A New Finite-Difference Representation for the Vorticity at a Wall with Suction

Abstract

In two-dimensional convective transport, the vorticity at a wall is usually not well specified. There exist several representations to relate the vorticity at a wall to the stream function and interior vorticity values. These are shown to be inadequate when suction occurs at the wall. A new representation is proposed and shown to be significantly superior to the existing ones. The analysis can also be applied to heat transfer calculations at a wall with suction.     

Small-angle X-ray scattering studies on melting and recrystallization behaviors of poly(oxyethylene) crystallites in poly(d,l-lactide)/poly(oxyethylene) blends

Direct determination of the discrete distribution for crystalline lamellar thickness has been performed for poly(d,l-lactic acid)/poly(oxyethylene) (PDLLA/PEG) blends by conducting small-angle X-ray scattering (SAXS) measurements using synchrotron radiation. The PDLLA used was an random (racemic) copolymer of bio-based poly(l-lactic acid) (PLLA) and poly(d-lactic acid) (PDLA) with the lactide monomer ratio of l:d = 50:50. It is known that PLA is miscible with PEG in the amorphous state. In the current paper, we report comprehensive results on structural analyses of PDLLA/PEG blends in the course of heating and cooling process using SAXS to elucidate the change in the thickness distribution of the lamellae. As a consequence, it was found that the distribution of the lamellar thickness moves toward the larger value (in other words, lamellar thickening) as temperature approaches the melting point. Typically, the thickness distribution was dispersed in the range of 10–20 nm at room temperature and it changed toward 40 nm in the vicinity of the melting temperature. To the best of our knowledge, this is the first report of direct determination of the discrete distribution for the crystalline lamellar thickness and their in-situ changes in the course of the lamellar thickening process. As a result, the lamellar thickening was found to occur at much lower temperature for the blend samples with 10% and 20% of PDLLA contents as compared to the PEG 100% sample. This phenomenon can be ascribed to the melting point depression owing to the miscibility between PEG and PDLLA. Thereby, thinner lamellae were melted and thicker ones appeared at much lower temperature for the blends than for the PEG 100% sample. As for the average repeating distance (long period) of the lamellar stacks, an abrupt increase similar to the critical divergence was observed (from 25 nm to 50 nm) in the heating process. Not only for the melting behavior but also in the course of recrystallization, change in the lamellar-thickness distribution was uncovered, which shows strong hysteresis depending on what temperature the sample was cooled down from.     

Chromium(III) compounds as catalysts for Hydrocarbon Oxidation and hydroperoxide decomposition

Chromium stearate and chromium acetylacetonate are very active catalysts both for the oxidation of hydrocarbons by molecular oxygen and for the decomposition of organic hydroperoxides. During these reactions they also catalyze the oxidation of secondary alcohols to the corresponding ketones by organic hydroperoxides. From organic hydroperoxides and chromium(III)compounds chromium (VI) compounds are formed which are probably the effective agents oxidizing secondary alcohols to ketones.     

Fabrication and Thermal Dissipation Properties of Carbon Nanofibers Derived from Electrospun Poly(Amic Acid) Carboxylate Salt Nanofibers

Polyimides (PIs) possess excellent mechanical properties, thermal stability, and chemical resistance and can be converted to carbon materials by thermal carbonization. The preparation of carbon nanomaterials by carbonizing PI‐based nanomaterials, however, has been less studied. In this work, the fabrication of PI nanofibers is investigated using electrospinning and their transformation to carbon nanofibers. Poly(amic acid) carboxylate salts (PAASs) solutions are first electrospun to form PAAS nanofibers. After the imidization and carbonization processes, PI and carbon nanofibers can then be obtained, respectively. The Raman spectra reveal that the carbon nanofibers are partially graphitized by the carbonization process. The diameters of the PI nanofibers are observed to be smaller than those of the PAAS nanofibers because of the formation of the more densely packed structures after the imidization processes; the diameters of the carbon nanofibers remain similar to those of the PI nanofibers after the carbonization process. The thermal dissipation behaviors of the PI and carbon nanofibers are also examined. The infrared images indicate that the transfer rates of thermal energy for the carbon nanofibers are higher than those for the PI nanofibers, due to the better thermal conductivity of carbon caused by the covalent sp² bonding between carbon atoms.     

Phase Stability and Physical Properties of Cubic and Tetragonal ZrO2 in the System ZrO2–Y2O3–Ta2O5

The cubic ( c -ZrO₂) and tetragonal zirconia ( t -ZrO₂) phase stability regions in the system ZrO₂–Y₂O₃–Ta₂O₅ were delineated. The c -ZrO₂ solid solutions are formed with the fluorite structure. The t -ZrO₂ solid solutions having a c/a axial ratio (tetragonality) smaller than 1.0203 display high fracture toughness (5 to 14 MPa · m^1/2), and their instability/transformability to monoclinic zirconia ( m -ZrO₂) increases with increasing tetragonality. On the other hand, the t -ZrO₂ solid solutions stabilized at room temperature with tetragonality greater than 1.0203 have low toughness values (2 to 5 MPa · m^1/2), and their transformability is not related to the tetragonality.     

Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression,naive Bayes and RBFNetwork models for the Long County area (China)

The main goal of this study is to assess and compare three advanced machine learning techniques, namely, kernel logistic regression (KLR), naïve Bayes (NB), and radial basis function network (RBFNetwork) models for landslide susceptibility modeling in Long County, China. First, a total of 171 landslide locations were identified within the study area using historical reports, aerial photographs, and extensive field surveys. All the landslides were randomly separated into two parts with a ratio of 70/30 for training and validation purposes. Second, 12 landslide conditioning factors were prepared for landslide susceptibility modeling, including slope aspect, slope angle, plan curvature, profile curvature, elevation, distance to faults, distance to rivers, distance to roads, lithology, NDVI (normalized difference vegetation index), land use, and rainfall. Third, the correlations between the conditioning factors and the occurrence of landslides were analyzed using normalized frequency ratios. A multicollinearity analysis of the landslide conditioning factors was carried out using tolerances and variance inflation factor (VIF) methods. Feature selection was performed using the chi-squared statistic with a 10-fold cross-validation technique to assess the predictive capabilities of the landslide conditioning factors. Then, the landslide conditioning factors with null predictive ability were excluded in order to optimize the landslide models. Finally, the trained KLR, NB, and RBFNetwork models were used to construct landslide susceptibility maps. The receiver operating characteristics (ROC) curve, the area under the curve (AUC), and several statistical measures, such as accuracy (ACC), F-measure, mean absolute error (MAE), and root mean squared error (RMSE), were used for the assessment, validation, and comparison of the resulting models in order to choose the best model in this study. The validation results show that all three models exhibit reasonably good performance, and the KLR model exhibits the most stable and best performance. The KLR model, which has a success rate of 0.847 and a prediction rate of 0.749, is a promising technique for landslide susceptibility mapping. Given the outcomes of the study, all three models could be used efficiently for landslide susceptibility analysis.

     

大尺寸TFT-LCD电视的彩色和图像增强

最近几年,薄膜晶体管液晶显示器(TFT-LCD)技术取得了快速而显著的进步,其性能超过了PDP、CRT以及投影显示。毫无疑问,TFT-LCD已经成为高清电视应用的最佳实现方案。本文将介绍进一步增强大尺寸LCD电视的彩色和图像性能的技术。     

基于激光扫描技术的三维模型重建

通过分析三维激光扫描系统获取的点云数据,得到了利用点云数据构建三维模型的技术、方法和流程。介绍了利用地面三维激光扫描仪获取点云数据的过程以及结合RiSCAN PRO软件和Geomagic Studio软件进行建模的方法。对原始测量的点云数据进行处理(去除噪声,平滑,对多站点数据做拼接配准,提取目标建筑物等)得到正确和完整的目标建筑物的表面信息,然后构建三角网建立它的三维表面模型,最后通过所拍的照片进行纹理映射得到真实的三维模型。实验结果表明,利用上述方法可以有效地处理三维激光扫描获取的点云数据,实现对建筑物快速三维可视化建模。     

PRNN/ERLS-based predictive QoS-promoted DBA scheme for upstream transmission in EPON

This article proposes a PRNN/ERLS-based predictive QoS-promoted dynamic bandwidth allocation (PQ-DBA) scheme for upstream transmission in Ethernet passive optical network (EPON) systems. The proposed PQ-DBA scheme originally divides incoming packets of voice, video, data service traffic into six priorities, where packets having less room before QoS requirements violation or being in starvation situation will be dynamically promoted to high priority cycle-by-cycle. It predicts packets arriving at prediction interval for ONUs using pipeline recurrent neural network (PRNN)/extended recursive least squares (ERLS) so that the bandwidth allocation can be more up-to-date and then accurate. Simulation results show that the proposed PQ-DBA scheme achieves higher system utilization and lower average voice, video, data packet delay time than the DBAM scheme [Luo and Ansari, OSA J Opt Netw 4(9):561–572] by 4, and 21, 90, 43%, respectively, and the PQ-DBA scheme but without prediction by 2, and 26, 29, 34%, respectively.