纯电动汽车磷酸铁锂电池组的建模及优化

鉴于传统神经网络和支持向量机机理复杂、计算量大的缺陷,很难实时跟踪磷酸铁锂电池组复杂快速的内部反应,影响电池荷电状态的估算精度,提出应用一种简单、有效的极限学习机对一额定容量为100Ah、额定电压为72V的纯电动汽车磷酸铁锂电池组建模,并分别与BP神经网络、RBF神经网络、支持向量机进行对比。随后,以学习时间和泛化性能为优化目标,应用粒子群方法寻找最佳隐层节点个数。结果表明,基于极限学习机的磷酸铁锂电池组模型的学习时间、泛化性能优于BP神经网络、RBF神经网络、支持向量机;隐层节点优化后,模型的学习时间和泛化性能达到最优。     

装备使用与保障研究数据的生成方法研究

装备使用与保障数据是开展装备科学研究的重要依据,而由于管理不善、保密、样本过少等原因常常导致相关数据缺少应有的积累,无法满足实际研究的需要。为了克服这一困难,文章提出通过算法生成数据予以解决。首先根据数据的应用特性,将装备使用与保障数据看作简单数据、规律已知数据和规律未知数据三类,分别制定生成策略。对于简单数据和规律已知数据,通过已有的商用软件或简单的自定义方法生成;对于规律未知数据,采用模式注入或特性继承的方法生成。在某大型装备管理综合信息系统的设计开发中,对这些生成方法进行了工程实践,结果表明了方法的正确性和可行性。     

粘土担载的钼基催化剂的制备、结构及CO加氢合成醇性能

采用溶胶凝胶法与等体积浸渍相结合制备了一系列以粘土为载体的K-Co-Mo催化剂. 采用XRD、N₂等温吸脱附、H_{26+的还原,但对Mo⁴⁺和Co²⁺的还原没有明显的影响. 催化剂经还原后,在其表面生成了一种更低价态的Mo^δ+(1<δ<4)物种,被认为是合成醇的活性中心. 与非负载催化剂相比,粘土担载的K-Co-Mo具有更高的合成醇性能. 负载型催化剂具有较高的活性物种分散度,并且其介孔结构在一定程度上延长了合成醇反应中间体的滞留时间,从而促进了低碳醇的生成. 经773 K还原的催化剂具有较高的活性,其原因可为催化剂表面具有较高含量的Mo^δ+物种.}     

Highly Stable,Water‐Dispersible Metal‐Nanoparticle‐Decorated Polymer Nanocapsules and Their Catalytic Applications

A facile synthesis of highly stable, water‐dispersible metal‐nanoparticle‐decorated polymer nanocapsules (M@CB‐PNs: M=Pd, Au, and Pt) was achieved by a simple two‐step process employing a polymer nanocapsule (CB‐PN) made of cucurbit[6]uril (CB[6]) and metal salts. The CB‐PN serves as a versatile platform where various metal nanoparticles with a controlled size can be introduced on the surface and stabilized to prepare new water‐dispersible nanostructures useful for many applications. The Pd nanoparticles on CB‐PN exhibit high stability and dispersibility in water as well as excellent catalytic activity and recyclability in carbon–carbon and carbon–nitrogen bond‐forming reactions in aqueous medium suggesting potential applications as a green catalyst.     

抗污染薄层复合聚酰胺膜的结构设计及改性策略

由活性层和支撑层组成的薄层复合(TFC)聚酰胺(PA)膜,是目前广泛应用于纳滤、反渗透、正渗透和压力延迟渗透过程中的高性能脱盐膜,具有水通量大和截盐率高等优异性能。然而,由于TFC-PA膜存在活性层疏水性强、支撑层孔径大等特点,致使TFC-PA膜在实际使用过程中极易受到膜污染,制约了TFC-PA膜的进一步推广和使用。本文讨论分析了TFC-PA膜的结构特点和表面性质,总结归纳了在不同膜过程中TFC-PA膜污染形成的原因及特点,详细论述了国内外抗污染TFC-PA膜的研究进展。本文重点介绍了活性层抗污染改性和支撑层抗污染改性方法,并对其抗污染机理以及存在的问题进行了阐述与分析,最后对抗污染TFC-PA膜的结构设计与表面改性策略进行了总结及展望。     

PEFC catalyst layers: Effect of support microstructure on both distributions of Pt and ionomer and cell performance and durability

In order to improve the performance and durability of polymer electrolyte fuel cells (PEFCs), various improvements in the microstructures of cathode catalyst layers (CLs) were initiated in the early 1990s. More recent advances in CL materials are highlighted, including carbon supports for improved accessibility of Pt nanoparticles (NPs), adsorption of ionomer on the Pt surface, high-oxygen-permeability ionomers, corrosion resistance of mesoporous and microporous carbons, and conductive ceramic supports with a fused-aggregate network structure. These approaches are summarized as stepwise improvements. The influences of the support structure on the distribution of Pt NPs and ionomer are reviewed, as well as their effects on performance and durability. These approaches for carbon supports are extended to conductive ceramic supports and the unique advantages are discussed.     

Kinetic Isotope Effect as a Tool To Investigate the Oxygen Reduction Reaction on Pt-based Electrocatalysts – Part II: Effect of Platinum Dispersion

We investigated the oxygen reduction reaction (ORR) mechanism on Pt nanoparticles (NPs) dispersed on several carbon blacks with various physicochemical properties (i. e. specific surface ranging from 80 to 900 m² g⁻¹, different graphitization degree, etc.). Using the kinetic isotope effect (KIE) along with various electrochemical characterizations, we determined that the rate determining step (RDS) of the ORR is a proton-independent step when the density of Pt NPs on the surface of the carbon support is high. Upon decrease of the density of Pt NPs on the surface, the RDS of the ORR starts involving a proton, as denoted by an increase of the KIE >1. This underlined the critical role played by the carbon support in the oxygen reduction reaction electrocatalysis by Pt supported on high surface area carbon.     

基于支座反力影响线曲率差分的等截面连续梁损伤识别方法

为了实现仅采用损伤状态信息对等截面连续梁进行损伤识别,通过推导三跨不等跨连续梁在移动荷载作用下的支座反力影响线,发现支座反力影响线求曲率并作差分后的曲线在损伤位置会发生突变,基于该现象提出了一种损伤定位方法,进一步建立了损伤程度计算方法,可对损伤程度进行较精确的定量。通过一三跨连续梁和一四跨连续梁工程实例的仿真分析,证明了支座反力影响线曲率差分指标损伤定位和相应的损伤程度定量方法对等截面连续梁损伤识别具有可行性。     

基于二阶段异质随机森林的汽油辛烷值预测

构建了基于二阶段异质随机森林的汽油辛烷值预测模型.首先利用样本-位点信息表知识约简模型,筛选出对汽油辛烷值影响大的位点数据作为第一阶段;然后,利用集成学习思想集成支持向量回归和动态时间序列神经网络,构建异质随机森林预测模型作为第二阶段.利用十折交叉法验证模型精度,结果表明该集成学习算法具有有效性和高精度.     

基于SVM的固化土无侧限抗压强度模型

为实现较少试验次数下固化土无侧限抗压强度(qu)的准确预测, 提出了基于支持向量机(SVM)的固化土qu的预测模型. 以固化剂各组分掺入比、龄期、初始含水量、固化剂掺量等因素为输入量, 固化土的qu作为输出量, 以径向基为核函数, 采用网格搜索法和交叉验证法进行参数优化, 建立了基于SVM的固化土qu的预测模型. 算例分析表明: 该模型适用于任意条件下固化土qu的精确预测, 且在较小试验成本下实现与响应面法相当的预测精度.