Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

基于超声红外技术对金属管内壁缺陷的检测

为提高管道的运送效率,及时检测排除管道内壁的缺陷非常重要。提出利用超声红外无损检测方法对管道内部进行检测。超声主动热激励试件,高频红外热像仪记录试件表面温度变化,结合了超声摩擦生热和红外热成像的优点。对壁厚约为3.3mm检测难度较大的金属管内壁缺陷进行了检测。通过对采集数据和热图的处理分析,准确快速地确定缺陷所在的位置。实物对比分析表明：超声热激励红外无损检测技术可以对金属管道内壁缺陷进行准确检测定位。     

基于光纤光栅的输油管道安全监测系统

针对穿插于滑坡体内的输油管道,提出一种基于光纤光栅传感的管道安全监测系统。系统由光开关和光纤光栅解调仪共同完成数据的自动测量和存储,并利用GPRS方式进行数据传输。利用已知管道上三点应力求最大应力的方法,选用自行研制的光纤光栅传感器监测管体应力。该传感器除了具有抗电磁干扰、耐腐蚀、稳定性好的优点,还可以实现温度补偿,不但排除了温度对测量结果的影响,还可以测量环境温度。经实际应用证明：该监测系统可实现实时监测,性能稳定。     

Water-soluble inhibitor on microbiologically influenced corrosion in diesel pipeline

The effect of water-soluble corrosion inhibitor on the growth of bacteria and its corrosion inhibition efficiency were investigated. Corrosion inhibition efficiency was studied by rotating cage test and flow loop techniques. The nature of biodegradation of corrosion inhibitor was also analyzed by using Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance spectroscopy (NMR) and Gas chromatography and mass spectrometer (GC–MS). The bacterial isolates (Serratia marcescens ACE2, Bacillus cereus ACE4) have the capacity to degrade the aromatic and aliphatic hydrocarbon present in the corrosion inhibitor. The degraded products of corrosion inhibitor and bacterial activity determine the electrochemical behaviour of API 5LX steel. The influence of bacterial activity on degradation of corrosion inhibitor and its influence on corrosion of API 5LX have been evaluated by employing weight loss techniques and electrochemical studies. The main finding of this paper is that the water-soluble corrosion inhibitor is consumed by the microbial action, which contributes to the decrease in inhibitor efficiency. The present study also emphasis the importance of evaluation of water-soluble corrosion inhibitor in stagnant model (flow loop test) and discusses the demerits of the water-soluble corrosion inhibitors in petroleum product pipeline.     

跨断层埋地管线-土接触非连续变形分析

跨断层埋地管线系统主要由管线及其周围土体两种不同介质组成,具有分析介质不连续性特性.为实现对管-土接触介质的不连续性分析,采用非连续变形分析与有限元分析相结合的方法,将跨逆断层埋地管线系统从实际工作状态中取出一部分作为分析对象.利用有限元分析方法对管线及其周围土体进行网格划分;而管-土之间的相互作用,利用非连续变形分析中的不连续介质接触处理方法实现模拟.通过模型的数值分析,研究了逆断层作用下管-土之间的非连续变形相互作用状态,验证了利用非连续变形分析与有限元方法相结合解决埋地管线-土接触的可行性和有效性,为管-土相互作用分析提供了新的研究思路和研究方法.     

各向同性钢材的断裂模型和屈服模型

基于钢材断裂前必先屈服的基本事实, 以钢材断裂面为屈服面后继扩大直至材料完整性(连续性）发生破坏为假设, 以已有的屈服模型的共同特征为切入点, 建议了各向同性钢材在主应力空间的二次函数型断裂模型和屈服模型. 根据不同钢材的特征应力值, 量化了各向同性钢材的二次函数型断裂模型和屈服模型. 依据不同钢材的特征应力值的相互关系, 建议的各向同性钢材的二次函数型断裂模型和屈服模型相应地描述为主应力空间的圆柱面、椭球面、抛物面和双曲面. 建议的各向同性钢材的二次函数型断裂模型和屈服模型较已有的强度模型更具一般性.     

海洋结构物摩擦学问题的研究进展

海洋结构物主要包括海上钻井平台、油气开采平台、FPSO、海底输油管线及海上大型储油罐等大型海上结构物.海洋结构物总是处于波浪、海流、风暴、海冰等严峻海洋环境中,并受到海生物污损、海洋腐蚀、磨损等多方面因素相互作用的影响,摩擦学问题无处不在.论文针对海洋平台结构、流体处理及运输设备、定位设备及作业设备四方面的摩擦学问题进行论述,主要介绍了海洋平台结构、管道系统及海水泵、锚链及螺旋桨、钻井套管及电潜泵等海工设备的工作特点,概述了国内外关于这类海工设备的摩擦学问题的研究现状,并对海洋结构物的摩擦学研究重点进行了展望.     

管道大范围屈服断裂评估的研究现状与进展

高强度、高韧性管材的大量应用, 提出管道大范围屈服断裂问题. 针对现有的断裂力学方法应用于管道大范围屈服断裂评估的局限性, 分别从双参数断裂力学、基于约束校正的断裂韧性测试、基于应变的断裂评估和基于应变的失效评估图4个方面详细地介绍了管道大范围屈服断裂评估的研究现状. 指出目前基于约束校正的管道断裂韧性测试的主要方法是SENT试件方法和表观断裂韧性方法, 评述了基于SENT试件约束校正的断裂评估研究现状及存在的问题. 阐述了基于应变断裂评估的基本原理, 并从驱动力方程和CTOD失效准则两方面介绍了基于应变的断裂评估方法的研究工作成果. 最后提出了需要进一步研究的问题.      

基于CTOD/CTOA管道钢断裂韧性测试方法研究进展

高级别管线钢的一大特点是韧度高,导致管材裂纹尖端周围经常处于大范围屈服状态,现有基于高约束试件的断裂韧性测试方法,很难满足新型管材的断裂韧性测试要求. 本文回顾了基于CTOD 和CTOA的断裂韧度参数,详细介绍了管道钢断裂韧性测试方法的研究现状和发展趋势,分析了影响管道钢断裂韧性测试准确性的各种因素,为管道钢断裂韧性的测试提供帮助.     

防止温度应力下海底管线发生整体屈曲的工程措施研究

为减小油气输送难度和避免原油固化,石油、天然气通常在高温高压下输送．输送过程中的高温和高压导致海底管线中产生较大的附加应力,附加应力的不断累积造成管线发生整体屈曲．对于埋地的海底管线通常会产生竖向屈曲大变形而影响使用甚至破坏．因此,需对有可能产生整体屈曲的管线采取工程防护措施．结合我国海洋工程中管线常用的铺设及保护措施,对处于保护状态下管线由温度应力引起的整体屈曲特性进行理论分析和数值推导,对沟槽保护、沟槽掩埋保护以及压块保护措施的有效性进行了系统分析和对比．