Optimization of the surface texture for silicon carbide sliding in water

Surface texturing has been recognized as an effective means to improve the tribological performances of sliding surfaces. Usually, generation additional hydrodynamic pressure to increase the load carrying capacity is regarded as the most significant effect of surface texture. In the case of silicon carbide sliding against identical material in water, the experimental results indicate that surface texture is also helpful to improve the running-in progress to smooth the contact surfaces, showing another reason to result in low friction. Based on the consideration of enhancing the generation of hydrodynamic pressure and improving running-in progress, a surface texture pattern, which was combined with large (circle, 350 μm in diameter) and small (rectangular, 40 μm in length) dimples, was designed to maximize the texture effect on the load carrying capacity of SiC surfaces sliding in water. The friction coefficient of such textured surface was evaluated and compared with that of untextured and those only with large or small dimples only. The friction reduction mechanisms of the patterns with different dimples in size are discussed.     

On decomposition of continuity

Summary The main purpose of this paper is to introduce the concepts of η-sets, ηζ-sets,η-continuity and ηζ-continuity and to obtain a decomposition of continuity.     

一类多维指数分布的参数估计

考虑生存函数为(F)(x1,x2,…,xn)=P{X1＞x1,…,Xn＞xn}=exp{-[n∑i=1(xi/θi)1/δ]δ}(0＜xi＜∞,0＜δ≤ 1,0＜θi＜∞,i=(1,n))的一类多维指数分布,给出了它的密度函数的表示式,并讨论了它的性质.提出了相关参数δ的估计(^δ),证明了(^δ)有相合性和渐近正态性,得到了(^δ)的渐近方差σ2δ.最后还给出了若干随机模拟的结果.     

k-树的补图的最小填充和树宽

一个图的最小填充问题是寻求边数最少的弦母图,一个图的树宽问题是寻求团数最小的弦母图,这两个问题分别在稀疏矩阵计算及图的算法设计中有非常重要的作用．一个k-树G的补图G称为k-补树．本文给出了k-补树G的最小填充数f(G) 及树宽TW(G)．     

Affine-scaling for linear programs with free variables

The affine-scaling modification of Karmarkar's algorithm is extended to solve problems with free variables. This extended primal algorithm is used to prove two important results. First the geometrically elegant feasibility algorithm proposed by Chandru and Kochar is the same algorithm as the one obtained by appending a single column of residuals to the constraint matrix. Second the dual algorithm as first described by Adler et al., is the same as the extended primal algorithm applied to the dual.