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随着频率使用率的提高, 射电天文台址地面或空间存在强电磁干扰致使望远镜接收机系统处于非线性状态. 为减少强电磁干扰的影响、提高天文观测效率, 提出了一种基于望远镜远场区域的强干扰源规避方法. 首先, 通过仿真分析确定的射电望远镜远场方向图, 结合望远镜与干扰源之间的位置关系, 分析了强电磁干扰到达射电望远镜焦点处的功率响应, 并依据接收机第2阶中频放大器性能参数, 确定射电望远镜处于非饱和状态的规避角度计算方法. 其次, 采用该方法计算分析了民航飞机对射电望远镜的影响, 若民航飞机上有主动发射的干扰源, 且不经过反射等传播现象, 当射电望远镜主波束轴偏开一定方向后, 可有效降低对射电望远镜的干扰强度. 相似文献
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针对悬臂柱顶有拉梁和无拉梁层间隔震体系的抗震性能问题,运用增量动力分析(IDA)方法进行弹塑性分析,模拟结构从弹性到弹塑性直至最后倒塌的全过程。通过调幅地震动得到相应的层间位移角及峰值加速度,分别绘制单条与多条IDA曲线分析拉梁对隔震结构动力响应的影响,研究两种结构的抗震性能。结果表明:在相同性能点,有拉梁和无拉梁对纤维铰弯矩值和曲率值基本无影响,而在不同性能点,纤维铰状态明显不同;两种体系从正常使用阶段到防止倒塌阶段所需的加速度峰值的差距慢慢增大;在极罕遇地震下,柱顶有拉梁层间隔震体系的下部结构抗震性能要高于柱顶无拉梁层间隔震体系。 相似文献
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为了研究盆地基岩倾角对盆地地表动力反应的影响,选取了一个跨度2 km,深度500 m的二维成层盆地为研究对象进行有限元动力反应分析。以持时0.25 s的狄拉克脉冲作为输入地震动,探讨了P波和SV波垂直入射时,盆地基岩倾角从10°\,20°\,30°\,40°依次增加的情况下盆地地震反应。结果表明:入射波在倾斜基岩处发生波型转化,同时产生面波,在盆地中心区域发生汇聚;随着基岩倾角的增加地表中心处的卓越频率有减小的趋势。 相似文献
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To monitor chalk cliff face along the Normandy coast (NW France) which is prone to erosion, we tested the potential of cliff face 3D reconstruction using pairs of images with high angle of incidence at different dates from the agile Pléiades satellites. The verticality aspect of the cliff face brings difficulties in the 3D reconstruction process. Furthermore, the studied area is challenging mainly because the cliff face is north-oriented (shadow). Pléiades images were acquired over several days (multi-date stereoscopic method) with requested incidence angles until 40°. 3D reconstructions of the cliff face were compared using two software: ASP® and ERDAS IMAGINE®. Our results are twofold. Firstly, despite ASP® provides denser point clouds than ERDAS IMAGINE® (an average of 1.60 points/m² from 40° incidence angle stereoscopic pairs on the whole cliff face of Varengeville-sur-Mer against 0.77 points/m² respectively), ERDAS IMAGINE® provides more reliable point clouds than ASP® (precision assessment on the Varengeville-sur-Mer cliff face of 0.31 m ± 2.53 and 0.39 m ± 4.24 respectively), with a better spatial distribution over the cliff face and a better representation of the cliff face shape. Secondly, the quality of 3D reconstructions depends mostly on the amount of noise from raw images and on the shadow intensity on the cliff face (radiometric quality of images). 相似文献
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Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents. 相似文献
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On 25th January 2019, the tailings dam of the Brumadinho iron mine operated by Vale S/A failed catastrophically. The death toll stood at 259 and 11 people remained missing as of January 2020. This tragedy occurred three years after Mariana’s tailings dam rupture – the most significant tailing dam disaster in Brazilian history. Thus far, a systematic investigation on the cause and effect of the failure has yet to be conducted. Here, we use satellite-driven soil moisture index, multispectral high-resolution imagery and Interferometric Synthetic Aperture Radar (InSAR) products to assess pre-disaster scenarios and the direct causes of the tailings dam collapse. A decreasing trend in the moisture content at the surface and the full evanescence of pond water through time (2011–2019) suggest that the water was gradually penetrating the fill downwards and caused the seepage erosion, saturating the tailings dam. Large-scale slumping of the dam (extensional failure) upon the rupture indicates that the materials of the fill were already saturated. InSAR measurements reveal a dramatic, up to 30 cm subsidence in the dam (at the rear part) within the past 12 months before the dam collapse, signifying that the sediments had been removed from the fill. Although the information on the resistance level of the tailings dam to infiltrations is not available, these pieces of evidence collectively indicate that the seepage erosion (piping) is the primary cause for the chronic weakening of the structure and, hence, the internal “liquefaction” condition. Upon the collapse, the fully saturated mud tailings flowed down the gentle slope area (3.13 × 106 m2), where 73 % were originally covered by tree, grass or agricultural tracts. The toxic mud eventually reached the Paraopeba River after travelling 10 km, abruptly increasing the suspended particulate matter (SPM) concentration and the toxic chemical elements in the river, immediately affecting the local livelihoods that depend on its water. The Paraopeba River is a major tributary of the San Francisco River, the second-longest river in Brazil reaching the Atlantic Ocean. We anticipate that the environmental repercussions of this toxic seepage will be felt throughout the entire basin, especially riverine communities located downstream. 相似文献
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广西土壤有机质空间变异特征及其影响因素研究 总被引:2,自引:0,他引:2
基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明:广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。 相似文献