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《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2020,65(3):943-958
Spatial and temporal variations of Total Electron Content (TEC) can affect GNSS high accuracy positioning. Enhanced estimation of ionospheric variations and their de-correlation can benefit differential and point positioning rapid solutions. Global and regional TEC maps can provide the overall state of ionopsheric variations in space and time domains within their accuracy limits. In this paper, these maps are exploited to retrieve ionospheric variations by means of variograms and their associated covariance functions of TEC residuals over Canadian region during geomagnetically quiet and disturbed conditions. A number of theoretical variogram functions are reviewed for modeling covariance of TEC residuals. The variogram modeling of residuals during a strong geomagnetic storm revealed variances of one order of magnitude larger compared to a rather quiet condition. Variogram models are also used in regional and local kriging interpolation experiments and their performances are evaluated. Global maps of TEC RMS by International GNSS Service and two of its analysis centres are also compared over the Canadian region during a two-year period. Realistic representation of regional variances using estimated variograms when compared to global ionospheric RMS maps are also presented. 相似文献
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考虑到涡轮转子径向变形对涡轮叶尖径向间隙以及篦齿径向封严间隙的影响,提出涡轮转子径向变形多目标协同稳健性优化方法。利用基于Kriging模型的分布式协同响应面法(DCRSM)分别建立涡轮转子和涡轮篦齿的参数与径向变形间的响应面模型,并求解单目标下的稳健最优解。采用理想点法建立涡轮转子和篦齿径向变形多目标协同稳健性优化模型,并进行多目标协同稳健性优化求解。优化结果显示:提出的多目标协同稳健性优化方法与单目标稳健性优化方法相比涡轮转子和篦齿径向变形量的标准差分别降低了2.6%和4.9%。提出的方法为涡轮转子参数设定提供一定的参考。 相似文献
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为有效求解大资源黑盒子问题如叶轮机械设计优化等,提出了基于子元模型的全局优化与设计空间知识挖掘方法MBOE。该方法包括全局优化算法MBGO与数据挖掘两部分,其中MBGO算法需要极少的函数估值即可获得全局最优解;数据挖掘技术能有效分析变量间的相关关系,揭示最优设计性能提高的本质原因。利用MBOE,完成NASA Rotor37转子叶栅三维气动设计优化与知识挖掘,最优设计等熵效率相对参考设计提高1.74%。同时,利用MBGO算法所需要的计算量仅为进化算法的1/5。数据挖掘结果表明叶栅前缘及三维积叠参数对叶栅气动性能影响较大,最优设计由于上述叶型参数的改善有效减弱了叶栅进口激波损失,使得最优设计气动性能明显提高。由此,MBOE方法的正确性和有效性得到了验证。 相似文献
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将反一阶可靠性分析方法与多学科可行方法相结合,提出了一种适用于涡轮叶片复杂结构的可靠性及多学科设计优化方法.在优化过程中使用Kriging近似模型并不断提高模型精度,解决了多学科可行方法反复调用仿真程序进行多学科分析,计算量较大的问题.该方法将可靠性分析与多学科优化过程分离,提高了优化计算效率.以某型涡轮叶片的设计优化为例,对该方法进行了验证并与传统双循环方法进行了对比.结果表明,优化结果满足可靠性的要求,与双循环方法相比优化效率提高63.8%,证明了该方法在工程应用中的可行性和有效性. 相似文献
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