光盘的出错率分析和研究

本文通过对光存储系统出错特性的分析，研究了一些描述出错特性的主要参数，并且给出了描述出错特性的Ｇｉｌｂｅｒｔ模型及其改进型模型。     

动态毛吸法测定纤维表面能

本文用浸润测定仪对玻璃纤维和Kevlar-49芳纶纤维进行了表面能测定,讨论了纤维束柱末端沾湿量的影响,提出了浸润仪测试数据的正确处理方法,求得了Kevlar-49纤维的表面能并对其色散分量和非色散分量进行了解析.     

Anaerobic digestion of alkaline black liquor using an up-flow anaerobic sludge blanket reactor

The anaerobic digestion of alkaline black liquor from a cereal straw pulping mill was studied in batch (serum bottles) and continuous systems (up-flow anaerobic sludge blanket reactor—UASB). The batch digestion studies confirmed that lignin and related compounds (LRC) in the alkaline black liquor were the main inhibitory substances and could not be decomposed by anaerobic bacteria. At organic loading rates of 5–10 kg COD m^?3 day^?1, the UASB reactor achieved 50–60% COD removal efficiencies. Gas production was 2–3 dm³ per dm³ of alkaline black liquor. Two different sludge types were examined in the reactor: granular and cluster-like sludges. Sludge in a cluster, which involved many small granules and flocs, tended to form larger aggregates and possessed good settling ability.     

温度,压力对漂移室气体增益的影响

研究了温度及气体压力对漂移室（工作于正比区）气体放大倍数的影响，温度和气体压力的变化范围分别是５￣４０℃及９０￣１０５ｋＰａ。用实验数据拟合得到了函数关系并测量了几种饱和度下函数中的参数值。     

V型天线的行波加载公式

本文研究了ｖ型天线上电流分布与阻抗加载的关系，导出了支持天线上行波电流的阻抗加载公式。讨论了天线张角、振子半径以及振子长度与加载量的关系和规律，说明了加载Ｖ型天线的宽带特性。文中还计算了在高斯脉冲激励下，不同加载量的天线上瞬态电流的分布，由此可以表明所导加载公式的正确性与重要性。     

浅谈中华老字号六味斋豆腐干系列包装再设计

随着社会经济的发展,面对消费者货比三家的消费之道,为了跟上或者引领消费者的消费理念,商家在不断地自我更新和自我完善。产品包装的更新换代成了商家必须考虑的问题之一。承前继后,不断发展是设计师与商家一直努力追求着的理念。本文以六味斋豆腐干系列包装再设计为例浅析再设计的方法和原则。在一连串的整合、分析、探讨后,我们在企业品牌核心理念的基础上,用包装在设计的手段来更新我们的生活。     

边界对齐的平滑三维对称标架场

为了把广泛应用于网格四边形化和纹理合成的二维表面标架场拓展到三维,提出一种生成三维对称标架场的方法.不同于表面对称标架场(四对称方向场),二维标架场的对称性能用一个切平面的旋转角度来表示,而三维对称标架场的对称性却不能这样简单地表示.为了解决这个问题,利用球面函数来获得一个对称性表述,该表述对于绕任意一个轴的π/2旋转以及它们的复合是不变的.基于球面函数的表示可以获得一个有效的标架场光顺程度的度量,并以球面调和分析进行加速计算;基于一组边界约束,可以通过极小化这个度量函数来获得一个光顺的标架场,该标架场在表面上能很好地对齐法线.最后通过表面投影、流线追踪和奇异点来可视化这个标架场,并将这个光顺的标架场用于六面体网格生成,且讨论了它在生成高质量纯六面体网格方面的潜力,其与表面标架场在生成四边形网格方面的潜力是一致的.     

A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems

Surrogate model-assisted multi-objective genetic algorithms (MOGA) show great potential in solving engineering design problems since they can save computational cost by reducing the calls of expensive simulations. In this paper, a two-stage adaptive multi-fidelity surrogate (MFS) model-assisted MOGA (AMFS-MOGA) is developed to further relieve their computational burden. In the warm-up stage, a preliminary Pareto frontier is obtained relying only on the data from the low-fidelity (LF) model. In the second stage, an initial MFS model is constructed based on the data from both LF and high-fidelity (HF) models at the samples, which are selected from the preliminary Pareto set according to the crowding distance in the objective space. Then the fitness values of individuals are evaluated using the MFS model, which is adaptively updated according to two developed strategies, an individual-based updating strategy and a generation-based updating strategy. The former considers the prediction uncertainty from the MFS model, while the latter takes the discrete degree of the population into consideration. The effectiveness and merits of the proposed AMFS-MOGA approach are illustrated using three benchmark tests and the design optimization of a stiffened cylindrical shell. The comparisons between the proposed AMFS-MOGA approach and some existing approaches considering the quality of the obtained Pareto frontiers and computational efficiency are made. The results show that the proposed AMFS-MOGA method can obtain Pareto frontiers comparable to that obtained by the MOGA with HF model, while significantly reducing the number of evaluations of the expensive HF model.

     

High-performance simulations of turbulent boundary layer flow using Intel Xeon Phi many-core processors

The Journal of Supercomputing - Direct numerical simulations (DNS) of turbulent flows have increasing importance because they not only provide fundamental understanding of turbulent flows but also...