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651.
以 KNG-CZ030石墨烯(graphene nanoplatelets,GNPs)为导电填料,环氧树脂(E-54)为聚合物基体,2-乙基-4甲基咪唑(2,4-EMI)为固化剂,采用溶液混合和超声分散的方法制备导电复合材料。通过添加无机粒子(NaCl, TiO2),研究了无机粒子对石墨烯微片分散均匀性的影响以及对 GNPs /E-54复合材料导电性能的影响。实验结果表明:加入 NaCl 和 TiO2提高了石墨烯微片在基体中的分散性,降低了复合材料室温体积电阻率,即提高了导电性能;NaCl /GNPs /E-54和 TiO2/GNPs /E-54复合材料室温体积电阻率为106Ω·m 时,石墨烯质量分数分别为0.75%和0.73%,与未添加无机粒子的 GNPs /E-54复合材料质量分数0.97%相比有所降低。 相似文献
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基于UPF的航天器自主天文导航方法 总被引:6,自引:0,他引:6
利用红外地球敏感器和星敏感器直接敏感地平的天文导航方法是一种成熟、可靠的自主导航方法。这种导航方法的状态方程和量测方程都是严重非线性的,且在建立航天器轨道动力学模型时,通常将二阶带谐摄动项建模,而将其他摄动项等效为高斯白噪声,由于这些摄动项都有其精确的模型,通常不服从高斯分布。本文提出将UPF(Unscented Particle Filter)滤波方法应用于航天器自主天文导航,该方法用UKF(Unscented Kalman Filter)得到粒子滤波的重要性采样密度函数,从而克服了标准的粒子滤波没有考虑最新量测信息和UKF只能应用于噪声为高斯分布的不足。仿真结果表明,该方法可以取得比标准的粒子滤波和UKF更快的滤波收敛性和更高的滤波精度。 相似文献
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守恒光滑法CSA(Conservative Smoothing Approach)是解决传统SPH(Smoothed Particle Hydrodynamics)法稳定性问题的一种很有效的方法.研究发现在SPH法中运用所谓的守恒光滑法并不能保证系统的总物理量(质量、动量或者能量)在每个时间步均守恒,而是随着时间在理论值附近波动,对计算结果的精度有一定的影响.对此提出了守恒光滑法的修正公式,对SPH控制方程得到的各个粒子的物理量进行CSA光滑,然后运用文中提出的CSA的修正公式把对该粒子物理量的改变量加权平均给邻域内各个粒子,从而确保了SPH算法中系统的总物理量(质量、动量以及能量等)在每个时间步均守恒,而且由于减少了CSA对SPH得到的各个粒子物理量的过分光滑,从而提高了计算精度.物理意义、理论推导以及文中的算例均证明了这种修正的有效性. 相似文献
657.
K. Watanabe R.P. Lin S. Krucker R.J. Murphy G.H. Share M.J. Harris M. Gros Y. Muraki T. Sako Y. Matsubara T. Sakai S. Shibata J.F. Valds-Galicia L.X. Gonzlez A. Hurtado O. Musalem P. Miranda N. Martinic R. Ticona A. Velarde F. Kakimoto Y. Tsunesada H. Tokuno S. Ogio 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2009,44(7):789-793
Relativistic neutrons were observed by the neutron monitors at Mt. Chacaltaya and Mexico City and by the solar neutron telescopes at Chacaltaya and Mt. Sierra Negra in association with an X17.0 flare on 2005 September 7. The neutron signal continued for more than 20 min with high statistical significance. Intense emissions of γ-rays were also registered by INTEGRAL, and during the decay phase by RHESSI. We analyzed these data using the solar-flare magnetic-loop transport and interaction model of Hua et al. [Hua, X.-M., Kozlovsky, B., Lingenfelter, R.E. et al. Angular and energy-dependent neutron emission from solar flare magnetic loops, Astrophys. J. Suppl. Ser. 140, 563–579, 2002], and found that the model could successfully fit the data with intermediate values of loop magnetic convergence and pitch-angle scattering parameters. These results indicate that solar neutrons were produced at the same time as the γ-ray line emission and that ions were continuously accelerated at the emission site. 相似文献
658.
Z.K. Smith W.J. Murtagh 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2009,44(7):775-788
Predicting the occurrence of large geomagnetic storms more than an hour in advance is an important, yet difficult task. Energetic ion data show enhancements in flux that herald the approach of interplanetary shocks, usually for many hours before the shock arrival. We present a technique for predicting large geomagnetic storms (Kp 7) following the arrival of interplanetary shocks at 1 AU, using low-energy energetic ions (47–65 keV) and solar wind data measured at the L1 libration point. It is based on a study of the relationship between energetic ion enhancements (EIEs) and large geomagnetic storms by Smith et al. [Smith, Z., Murtagh, W., Smithtro, C. Relationship between solar wind low-energy energetic ion enhancements and large geomagnetic storms. J. Geophys. Res. 109, A01110, 2004. doi:10.1029/ 2003JA010044] using data in the rise and maximum of solar cycle 23 (February 1998–December 2000). An excellent correlation was found between storms with Kp 7 and the peak flux of large energetic ion enhancements that almost always (93% of time in our time period) accompany the arrival of interplanetary shocks at L1. However, as there are many more large EIEs than large geomagnetic storms, other characteristics were investigated to help determine which EIEs are likely to be followed by large storms. An additional parameter, the magnitude of the post-shock total magnetic field at the L1 Lagrangian point, is introduced here. This improves the identification of the EIEs that are likely to be followed by large storms. A forecasting technique is developed and tested on the time period of the original study (the training data set). The lead times, defined as the times from the arrival of the shock to the start of the 3-h interval of maximum Kp, are also presented. They range from minutes to more than a day; the average for large storms is 7 h. These times do not include the extra warning time given when the EI flux cross the high thresholds ahead of the shock. Because the data-stream used in the original study is no longer available, we extended the original study (1998–2000) to 2001, in order to: (a) investigate EIEs in 2001; (b) present a validation of the technique on an independent data set; (c) compare the results based on the original (P1) energy channel to those of the replacement (P1′) and (d), determine new EIE thresholds for forecasting geomagnetic storms using P1′ data. The verification of this P1′ training data set is also presented, together with lead times. 相似文献
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