多元合金化大断面球墨铸铁组织和性能的分析

为了提升大断面球墨铸铁综合力学性能，通过复合添加微量合金元素铜、锑、锡、钼对大断面球墨铸铁进行微合金化处理，借助金相显微镜(OM)、扫描电子显微镜(SEM)及力学性能测试等手段，研究了Cu Sb Sn Mo复合微合金化大断面球墨铸铁微观组织和力学性能。结果表明，试验球墨铸铁具有良好的综合力学性能。大断面球墨铸铁中添加铜、锑、锡、钼后优化了材料的组织结构，基体组织为珠光体＋少量牛眼状铁素体；试样石墨组织细小、圆整，分布均匀。同时，合金元素的复合加入使得其抗拉强度达到800 MPa以上，硬度约为280HB，伸长率达到5%以上。拉伸断口分析表明，微合金化大断面球墨铸铁断裂模式以解理断裂为主，伴有少量的塑性变形。     

叠合盆地凸起区多期复杂断裂特征及形成机制——以准噶尔盆地车排子凸起为例

以高精度三维地震资料为基础,结合构造演化恢复和区域构造背景,系统研究了准噶尔盆地车排子凸起断裂分布和形成机制。结果表明,车排子凸起发育深部和浅部2套断裂体系,深部断裂体系和浅部断裂体系分别发育3种断裂样式。车排子凸起共经历5个构造演化阶段,其中,晚二叠世挤压-逆冲控制了深部断裂体系的初始形成,晚侏罗世逆冲-走滑控制了深部断裂体系的最终定型,新近纪叠加掀斜、局部伸展控制了浅部断裂体系的形成。不同断裂体系在油气成藏过程中均起到了重要作用。其中:深部断裂体系的红车断裂是重要的油源断裂,低序级断层控制形成了石炭系火山岩优质储集体;浅部断裂体系使得油气向浅部层系运移调整,同时形成了断块圈闭、断鼻圈闭和断层-岩性圈闭等丰富的圈闭类型。     

埋地管道泄漏内封堵装置设计与研究

针对流体输送埋地管道泄漏问题,设计了一种利用管道机器人携带封堵气囊进行快速应急封堵修复的埋地管道泄漏内封堵装置。采用矩阵变换方法建立了牵引系统驱动轮过弯方程,利用MATLAB软件对过弯方程进行了验证,同时利用ADAMS软件仿真分析过弯路径与驱动轮转角对牵引系统行走速度的影响。研究结果表明:由两个串联封堵器组成的应急封堵系统可满足复杂工况下的管道泄漏封堵要求;牵引系统驱动轮在弯管内部行走时,单轮速度呈周期性变化,但三个驱动轮整体周期运动特性一致;驱动轮转角在25°~40°时,牵引系统行走速度与驱动轮转角成正比,且转角为30°时驱动效果最好。该内封堵装置的结构设计可为管道泄漏应急封堵领域装备的研发提供重要参考。     

Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

Selective Analysis of Sulfur-Containing Species in a Heavy Crude Oil by Deuterium Labeling Reactions and Ultrahigh Resolution Mass Spectrometry

A heavy crude oil has been treated with deuterated alkylating reagents (CD₃I and C₂D₅I) and directly analyzed without any prior fractionation and chromatographic separation by high-field Orbitrap Fourier Transform Mass Spectrometry (FTMS) and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) using electrospray ionization (ESI). The reaction of a polycyclic aromatic sulfur heterocycles (PASHs) dibenzothiophene (DBT), in the presence of silver tetrafluoroborate (AgBF₄) with ethyl iodide (C₂H₅I) in anhydrous dichloroethane (DCE) was optimized as a sample reaction to study heavy crude oil mixtures, and the reaction yield was monitored and determined by proton nuclear magnetic resonance spectroscopy (¹H-NMR). The obtained conditions were then applied to a mixture of standard aromatic CH-, N-, O- and S-containing compounds and then a heavy crude oil, and only sulfur-containing compounds were selectively alkylated. The deuterium labeled alkylating reagents, iodomethane-d₃ (CD₃I) and iodoethane-d₅ (C₂D₅I), were employed to the alkylation of heavy crude oil to selectively differentiate the tagged sulfur species from the original crude oil.     

The organization of biological sequences into constrained and unconstrained parts determines fundamental properties of genotype–phenotype maps

Biological information is stored in DNA, RNA and protein sequences, which can be understood as genotypes that are translated into phenotypes. The properties of genotype–phenotype (GP) maps have been studied in great detail for RNA secondary structure. These include a highly biased distribution of genotypes per phenotype, negative correlation of genotypic robustness and evolvability, positive correlation of phenotypic robustness and evolvability, shape-space covering, and a roughly logarithmic scaling of phenotypic robustness with phenotypic frequency. More recently similar properties have been discovered in other GP maps, suggesting that they may be fundamental to biological GP maps, in general, rather than specific to the RNA secondary structure map. Here we propose that the above properties arise from the fundamental organization of biological information into ‘constrained'' and ‘unconstrained'' sequences, in the broadest possible sense. As ‘constrained'' we describe sequences that affect the phenotype more immediately, and are therefore more sensitive to mutations, such as, e.g. protein-coding DNA or the stems in RNA secondary structure. ‘Unconstrained'' sequences, on the other hand, can mutate more freely without affecting the phenotype, such as, e.g. intronic or intergenic DNA or the loops in RNA secondary structure. To test our hypothesis we consider a highly simplified GP map that has genotypes with ‘coding'' and ‘non-coding'' parts. We term this the Fibonacci GP map, as it is equivalent to the Fibonacci code in information theory. Despite its simplicity the Fibonacci GP map exhibits all the above properties of much more complex and biologically realistic GP maps. These properties are therefore likely to be fundamental to many biological GP maps.     

基于特征融合的中文简历解析方法研究

针对基于规则和统计的传统中文简历解析方法效率低、成本高、泛化能力差的缺点，提出一种基于特征融合的中文简历解析方法，即级联Word2Vec生成的词向量和用BLSTM（Bidirectional Long Short-Term Memory）建模字序列生成的词向量，然后再结合BLSTM和CRF（Conditional Random Fields）对中文简历进行解析（BLSTM-CRF）。为了提高中文简历解析的效率，级联包含字序列信息的词向量和用Word2Vec生成的词向量，融合成一个新的词向量表示；再由BLSTM强大的学习能力融合词的上下文信息，输出所有可能标签序列的分值给CRF层；再由CRF引入标签之间约束关系求解最优序列。利用梯度下降算法训练神经网络，使用预先训练的词向量和Dropout优化神经网络，最终完成对中文简历的解析工作。实验结果表明，所提的特征融合方法优于传统的简历解析方法。     

Detection of correlation characteristics between financial time series based on multi-resolution analysis

Interactions between financial time series are complex and changeable in both time and frequency domains. To reveal the evolution characteristics of the time-varying relations between bivariate time series from a multi-resolution perspective, this study introduces an approach combining wavelet analysis and complex networks. In addition, to reduce the influence the phase lag between the time series has on the correlations, we propose dynamic time-warping (DTW) correlation coefficients to reflect the correlation degree between bivariate time series. Unlike previous studies that symbolized the time series only based on the correlation strength, the second-level symbol is set according to the correlation length during the coarse-graining process. This study presents a novel method to analyze bivariate time series and provides more information for investors and decision makers when investing in the stock market. We choose the closing prices of two stocks in China’s market as the sample and explore the evolutionary behavior of correlation modes from different resolutions. Furthermore, we perform experiments to discover the critical correlation modes between the bull market and the bear market on the high-resolution scale, the clustering effect during the financial crisis on the middle-resolution scale, and the potential pseudo period on the low-resolution scale. The experimental results exactly match reality, which provides powerful evidence to prove that our method is effective in financial time series analysis.     

Pull out of FRP reinforcement from masonry pillars: Experimental and numerical results

In this paper, debonding phenomena between carbon fiber reinforced polymer (CFRP) strips and masonry support were investigated on the basis of single-lap shear tests, considering different dimensions of the bond length. To capture the post-peak response of the CFRP–masonry joint, the slip between the support and the reinforcement strip was controlled using a clip gauge positioned at the end of the reinforcement. The tests were simulated by means of a finite element model able to capture the post-peak snap-back behavior due to the failure process. The numerical model is based on zero-thickness interface elements and on a proper non-linear cohesive law. The comparison between experimental and numerical results was performed in terms of overall response, measured by both the machine stroke and the clip gauge positioned at the free end of the reinforcement. The cases of effective bond length greater and lesser than the minimum anchorage length, suggested by the CNR Italian recommendation, were considered.