ODP204航次天然气水合物的可能有利储层——浊积层

为了解岩性在天然气水合物分布中的作用, 利用岩矿鉴定、扫描电镜和能谱法对ODP204航次的 4个站位 10个钻孔共计 115个沉积物样品进行分析, 发现沉积物中矿物成分基本相近, 以粘土矿物为主, 含少量以石英为主的陆源碎屑。样品中含有丰富的硅藻和有孔虫等微体化石, 可形成硅藻粘土—硅藻土、有孔虫硅藻土或凝灰质硅质生物粘土。石英碎屑大多呈棱角状, 粒径小、含量少, 同时, 样品中可见透镜体、团块或旋涡状层状结构以及杂乱堆积的斑杂构造。上述特征表明沉积物为含有大量深海或半深海的浊流沉积物或其夹层。由于钻井岩心中有相当部分的天然气水合物样品分布在上述沉积物中, 推断这些浊流沉积物很可能是ODP204航次天然气水合物的有利储层。     

平差系统的模型误差及其识别方法研究

论述了模型误差影响参数估值的一些理论问题,指出了随机模型误差和函数模型误差之间的相互作用和转化。为讨论平差系统最优模型的选取,给出了与现有文献将模型误差纳入平差系统的思路不同的一个估计和识别模型误差的理论基础公式,由此导出了相应的实用公式,给出了平差系统模型的优选方法。     

A new method for indentifying the model error of adjustment system

Some theory problems affecting parameter estimation are discussed in this paper. Influence and transformation between errors of stochastic and functional models is pointed out as well. For choosing the best adjustment model, a formula, which is different from the literatures existing methods, for estimating and identifying the model error, is proposed. On the basis of the proposed formula, an effective approach of selecting the best model of adjustment system is given. Project supported by the Open Research Fund Program of the Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University (No. 905276031-04-10).     

Structural damage detection using the optimal weights of the approximating artificial neural networks

This work presents a novel neural network‐based approach to detect structural damage. The proposed approach comprises two steps. The first step, system identification, involves using neural system identification networks (NSINs) to identify the undamaged and damaged states of a structural system. The partial derivatives of the outputs with respect to the inputs of the NSIN, which identifies the system in a certain undamaged or damaged state, have a negligible variation with different system errors. This loosely defined unique property enables these partial derivatives to quantitatively indicate system damage from the model parameters. The second step, structural damage detection, involves using the neural damage detection network (NDDN) to detect the location and extent of the structural damage. The input to the NDDN is taken as the aforementioned partial derivatives of NSIN, and the output of the NDDN identifies the damage level for each member in the structure. Moreover, SDOF and MDOF examples are presented to demonstrate the feasibility of using the proposed method for damage detection of linear structures. Copyright © 2001 John Wiley & Sons, Ltd.     

Parameter identification of inelastic structures under dynamic loads

The generalized model of differential hysteresis contains 13 control parameters with which it can curve‐fit practically any hysteretic trace. Three identification algorithms are developed to estimate the control parameters of hysteresis for different classes of inelastic structures. These algorithms are based upon the simplex, extended Kalman filter, and generalized reduced gradient methods. Novel techniques such as global search and internal constraints are incorporated to facilitate convergence and stability. Effectiveness of the devised algorithms is demonstrated through simulations of two inelastic systems with both pinching and degradation characteristics in their hysteretic traces. Owing to very modest computing requirements, these identification algorithms may become acceptable as a design tool for mapping the hysteretic traces of inelastic structures. Copyright © 2002 John Wiley & Sons, Ltd.     

应用CP网络进行岩性识别

为通过测井解决岩性识别问题，引入了具有分类准确、算法简练等优点的CP（Counter-Propagation)网络。在详细介绍CP网络的网络模型和算法的基础上，结合某油田的实际测井资料，进行了CP网络识别研究。应用结果表明：CP网络训练周期短、识别准确率高、不存在收敛问题。通过试验研究得出结论：CP网络完全可以用于解决岩性识别等问题，具有广阔的应用前景。     

沉积物物源定量识别的非线性规划模型——以东海陆架北部表层沉积物物源识别为例

依据“质量守衡”原理和沉积物物源难以穷尽的认识 ,提出了沉积物物源定量识别的非线性规划数学模型。利用该模型实现了东海陆架北部表层沉积物物源的定量计算 ,阐明了长江、黄河入海物质的大致分布特征。长江沉积物主要分布于 32°N以南、台湾暖流以西的海域 ,黄河沉积物主要分布于 32°N以北、台湾暖流以东的海域。长江、黄河两类沉积物的这种分布格局与本海域的流系分布相吻合。     

Parameter identification for lined tunnels in a viscoplastic medium

This paper is dedicated to the identification of constitutive parameters of elasto‐viscoplastic constitutive law from measurements performed on deep underground cavities (typically tunnels). This inverse problem is solved by the minimization of a cost functional of least‐squares type. The exact gradient is computed by the direct differentiation method and the descent is done using the Levenberg–Marquardt algorithm. The method is presented for lined or unlined structures and is applied for an elastoviscoplastic constitutive law of the Perzyna class. Several identification problems are presented in one and two dimensions for different tunnel geometries. The used measurements have been obtained by a preliminary numerical simulation and perturbed with a white noise. The identified responses match the measurements. We also discuss the usage of the sensitivity analysis of the system, provided by the direct differentiation method, for the optimization of in situ monitoring. The sensitivity distribution in space and time assess the location of the measurements points as well as the time of observation needed for reliable identification. Copyright © 2002 John Wiley & Sons, Ltd.     

ENSO循环过程对南极海冰的影响

应用 1 951- 2 0 0 2年NINO特征指数 (NINO1 +2 ,NINO3 ,NINO4 ,NINO3 .4)和 1 973-1 998年南极海冰北界范围以及 1 950- 2 0 0 1年SODA海洋温度资料。首先分析探讨了在ElNi no期间 ,堆积于赤道东太平洋的异常暖水在南半球的传播途径 ,进而研究了ENSO以及东南太平洋异常海温场与南极海冰之间的关系。结果表明 ,在ElNino期间 ,堆积于赤道东太平洋的异常暖水 ,是沿秘鲁和智利沿岸向极传播。其传播过程持续大约 1年的时间 ,但未发现沿南赤道流的西传现象。ENSO循环过程与南极海冰变化存在一定联系 ,特别是Amundsen Belling shausen海和南极半岛海冰的变化与ENSO暖事件 (ElNino)较为密切。当ElNino事件发生后 ,时滞 2年左右的时间 ,Amundsen Bellingshausen海和南极半岛的海冰将出现明显的减少现象 ,特别是南极半岛的海冰减少最为明显。ElNino事件对南极海冰的影响过程是 ,堆积于赤道东太平洋的大量异常暖水 ,沿南美 (秘鲁和智利 )沿岸近海向极地传播 ,异常暖水的这种向极传播过程将引起近极的海温场出现异常升高 ,最终导致Amundsen Bellingshausen海和南极半岛地区的海冰减少。自 2 0世纪 80年代以来 ,Amundsen Bellingshausen海和南极半岛的海冰出现明显减少的趋势 ,与这一时期的ElNino事件的频繁发生     

沃尔什变换在测井曲线分层中的应用研究

在岩性复杂的变质岩地区实施的大陆科学钻探，是通过采集井下不同深度岩石物理化学性质和物理场的各种数据，研究地壳特征及演化过程的各种科学问题。利用测井资料达到岩性剖面的重建是大陆科学钻探的重要目的之一。章利用沃尔什变换对钻孔岩性剖面进行分层，大重建的岩性剖面结果可以看出，该方法对于变质岩地区不同岩性的划分还是比较有效的。