An accurate method to predict the stress concentration in composite laminates with a circular hole under tensile loading

The paper presents a theoretical-numerical hybrid method for determining the stresses distribution in composite laminates containing a circular hole and subjected to uniaxial tensile loading. The method is based upon an appropriate corrective function allowing a simple and rapid evaluation of stress distributions in a generic plate of finite width with a hole based on the theoretical stresses distribution in an infinite plate with the same hole geometry and material. In order to verify the accuracy of the method proposed, various numerical and experimental tests have been performed by considering different laminate lay-ups; in particular, the experimental results have shown that a combined use of the method proposed and the well-know point-stress criterion leads to reliable strength predictions for GFRP or CFRP laminates with a circular hole. Russian translation published in Mekhanika Kompozitnykh Materialov, Vol. 43, No. 4, pp. 531–570, July–August, 2007.     

模糊神经网络在复合地基沉降量预测中的应用

复合地基后期沉降变形对于建筑物设计及安全具有重要意义,针对通过长期沉降观测以得到复合地基的最终沉降需要耗费较多资源的问题,提出了一种基于模糊神经网络的预测方法.该方法考虑沉降变化过程有较大的随机性和模糊性,直接将样本数据进行模糊化,所得的模糊数代表了样本点集与控制点集中各分量之间的相关度,并依此建立模糊BP神经网络进行学习和估算.实验结果表明了该方法对沉降进行预测是可行与有效的,且在相对误差的有效控制方面优于BP网络方法与灰色方法.     

微通道板增益疲劳机理研究

微通道板的增益疲劳是微通道板的主要问题之一，本文分析了微通道板的表面结构模型，同通道板活性表面上碱金属的逸出和碳的增加是导致微通道板的增益疲劳的主要原因，另外，探讨碱金属逸出的机理和碳污染的来源，介绍延长微通道板工作寿命的有效方法。     

不同常压流化床煤气化方案的模型预测 Ⅰ. 模型建立及验证

为评价不同气化方案对常压流化床气化的影响，从化学动力学角度并结合化学平衡建立了流化床气化模型，该模型考虑了煤热解和气化所经历的各反应过程。模型预测结果与文献报道的试验数据吻合较好，气化组分的平方误差和在10%左右，表明该模型可以用来预测各种气化方案对常压流化床气化的气化过程、生成煤气组分和气化效率等方面的影响。     

Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using and nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the ‘measured’ and ‘estimated’ RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only NMR data) also showed high correlation between the ‘measured’ and ‘estimated’ RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.     

Identification of a chemical indicator of the rupture of 1,4-β-glycosidic bonds of cellulose in an oil-impregnated insulating paper system

In this study, headspace gas chromatography/mass spectrometry has been used to assess the volatile by-products generated by the ageing of oil-impregnated paper insulation of power transformers. Sealed-glass ampoules were used to age under oxidative conditions 0.5-g specimens of insulating paper in 9 mL of inhibited mineral oil in a temperature range of 60–120 °C and moisture of 0.5, 1 and 2% (w/w). A linear relationship between one of the oil-soluble degradation by-products, i.e. methanol, and the number of ruptured 1,4-β-glycosidic bonds of cellulose, regardless of the type of paper (ordinary Kraft or thermally-upgraded (TU) Kraft paper), was established for the first time in this field. Ageing at 130 °C of model compounds of the Kraft paper constituents (α-cellulose, hemicellulose and lignin) and two cellulosic breakdown by-products (D-(+)-glucose and 1,6-anhydro-β-d-glucopyranose) confirmed that the α-cellulose degradation was mostly responsible for the presence of this molecule in the system. Furthermore, additional 130 °C-tests with six different papers and pressboard samples under a tight control of initial moisture indicated that at least one molecule of methanol is formed for each rupture of 1,4-β-glucosidic bond of the molecular chains. Stability tests showed that the ageing indicator is stable under the oxygen and temperature conditions of open-breathing transformers. The presence of methanol was detected in 94% of oil samples collected from over than 900 in-service pieces of equipment, confirming the potential for this application. Lastly, the tests have shown that oil-oxidation by-products and TU-nitrogenous agents modify the methanol partitioning coefficients in the paper/oil/air system, which makes their study essential over a range of field conditions encountered by power transformers. Results are presented and discussed in comparison with 2-furfuraldehyde, which is the current reference in the domain.     

螺旋结构与旋光性——2.脂族链状化合物的螺旋结构和旋光性

利用弯曲键理论,详细讨论了旋光性的脂肪族链状化合物分子内存在的螺旋结构,同样是右螺是右旋的,左螺旋是左旋的。从螺旋方向可以推断旋光方向,知道旋光方向也可以推断构型。     

Structure-property modelling of complex formation of strontium with organic ligands in water

The method of substructural molecular fragments based on representation of the molecular graph by ensembles of fragments and involving calculations of those contributions to the given property is applied to the modelling of stability constants of the complexes of strontium(II) with organic ligands in water. Reliability of predictions of developed structure-property models was examined using three different test sets of structurally diverse ligands. The obtained models have been used for generation and screening of combinatorial library of virtual ligands. Some hypothetical efficient Sr(II) binders were suggested.     

What to Learn from a Comparative Genomic Sequence Analysis of <Emphasis Type="Italic">L</Emphasis>-Carnitine Dehydrogenase

Summary. In contrast to eukaryotic cells certain eubacterial strains have acquired the ability to utilize L-carnitine (R-(–)-3-hydroxy-4-(trimethylamino)butyrate) as sole source of energy, carbon and nitrogen. The first step of the L-carnitine degradation to glycine betaine is catalysed by L-carnitine dehydrogenase (L-CDH, EC 1.1.1.108) and results in the formation of the dehydrocarnitine. During the oxidation of L-carnitine a simultaneous conversion of the cofactor NAD⁺ to NADH takes place. This catabolic reaction has always been of keen interest, because it can be exploited for spectroscopic L-carnitine determination in biological fluids – a quantification method, which is developed in our lab – as well as L-carnitine production.Based on a cloned L-CDH sequence an expedition through the currently available prokaryotic genomic sequence space began to mine relevant information about bacterial L-carnitine metabolism hidden in the enormous amount of data stored in public sequence databases. Thus by means of homology-based and context-based protein function prediction is revealed that L-CDH exists in certain eubacterial genomes either as a protein of approximately 35 kDa or as a homologous fusion protein of approximately 54 kDa with an additional putative domain, which is predicted to possess a thioesterase activity. These two variants of the enzyme are found on one hand in the genome sequence of bacterial species, which were previously reported to decompose L-carnitine, and on the other hand in gram-positive bacteria, which were not known to express L-CDH. Furthermore we could not only discover that L-CDH is located in a conserved genetic entity, which genes are very likely involved in this L-carnitine catabolic pathway, but also pinpoint the exact genomic sequence position of several other enzymes, which play an essential role in the bacterial metabolism of L-carnitine precursors.     

疏水分配常数用于反相液相色谱保留值的预测

在反相液相色谱保留值基本方程log k_′=a+_cC_B的基础上,描述了采用疏水分配常数及氢键作用能来预测a、c参数的方法,并系统讨论了疏水分配常数对参数a、c的影响,借此对反相液相色谱宽浓度范围内的保留值进行了预测。