ICMMS框架下水电厂溢洪闸门综合自动化系统

在吸收现有的智能控制、维护、技术管理集成系统（ICMMS）研究成果的基础上，以湖北省清江公司隔河岩水电厂溢洪闸门综合自动化系统为研究对象，在ICMMS框架下建立溢洪闸门综合自动化系统，将智能故障诊断技术应用于溢洪闸门系统建立优化维护系统，构成统一的ICMMS，以实现控制、维护、技术管理三者在功能上互相协调，在信息和资源上共享，力求最大限度的经济和社会效益。     

Automatic detection and validity of the sea-ice edge: an application of enhanced-resolution QuikScat/SeaWinds data

Sea-ice edge detection is an essential task at the different national ice services to secure navigation in ice-covered seas. Comparison between the Remund and Long ice mask image from enhanced-resolution QuikScat/SeaWinds (QS) products and the analyzed ice edge from high-resolution RADARSAT synthetic aperture radar has shown that the automatically determined QS ice mask underestimates the Arctic ice extent. QS data was statistically analyzed by colocating the data with ice charts around Greenland and with the National Aeronautics and Space Administration Team's Special Sensor Microwave/Imager (SSM/I) ice concentration algorithm over the whole Arctic region. All variables, i.e., the backscatter in vertical and horizontal polarization, the active polarization ratio (APR) and the daily standard deviation, are sensitive to ice types and are strongly correlated with ice concentration when the relationship is expressed in exponential form. Our study showed that the APR is especially suitable for ice-ocean separation, and a threshold of -0.02 was determined. An ice edge algorithm based on this APR threshold was developed using the other variables with conservative season-dependent thresholds to eliminate additional ocean noise. Also, the history of the ice cover is considered in order to detect single ice fields that are separated from the main Arctic pack ice. Validation with RADARSAT 1 and with the Advanced Very High Resolution Radiometer showed that the new algorithm successfully detects very low ice concentrations of about 10% during the entire year. The validity of the detected ice edge for near-real-time issues is also discussed in relation to the ice motion in the Marginal Ice Zone and the integration time necessary to produce the enhanced-resolution images. The new algorithm improves the automatic global ice edge resolution by a factor of two when compared to SSM/I products and could be used in both model initialization and data assimilation.     

New learning subspace method for image feature extraction

Image pattern recognition is the most i mportant re-search directions currently,and feature extraction is itscoretechnology.Researchinthisfield dates backat leastto the 1940s ,but most feature extraction techniques re-quire users to give a priori probabil…     

基于有限状态机的电网多源时空数据的区块链追溯方法研究

电网基础数据类型多、变化关系复杂,地理空间、时间周期跨度大,数据追溯困难,该文提出基于区块链技术的电网多源数据追溯方法。根据电网基础数据时空分布及数据流变动性特点,建立了基于区块链的多源数据追溯架构,研究了数据追溯依赖关系及溯源路径结构。提出了基于有限状态机模型的数据溯源的路径结构分析图,及路径构建算法,研究了多源时空数据区块的平行追溯方式。构建了基于有限状态机溯源路径的电网多源时空数据追溯优化流程,研究了多层次溯源数据区块时空序列关联性。工程实例表明,基于区块链、有限状态机可高效灵活追溯电网基础多源时空数据的完整可信分布序列。     

Experimental study of enhanced oil recovery by CO2 huff-n-puff in shales and tight sandstones with fractures

The fractures and kerogen,which generally exist in the shale,are significant to the CO2 huff-n-puff in the shale reservoir.It is important to study the effects ...     

瓦斯抽放系统在排放密闭巷道瓦斯过程中的应用

瓦斯抽放的方法有本煤层抽放、邻近层抽放和采空区抽放。传统排放密闭内的瓦斯方法是控制风流排放法,但如何安全、可靠排放密闭巷道内瓦斯问题却有待探索。文章就如何对密闭巷道内的瓦斯进行抽排作浅显论述。     

极端天气下基于时间卷积神经网络的新能源出力评估策略

新能源高渗透率背景下,极端天气造成的出力骤降对电力系统安全运行构成严重挑战,准确评估极端天气下的新能源出力深度是制定电力系统运行方式的重要依据。本文提出一种基于改进的深度时间卷积神经网络(deep temporal convolutional network,DeepTCN)的新能源出力评估方法。通过设计具有动态输入权重的时间卷积神经网络架构,准确量化估计了极端天气对新能源出力的影响,从而为制定极端天气下的电力系统运行方式提供风险程度信息。基于实际电力系统新能源出力数据集的算例结果表明,与常规的时序预测方法相比,所提方法的标准化均方根误差、对称平均绝对百分比误差和平均绝对标度误差3个指标分别最高可提升1.2,0.1和0.22。所提方法能够实现对极端天气下新能源出力的更精准评估。     

一种新的TOC含量拟合方法研究与应用

由于取样的限制,通常在烃源岩评价中往往只能获得十分有限的实测烃源岩的TOC含量数据。但随着我国多数盆地精细勘探的深入,需要更加精细的烃源岩评价,因此,人们对测井数据拟合烃源岩的TOC含量变化越来越重视。目前该技术最先进的是人工神经网络拟合方法,但多种神经网络在拟合高成熟度碳酸盐岩烃源岩地层的TOC含量时相关性均不够高。针对研究区内烃源岩的特点,尝试了一种用图版分类-模糊排队-BP神经网络联合拟合TOC含量的新方法。利用该方法对鄂尔多斯盆地马家沟组的测井资料和实测总有机碳资料进行数据处理,将结果与ΔlogR方法、模糊神经网络方法的结果相比较,证实该方法的结果与实测值有更好的相关性,为系统了解鄂尔多斯盆地下古生界烃源岩发育提供了一定的科学依据。     

利用TSUPREM-4对低压VDMOS进行虚拟制造

介绍了低压VDMOS的结构和各个参数及相互间的关系,并按TSUPREM-4工艺仿真软件的工艺流程顺序给出了各步工艺的设计思路、方法、注意事项。对外延层厚度进行了计算,并用该软件实现了耐压55 V,导通电阻11 MΩ的低压VDMOS器件结构的工艺设计,绘出了仿真结构图。     

Characterization of a Thermostable and Surfactant-Tolerant Chondroitinase B from a Marine Bacterium Microbulbifer sp. ALW1

Chondroitinase plays an important role in structural and functional studies of chondroitin sulfate (CS). In this study, a new member of chondroitinase B of PL6 family, namely ChSase B6, was cloned from marine bacterium Microbulbifer sp. ALW1 and subjected to enzymatic and structural characterization. The recombinant ChSase B6 showed optimum activity at 40 °C and pH 8.0, with enzyme kinetic parameters of K_m and V_max against chondroitin sulfate B (CSB) to be 7.85 µg/mL and 1.21 U/mg, respectively. ChSase B6 demonstrated thermostability under 60 °C for 2 h with about 50% residual activity and good pH stability under 4.0–10.0 for 1 h with above 60% residual activity. In addition, ChSase B6 displayed excellent stability against the surfactants including Tween-20, Tween-80, Trion X-100, and CTAB. The degradation products of ChSase B6-treated CSB exhibited improved antioxidant ability as a hydroxyl radical scavenger. Structural analysis and site-directed mutagenesis suggested that the conserved residues Lys248 and Arg269 were important for the activity of ChSase B6. Characterization, structure, and molecular dynamics simulation of ChSase B6 provided a guide for further tailoring for its industrial application for chondroitin sulfate bioresource development.