高模量聚丙烯管材料的结构与性能

采用升温淋洗分级(TREF)方法对高模量聚丙烯管材料进行了分级,并应用凝胶渗透色谱(GPC)、傅立叶变换红外光谱(FT-IR)、结晶淋洗分级(CEF)和差示扫描量热(DSC)等方法研究了其组成、序列结构与相对分子质量及分布。结果表明:材料由高规整度的均聚聚丙烯、含有少量乙烯链段的聚丙烯、含乙烯和丙烯长链段的乙丙共聚物和乙丙无规共聚物组成。均聚聚丙烯相含量最高,为材料的主要组成部分,提供了材料的刚性;乙丙无规共聚物组分分子量较大且分布较宽,构成了材料的橡胶相,保证了材料的抗冲强度;含乙烯和丙烯长链段的共聚物含量较低,但对材料性能的提高起到了重要作用。     

炭纤维前驱体丙烯腈-丙烯酰胺共聚物研究

以二甲基亚砜为溶剂,偶氮二异丁腈为引发剂,用溶液聚合法合成了炭纤维用丙烯腈(AN)-丙烯酰胺(AM)共聚物.低转化率下,测得单体竞聚率,讨论了聚合机理模型.采用统计方法,推测了不同转化率下AN与少量AM(AM的摩尔分数＜5%)共聚物的微观结构.结果表明,在该聚合体系中,AN、AM的竞聚率值分别为r(AN)=0.46,r(AM)=0.01;AN与AM聚合机理为末端基终止模型;AM的引入降低了AN单元的数均序列长度;随着转化率的提高,链段分布逐渐变宽,AN长序列单元逐渐增加.     

离聚体的微观链运动与玻璃化转变温度

本文用动态力学谱和~(13)C NMR方法分别测定了丙烯酸-1,1,5-三氢全氟戊酯与丙烯酸共聚物为基础的离聚体的玻璃化转变温度T_s和~(13)C自旋-自旋驰豫时间t_2,用描述高分子主链链段运动的VJGM模型计算了所测样品的链段运动活性。结果表明,离聚体样品的玻璃化转变温度与离聚体大分子链运动活性密切相关,大分子的微观链段运动越困难,玻璃化转变温度越高。     

PEG改性聚乳酸嵌段共聚物降解性能研究

辛酸亚锡催化下开环聚合制备聚乳酸(DL-PLA)-聚乙二醇(PEG)-聚乳酸三嵌段共聚物.用GPC、DSC、1 H-NMR、质量损失、静态接触角等方法在pH=7.4磷酸盐缓冲液中,37℃下研究了分子量Mn=400、1000和4000的PEG改性DL-PLA的降解行为.结果表明,PEG嵌段增强了共聚物的亲水性,降低了共聚物Tg,加速了共聚物降解,随着PEG分子量增加及两端DL-PLA链段增长,共聚物分子量下降速率加快.由研究结果得出,共聚物降解期间DL-PLA链段中的酯键随机断裂,PEG两端DL-PLA链段逐渐变短;降解后期DL-PLA链段进一步变短,并有短链DL-PLA均聚物产生,当PEG两端DL-PLA链段足够短时,共聚物在介质中溶解.     

氧亚甲基连接的聚氧化乙烯统计共聚物的热性能研究EI

研究了统计共聚物(Statistic Copolymer)氧亚甲基连接的聚氧化乙烯(OM-POE)的热力学行为,探索了聚合物链中氧化乙烯链段的平均长度和长度分布对聚合物及其共混物的玻璃化温度、熔点、熔化热及结晶度的影响。结果表明,不同长度的氧化乙烯链段无规地进入分子链中,熔点与组成的关系可用Flory的无规共聚物熔点方程来描述。     

LLDPE/EVA/ZnO纳米复合材料的制备与BP-Markov性能预测研究

制备了LLDPE/EVA/ZnO纳米复合材料,并测试了其力学性能.结合BP 神经网络和Markov链建立了BP-Markov模型,并利用此模型对LLDPE/EVA/ZnO纳米复合材料的多指标性能进行了预测.结果表明BP-Markov模型应用于聚合物/无机物纳米复合材料的多指标性能预测具有较高的精度和可靠性,Markov链解决了神经网络在做多指标性能预测时误差的随机性和波动性问题,充分的发挥了神经网络与Markov链预测模型的优点,为在数据有限且具有随机因素的情况下实验数据的分析提供了一种新的思路.     

异丁烯醇聚氧乙烯醚与丙烯酸的竞聚率及共聚物链段分布EI北大核心CSCD

以过硫酸铵(APS)为引发剂,在50℃对异丁烯醇聚氧乙烯醚(HPEG)大单体与丙烯酸(AA)进行低转化率(<15%)的水溶液共聚反应。用凝胶渗透色谱和高效液相色谱分别测定反应体系中HPEG和AA剩余量。依据设计反应单体投料比,K-T作图法处理数据,得到异丁烯醇聚氧乙烯醚(HPEG)与丙烯酸(AA)的竞聚率分别为:r1(HPEG)=0.017,r2(AA)=1.70。进而分析了HPEG与AA共聚物P(HPEG-co-AA)的链段微结构和链节分布。当投料比为1∶4时,二元共聚物P(HPEG-co-AA)中HPEG以1个单体单元存在。丙烯酸均聚形成的链段以3~15个单体单元的链段长度为主,链段数均长度为7.8。     

苯乙烯／丁二烯的阴离子反应挤出聚合机理

在双螺杆挤出机中以有机锂为引发剂,采用丁二烯(B)与苯乙烯(S)混合单体,本体一步合成了苯乙烯/丁二烯(S/B)共聚物。采用差示-紫外联用的双检测GPC对共聚物的组成分布进行了研究,结果表明,相比高分子量的共聚物,低分子量共聚物的组成分布比较均一。采用小角激光光散射仪(MALLS)联用GPC对降解后样品进行测试表明,共聚物分子链是由一个聚苯乙烯长嵌段连接着大量的(S-B)小嵌段构成的。     

聚酰胺6-聚氨酯嵌段共聚物的制备及其性能研究

为了改善浇铸聚酰胺6(MC-PA 6)的冲击韧性,制备了聚酰胺6-聚氨酯(PA 6-PU)嵌段共聚物.采用示差扫描量热分析(DSC)、动态力学性能分析(DMTA)以及静态力学性能测试研究了PU柔性组分对PA 6-PU嵌段共聚物结构和性能的影响.结果表明,当PU柔性组分含量为15%~20%(质量分数,下同)时,共聚物中出现了2个熔融峰,表明晶粒尺寸分布较宽;DMTA确定PA 6-Pu嵌段共聚物只有1个玻璃化温度(α松弛峰),说明共聚物为单相体系.PA 6-PU嵌段共聚物的力学性能数据表明,随PU组分含量的增加,共聚物的拉伸强度下降,但50℃和25℃时的冲击强度大幅度提高.     

俄歇极角角分布的大角度行为

测量了纯金样品Au(69eV),纯铜样品Cu(60eV和Cu(920eV)俄歇信号的极角角分布,考察了它们的大角度行为。用多种函数对角分布进行拟合。拟合参数与电子能量无关。分布大体上符合cosθ规律。大角度时对cosθ的偏差用表面不平整可得到最好的解释。样品浓度不连续分布的模型与数据符合不好。计及俄歇电子在表面上折射的角分布公式由于在大角度下发散而与实验完全不符。     

Quantitative 13C NMR analysis of sequence distributions in poly(ethylene-co-1-hexene)

Different 13C NMR methods of determining triad distributions in two poly(ethylene-co-1-hexene) copolymers are examined using high signal-to-noise ratio 13C NMR spectra of the copolymers dissolved in deuterated 1,2,4-trichlorobenzene at 398 K. This examination includes a comparison of three integration techniques. The experimental impact of decoupler sidebands and significantly nonequal 13C NOE values are examined. A least-squares regression analysis technique for solving for triad mole fractions is tested and appears to be more reliable than two published algebraic expressions (and other expressions examined in the work reported here). The resultant triad mole fractions are compared to sequence distribution parameters expected by Bernoullian and first-order Markovian statistical models. On the basis of 13C NMR-determined average reactivity ratios, the copolymer designated sample B (5.3 mol % 1-hexene) appears to be a Bernoullian copolymer resulting from a single-site catalytic system. The copolymer designated sample S (3.6 mol % 1-hexene overall) is better described as a mixture of polyethylene and a Bernoullian copolymer with 6.4 mol % 1-hexene content, and thus appears to result from a multisite catalytic system.     

基于贝叶斯理论及MCMC-MH算法推演地基土材料阻尼比的概率分布模型

浅层土壤的材料阻尼比参数分布可以通过多通道表面波(MASW)分析法提取的表面波衰减曲线来反演识别,但是衰减曲线对于较大深度和小空间尺度土壤性质的变化不敏感,反演的土壤材料阻尼比分布是非唯一的和不确定的。基于该研究建立了土体材料阻尼比随深度变化的先验概率分布模型,利用Nataf变换和Karhunen-Loeve将其分解为标准高斯变量与特征值及特征向量的乘积和;随后依据贝叶斯理论,以TLM-PML模型结合频率波数域-半功率带宽法对衰减曲线进行正演,并与试验数据联合构建似然函数,使用蒙特卡洛马尔科夫链(MCMC)-Metropolis(MH)算法得到土体材料阻尼比的后验概率分布模型;对马尔科夫链的收敛性和独立性进行检验获得了多组相互独立的后验样本数据;用独立的后验样本计算出自由场振动响应,利用核密度估计得到具有一定置信度的置信区间,并与试验数据进行比较,验证了该研究提出的土体阻尼比非确定性概率模型的合理性和可靠性。     

Modeling emergency evacuation for major hazard industrial sites

A model providing the temporal and spatial distribution of the population under evacuation around a major hazard facility is developed. A discrete state stochastic Markov process simulates the movement of the evacuees. The area around the hazardous facility is divided into nodes connected among themselves with links representing the road system of the area. Transition from node-to-node is simulated as a random process where the probability of transition depends on the dynamically changed states of the destination and origin nodes and on the link between them. Solution of the Markov process provides the expected distribution of the evacuees in the nodes of the area as a function of time. A Monte Carlo solution of the model provides in addition a sample of actual trajectories of the evacuees. This information coupled with an accident analysis which provides the spatial and temporal distribution of the extreme phenomenon following an accident, determines a sample of the actual doses received by the evacuees. Both the average dose and the actual distribution of doses are then used as measures in evaluating alternative emergency response strategies. It is shown that in some cases the estimation of the health consequences by the average dose might be either too conservative or too non-conservative relative to the one corresponding to the distribution of the received dose and hence not a suitable measure to evaluate alternative evacuation strategies.     

On the Markov approximation of fatigue crack growth

Some recent developments on the probabilistic modelling of fatigue crack growth are reviewed here and special attention is given to several Markov approximations. A continuously parametered discrete Markov process model is then introduced. In terms of analytical sophistication, this model represents an approach between the Markov chain model and the continuous Markov process model used by other researchers. It is easy to apply and probabilistic quantities such as the distribution function of random time reaching a certain crack size, the probability of crack exceedance at a given time, constant-probability crack growth curves and generation of the crack sample functions can also be easily obtained. Three numerical examples are illustrated using the proposed model and the results are compared with available experimental data and other researchers' results.     

基于改进HMM和Pearson相似度分析的滚动轴承自适应寿命预测方法

基于数据驱动思想,提出了一种相同工况下的滚动轴承寿命预测方法。针对轴承全寿命监测数据,根据K-means聚类算法划分轴承运行状态空间,考虑到隐马尔科夫模型主链为状态链的不足,对状态转移矩阵重新定义,将主链改进为寿命链,建立了基于改进HMM的全寿命状态驻留时间模型;将观测轴承数据、实时与建模数据进行Pearson相似度分析,构造寿命比例调节系数,实现寿命模型参数的动态修正和观测轴承寿命的自适应预测。采用美国辛辛那提大学实验中心轴承试验数据开展了应用研究,通过一组轴承全寿命数据实现了对其它轴承不同阶段及全寿命的预测,与传统的隐马尔科夫模型、灰色模型预测等方法预测结果相比,所提算法兼具较好的预测准确性和模型的泛化性。     

基于EMD多尺度威布尔分布与HMM的轴承性能退化评估方法

轴承作为旋转机械中的重要部件,对其性能退化状态进行准确评估是开展预测性维护的重要前提.针对现有性能退化指标在鲁棒性和敏感性上的不足,提出一种基于多尺度威布尔分布与隐马尔可夫模型(Hidden Markov model,HMM)的滚动轴承性能退化评估方法.首先,采用经验模态分解(empirical mode decomp...     

Advanced Scientific Computing in BASIC With Applications in Chemistry,Biology, and Pharmacology

Tuning and calibration are processes for improving the representativeness of a computer simulation code to a physical phenomenon. This article introduces a statistical methodology for simultaneously determining tuning and calibration parameters in settings where data are available from a computer code and the associated physical experiment. Tuning parameters are set by minimizing a discrepancy measure while the distribution of the calibration parameters are determined based on a hierarchical Bayesian model. The proposed Bayesian model views the output as a realization of a Gaussian stochastic process with hyper-priors. Draws from the resulting posterior distribution are obtained by the Markov chain Monte Carlo simulation. Our methodology is compared with an alternative approach in examples and is illustrated in a biomechanical engineering application. Supplemental materials, including the software and a user manual, are available online and can be requested from the first author.     

采用自适应邻域马尔可夫场的极化SAR图像分割

提出了一种新的马尔可夫场(MRF)极化SAR图像分割方法,对于图像中的每个像素,利用极化SAR数据总功率(span)图,得到该像素的马尔可夫场自适应邻域系统,且对区域标号过程的参数进行修正.使用该方法对机载极化SAR数据进行分割,实验结果表明,与传统的马尔可夫场方法、最大似然方法相比,该方法可以得到较好的分割结果.     

Reliability analysis of the dynamic system for the Chen model through sequential order statistics

Recently, the two-parameter Chen distribution has widely been used for reliability studies in various engineering fields. In this article, we have developed various statistical inferences on the composite dynamic system, assuming Chen distribution as a baseline model. In this dynamic system, failure of a component induces a higher load on the surviving components and thus increases component hazard rate through a power-trend process. The classical and Bayesian point estimates of the unknown parameters of the composite system are obtained by the method of maximum likelihood and Markov chain Monte Carlo techniques, respectively. In the Bayesian framework, we have used gamma priors to obtain Bayes estimates of unknown parameters under the squared error and generalized entropy loss functions. The interval estimates of the baseline reliability function are obtained by using the Fisher information matrix and Bayesian method. A parametric hypothesis test is presented to test whether the failed components change the hazard rate function. A compact simulation study is carried out to examine the behavior of the proposed estimation methods. Finally, one real data analysis is performed for illustrative purposes.     

区域物流规模的改进灰色马尔可夫预测

在分析灰色GM(1,1)方法、灰色马尔可夫方法的基础上,建立区域物流规模预测的改进灰色马尔可夫模型,以国家统计局公布的陕西省1997-2006年货物周转量的统计数据为依据,对其2007-2008年的物流规模进行预测.与灰色GM(1,1)方法、灰色马尔可夫方法的预测结果相比,改进灰色马尔可夫链模型对区域物流规模的预测更加有效.