过渡金属对Au-Pd/TiO_2-Al_2O_3催化剂加氢脱硫性能的影响

研究了掺杂过渡金属Ru,Ni,Co对Au-Pd/TiO2-Al2O3催化剂催化噻吩加氢脱硫活性的影响,并采用X射线衍射、电感耦合等离子发射光谱、程序升温还原和程序升温脱附等方法对TiO2-Al2O3复合载体、Au-Pd/TiO2-Al2O3和Au-Pd-TM/TiO2-Al2O3(TM表示过渡金属)催化剂进行了表征。实验结果表明,掺杂过渡金属未改变Au-Pd/TiO2-Al2O3催化剂的结构;掺杂Ru或Ni增强了Au-Pd/TiO2-Al2O3催化剂的活性组分与TiO2-Al2O3复合载体的相互作用,降低了反应活化能,提高了催化剂活性组分的分散度和活性比表面积,改善了Au-Pd/TiO2-Al2O催化剂的吸附性能,从而提高了Au-Pd/TiO2-Al2O3催化剂催化噻吩加氢脱硫的活性;而掺杂Co的效果则与之相反。     

Deformation behavior of dispersion-strengthened copper at high temperature

1. Introduction Dispersion-strengthened copper (DSC) is a promising material developed recently. Considerable attention has been focused on it because of its excel- lent high-temperature properties. The metallic mate- rial, which is strengthened by solution strengthening, deformation strengthening, and ageing strengthening, is always low at high temperature, and the strength- ening factor contradicts with the electrical conduc- tivity of the material to a certain extent [1-2]. But DSC has g…     

"S"系列扭杆弹簧镦锻成形工艺

以Φ27.5扭杆弹簧为例，阐述了“S”系列扭杆弹簧镦锻成形工艺及模具设计。     

应用油团聚(SGHFF)技术高效脱除煤炭中黄铁矿硫的研究

介绍了应用油团聚（ＳＧＨＦＦ） 技术高效脱除煤炭中硫的过程, 探讨了煤炭粉碎粒度及水量对煤炭中硫的脱除率的影响。实验结果表明, 硫含量为２．１６ ％ 的烟煤, 脱除率可达到６７ ％ 。     

深冷处理对6082铝合金焊接接头性能的影响

研究了深冷处理前后康复器械用6082铝合金TIG焊接接头的显微硬度、拉伸性能以及拉伸断口形貌。结果表明,6082铝合金焊接接头经540℃×50 min固溶水冷和-196℃×20 h深冷处理后,强度和塑性都得到明显改善,强度提高了61.3%,断后伸长率提高到未经深冷处理接头的4.5倍,焊接接头的硬度得到提高,显微气孔和疏松等缺陷基本消除。     

淬火时效对4032B铝合金组织和性能的影响

研究了淬火时效对4032B铝合金组织和性能的影响.结果表明,4032B铝合金材料对淬火时效非常敏感,强度随时效后析出相的增多迅速增强,而塑性相应降低;所研制的4032B铝合金棒材T6态的抗拉强度、屈服强度和伸长率的平均值分别为408.70 MPa、385.92 MPa和3.9％.     

面向地震灾害的社会帐篷募集点预选址问题

预先优化社会帐篷募集点选址,有助于地震等灾难期间有效征集社会帐篷开展救援工作。研究不同地震场景下社会帐篷募集点预选址问题,以最小化经济成本和时间成本为目标,建立双层随机规划模型,确定社会帐篷募集点选址方案。考虑模型中权重等参数的影响,设计五种实验,并对实验结果进行讨论。通过实际算例,以上海浦东新区为背景,以23个省份作为不同地震场景,验证模型的实用性。最后考虑雅安地震,分析确定场景下参数对结果的影响。     

基于小波投影和离散哈希的图像检索

现有的哈希方法难以快速实现原始特征空间的近似映射.针对此问题,文中提出基于小波投影的哈希方法.基于Haar小波变换构造投影矩阵,使用迭代算法优化投影矩阵和离散优化二进制码,重构量化误差.利用投影矩阵将图像的原始特征向量快速投影至低维空间,并进行二进制嵌入,完成图像的哈希编码.在图像数据集上的实验表明,文中方法可有效提升编码效率.     

一种ZigBee网络中基于优先级的CSMA/CA优化算法

本文针对ZigBee网络中的MAC层核心算法CSMA/CA不能区分业务优先级和在高网络负荷中性能较差的问题,提出了根据网络负荷设置竞争窗口的方法来确定网络中不同业务的优先级;同时,根据网络负荷来自适应调整算法中的退避指数,进一步优化网络性能.对网络模型进行了数学建模和分析,并且利用NS2软件建立仿真场景进行了网络仿真,仿真结果表明改进后的算法以较小的时延代价提高了网络吞吐量,并降低了丢包率,从而使网络整体性能得到优化.     

L-PowerGraph: a lightweight distributed graph-parallel communication mechanism

In order to process complex and large-scale graph data, numerous distributed graph-parallel computing platforms have been proposed. PowerGraph is an excellent representative of them. It has exhibited better performance, such as faster graph-processing rate and higher scalability, than others. However, like in other distributed graph computing systems, unnecessary and excessive communications among computing nodes in PowerGraph not only aggravate the network I/O workload of the underlying computing hardware systems but may also cause a decrease in runtime performance. In this paper, we propose and implement a mechanism called L-PowerGraph, which reduces the communication overhead in PowerGraph. First, L-PowerGraph identifies and eliminates the avoidable communications in PowerGraph. Second, in order to further reduce the required communications L-PowerGraph proposes an edge direction-aware master appointment strategy, in which L-PowerGraph appoints the replica with both incoming and outgoing edges as master. Third, L-PowerGraph proposes an edge direction-aware graph partition strategy, which optimally isolates the outgoing edges from the incoming edges of a vertex during the graph partition process. We have conducted extensive experiments using real-world datasets, and our results verified the effectiveness of the proposed mechanism. For example, compared with PowerGraph under Random partition scenario L-PowerGraph can not only reduce up to 30.5% of the communication overhead but also cut up to 20.3% of the runtime for PageRank algorithm while processing Live-journal dataset. The performance improvement achieved by L-PowerGraph over our precursor work, LightGraph, which only reduces the synchronizing communication overhead, is also verified by our experimental results.