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Intercalated polyoxymethylene (POM)/molybdenum disulfide (MoS 2 ) nanocomposites were prepared by in situ intercalation/polymerization. The structures of the composites were characterized by means of powder X-ray diffraction (XRD) and transmission electron microscopy. The XRD pattern showed that the polymer was inserted into the MoS 2 galleries. The interlayer spacing of the intercalated phase increased from 6.15 to 11.18 Å . The thermal behavior of the composites was also investigated through thermogravimetric analysis. The results show that the heat resistance of the intercalated composites decreased slightly. The tribological behavior of POM/MoS 2 was investigated on an MQ-800 end-face tirbometer under dry friction. The worn surfaces were observed by scanning electron microscopy. The results show that POM/MoS 2 presented better friction reduction and wear resistance, especially under high load. The friction mechanism of the nanocomposites is also discussed in association with X-ray photoelectron spectroscopy.

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ABSTRACT:Ice jams can sometimes occur in high latitude rivers during winter and the resulting water level rise may generate costly and dangerous flooding such as the recent ice jam flooding in the Nechako River in downtown Prince George in Canada. Thus, the forecast of water level and ice jam thickness is of great importance. This study compares three methods to simulate and forecast water level and ice jam thickness based on field observations of river ice jams in the Quyu Reach of the Yellow River in China. More specifically, simulation results generated by the traditional multi variant regressional method are compared to those of the back propagation neural network and the support vector machine methods. The forecast of ice jam thickness and water level under ice jammed condition have been conducted in two different approaches, 1) simulation of water level and ice jam thickness in the second half of the period of measurement using models developed based on data gained during the first half of the period of measurement, 2) simulation of water level and ice jam thickness at the downstream cross sections using models developed based on data gained at the upstream cross sections. For this reason, as the results of simulation and field observations indicated, the back propagation neural network method and the support vector machine method are superior in terms of accuracy to the multi-variant regressional method.

An analytical vibration response in the time domain for an axially translating and laterally vibrating string with mixed boundary conditions is considered in this paper. The domain of the string is a constant, dependent upon the general initial conditions. The translating tensioned strings possess different types of mixed boundary conditions, such as fixed dashpot, fixed spring-dashpot, fixed mass-spring-dashpot. An analytical solution using a reflected wave superposition method is presented for a finite translating string. Firstly, the cycle of boundary reflection for strings is provided, which is dependent upon the string length. Each cycle is divided into three time intervals according to the travelling speed and direction of the string. Applying D'Alembert's principle and the reflection properties, expressions for the reflected waves under three different non-classical boundary conditions are derived. Then, the vibrational response of the axially translating string is solved for three time intervals by using a reflected wave superposition method. The accuracy and efficiency of the proposed method are confirmed numerically by comparison to simulations produced using a Newmark-β method solution. The energy expressions for a travelling string with a fixed dashpot boundary condition is obtained and the time domain curves for the total energy and the change of energy at the boundaries are given.