槽孔式水力驱动控制棒槽孔阻力系数实验研究

对槽孔式水力驱动控制棒槽对孔阻力系数进行了大量实验研究，获得了槽孔式水力驱动控制棒槽对孔阻力系数和其随槽对孔位移的变化规律，分析了槽对孔阻力系数与控制棒槽对孔结构参数之间的关系。结果表明：随槽对孔位移的增加，槽对孔阻力系数从某一较大的定值迅速降低到某一较小的定值，然后再迅速反回到初始的定值，形成一个对称的宽幅波谷；槽高使阻力系数曲线波谷幅宽发生变化，也使完全不重合段的阻力系数发生变化；随内套孔径的增大，阻力系数有所降低，其对阻力系数的影响也进一步减弱。孔径增大到一定程度，阻力系数基本不受孔径参数的影响。     

Zr-2/Cr反应扩散研究

研究了Zr-2/Cr扩散偶在1023－1123K范围内的反应扩散，用扫描电镜观察反应宽度，用能谱仪（EDS）测定了反应层Zr,Fe和Cr沿扩散方向的浓度分布，研究了反应层的生长动力学，结果表明，反应层生长基本符合抛物经规律，生长过程受扩散控制，用Boltzman-Matano-Heumann模型计算了Cr在反应层Zr（Fe,Cr）2中的互扩散系数D，得到了互扩散系数D与温度的Arrhenius方程，由计算的扩散数据与Cr在Zr中形成稀固溶体时Cr的扩散数据比较可知，Cr在金属间化合物Zr（Fe,Cr）2中的扩散比在稀因溶体中的扩散快5个数量级。     

变井储系数的确定方法及其在反褶积分析中的应用

中针对变井储试井分析问题，给出了确定变井储系数及计算续流量的方法，并用反褶积分析积分析方法解释了未出现径向流的早期测压数据，给出了解决早期试井资料分析问题的有效方法。     

聚碳硅烷的分子量分布与可纺性研究

阐述了聚碳烷的合成及其分子量分布，讨论了高低分子含量对聚碳硅烷熔点及可纺性的影响，而且提出了分子量分布的控制标准与方法。     

β—BBO晶体的电光性能

用干涉法测量了β－ＢＢＯ晶体的电光系数：γ２２＝２．６，γ３３＝０．２３，γ３１＝０．２５，γ５１＝－３．５×１０－１２ｍ／Ｖ。结果表明如果在Ｙ方向加电场，Ｚ方向通光，β—ＢＢＯ晶体可能制作成有应用价值的光开关。     

基底元素表面富集与扩散阻档层

根据An－Ag系统以及An－Cu系统的扩散系数计算，提出了扩散阻挡层模型。利用这个模型对Au－Ag系统进行有关实验，得利了较好的验证。     

Calculation of second virial coefficients and gaseous viscosities of the refrigerants HFC-32 (CH2 F2), HFC-23 (CHF3), and HCFC-22 (CHC1F2)

The second virial coefficients of refrigerants HFC-32 (CH₂F₂), HFC-23 (CHF₃), and HCFC-22 (CHC1F₂) have been correlated on the bisis of site site model potential and have been compared with experimental results. The molecular interactions consisted of repulsion dispersion and electrostatic parts. From the site site potentials adjusted to the experimental second virial coefficients, spherically averaged potentials have been determined and a subsequent calculation of gaseous viscosity has been carried out. Agreement between measured and calculated values of second virial coellicients and gaseous viscosity is satisfactory. Calculated values of second virial coefficients and gaseous viscosity beyond available experimental data, therefore. can be assumed as a reliable extrapolation to lower and higher temperatures.     

Vapor-phase viscosity of phenol

New measurements of the vapor-phase viscosity of phenol were performed from 437 up to 624 K and for densities between 0.006 and 0.023 mol · L^–1 in an all-quartz oscillating-disk viscometer with small gaps. Thus, including our own measurements reported earlier, experimental data are available in the temperature range between 376 and 639 K and in the density range from 0.001 up to 0.023 mol · L^–1. The data were evaluated with a density series for the viscosity in which only a linear density contribution is included. The values of the second viscosity virial coefficient obtained for phenol as well as for benzene, toluene, and p-xylene were compared with results of the Rainwater-Friend theory and of the modified Enskog theory on the basis of the Lennard-Jones 12-6 potential. The agreement is reasonable, when the potential parameter ratios determined by Bich and Vogel are used. The influence of bound dimers seems to be already taken into account in the three-monomer contribution according to Hoffman and Curtiss.Paper dedicated to Professor Joseph Kestin.     

聚醚合成工业齿轮油的研制

以聚醚为基础油辅以抗磨剂、抗氧剂、防锈剂等多种添加剂研制而成的KGW聚醚合成工业齿轮油具有优异的黏温性能和低温性能，优异的极压抗磨性，极优的减摩性能，可满足高负荷、强冲击等苛刻条件下各类齿轮传动装置的润滑要求。该系列产品达到国外同类油品质量水平。     

Comments on the shortcomings of predicting the precision of Cavalieri volume estimates based upon assumed measurement functions

It is well known that the estimation of an object's volume by means of serial cross-sections, the so-called Cavalieri method, yields an unbiased estimate. But by itself it provides no means by which to estimate how precise this estimate is unless the shape of the volume is fully known beforehand. This knowledge can only be partially determined from the serial section information that is collected. Methods have been developed that claim to surmount this difficulty by using the serial section data to create a mathematical model of the volume's shape properties. The model then is used to estimate (predict) the precision of the volume estimate (its CE) from the single set of data available. Unfortunately, the theory underlying the model is flawed and so the model itself amounts to no more than an unsubstantiated guess about the shape of the volume. Therefore, the precision of the volume estimates that one obtains from the method is only as good as the model and this cannot be ascertained from the single set of acquired data. In this letter I explain the inadequacies of the modelling method. I suggest that it be used only with caution, if at all. Instead I suggest two alternative ways to predict the CE, one that is based upon a rule-of-thumb approach to the object's shape, and another that is based upon spectral analysis of the measurement function and that is easy to implement with available computer software.