基于PSR-WSVM模型的边坡位移预测

为建立高精度的边坡位移预测模型，采用相空间重构（PSR）将边坡位移时间序列数据转换为多维数据，同时构造小波核函数改进的支持向量机模型，建立PSR-WSVM模型并应用于边坡位移预测。将PSR-WSVM模型预测结果与传统支持向量机（SVM）模型、小波支持向量机（WSVM）模型和基于相空间重构的支持向量机（PSR-SVM）模型预测结果进行对比，通过平均绝对误差（MAE）、平均绝对误差百分比（MAPE）和均方根误差（RMSE）3个精度评价指标验证PSR-WSVM模型的可行性。工程实例结果表明，PSR-WSVM模型预测结果的3个精度评价指标都优于另外3种模型，边坡位移预测的精度明显提升。     

张力腿平台筋腱支撑浮筒结构设计研究

在张力腿平台筋腱与海底桩基连接后,需要筋腱支撑浮筒为筋腱提供足够的浮力,保证筋腱在平台运抵工作海域之前不会发生倾覆。针对南海油田自主研发的张力腿平台筋腱实际尺寸及设计要求,设计了适用于1 061 mm(40英寸)筋腱、500米水深的张力腿平台筋腱支撑浮筒,并对筋腱支撑浮筒主要受力进行了分析计算,根据所计算的载荷情况对关键部件进行了有限元仿真分析,验证了结构强度的可靠性,并得到了结构的应力集中点与最大变形点,为筋腱支撑浮筒的结构设计提供了参考。     

Damage assessment for submarine photoelectric composite cable under anchor impact

The impact of dropped anchor on submarine photoelectric composite cables may possibly cause electrical faults, i.e. electricity and optical signal transmission failure. In order to study the impact capacity and structural impact failure mechanism, a test setup is designed originally to examine the structural and functional integrity. A detailed finite element model (FEM) is created, considering material nonlinearity and component interaction. A parametric analysis has been performed to predict the deformation of components and impact forces, under different impact velocities and collision directions. Relationships between the armor layer indentation rate and that of internal power and optical units are achieved. The impact deformation of internal entities can be evaluated intuitively by armor layer indentation. The proposed experimental and numerical methods are well correlated, suitable to assess the impact capacity of subsea power cables and assist the protection design of subsea power cables in engineering.     

CORROSION RESISTANCE OF INTERFERENCE FILM ON STAINLESS STEEL

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STRESS CORROSION CRACKING OF AISI 321 STAINLESS STEEL IN ACIDIC SEAWATER

ImooUonONSCCisoneofthemosttwortantcausoffailureofstaiuleSsstalequipmentandfacilitieS.Studiesonunh0refacilitiesshowedthatanaddicchloridesolutionfilmcouldbefo~onthescheeofstalandthatstaiuleSSstalisinaCtivedissolutionstateinaedicchloridesolutionopinetal.,l99O;Gnanamoorthyetal.,l99O).ltisgenerallythoughtxthatSCCcannotoimrwhenthematerialisinaCtiveanodicdissolutionstate,soitsomcewithresultingcasualties(0ldfieldetal.,l99O)arousedattentiont0it.SomeSCCmeCanisrnsproposedpeuang,l988,Newmanctal.,…     

EFFECT OF SULPHATE-REDUCING BACTERIA ON ELECTRO-CHEMICAL CORROSION BEHAVIOR OF 16Mn STEEL IN SEA MUD

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Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

广州地区深基坑支护形式研究

介绍了广州地区基坑支护近年来的主要类型及其适用范围,并在分析选型各影响因素的基础上,总结出设计选型的要点。     

软硬互层金刚石复合片钻头在地浸砂岩型铀矿中的研究及应用

针对近年在巴音戈壁盆地及鄂尔多斯盆地钻探所遇到的复杂地质情况,研究试验了PDC钻头,在地浸砂岩铀矿钻探生产中取得了良好的效果,并制定总结了相应的钻进参数.     

基于AGA的SVM需水预测模型研究

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.