一种适用于有限长度混合相位未知脉冲的最小平方反褶积新方法

普通的最小平方反褶积只有在子波为最小相位脉冲和反射序列为白噪声的假设下才是成立的,而对于混合相位未知脉冲来说,这种最小平方反褶积就不再适用了。本文提出一种适合于有限长度混合相位未知脉冲的最小平方反褶积方法。运用此法只需预先估计一个混合相位子波的长度。合成数据的试验结果表明,该方法有较好的效果,且对预先估计出的子波长度不敏感。文中还证明混合相位未知脉冲最小平方反褶积等效于一种有间隙的平滑误差滤波器的作用,而这种有间隙的平滑误差滤波又可分解为一个前向多步预测误差滤波与一个后向多步预测误差滤波之和。可以预计这种新的反滤积方法将在地震数据处理中得到有效的应用。     

TBM地区低孔渗高产气储层预测

 本文从TBM地区目的层的地质和地球物理特征分析出发，以三维地震资料为基础，综合利用人工和神经网络波形分类等定性储层预测方法和利用反演及敏感地震属性分析，对TBM地区低孔渗砂岩分布区开展了砂体展布特征分析和天然气高产区预测研究。根据研究结果部署了10口钻井，已完钻的4口井中有3口获得高产气流（其中DK27井日产天然气36.8×10⁴m³）。值得指出的是，目前所用的预测方法还不能预测厚度小于6m的单砂层或砂层组构成的储层。     

上海市用电负荷管理系统主站异地冗灾备份方案研究

对上海市用电负荷管理系统主站灾备系统的建设进行可行性研究,根据系统现有结构,结合主流技术提出建议性的方案.重点对各种设备技术进行分析,包括涉及计算机、网络、软件等各方面的设备技术,提出建设原则及实施建议.     

1960年以来渭河下游河道的自动调整作用

1960年以来，渭河下游河道来水来沙条件和边界条件都发生了较大的变化，河道纵横剖面形态针对这些变化进行了相应的调整，通过分析河相关系、主槽面积、河底高程以及弯曲系数的调整规律，对渭河下游河道的自动调整作用进行了研究。     

垫层载荷试验应注意的几个问题

介绍了垫层上载荷试验的类型，通过工程实例对不同类型垫层上的载荷试验应注意的问题进行了分析和探讨，这对通过载荷试验确定双层地基承载力具有一定的实际意义，可供同类工程参考借鉴。     

Performance analysis of IEEE 802.11 ad hoc networks in the presence of exposed terminals

The paper evaluates the performance effects of exposed terminals in IEEE 802.11 ad hoc networks in finite load conditions. It derives analytical models for the estimation of channel utilization and media access delay for IEEE 802.11 ad hoc networks in finite load conditions with and without exposed terminals. The simulation results show that the analytical estimated channel utilization and media access delay metrics are fairly accurate.     

裂缝性潜山储层地震描述技术

裂缝是潜山油气藏的重要储集层 ,潜山的油气产出与裂缝的发育情况密切相关 ,因此 ,对裂缝发育控制因素和裂缝发育规律进行了分析和探讨。尽管单条裂缝在地震资料上难以识别 ,但是裂缝带在地震资料上有其特征。描述了裂缝储层的地球物理特征 ,并利用测井约束反演技术、吸收系数技术、地震相分类和相干分析技术对潜山储层进行预测。通过在车古 2 0 1潜山的应用实例分析 ,说明以上 4种储层描述技术比较有效     

On-line emission and economic load dispatch using adaptive Hopfield neural network

This paper presents an adaptive Hopfield neural network (AHNN) based methodology, where the slope of the activation function is adjusted, for finding approximate Pareto solutions for the multi-objective optimization problem of emission and economic load dispatch (EELD). We have placed emphasis on finding solutions quickly, rather than the global Pareto solutions, so that our algorithm can be employed in large on-line power systems where variations in load are quite frequent. To enable faster convergence, adaptive learning rates have been developed by using energy function and applied to the slope adjustment method. The proposed algorithm has been tested on selected IEEE bus benchmark systems. The convergence of AHNN is found to be nearly 50% faster than the non-adaptive version.     

Superconductivity and Structure

The degree of the isolation of the CuO₂ planes (e.g. distance or bond valence to the apical coordination) has been shown by quantitative algorithms to be the major factor in determining aspects of the doping curves. They include the magnitude of the optimal number of doped holes (h_op) and the corresponding T _cop. It is shown that the roots of these phenomenological laws lie in a related structural dependence of super-exchange. The latter is expressed in the pseudo-gap or Neel temperature of the undoped parent compound. A fruitful language can be developed which deals with a buildup of complex quantum chemical features by bringing two holes into vicinity of a super-exchange O, forming a “local” Cu₂O₇ pair. Structural considerations also dictate that stress is relieved by alternate orthogonal pair orientation. This leads to plaid patterns with primary and secondary channels of charge. The presence of these two types of charge channels is involved in the mechanism of superconducting charge transport. Similar structuring of doped charge into plaid patterns of “local” pairs has been proposed for “all” high T _c superconductivity. STM now gives pictorial representation of the remnants of such an electronic crystal structure. The response of these bond-ordering motifs to structural details is further discussed. These ideas supply organization to the manifold experimental situation and provide opportunities for a unifying theory for high T _c superconductivity in terms of real space structuring of “local” pairs, largely on crystal-chemical principles.     

Modelling of fatigue damage progression and life of CFRP laminates

A progressive fatigue damage model has been developed for predicting damage accumulation and life of carbon fibre‐reinforced plastics (CFRP) laminates with arbitrary geometry and stacking sequence subjected to constant amplitude cyclic loading. The model comprises the components of stress analysis, fatigue failure analysis and fatigue material property degradation. Stress analysis of the composite laminate was performed by creating a three‐dimensional finite element model in the ANSYS FE code. Fatigue failure analysis was performed by using a set of Hashin‐type failure criteria and the Ye‐delamination criterion. Two types of material property degradations on the basis of element stiffness and strength were applied: a sudden degradation because of sudden failure detected by the fatigue failure criteria and a gradual degradation because of the nature of cyclic loading, which is driven by the increased number of cycles. The gradual degradation of the composite material was modelled by using functions relating the residual stiffness and residual strength of the laminate to the number of cycles. All model components have been programmed in the ANSYS FE code in order to create a user‐friendly macro‐routine. The model has been applied in two different quasi‐isotropic CFRP laminates subjected to tension–compression (T–C) fatigue and the predictions of fatigue life and damage accumulation as a function of the number of cycles were compared with experimental data available in the literature. A very good agreement was obtained.