EXTERNAL FLUID HEATING OF A POROUS ED

This work deals with the thermal analysis of externally heated porous beds of finite length. A one dimensional model was developed that includes conduction and storage in both the fluid and bed, convective exchange between the fluid and bed, and the effect of adsorption/desorption in the bed. This model results in two coupled differential equations for the fluid and bed temperatures as functions of four independent dimensionless parameters. These equations were solved numerically using finite difference approximations. A truncation error analysis was carried out to maintain an accurate solution. The method of normalization is such that the results of this analysis are of use in bed design when the breakthrough characteristics in finite length beds are of interest. A method to measure bed thermal performance is defined and a means to optimize bed thermal performance is presented. An experiment was conducted to validate the numerically obtained results. A comparison of numerical to experimental results is presented     

无线传感器网络分簇拓扑控制算法

通过对经典的分簇算法HEED和EEUC进行研究与分析,对它们不足之处进行了改进,提出了一种新的基于双簇首节能的无线传感器网络分簇拓扑控制算法,即DCHEB算法。该算法提出了一种新的簇划分方案,通过此方案可以对无线传感器网络进行合理分簇,使得簇首节点位于合适的位置上,平均了各个簇的节点个数,可以避免簇内的边缘节点过早死亡。最后通过理论分析和仿真工具验证了该算法对减少无线传感器网络的能量消耗和延长其生存时间有很好的作用。     

Prevention from Soft Errors via Architecture Elasticity

Due to the decreasing threshold voltages, shrinking feature size, as well as the exponential growth of on-chip transistors, modern processors are increasingly vulnerable to soft errors. However, traditional mechanisms of soft error mitigation take actions to deal with soft errors only after they have been detected. Instead of the passive responses, this paper proposes a novel mechanism which proactively prevents from the occurrence of soft errors via architecture elasticity. In the light of a predictive model, we adapt the processor architectures h01istically and dynamically. The predictive model provides the ability to quickly and accurately predict the simulation target across different program execution phases on any architecture configurations by leveraging an artificial neural network model. Experimental results on SPEC CPU 2000 benchmarks show that our method inherently reduces the soft error rate by 33.2% and improves the energy efficiency by 18.3% as compared with the static configuration processor.     

复合蓄热材料的研制与应用

以KAl(SO4)2·12H2O为相变材料,以多孔陶瓷为基体,采用熔融浸渍法制备了复合相变蓄热材料。此复合相变材料结合了潜热蓄热材料与显热蓄热材料的优点,并克服了无机盐相变材料相变过程无定型的缺点及陶瓷蓄热显热小的缺点。将自制的复合蓄热材料实际应用于咖啡壶加热设备中,实验结果表明加入复合蓄热材料后的咖啡壶每小时节能率达38.8%。     

羧甲基纤维素接枝丙烯酰胺高吸水树脂的制备

以羧甲基纤维素、丙烯酰胺为原料,采用氧化还原引发体系,通过自由基接枝共聚制备了高吸水树脂,分别考察了原料配比、引发剂浓度、交联剂浓度、聚合温度、树脂粒径等因素对高吸水树脂吸收能力的影响,确定了最佳制备条件.     

基于模拟分析技术和随机搜索算法的化工过程能量集成方法研究

夹点和模拟分析技术已在化工能量集成中广泛应用.今以夹点技术为基础,对化工过程系统用能进行诊断,根据"过程用能一致性"原则提出能量集成改造方案,通过改变塔压实现塔顶冷凝器与塔底再沸器的热集成多效蒸馏.夹点技术实现的优化目标仅是热回收最大或公用工程能耗最小,不能实现包括设备整体费用最小的过程全局最优化.研究基于模拟技术,通过灵敏度分析,得到精馏塔各操作参数的样本映射数据,通过多项式拟合得到参数关联方程,并在遗传算法及模式搜索中设计过程费用函数,提出了将模拟分析技术与随机搜索算法相结合的,以过程费用函数最小化为优化目标的能量集成方法.工业实例的成功设计应用证明了其有效性和可行性.     

Synergic effect of Pd/γ-alumina and Cu/ZSM-5 on the performance of NO x storage reduction catalyst

NO _x reduction with a combination of catalysts, Pd catalyst, NO _x storage reduction (NSR) catalyst and Cu/ZSM-5 in turn, was investigated to elucidate for the high NO _x reduction activity of this catalyst combination under oxidative atmosphere with periodic deep rich operation. The catalytic activity was evaluated using the simulated exhaust gases with periodically fluctuation between oxidative and reductive atmospheres, and it was found that the NO _x reduction activity with this catalyst combination was apparently higher than that of the solely accumulation of these individual activities, which was caused by the additional synergic effect by this combination. The Pd catalyst upstream of the NSR catalyst improved NO _x storage ability by NO₂ formation under oxidative atmosphere. The stored NO _x was reduced to NH₃ on the NSR catalyst, and the generated NH₃ was adsorbed on Cu/ZSM-5 downstream of the NSR catalyst under the reductive atmosphere, and subsequently reacted with NO _x on the Cu/ZSM-5 under the oxidative atmosphere.     

基于阈值滤波的太阳能智能追踪系统设计

针对太阳能利用率不高的现状,设计了以MSP430F169单片机为核心的智能型太阳能自动追踪系统,采用基于阈值滤波的最大功率点追踪控制算法,提高了系统太阳能板追踪太阳的灵敏度,采用风速监测模块,增强了系统的稳定性。结果表明,相比固定电池板,系统吸收太阳能的转换效率提高了约95%,对提高太阳能的吸收效率,合理地利用太阳能具有重要的研究价值。     

基于短时能量和最小相对均方误差准则的神经网络语音水印方法

针对传统最小均方误差（LMS）和最小二乘准则（RLS）的神经网络语音水印的局限性,提出了基于短时能量和最小相对均方误差（LRMS）准则的神经网络语音水印算法。首先在首帧语音中嵌入同步序列,然后求出每帧的短时能量并对大于设定阈值的语音帧进行小波变换,最后利用以LRMS准则构建的神经网络实现水印的嵌入和提取。通过合理设定短时能量阈值,实现了水印容量和鲁棒性的平衡,而采用Levenberg-Marguardt（LM）算法地让网络迅速收敛。理论分析和实验结果表明,与文献[8]相比,本文提出的神经网络方案收敛速度更快,对于噪声,低通滤波,重采样,重量化等攻击有更强的鲁棒性,性能平均提高了5%。     

规模储氢技术及其研究进展

介绍了几种常用的储氢技术如高压压缩储氢技术、吸氢物质强化压缩储氢技术、液化储氢技术和金属氢化物储氢技术的研究进展,并对规模储氢技术的发展前景进行了预测和展望,指出规模储氢技术目前急待解决的问题是提高储氢密度、储氢安全性和降低储氢成本。