Step Structure in Cold-Rolled Deformed Nanocrystalline Nickel

The microstructure characteristic of the cold-rolled deformed nanocrystalline nickel metal is studied by transmission electron microscopy. The results show that there are step structures nearby the grain boundary (GB), and the contrast of stress field in front of the step corresponds to the step in the shape. It is indicated that the interaction between twins and dislocations is not a necessary condition to realizing the deformation. In the later stage of the deformation when the grain size becomes about 100nm, the deformation can depend upon the moving of the boundary of the stack faults (SFs) which result from the partial dislocations emitted from GBs. However, when the size of SFs grows up, the local internal stress which is in front of the step gradually becomes higher. When this stress reaches a critical value which stops the gliding of the partial dislocations, the SFs will stop to grow up and leave a step structure behind.

Effective Stress and Liquefaction of Seabed Under the Action of Standing Waves

波浪作用下海床的稳定性与液化分析是海底管线、防波堤和海洋平台设计中必须仔细考虑的问题。推荐了一个循环载荷作用下土体的弹塑性实用本构模型,并给出了一种粉土的模型参数,该模型直接根据初始应力状态和循环应力的大小与作用时间计算土体的塑性应变增量,在有限元计算中不需要引入弹塑性矩阵。采用Biot理论和有限单元法,对海床有效应力的变化过程分析表明,波腹点下海床存在较大的液化可能性。波浪作用对海床存在一定的压密作用。

A generalized wave action conservative equation for the dissipative dynamical system in the nearshore region

To describe the various complex mechanisms of the dissipative dynamical system between waves, currents, and bottoms in the nearshore region that induce typically the wave motion on large-scale variation of ambient currents, a generalized wave action equation for the dissipative dynamical system in the nearshore region is developed by using the mean-flow equations based on the Navier-Stokes equations of viscous fluid, thus raising two new concepts: the vertical velocity wave action and the dissipative wave action, extending the classical concept, wave action, from the ideal averaged flow conservative system into the real averaged flow dissipative system (that is, the generalized conservative system). It will have more applications.

Bayesian learning of noisy Markov decision processes

This work addresses the problem of estimating the optimal value function in a Markov Decision Process from observed state-action pairs. We adopt a Bayesian approach to inference, which allows both the model to be estimated and predictions about actions to be made in a unified framework, providing a principled approach to mimicry of a controller on the basis of observed data. A new Markov chain Monte Carlo (MCMC) sampler is devised for simulation from theposterior distribution over the optimal value function. This step includes a parameter expansion step, which is shown to be essential for good convergence properties of the MCMC sampler. As an illustration, the method is applied to learning a human controller.