FLU-net：用于表征页岩储层微观孔隙的深度全卷积网络

页岩孔隙是页岩气储集的主要空间,孔隙的形状、大小、连通性与发育程度很大程度上决定了页岩储集层的储集性能,因此,页岩气开采首先需要对其孔隙有充分的认识。基于阈值分割法获取页岩孔隙结构参数是目前页岩微观结构表征的一种重要手段,但是受扫描电镜图像灰度分布差异的影响,该方法需要逐一修改图像的最佳分割阈值以达到最好的孔隙分割效果,且阈值分割方法无法直接划分孔隙类别,这给后续的页岩微观结构定量表征带来了麻烦。为了实现页岩孔隙的智能识别和分类,笔者设计基于像素级语义分割的深度全卷积神经网络FLU-net,对页岩孔隙识别并分类为有机孔、无机孔（粒内孔、粒间孔）及裂缝,并结合孔隙尺度分类统计方法,分析不同类型孔隙发育数量、孔径大小、孔隙度等参数,实现页岩储层微观孔隙结构的自动化定量表征。以重庆渝西区块足201井区和四川盆地威远地区威204井区的页岩扫描电镜图像为研究对象,在对1 600幅页岩扫描电镜图像原始数据进行人工标注并划分数据集后,使用FLU-net进行孔隙识别,结果表明,本方法具有较高的准确率,同时自动化程度和泛化能力均高于传统预测方法。因此,扫描电镜与基于深度学习的语义分割模型结合是定量研究页岩微观结构表征的有效手段。     

基于GJB899A的可靠性统计试验方案分析

可靠性试验作为可靠性工程的重要一环,是衡量产品是否满足可靠性要求的重要手段之一。 GJB899A《可靠性鉴定和验收试验》给出了一系列统计试验方案,主要涉及定时截尾试验方案和序贯截尾试验方案。针对这 2 类试验方案的原理开展分析,根据试验方案的所需参数明确方案的确定方法,给出可靠性指标的验证方式。结合应用示例进行了分析说明,用以指导工程人员根据被试产品的可靠性要求选择合适的可靠性试验方案,可以有效帮助研制方和订购方开展可靠性试验。     

细菌源3-羟基脂肪酸作为环境变化代用指标的研究进展

细菌源3-羟基脂肪酸(C10-C18)作为环境变化指示指标具有良好的应用前景,但相关研究还很不系统,在海洋环境中的应用刚刚起步.3-羟基脂肪酸主要用于环境中pH和温度的重建,通过其支链比(异构和反异构3-羟基脂肪酸之和/正构3-羟基脂肪酸之和)与pH的显著正相关关系反演环境中的pH,通过其C15和C17同系物的反异构/...     

泉州湾赤潮藻类优势种细胞密度回归方程研究

于2006年5-11月对东海泉州湾赤潮监控区四个监测站位开展赤潮常规监测。根据监测结果,分别以各站位23项水质理化生物环境因子指标为自变量,相应赤潮藻类优势种的细胞密度为因变量,进行多元逐步回归分析,建立了各站位优势种中肋骨条藻(Skeletonema costatum)、太平洋海链藻(Thalassiosira pacifica)、微小原甲藻(Prorocentrum minimum)、尖刺拟菱形藻(Pseudo-nitzschia pungens)、丹麦细柱藻(Leptocylindrus danicus)和旋链角毛藻(Chaetoceros curvisetus)等的细胞密度多参量回归方程。结果表明,所有回归方程的复相关系数都接近于1,方差分析的结果均为回归极显著,表明所建立的回归方程可作为相应赤潮优势种细胞密度预报方程的高度有效性,将对今后泉州湾的赤潮预报提供良好的指导作用。     

The comparison of altimeter retrieval algorithms of the wind speed and the wave period

With the launch of altimeter,much effort has been made to develop algorithms on the wind speed and the wave period.By using a large data set of collocated altimeter and buoy measurements,the typical wind speed and wave period algorithms are validated.Based on theoretical argument and the concept of wave age,a semi-empirical algorithm for the wave period is also proposed,which has the wave-period dimension,and explicitly demonstrates the relationships between the wave period and the other variables.It is found that Ku and C band data should be applied simultaneously in order to improve either wind speed or wave period algorithms.The dual-band algorithms proposed by Chen et al.(2002) for the wind speed and Quilfen et al.(2004) for the wave period perform best in terms of a root mean square error in the practical applications.     

Analytical Study on Wave Diffraction from a Vertical Circular Cylinder in Front of Orthogonal Vertical Walls

In this paper, the principle of mirror image is used to transform the problem of wave diffraction from a circular cylinder in front of orthogonal vertical walls into the problem of diffraction of four symmetric incident waves from four symmetrically arranged circular cylinders, and then the eigenfunction expansion of velocity potential and Grafs addition theorem are used to give the analytical solution to the wave diffraction problem. The relation of the total wave force on cylinder to the distance between the cylinder and orthogonal vertical walls and the incidence angle of wave is also studied by numerical computation.     

不同营养条件下铜绿微囊藻(Microcystis aeruginosa)和小球藻(Chlorella vulgaris)的生长竞争行为

蓝藻的暴发通常是藻类之间竞争的结果,了解环境中蓝藻与其它藻类的竞争特点和生存策略对揭示藻华暴发的机制及治理具有重要意义。本文以营养竞争为例,以铜绿微囊藻(Microcystis aeruginosa)和小球藻(Chlorella vulgaris)为受试对象,通过测定细胞密度、胞内C、N、P、S四种主要元素含量以及培养基中总氮(TN)、总磷(TP)的消耗,研究不同营养等级(超富营养、富营养、中营养、贫营养)以及单独N、P限制下两种藻在单独培养和共生培养条件下的生长特征和竞争行为。结果表明:(1)在超富营养、富营养、中营养、贫营养条件时,单独培养下的两种藻生物量与营养丰富程度呈正相关;(2)共培养条件下,在高营养水平时铜绿微囊藻在竞争中占优势,低营养水平时小球藻具有竞争优势;(3)胞内C、N、P、S的测定发现,随着营养水平的下降,两种藻胞内N、P的百分含量逐渐减少,而C、S并未呈现显著变化;(4)N限制时,铜绿微囊藻的半饱和常数Ks及最大比增长率μmax均大于小球藻;P限制条件下铜绿微囊藻的半饱和常数Ks小于小球藻,而最大比增长率μmax大于小球藻。综合分析,同一营养条件下,铜绿微囊藻竞争优势的先决因子是N,小球藻是P。因此,从营养竞争与生物适应力角度考虑,降低水体中富余的N或适当提高P的浓度可让小球藻获得竞争优势,对限制单一物种的形成具有平衡作用,可作为防治藻华的潜在方法。     

玻璃钢渔船总纵弯曲的实船试验研究

本文通过实船试验研究玻璃钢渔船的总纵弯曲,以求得玻璃钢渔船应变和挠度随载荷的变化特性,从而了解玻璃钢渔船的总纵强度。     

Robust LS-SVM regression for ore grade estimation in a seafloor hydrothermal sulphide deposit

Due to the geological complexities of ore body formation and limited borehole sampling, this paper proposes a robust weighted least square support vectormachine (LS-SVM) regression model to solve the ore grade estimation for a seafloor hydrothermal sulphide deposit in Solwara 1, which consists of a large proportion of incomplete samples without ore types and grade values. The standard LS-SVM classification model is applied to identify the ore type for each in complete sample. Then, a weighted K-nearest neighbor (WKNN) algorithm is proposed to interpolate the missing values. Prior to modeling, the particle swarm optimization (PSO) algorithm is used to obtain an appropriate splitting for the training and test data sets so as to eliminate the large discrepancies caused by randomdivision. Coupled simulated annealing (CSA) and grid search using 10-fold cross validation techniques are adopted to determine the optimal tuning parameters in the LS-SVM models. The effectiveness of the proposed model by comparing with other well-known techniques such as inverse distance weight (IDW), ordinary kriging (OK), and back propagation (BP) neural network is demonstrated. The experimental results show that the robust weighted LS-SVM outperforms the othermethods, and has strong predictive and generalization ability.     

基于证据理论框架的分布式态势估计模型研究

作战环境信息作为一类重要的信息,在战场指挥决策中发挥着越来越重要的作用。 根据态势估计理论研究需要,对态势感知层中态势要素的提取进行了分析;在此基础上,应用证据理论和贝叶斯估计方法,构建了单检测站时域融合模型、多检测站空域融合模型。 为发挥作战环境在决策中的信息价值,构建了受环境制约下的时空融合模型;最后就该问题的下一步研究方向进行了展望。