连续损伤力学基临界奇异指数与破坏时间预测

响应量在临近破坏时呈现出临界幂律奇异性加速特征,是一种被广泛证实的灾变破坏前兆,并被火山、滑坡和岩石破坏实验等后验预测结果证实为一种对破坏时间进行短临期预测的可行方法.但是,奇异性指数测量值的较大分散性导致了对其具体取值的争议和预测效果的不确定性.因此,理解奇异性指数取值特征及其内在物理控制因素,成为了一个核心问题.本文基于连续介质损伤力学和材料时间相关失效特征,构建了刻画损伤加速发展通向破坏过程的力学模型.导出了恒名义应力蠕变加载和控制名义应力随时间线性增大两种典型加载方式下,损伤和应变率加速发展通向破坏的临界幂律奇异性前兆特征.阐明了临界幂律奇异性指数取值依赖于材料损伤与承受真应力之间的非线性关系这一内在物理根源,表明了实际测量中奇异性指数的分散性不完全归结于测量数据误差,而是有着内在物理控制因素.针对破坏前奇异性指数的不确定性,建议了在未知奇异性指数条件下预测破坏时间的方法,并基于花岗岩脆性蠕变破坏实验进行了验证和说明.      

Temperature dependence of the properties of ternary systems ethanol + water + an aliphatic alkane (C6-C9)

The measures and calculation of different properties such as refractive index, density, speed of sound, excess molar volume, and isentropic compressibility of the ternary heterogeneous compounds by ethanol + water + (n-hexane, n-heptane, n-octane, n-nonane) have been performed in the range 288.15–323.15 K and atmospheric pressure. Attending to the accurate results of these models, the equation of state enclosing mixing rules is indicated as a simple estimation of the procedures of these properties for this kind of multicomponent systems.     

考虑防御系统延迟使其预测误差最大的突防弹道设计

对中段多脉冲机动突防弹道的设计问题进行了研究。采用的原理与方法有别于成熟的航天器多脉冲变轨,而是基于路径规划的思想对弹道设计问题简化。考虑敌方防御系统延迟,改进多脉冲点火模型,并基于变射面的思想对关机点参数进行了设计及优化。然后,从使敌方预测误差最大的角度提出评价函数,并利用遗传算法进行优化。最后,给出了一种同时满足导弹机动突防与打击精度要求的多脉冲弹道设计方法。从模型的可行性,方法的有效性、灵活性、迭代效率及精度等方面进行了仿真验证分析。在PC机仿真中,20 s内就设计出一条保证打击精度的中段突防弹道。结果表明,建立的模型是可行的,提出的突防弹道设计方法是快速有效的。     

Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures

Automated structure verification using ¹H NMR data or a combination of ¹H and heteronuclear single‐quantum correlation (HSQC) data is gaining more interest as a routine application for qualitative evaluation of large compound libraries produced by synthetic chemistry. The goal of this automated software method is to identify a manageable subset of compounds and data that require human review. In practice, the automated method will flag structure and data combinations that exhibit some inconsistency (i.e. strange chemical shifts, conflicts in multiplicity, or overestimated and underestimated integration values) and validate those that appear consistent. One drawback of this approach is that no automated system can guarantee that all passing structures are indeed correct structures. The major reason for this is that approaches using only ¹H or even ¹H and HSQC spectra often do not provide sufficient information to properly distinguish between similar structures. Therefore, current implementations of automated structure verification systems allow, in principle, false positive results. Presented in this work is a method that greatly reduces the probability of an automated validation system passing incorrect structures (i.e. false positives). This novel method was applied to automatically validate 127 non‐proprietary compounds from several commercial sources. Presented also is the impact of this approach on false positive and false negative results. Copyright © 2012 John Wiley & Sons, Ltd.     

Structure Prediction of Binary Pernitride MN2 Compounds (M=Ca,Sr, Ba,La, and Ti)

Metal‐pernitride compounds belong to a class of chemical systems in which both the complex ions and the non‐bonding electrons may play roles in the formation of their modified crystalline structures. To investigate this issue, the energy landscapes of pernitrides of metals with different maximum valence (M=Ca, Sr, Ba, La, and Ti) were globally explored on the ab initio level at standard and high pressures, thereby yielding possible (meta)stable modifications in these systems together with information on how the landscape changed as function of the valence of the metal cation. For all of the systems in which no compounds had been synthesized so far, we predicted the existence of kinetically stable modifications that should, in principle, be experimentally accessible. In particular, TiN₂ should crystallize in a new structure type, TiN₂‐I.     

基于RBM的神经网络时间序列预测

为了克服神经网络依赖初始化结果,泛化能力不强的缺点,提出一种基于受限玻尔兹曼机(RBM)的神经网络模型.利用无监督学习方法优化神经网络的初始权值和阈值,将RBM与神经网络融合起来,模型与时间序列神经网络做实验对比,结果表明,基于受限的玻尔兹曼机的神经网络模型优于神经网络预测模型,模型可以提高预测的精准度,具有一定的应用意义.     

An integrative in silico approach to the structure of Omp33-36 in Acinetobacter baumannii

Omp33-36 in A. baumannii, a bacterium causing serious nosocomial infections, is a virulence factor associated with the pathogen metabolic fitness as well as its adherence and invasion to human epithelial cells. This protein is also involved in interaction of the bacteria with host cells by binding to fibronectin. Moreover, Omp33-36 renders cytotoxicity to A. baumannii in addition to inducing apoptosis and modulation of autophagy. In the present study, an integrated strategy is launched to pierce into the 3D structure of Omp33-36 protein. The signal peptide within the sequence was determined, then, topology as well as secondary and tertiary structures of the protein were predicted. The mature protein assigned as a 14-stranded barrel in which residues 1–19 is removed as signal peptide. The obtained 3D models were evaluated in terms of quality; and then, served as queries to find similar protein structures. The hits were analyzed regarding topology among which 14-stranded were considered. The most qualified model was refined and then its sequence aligned to its counterpart similar structure protein (CymA from Klebsiella oxytoca). The determined structure of Omp33-36 could justify its porin function and carbapenem-resistance associated with the loss of this protein.     

Planar Tetracoordinate Silicon in Organic Molecules As Carbenoid-Type Amphoteric Centers: A Computational Study

Designing and synthesizing a stable compound with a planar tetracoordinate silicon (ptSi) center is a challenging goal for chemists. Here, a series of potential aromatic ptSi compounds composed of four conjugated rings shared by a centrally embedded Si atom are theoretically designed and computationally verified. Both Born–Oppenheimer molecular dynamics (BOMD) simulations and potential energy surface scannings verify the high stability and likely existence of these compounds, particularly Si-16-5555 (SiN₄C₈H₈) with 16 π electrons, under standard ambient temperature and pressure. Notably, the Hückel aromaticity rule, which works well for single rings, is inconsistent with the high stability of Si-16-5555 where the 16 p electrons are spread over four five-membered rings fused together. Bonding analyses show that the strong electron donation from the peripheral 12-membered conjugated ring with 16 π electrons to the vacant central atomic orbital Si 3p_z leads to the stabilization for both the ptSi coordination and planar aromaticity. The partial occupation of Si 3p_z results in the peculiar carbenoid-type behaviors for the amphoteric center. By modulating the electron density on the ring with substituent groups, we can regulate the nucleophilic and electrophilic properties of the central Si.     

Physical implication of two problems in transition prediction of boundary layers based on linear stability theory

Up to now,the most widely used method for transition prediction is the one based on linear stability theory.When it is applied to three-dimensional boundary layers,one has to choose the direction,or path,along which the growth rate of the disturbance is to be integrated.The direction given by using saddle point method in the theory of complex variable function is seen as mathematically most reasonable.However,unlike the saddle point method applied to water waves,here its physical meaning is not so obvious,as the frequency and wave number may be complex.And on some occasions,in advancing the integration of the growth rate of the disturbance,up to a certain location,one may not be able to continue the integration,because the condition for specifying the direction set by the saddle point method can no longer be satisfied on the basis of continuously varying wave number.In this paper,these two problems are discussed,and suggestions for how to do transition prediction under the latter condition are provided.