碳热还原杂化前驱体合成SiC-TaC纳米复合粉体

以五氯化钽(TaCl5)、正硅酸乙酯(TEOS)和葡萄糖(C6H12O6 H2O)为原料制备了葡萄糖复合凝胶,凝胶经过450℃煅烧得到C-SiO2-Ta2O5杂化前驱体,通过碳热还原前驱体,于1200～1500℃合成了SiC-TaC纳米复合粉体,并用X射线衍射扫描电镜和能谱仪对产物进行表征。结果表明:凝胶中无定型的SiO2和Ta2O5可通过Si—O—Ta键合,均匀分布的Si—O—Ta—C长链使得杂化前驱体内部结合成为牢固的互穿网络结构;TaC于1200℃时得到,而SiC可在1400℃开始合成,反应可在1500℃完成。在不同的钽硅摩尔比下,SiC-TaC纳米复合粉体具有差异性形貌。当钽硅比约为0.02时,SiC与TaC纳米晶粒颗粒分布均匀,同质化明显。随着钽硅比的升高,SiC有从球状转变为纳米线状的趋势。     

粗面岩储集层录井评价方法

辽河油田粗面岩油气藏比较发育，但储集层的均质性较差，增加了对其评价的难度。该文利用核磁共振技术和气相色谱技术在储集层评价上具有的独特技术优势，经过现场录井的不断实践，总结了粗面岩油气层的综合解释方法，建立了粗面岩储集层评价标准，并在实际中加以应用，取得了较好的效果，为辽河油田的进一步勘探和开发提供了可靠的依据。     

MLD结构下电磁兼容混响室内场均匀性分析

为了进一步提高电磁兼容混响室内场均匀性,提出了最大长度散射体(MLD)一种新的位置,通过时域有限差分(FDTD)方法对混响室内的场进行了仿真分析,并与设置搅拌器情况下的混响室内场均匀性以及散射体位于混响室内6个面情况下混响室内的场均匀性作了比较。结果表明提出的散射体位置可有效地提高混响室内场均匀性。     

掺钕磷酸盐玻璃的小信号增益性能

测试了应用于神光Ⅱ系列装置93片N31型钕玻璃的小信号增益系数。结果表明,Nd2O3质量分数为2.2%的钕玻璃平均小信号增益系数为0.0387 cm-1,Nd2O3质量分数为3.0%的钕玻璃平均小信号增益系数为0.0416 cm-1,两种浓度的钕玻璃不同样品间小信号增益系数的起伏范围分别为0.86%和0.76%。根据所测定的增益值,表明N31型钕玻璃的增益起伏符合神光Ⅱ系列装置要求,为实现该装置中每一路增益性能的平衡提供了有力保障,也为今后对更大尺寸钕玻璃增益性质的控制提供了经验。     

改善PCB镀铜均镀性

该文阐述了改善PCB镀铜均镀性的基本方法。     

用激光冲击波无损评估材料内部的均一性

利用脉冲激光诱导的冲击波对材料的内部组织结构进行无损评估，首次通过测量激光在铝和碳纤维／环氧复合材料中诱导的冲击波获得了材料内部的均一性信息。     

某杂填土场地地基勘探评价

对上海某建筑物拟建场地杂填土地基进行专项评价分析，查明拟建工程场地浅部杂填土层的均匀性，确定杂填土层的地基极限承载力，评价保留杂填土地基的可行性，并对地基处理提出了建议方案。     

The effect of a non-circular drawing sequence on delamination characteristics of pearlitic steel wire

In this study, a non-circular drawing (NCD) sequence was applied to investigate the effect of deformation behavior, microstructure and texture evolution on delamination characteristics of pearlitic steel wire under torsional deformation mode. The multi-pass NCD sequence was numerically and experimentally applied up to the 12th pass in comparison with conventional wire drawing (WD). For investigation of the deformation characteristics of the drawn wires, three-dimensional finite element and flownet analyses were carried out. These simulation results indicated that the NCD could impose relatively homogeneous plastic deformation on the wire compared to the WD. From the scanning electron microscopy and X-ray diffraction results, globular cementite and cylindrical texture component, which might increase likeliness of delamination fracture, were rarely observed in the NCD drawn wire. In the torsion test, the delamination fracture was observed in the WD drawn wire for the 10th pass while it did not occur for the 12th pass NCD. In addition, the ultimate tensile strength (UTS) of 2300 MPa grade wire was manufactured by the NCD and the UTS value was 257 MPa higher than the one of the WD. Therefore, it was demonstrated that the multi-pass NCD could impose relatively homogeneous plastic deformation on the wire, resulting in high-torsional ductility with better strength compared to the WD.     

综合颜色和形态特征的小麦田杂草识别方法

利用机器视觉技术把杂草精确识别出来是精细农业领域研究的热点问题之一。针对杂草与小麦叶子交叠的情况，提出一种综合颜色和形态特征的方法进行杂草识别。在L*a*b*颜色空间，选取a*作为特征量并用改进的最大类间方差法进行阈值分割获得植物图像；在HSI颜色空间，利用多层的同质性分割算法分离小麦与杂草；结合形态学特征开闭运算滤波及二值逻辑与运算获得杂草图像；模拟化学除草系统，从理论上评价整个系统的识别效率。实验结果表明：杂草正确识别率高达92.6%以上，且除草剂的使用量减少超过72.4%。     

Testing equality of covariance matrices when data are incomplete

In the statistics literature, a number of procedures have been proposed for testing equality of several groups’ covariance matrices when data are complete, but this problem has not been considered for incomplete data in a general setting. This paper proposes statistical tests for equality of covariance matrices when data are missing. A Wald test (denoted by T₁), a likelihood ratio test (LRT) (denoted by R), based on the assumption of normal populations are developed. It is well-known that for the complete data case the classic LRT and the Wald test constructed under the normality assumption perform poorly in instances when data are not from multivariate normal distributions. As expected, this is also the case for the incomplete data case and therefore has led us to construct a robust Wald test (denoted by T₂) that performs well for both normal and non-normal data. A re-scaled LRT (denoted by R^*) is also proposed. A simulation study is carried out to assess the performance of T₁, T₂, R, and R^* in terms of closeness of their observed significance level to the nominal significance level as well as the power of these tests. It is found that T₂ performs very well for both normal and non-normal data in both small and large samples. In addition to its usual applications, we have discussed the application of the proposed tests in testing whether a set of data are missing completely at random (MCAR).