared with grain size and the presence of special grain boundaries (i.e., Σ3), the content of high-angle grain boundaries (HAGBs) appeared to have the strongest influence on the corrosion rate of SiC in FLiNaK salt, since the corrosion rate increased six times as the concentration of high-angle grain boundaries increased from 19 to 32% for SiC-2 and SiC-1, respectively. These results stress the importance of controlling the content of HAGBs during the production process of SiC.     

Neural network-based flight control systems: Present and future

As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications.     

The effect of particle size distribution on the microstructure and properties of Al2O3 ceramics formed by stereolithography

Stereolithography (SL) shows advantages for preparing alumina-based ceramics with complex structures. The effects of the particle size distribution, which strongly influence the sintering properties in ceramic SL, have not been systematically explored until now. Herein, the influence of the particle size distribution on SL-manufactured alumina ceramics was investigated, including bending strength at room temperature, post-sintering shrinkage, porosity, and microstructural morphology. Seven particle size distributions of alumina ceramics were studied (in μm/μm: 30/5, 20/3, 10/2, 5/2, 5/0.8, 3/0.5, and 2/0.3); a coarse:fine particle ratio of 6:4 was maintained. At the same sintering temperature, the degree of sintering was greater for finer particle sizes. The particle size distribution had a larger influence on flexural strength, porosity and shrinkage than sintering temperature when the particle size distribution difference reached 10-fold but was weaker for 10 μm/2 μm, 5 μm/2 μm and 5 μm/0.8 μm. The sintering shrinkage characteristics of cuboid samples with different particle sizes were studied. The use of coarse particles influenced the accuracy of small-scale samples. When the particle size was comparable to the sample width, such as 30 μm/5 μm and 5 mm, the width shrinkage was consistent with the height shrinkage. When the particle size was much smaller than the sample width, such as 2 μm/0.3 μm and 5 mm, the width shrinkage was consistent with the length shrinkage. The results of this study provide meaningful guidance for future research on applications of SL and precise control of alumina ceramics through particle gradation.