Evaluation of the fracture toughness properties of polytetrafluoroethylene

Polytetrafluoroethylene (PTFE) (Dupont Tradename Teflon) is a common polymer with many structural applications including sheet, gaskets, bearing pads, piston rings and diaphragms. The interest here developed because this polymer is being considered as the major component of a newly proposed `reactive' material with a possible application as a projectile to replace common inertial projectiles. Little mechanical property data is available on this material since it is commonly used only as a coating material with the dominant properties being its low friction coefficient and high application temperature. Previous work (Joyce, 2003) on commercially available sheet PTFE material has demonstrated the applicability of the normalization method of ASTM E1820 (1999), the elastic-plastic fracture toughness standard to develop fracture toughness properties of this material over a range of test temperatures and loading rates. Additional work on the aluminum filled `reactive' derivative of the basic PTFE polymer (Joyce and Joyce, 2004) has also recently been completed. In this work, standard ASTM E1820 fracture toughness specimens machined from sintered pucks of PTFE were tested at four test temperatures and at a range of test rates to determine the J _Ic and J resistance curve characteristics of the PTFE material. The major results are that while crack extension is difficult at standard laboratory loading rates at ambient (21 °C) temperature or above, for temperatures slightly below ambient or for elevated loading rates, a rapid degradation of fracture resistance occurs and cracking occurs in a ductile or even nearly brittle manner.     

推动无障碍环境建设,实现人性化空间

正常的社会是健全人和残疾人共同生活的社会。作为社会进步和文明的重要标志, 建设无障碍环境已成为世界共同的课题。本文论述了无障碍设计的意义、国际动向、无障碍环境的成本及其在我国的落实情况, 以期提供一个新的思考方向引起更多的关注和理解,来推动无障碍环境建设,实现人性化空间。     

λCalculi with Explicit Substitutions Preserving Strong Normalization

This paper studies preservation of β-strong normalization by two different confluent λ-calculi with explicit substitutions defined in [96]; the particularity of these calculi, called λ _d and λ _dn respectively, is that both have a (weak) composition operator for substitutions. We apply an abstract simulation technique to reduce preservation of β-strong normalization of λ _d and λ _dn to that of another calculus, called λ _f having no composition operator. Then, preservation of β-strong normalization of λ _f is shown using the same technique as in [2]. As a consequence, λ _d and λ _dn become the first λ-calculi with explicit substitutions having (weak) composition and preserving β-strong normalization. As an aside, we also show how to apply our technique to reduce preservation of β-strong normalization of the calculus λ _v in [20] to that of λ _f . Received: August 19, 1997; revised version: November 13, 1998     

对三孔隙度交会图法进行测井曲线标准化的改进

由于三孔隙度交会图法不能解决欠压实、疏松岩性地层的测井曲线标准化问题,所以对其进行了改进。根据 东营凹陷一些关键井的测井资料,讨论了在测井井眼条件良好时选取纯砂岩、纯水层用交会图法进行测井曲线标 准化的方法,即引入声波地层因素公式后,欠压实的高孔隙地层的声波时差与补偿中子、声波时差与密度的关系均 为非线性关系,应用新的关系对三孔隙度资料进行测井曲线标准化。改进后的方法已得到东营凹陷13口探井资 料的验证是可行的。     

波动方程多尺度反演

本文基于多尺度反演思想提出波动方程多尺度反演方法。该方法的基本思路是：对反演的目标函数进行多尺度分解．在每一尺度下利用正则化方法反演求解，克服了反演问题的不适定性，获得全局最优解．使得反演结果的分辨率和保真性得到提高。本文利用小波变换实现多尺度反演，并且是先通过在大尺度上反演得到一个比较好的参数估计．再将此估计作为较小尺度的初值进行反演．直至获得全局最优解。文中的应用实例说明了该方法具有对初始模型依赖性低、收敛速度快、反演结果稳定的优点。     

基于ERP电子元器件数据库的标准化梳理方案的探讨

该文针对ERP中电子元器件数据库中部分物料命名模糊,尤其是物料信息库缺乏管控造成物料的一物多码的现状,提出了采用分类的方法对物料数据进行管理,结合物料主数据的基本构成及物料数据库存在的问题,给出了具体的解决方法。从而实现电子元器件数据库标准化管控,达到企业降本增效的目的。     

Group aggregating normalization method for the preprocessing of NMR-based metabolomic data

Data normalization plays a crucial role in metabolomics to take into account the inevitable variation in sample concentration and the efficiency of sample preparation procedure. The conventional methods such as constant sum normalization (CSN) and probabilistic quotient normalization (PQN) are widely used, but both methods have their own shortcomings. In the current study, a new data normalization method called group aggregating normalization (GAN) is proposed, by which the samples were normalized so that they aggregate close to their group centers in a principal component analysis (PCA) subspace. This is in contrast with CSN and PQN which rely on a constant reference for all samples. The evaluation of GAN method using both simulated and experimental metabolomic data demonstrated that GAN produces more robust model in the subsequent multivariate data analysis, more superior than both CSN and PQN methods. The current study also demonstrated that some of the differential metabolites identified using the CSN or PQN method could be false positives due to improper data normalization.