High-order numerical simulation and modelling of the interaction of energetic and inert materials

We present an integrated algorithm on a Eulerian grid, for multimaterial simulations of energetic and inert materials modelled by non-ideal equations of state. We employ high-resolution shock capturing numerical algorithms for each material inside its domain and use an overlap domain method across the interface, maintained by a recently developed, hybrid, level-set algorithm. For applications to condensed explosives we implement a non-ideal, wide-ranging equation of state and reaction rate law. For inert materials, like plastic, metal, water, etc., we implement a (linear in the pressure) Mie–Grüneisen, (U _p ?U _s ), equation of state. We present a series of verifications of the integrated multimaterial code and show validations against experiment. We show examples of simulations of various experiments associated with real or planned experiments, some of which contain energetic materials (specifically the condensed explosives PBX-9502 and PBX-9501).     

一种简单路由算法下的全互连立方体网络性能分析

本文研究在一种简单路由算法条件下全互连立方体网络(FCCN，Fully Connected Cubic Network)的性能。研究结果表明在应用简单路由算法的条件下，至少在80％以上的情况下可以得到最短路径，而且这个比例是随着网络规模的扩大而增大的，进而得到网络最大结点间距离和平均结点距离的公式，而且网络性能在通信局部性的条件下可以显著提高。计算结果证明FCCN在信息局部性系统中具有比较高的并行处理效率。     

Data-Path布图系统的数据管理

Data-Path布图系统需要有效的数据管理作为支撑。该数据管理工作主要包括数据格式转换、数据结构设计和数据接口设计等方面。针对一个实际的Data-Path布图系统，设计了Verilog文件到DEF文件的转换算法，进行了相关数据接口的实现，指出了数据管理的特点与实现方法。     

总线事务级验证模型仿真性能研究

系统芯片的功能验证一直是芯片设计中最具挑战性的部分。基于事务的验证方法学被用来解决功能验证中的困难。该方法学通过提高验证的抽象层次来降低验证复杂度。但同时也对使用该方法学构建的验证平台组件可重用性有了更高的要求。其中总线功能模型可以在验证中模拟设计中的其他模块,是构建验证平台的重要组件。本文在方法学的基础上,讨论了两种类型的总线功能模型,并给出了verilog硬件描述语言的实现模型,最后通过实验比较了两种总线功能模型的仿真性能。     

基于混合图的总体布线调整

本文提出了一种基于混合图的总体布线调整方法。混合图是对表示布局的有向图进行一系列精确的顶点分解而产生的。用得到的图模型来表示总体布线信息,从而可以在总体布局优化的同时估计布线对芯片面积的影响,并对总体布线进行调整。由于总体布线是自动更新的,所以布局同时随着布线的调整和模块的移动而改进。本文还提出了多种瓶颈的概念和瓶颈间走线随模块旋转而变化的规律。最后给出的实验结果表明,这种算法在减小芯片面积上获得比较好的结果。     

Approximate importance sampling Monte Carlo for data assimilation

Importance sampling Monte Carlo offers powerful approaches to approximating Bayesian updating in sequential problems. Specific classes of such approaches are known as particle filters. These procedures rely on the simulation of samples or ensembles of the unknown quantities and the calculation of associated weights for the ensemble members. As time evolves and/or when applied in high-dimensional settings, such as those of interest in many data assimilation problems, these weights typically display undesirable features. The key difficulty involves a collapse toward approximate distributions concentrating virtually all of their probability on an implausibly few ensemble members.

After reviewing ensembling, Monte Carlo, importance sampling and particle filters, we present some approximations intended to moderate the problem of collapsing weights. The motivations for these suggestions are combinations of (i) the idea that key dynamical behavior in many systems actually takes place on a low dimensional manifold, and (ii) notions of statistical dimension reduction. We illustrate our suggestions in a problem of inference for ocean surface winds and atmospheric pressure. Real observational data are used.     

Hierarchical condensation near phase equilibrium

A novel mechanism of new phase formation is studied both experimentally and theoretically in the example of quasi-equilibrium stationary condensation in an ion–plasma sputterer. Copper condensates are obtained to demonstrate that a specific network structure is formed as a result of self-assembly in the course of deposition. The fractal pattern related is inherent in the phenomena of diffusion limited aggregation. Condensate nuclei are shown to form statistical ensemble of hierarchically subordinated objects distributed in ultrametric space. The Langevin equation and the Fokker–Planck equation related are found to describe stationary distribution of thermodynamic potential variations at condensation. Time dependence of the formation probability of branching structures is found to clarify the experimental situation.     

On the motif distribution in random block-hierarchical networks

The distribution of motifs in random hierarchical topological networks defined by nonsymmetric random block-hierarchical adjacency matrices, is constructed for the first time. According to the classification of U. Alon et al. of network superfamilies (Milo et al., 2004 [11]) by their motifs distributions, our artificial directed random hierarchical networks fall into the superfamily of natural networks to which the neuron networks belong. This is the first example of a class of “handmade” topological networks with the motifs distribution as in a special class of natural networks of essential biological importance.     

Bayesian compressive sensing for cluster structured sparse signals

In traditional framework of compressive sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. Other than sparse prior, structures on the sparse pattern of the signal have also been used as an additional prior, called model-based compressive sensing, such as clustered structure and tree structure on wavelet coefficients. In this paper, the cluster structured sparse signals are investigated. Under the framework of Bayesian compressive sensing, a hierarchical Bayesian model is employed to model both the sparse prior and cluster prior, then Markov Chain Monte Carlo (MCMC) sampling is implemented for the inference. Unlike the state-of-the-art algorithms which are also taking into account the cluster prior, the proposed algorithm solves the inverse problem automatically—prior information on the number of clusters and the size of each cluster is unknown. The experimental results show that the proposed algorithm outperforms many state-of-the-art algorithms.     

BBU基带池集中设置的探讨和建议

针对底层网络的特点,分析BBU＋RRU站点集中化建设的优缺点,给出了集中化建设“分片、选点、保障”的新思路,并总结了BBU集中化建设的工程经验,提出了建设建议。