Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Influence of third monomer on the crystal phase transition behavior of ethylene-tetrafluoroethylene copolymer

Crystal phase transition between the low- and high-temperature phases has been investigated for ethylene (E)-tetrafluoroethylene (TFE) alternating copolymer (ETFE) containing the third monomeric species by the temperature dependent measurements of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) and differential scanning calorimetry. Nonafluoro-1-hexene (NFH) and hexafluoropropylene (HFP) were chosen as the third monomers, where they are different in the side-branch length, -(CF₂)₃CF₃ and -CF₃, respectively. In the case of E/TFE/NFH copolymer (ET-C4F9), the crystal phase transition temperature of the original ETFE two-components copolymer was not very much affected by the existence of NFH in the range of NFH content from 0.7 to 3 mol%. Contrarily, the crystal phase transition temperature of E/TFE/HFP copolymer (ET-CF3) was found to decrease drastically with increasing HFP content. The melting temperature and the higher-order structure were also affected sensitively depending on the HFP content. This difference in phase transition behavior between ET-C4F9 and ET-CF3 copolymers is reasonably interpreted as follows: the short side groups (-CF₃) of HFP monomeric unit are included in the crystal lattice of E/TFE chains and the unit cell is expanded gradually with an increment of the HFP content, resulting in the decrease in phase transition point because of easier thermal motion of the chains. On the other hand, the long side groups [-(CF₂)₃CF₃] of NFH monomeric units are excluded out of the crystal lattice and located on the lamellar surfaces or in the amorphous region and do not affect very much the phase transition temperature even when the NFH content is increased. In association with such a change in crystal structure, the long period of stacked lamellar structure was found to decrease remarkably in the case of NFH, whereas it does not change very much for HFP, consistent with the interpretation of the above-mentioned WAXD data.     

青藏铁路物资储备基地建设

结合青藏铁路建设物资储备基地的实际情况，探讨了铁路线统购统发材料的管理模式及业务流程，总结出在实际工作中应借鉴的经验和注意的问题。     

新型高温永磁体的研制

通过分析影响磁体高温性能的因素,设计了新磁体的成分为:Cu含量高,Fe含量低,Zr适量,Sm含量高;采用粉末冶金工艺制备了高温Sm_2(CoFeCuZr)_(17)永磁体。制得的磁体室温磁性能为:B_r1.075 T,H_(ei)2 098.2 kA/m,H_(eb) 776.1 kA/m,H_k843.8 kA/m,(BH)_(max)210.0 kj/m~3;在200℃时的磁性能为:B_r0.991 T,H_(ci)1 175.7 kA/m,H_(cb)531.7 kA/m,H_k577.9 kA/m,(BH)_(max)172.5 kJ/m~3;矫顽力温度系数β(20～200℃)为-0.24％/℃。经理论分析和实验验证,磁体的使用温度均超过400℃,为高温环境(高于400℃)提供了一种实用性永磁材料。     

聚酯装置熔体过滤器的国产化改造

熔体过滤器为聚酯装置关键设备,其国产化问题一直未能解决。该文通过对天津分公司200kt/a聚酯装置熔体过滤器改造方案的介绍,探讨了其国产化条件,分析了国产熔体过滤器的结构特点,并与进口过滤器进行了对比,提出了一些看法。     

结构安全性综合评估方法的研究

已有结构的安全性的评估是关系到社会经济、安全的重大问题。本文作者从临界结构入手，以构件失效影响面积为参考，得到了计算构件重要性系数的简便方法，结合构件的可靠度提出了定性与定量结合的结构安全性综合评估方法。从工程实例来看，本文提出的方法简单实用，与现行的鉴定标准符合得比较好。     

Reconstruction of reflectance spectra using weighted principal component analysis

The weighted principal component analysis technique is employed for reconstruction of reflectance spectra of surface colors from the related tristimulus values. A dynamic eigenvector subspace based on applying certain weights to reflectance data of Munsell color chips has been formed for each particular sample and the color difference value between the target, and Munsell dataset is chosen as a criterion for determination of weighting factors. Implementation of this method enables one to increase the influence of samples which are closer to target on extracted principal eigenvectors and subsequently diminish the effect of those samples which benefit from higher amount of color difference. The performance of the suggested method is evaluated in spectral reflectance reconstruction of three different collections of colored samples by the use of the first three Munsell bases. The resulting spectra show considerable improvements in terms of root mean square error between the actual and reconstructed reflectance curves as well as CIELAB color difference under illuminant A in comparison to those obtained from the standard PCA method. © 2008 Wiley Periodicals, Inc. Col Res Appl, 33, 360–371, 2008     

Data decomposition using independent component analysis with prior constraints

In many data analysis problems, it is useful to consider the data as generated from a set of unknown (latent) generators or sources. The observations we make of a system are then taken to be related to these sources through some unknown function. Furthermore, the (unknown) number of underlying latent sources may be less than the number of observations. Recent developments in independent component analysis (ICA) have shown that, in the case where the unknown function linking sources to observations is linear, such data decomposition may be achieved in a mathematically elegant manner. In this paper, we extend the general ICA paradigm to include a very flexible source model, prior constraints and conditioning on sets of intermediate variables so that ICA forms one part of a hierarchical system. We show that such an approach allows for efficient discovery of hidden representation in data and for unsupervised data partitioning.