Comparing different methods of bed shear stress estimates in simple and complex flow fields

Bed shear stress is a fundamental variable in river studies to link ?ow conditions to sediment transport. It is, however, dif?cult to estimate this variable accurately, particularly in complex ?ow ?elds. This study compares shear stress estimated from the log pro?le, drag, Reynolds and turbulent kinetic energy (TKE) approaches in a laboratory ?ume in a simple boundary layer, over plexiglas and over sand, and in a complex ?ow ?eld around de?ectors. Results show that in a simple boundary layer, the log pro?le estimate is always the highest. Over plexiglas, the TKE estimate was the second largest with a value 30 per cent less than the log estimate. However, over sand, the TKE estimate did not show the expected increase in shear stress. In a simple boundary layer, the Reynolds shear stress seems the most appropriate method, particularly the extrapolated value at the bed obtained from a turbulent pro?le. In a complex ?ow ?eld around de?ectors, the TKE method provided the best estimate of shear stress as it is not affected by local streamline variations and it takes into account the increased streamwise turbulent ?uctuations close to the de?ectors. It is suggested that when single‐point measurements are used to estimate shear stress, the instrument should be positioned close to 0·1 of the ?ow depth, which corresponds to the peak value height in pro?les of Reynolds and TKE shear stress. Copyright © 2004 John Wiley & Sons, Ltd.     

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中国东部海区科学钻探工程CSDP-02井钻探效率统计分析

CSDP-02井是中国东部海区科学钻探工程2井,该井采用五开结构,完井井径98 mm,完井井深2843.18 m,历时504 d,创造了海洋科学钻探全取心井深世界纪录。本文介绍了该井的施工过程,对该井的钻进时间、钻探效率和回次进尺长度进行了系统的统计与分析。通过分析,对影响海上深部科学钻探效率的海况、后勤保障等因素进行了简单的阐述,为提高海上深孔钻探施工效率提供了参考依据。     

In situ measurements of sediment settling characteristics in floodplains using a LISST‐ST

Due to a lack of data on settling velocities (w_s) and grain size distributions (GSDs) in ?oodplain environments, sedimentation models often use calibrated rather than measured parameters. Since the characteristics of suspended matter differ from those of deposited sediment, it is impossible to derive the w_s and GSD from the latter. Therefore, one needs to measure in situ suspended sediment concentrations (SSCs), settling velocities, effective grain sizes and sedimentation ?uxes. For this purpose we used the LISST‐ST, a laser particle sizer combined with a settling tube. In 2002 (twice) and 2004, we located the LISST‐ST with an optical backscatter sensor and sediment traps in two ?oodplains in The Netherlands: one along the unembanked IJssel River, another along the embanked Waal River. Measurements revealed that the SSC in the ?oodplains varied in relation to the SSC in the river channel. Smaller ?ocs dominated the SSC, while larger ?ocs dominated the potential sedimentation ?uxes. The in situ GSD in the IJssel ?oodplain was signi?cantly coarser than in the Waal ?oodplain, while the dispersed median grain sizes were equal for both ?oodplains. Therefore, the dispersed median grain size was two to ?ve times smaller than the effective one. The in situ grain size exhibited a signi?cant positive relationship with w_s, although the w_s for the largest ?ocs showed high variability. Consequently, the variability in sedimentation ?uxes was also large. In the actual sedimentation ?uxes, and hence in sedimentation models, in situ grain sizes up to about 20 µm can be neglected. In ?oodplain sedimentation models the relation between settling velocity and in situ grain size can be used instead of Stokes's law, which is only valid for dispersed grain sizes. These models should also use adequate data on ?ow conditions as input, since these strongly in?uence the suspended sediment characteristics. Copyright © 2005 John Wiley & Sons, Ltd.     

基于CBERS-02遥感影像的湿地地表覆被分类研究

基于CBERS遥感影像多光谱数据,运用信息量、相关系数及OIF方法,分析了波段数据特征,获得了对影像数据的整体认识。 通过绘制地表覆被类型的样本均值光谱曲线,分析了多种地表覆被类型在5个影像波段中的光谱特征,得出了不同覆被类型在各波 段中的反射特性。基于典型地表覆被类型样本数据,分别针对影像的5个波段及第一主成分、归一化植被指数这两个重要特征,运 用盒须图进一步分析了不同地表覆被类型的分异特性。运用Z-test统计方法,筛选出了区分不同地表覆被类型的最优纹理特征。运 用面向对象分类技术开展了研究区覆被类型分类实验,验证了基于CBERS遥感影像进行内陆淡水湿地区地表覆被分类的可行性,丰 富了地表覆被信息提取方法,拓展了CBERS遥感影像的应用领域。     

Surface modification of ZrO2 nanoparticles with styrene coupling agent and its effect on the corrosion behaviour of epoxy coating

The surface of ZrO2 nanoparticles was modified by styrene coupling grafting method to improve the dispersion and interaction of the nanoparticles with the epoxy coating in which the modified ZrO2 nanoparticles were used as an additive. The grafting performance and microstructure of the nano- ZrO2/epoxy coating were analyzed by Fourier transformation infrared spectroscopy, X-ray diffraction, and scanning electron microscopy. The corrosion behavior of the nano-ZrO2/epoxy coating on mild steel was evaluated in neutral 3.5 wt% NaC1 solution using electrochemical impedance spectroscopy （EIS）. Both the coating capacitance and coating resistance fitted by the equivalent circuit from EIS were used to evaluate the protective performance of the coating towards the mild steel. The results show a superior stability and efficient corrosion protection by the modified ZrO2 nanoparticles. The epoxy coating containing 2 wt% modified ZrO2 nanoparticles exhibited the best corrosion performance among all the coating specimens. This research may provide an insight into the protection of mild steel using modified epoxy coatings.     

资源一号02C卫星遥感影像二级产品定位精度评价

以黄河三角洲飞雁滩资源一号02C(以下简称ZY-1 02C)卫星遥感影像二级产品为例,开展影像定位精度评价工作。经现场采集的亚米级地面控制点检验,5m全色影像的定位精度为10.4m,10m多光谱影像的定位精度为15.6m;经地面控制点精校正后,全色影像定位精度可达4.1m,多光谱影像定位精度可达7.3m。上述结果表明在实验区域ZY-1 02C卫星影像二级产品的定位能力在2个像元左右,经过几何精校正后,定位能力优于1个像元,可以满足海岸带遥感调查工作的需要。     

春玉米根系原位成像图片自动识别研究

微根窗成像技术推动了植物根系表型研究,但是根系长度和直径仍然需要人眼识别再绘制轨迹,消耗大量的人力和时间。为了解决这一难题,本研究将U-Net语义分割技术引入到植物根系图像识别中,研发了基于机器学习的iRoot-V02根系自动识别软件。采用iRoot-V02软件识别微根窗法获得的植物根系成像图片的根长、直径、投影面积、根尖数等参数。结果表明：iRoot-V02软件批处理600 dpi图片的速度为每张26.6 S;获取根系的骨架信息、总根长与人眼识别结果基本一致;按直径每0.1 mm为一级,获得不同直径的根长,与人眼识别结果的根长决定系数大于0.76;精确捕捉到根系生长旺盛期不同直径根长的变化;分析了300 dpi和600 dpi两种分辨率根系图片的参数,两种分辨率结果具有高相关性,因此可建立低分辨率根系参数和高分辨率根系参数之间的关系方程,采用低分辨率拍摄根系图像,通过方程转化成更准确的根系参数,减轻工作量。用iRoot-V02软件的根系生长信息近似于人眼识别,相比人眼识别在大批量根系图像智能识别、自动化、快速目标检测方面具有巨大优势。     

基于空谱融合与AlexNet算法的滨海湿地植被分类研究

为提高遥感影像融合质量,提升资源一号(ZY-1 02D)高光谱遥感影像滨海湿地植被分类精度,提出将ZY-1 02D高光谱影像与空间分辨率为10 m的哨兵2号(Sentinel-2)影像进行Brovey融合,并通过搭建AlexNet卷积神经网络对ZY-1 02D高光谱影像和Brovey融合影像的滨海湿地植被进行分类,与支持向量机、随机森林和BP神经网络分类算法进行精度对比。研究结果表明:经Brovey融合后,AlexNet、支持向量机、随机森林和BP神经网络算法的植被分类总体精度分别提高15.60%、7.00%、14.80%和10.00%,Kappa系数提高了21.35%、9.93%、18.97%、12.85%;基于Brovey影像融合与AlexNet算法的植被分类精度最高,总体精度为92.40%,Kappa系数为89.42%。空谱融合配合AlexNet卷积神经网络有效解决了高光谱遥感影像在滨海湿地植被分类应用中精度较低的问题,为滨海湿地植被资源动态监测提供技术和方法支撑。