Strength of cylinder joint adhesively bonded by coupling

Summary A method of joining two metal cylindrical shafts with adhesive coupling is proposed. Two cylindrical shafts with the same diameter are connected by bonding through a cylindrical coupling with epoxy resin. The strength of the shaft joint under tensile loading and torsional loading is investigated analytically and experimentally. The stress and strain distributions of the shaft joint is analyzed by the finite element method. The analyzed strain distributions in the joint are compared with experimental values. The joint strength is predicted by applying the strength laws of shafts, coupling, adhesive layer and adhesive interface between shaft and adhesive coupling. The effects of the coupling dimension on the joint strength are examined. It is shown that the adhesive shaft joint can transfer the load by which the cylindrical shafts are plastically deformed.This paper was refined by the author, K. Ikegami, during statying at Technische Universität München under the support of Deutscher Akademischer Austauschdients. The author is grateful to Professor Lippmann of Technische Universität München who is the host professor of the support.     

Weather Risk in Offshore Projects

Risk analysis tools have been used to help manage various projects. This paper describes a case study in which an extension to the stochastic project network model was developed for a risk analysis of an oil platform installation, quantifying the possible impact of the weather on the project's schedule. Examination of the weather data suggested the use of a Markov weather model combined with a separate residence time distribution for key states. The weather model was incorporated into the stochastic project network allowing the interactions of the various project uncertainties to be examined. While the weather introduced a significant additional risk to the project, analysis of management's options indicated that much of the risk might be avoided. In particular, the analysis quantified the benefits of scheduling the project start to take advantage of the seasonal variations and hiring heavy duty equipment to operate in more arduous conditions.     

Book reviews

Ohne Zusammenfassung

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Book reviews

     

Multivariate Gini Indices

Two extensions of the univariate Gini index are considered:R_D, based on expected distance between two independent vectors from the same distribution with finite meanμ ^d; andR_V, related to the expected volume of the simplex formed fromd+1 independent such vectors. A new characterization ofR_Das proportional to a univariate Gini index for a particular linear combination of attributes relates it to the Lorenz zonoid. TheLorenz zonoidwas suggested as a multivariate generalization of the Lorenz curve.R_Vis, up to scaling, the volume of the Lorenz zonoid plus a unit cube of full dimension. Whend=1, bothR_DandR_Vequal twice the area between the usual Lorenz curve and the line of zero disparity. Whend>1, they are different, but inherit properties of the univariate Gini index and are related via the Lorenz zonoid:R_Dis proportional to the average of the areas of some two-dimensioned projections of the lift zonoid, whileR_Vis the average of the volumes of projections of the Lorenz zonoid over all coordinate subspaces.     

Optimal Server Acquisition in Open Queueing Networks

Several production and flexible manufacturing systems can naturally be modelled using queueing networks. In this paper, we consider the problem of acquiring servers for the nodes of an open queueing network, so as to optimize the steady-state mean virtual system parameters subject to a budget constraint. A partial enumeration scheme and a heuristic method have been proposed to solve this problem. Empirical results based on randomly generated test problems are used to identify a class of problems for which the heuristic performs well.     

Glass transitions in hydrogen-bonded polymer complexes

Mutual precipitates of poly (N, N-dimethyl acrylamide) and poly (4-hydroxystyrene) were collected from dioxane, methanol, or acetone. The glass transition (T_g) temperatures of the precipitates are higher than the weight-average values. Clear films cast from dimethylformamide solutions have lower T_g values. Complexation also occurred between poly (ethyl oxazoline) and poly (4-hydroxystyrene) in dioxane and between poly (vinyl pyrrolidone) and poly (4-hydroxystyrene) in methanol. Again, the glass transition temperatures of the precipitates are higher than the values for the blend films. The ΔC_p values associated with the glass transitions of the complexes are smaller than those of the blends having the same compositions. Negative excess heat capacities of mixing have been observed for several precipitates.     

Specific high performance liquid chromatographic determination of the molecular weight and concentration of hyaluronic acid in complex mixtures by labelled hyaluronate binding proteins.

A simple High performance liquid chromatographic (HPLC) method for the specific determination of the molecular weight and concentration of hyaluronic acid (HA) in complex mixtures has been developed. Hyaluronate-binding proteins isolated from bovine cartilage labelled by 125I or fluoresceinisothiocyanate were used as specific markers. The specific binding affinities of the markers were compared and were found to have association constants of 1.6 x 10(7) M-1 and 1.2 x 10(7) M-1 respectively. The HA levels and molecular weight distributions can be easily determined in the range 10-500 ng/mL in complex mixtures by the use of markers, molecular sieving HPLC columns and appropriate detectors. It has been demonstrated clearly that the method is useful for the highly specific determination of the parameters in complex biological samples such as serum and synovial fluids and is recommended for clinical applications.     

On the reconstruction index of permutation groups: semiregular groups

Summary. The reconstruction index of all semiregular permutation groups is determined. We show that this index satisfies 3 ￡ r(G, W) ￡ 5 3 \leq \rho(G, \Omega) \leq 5 and we classify the groups in each case.