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61.
提出了 1种能够比较准确地识别剪切型体系的结构参数 (各层质量和层间刚度 )的方法———消去刚度法。该方法从剪切型结构体系的特征值问题出发 ,利用剪切型结构系统质量矩阵和刚度矩阵的特殊形式 ,通过消去各层的刚度系数 ,得到了结构系统的各层质量比表达式。在结构总质量已知的情况下 ,仅利用系统的任意两阶模态信息就可以确定出各层质量 ,并进而计算出层间刚度 ,实现了结构物理参数的递推识别。数值模拟结果表明 ,该方法识别精度较高 ,便于工程应用 ,可以用于类似结构体系的物理参数的初步估计。 相似文献
62.
给出2类双结构矩阵的标准型。作为应用,还利用新得出的标准型对这2类双结构矩阵特征值问题发展了结构算法,其中对第一类双结构矩阵特征值问题发展了只用实运算的结构算法。 相似文献
63.
J. Perbos P. Escudier F. Parisot G. Zaouche P. Vincent Y. Menard F. Manon G. Kunstmann D. Royer L. -L. Fu 《Marine Geodesy》2003,26(3):147-157
On 7 December 2001, Jason-1 was successfully launched by a Boeing Delta II rocket from the Vandenberg Air Force Base, California. The Jason-1 satellite will maintain the high accuracy altimeter service provided since 1992 by TOPEX/Poseidon (T/P), ensuring the continuity in observing and monitoring the Ocean Dynamics (intraseasonal to interannual changes, mean sea level, tides, etc.). Despite one-fourth the mass and power, the Jason-1 system has been designed to have basically the same performance as T/P, measuring sea surface topography at a centimetric level. This new CNES/NASA mission also provides near real-time data for sea state and ocean forecast. The first two months of the Jason-1 mission have been dedicated to the assessment of the overall system. The goals of this assessment phase were:
1. To assess the behavior of the spacecraft at the platform and payload levels (Jason-1 being the first program to call on the PROTEUS versatile multimission platform for Low and Medium Earth Orbit Missions developed in partnership between Alcatel Space and CNES);
2. To verify that platform performance requirements are met with respect to Jason-1 requirements;
3. To verify that payload instruments performance requirements evaluated at instrument level are met;
4. To assess the performance of the Jason-1 Ground System.
This article will display the main outputs of the assessment of the system. It will demonstrate that all the elements of the onboard and ground systems are within the specifications. Provision of data to the Jason-1 Science Working Team started at the end of March 2002. This is the goal of a six-month phase after closure of the initial assessment phase to derive the error budget of the system in terms of altimetry user products. 相似文献
1. To assess the behavior of the spacecraft at the platform and payload levels (Jason-1 being the first program to call on the PROTEUS versatile multimission platform for Low and Medium Earth Orbit Missions developed in partnership between Alcatel Space and CNES);
2. To verify that platform performance requirements are met with respect to Jason-1 requirements;
3. To verify that payload instruments performance requirements evaluated at instrument level are met;
4. To assess the performance of the Jason-1 Ground System.
This article will display the main outputs of the assessment of the system. It will demonstrate that all the elements of the onboard and ground systems are within the specifications. Provision of data to the Jason-1 Science Working Team started at the end of March 2002. This is the goal of a six-month phase after closure of the initial assessment phase to derive the error budget of the system in terms of altimetry user products. 相似文献
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科学计算可视化作为新一代的分析工具 ,正在进入物理海洋学领域。文中介绍对海洋调查数据进行可视化的关键问题——数据建模 ,并从分析海洋调查数据的特点出发提出针对海洋研究中可视化建模的原则和有效途径 ,给出相关的实现方法。其中 ,重点讨论局部体样条建模中必须面对的区域分割优化问题 ,引入遗传算法并给出较好的解决方案。 相似文献
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在对遗传算法交叉、变异后结果的处理方法进行改进并在将进化过程分段的基础上,提出1种新的混沌遗传算法。该算法利用混沌运动的遍历性择优产生初始群体,对每一轮遗传操作所得到的部分当前最优个体进行变尺度混沌搜索。仿真结果表明,该算法具有较高的优化效率,并能求得全局最优解。 相似文献
69.
Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data. 相似文献
70.