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991.
如何选取非岩性地基的处理方案对于不满足抗震适应性要求的核岛厂房地基而言具有重要的工程实用价值。结合国内某内陆核电不符合抗震适应性要求的实际厂址条件,给出地基处理方案评价的数值计算模型及分析过程。首先针对该核电工程实际项目,提出嵌岩桩、CFG桩及水泥土搅拌桩三种地基预处理方案,并以规范法验证处理后地基的承载力要求;进而通过建立非岩性地基条件下的桩-土-结构动力相互作用计算模型来综合考虑各方案对核岛厂房的地震响应影响,其中通过引入黏性人工边界和能量传递边界模拟无限地基辐射阻尼效应,采用等效线性法描述近场地基非线性特征,并基于上述有限元模型以全耦合方式考虑群桩效应的影响;最后从满足厂址地基适应性和经济效益两方面进行综合评价,给出针对本工程的最佳设计方案。该分析方法及研究成果可为类似条件下的核岛厂房非岩性地基处理方案的比选问题提供借鉴与参考。 相似文献
992.
Effect of ground motion selection methods on seismic collapse fragility of RC frame buildings 总被引:1,自引:0,他引:1
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Variation in the seismic collapse fragility of reinforced concrete frame buildings predicted using different ground motion (GM) selection methods is investigated in this paper. To simulate the structural collapse, a fiber‐element modelling approach with path‐dependent cyclic nonlinear material models that account for concrete confinement and crushing, reinforcement buckling as well as low cycle fatigue is used. The adopted fiber analysis approach has been found to reliably predict the loss in vertical load carrying capacity of structural components in addition to the sidesway mode of collapse due to destabilizing P–Δ moments at large inelastic deflections. Multiple stripe analysis is performed by conducting response history analyses at various hazard levels to generate the collapse fragility curves. To select GMs at various hazard levels, two alternatives of uniform hazard spectrum (UHS), conditional mean spectrum (CMS) and generalized conditional intensity measure (GCIM) are used. Collapse analyses are repeated based on structural periods corresponding to initial un‐cracked stiffness and cracked stiffness of the frame members. A return period‐based intensity measure is then introduced and applied in estimating collapse fragility of frame buildings. In line with the results of previous research, it is shown that the choice of structural period significantly affects the collapse fragility predictions. Among the GM selection methods used in this study, GCIM and CMS methods predict similar collapse fragilities for the case study building investigated herein, and UHS provides the most conservative prediction of the collapse capacity, with approximately 40% smaller median collapse capacity compared to the CMS method. The results confirm that collapse probability prediction of buildings using UHS offers a higher level of conservatism in comparison to the other selection methods. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
993.
Near-fault ground motions containing high energy and large amplitude velocity pulses may cause severe damage to structures. The most widely used intensity measure (IM) is the elastic spectral acceleration at the fundamental period of the structure (Sa(T1)); however, Sa(T1) is not a sufficient IM with respect to the effects of the pulse-like ground motions on structural response. For near-fault ground motions, including pulse-like and non–pulse-like time histories, we propose a vector-valued IM consisting of a new IM called instantaneous power (IP(T1)) and the Sa(T1). The IP(T1) is defined as the maximum power of the bandpass-filtered velocity time series over a time interval of 0.5T1. The IP(T1) is period-dependent because the velocity time series is filtered over a period range (0.2T1-3T1). This allows the IP(T1) to represent the power of the near-fault ground motions relevant to the response of the structure. Using two-dimensional models of the 2- and 9-story steel-frame buildings, we show that the proposed [Sa(T1), IP(T1)] vector IM gives more accurate estimates of the maximum inter-story drift and collapse capacity responses from near-fault ground motions than using the vector IM consisting of the Sa(T1), the presence of the velocity pulse, and the period of the velocity pulse. Moreover, for the structures considered, for a given Sa(T1), the IP(T1) is more strongly correlated with structural damage from near-fault ground motions than the combination of the velocity pulse and pulse period. 相似文献
994.
为降低高光谱遥感数据光谱空间的冗余度,提出一种快速的波段选择方法。该方法在波段子空间下进行,依次选择各子空间中方差最大的波段作为初始波段,设定目标函数,然后逐子空间替换波段使得目标性能更加优化,直至没有替换可以使得目标更优为止。在两个公开高光谱影像数据集上对比3种常用波段选择方法(ABC、AP、ABS)来验证提出方法的有效性,实验结果表明:(1)在印第安纳数据上,本文方法与ABC、AP、ABS所选波段子集相比平均相关性分别降低22.04%、52.61%、55.71%,最佳指数分别提高0.58%、51.73%、0.95%,总体分类精度分别提高0.16%、1.39%、23.07%,在搜索效率上与同类型的ABC方法相比提高6.61%—69.02%;(2)在帕维亚大学数据上,本文方法与ABC、AP、ABS所选波段子集相比平均相关性分别降低2.38%、0.51%、32.83%,最佳指数分别提高1.34%、17.97%、12.92%,总体分类精度分别提高0.31%、0.69%、8.53%,在搜索效率上与同类型的ABC方法相比提高19.13%—86.34%。本文提出的波段选择方法能够选择合适的波段子集满足不同的应用需要,是一种有效的波段选择方法。 相似文献
995.
Many experiments of object-based image analysis have been conducted in remote sensing classification. However, they commonly used high-resolution imagery and rarely focused on suburban area. In this research, with the Landsat-8 imagery, classification of a suburban area via the object-based approach is achieved using four classifiers, including decision tree (DT), support vector machine (SVM), random trees (RT), and naive Bayes (NB). We performed feature selection at different sizes of segmentation scale and evaluated the effects of segmentation and tuning parameters within each classifier on classification accuracy. The results showed that the influence of shape on overall accuracy was greater than that of compactness, and a relatively low value of shape should be set with increasing scale size. For DT, the optimal maximum depth usually varied from 5 to 8. For SVM, the optimal gamma was less than or equal to 10?2, and its optimal C was greater than or equal to 102. For RT, the optimal active variables was less than or equal to 4, and the optimal maximum tree number was greater than or equal to 30. Furthermore, although there was no statistically significant difference between some classification results produced using different classifiers, SVM has a slightly better performance. 相似文献
996.
997.
利用高分一号影像结合机载LiDAR数据进行面向对象的亚热带森林年度采伐迹地分类提取。在面向对象的遥感软件Ecognition中,首先利用森林小班数据参与分割,利用小班数据的属性信息确定林地和非林地区域,在林地区域再一次进行多尺度分割,并通过ESP工具确定最佳分割尺度,通过特征表达提取对象的光谱、纹理、形状、冠层高度模型(CHM)等特征信息,通过最小冗余最大相关性(mRMR)特征选择算法提取最优特征子集,且CHM在最优特征子集中。利用随机森林(RF)分类器进行年度森林采伐迹地分类提取。年度采伐迹地提取精度达到了87%,与没有CHM特征参与分类的情况对比,提取精度提高了13%。 相似文献
998.
999.
1000.
Zooplankton samples were collected using 505, 160 and 77 μm mesh nets around a power plant during four seasons in 2011. We measured total length of zooplankton and divided zooplankton into seven size classes in order to explore how zooplankton community size-structure might be altered by thermal discharge from power plant. The total length of zooplankton varied from 93.7 to 40 074.7 μm. The spatial distribution of mesozooplankton(200-2 000 μm) populations were rarely affected by thermal discharge, while macro-(2 000-10 000 μm)and megalo-zooplankton(10 000 μm) had an obvious tendency to migrate away from the outfall of power plant.Thus, zooplankton community tended to become smaller and biodiversity reduced close to power plant.Moreover, we compared the zooplankton communities in three different mesh size nets. Species richness,abundance, evenness index and Shannon-Wiener diversity index of the 505 μm mesh size were significantly lower than those recorded from the 160 and 77 μm mesh size. Average zooplankton abundance was highest in the 77 μm mesh net((27 690.0±1 633.7) ind./m~3), followed by 160 μm mesh net((9 531.1±1 079.5) ind./m~3), and lowest in 505 μm mesh net((494.4±104.7) ind./m~3). The ANOSIM and SIMPER tests confirmed that these differences were mainly due to small zooplankton and early developmental stages of zooplankton. It is the first time to use the 77 μm mesh net to sample zooplankton in such an environment. The 77 μm mesh net had the overwhelming abundance of the copepod genus Oithona, as an order of magnitude greater than recorded for 160 μm mesh net and 100% loss through the 505 μm mesh net. These results indicate that the use of a small or even multiple sampling net is necessary to accurately quantify entire zooplankton community around coastal power plant. 相似文献