Analysis of resistance factors for LRFD of soil nail pullout limit state using default FHWA load and resistance models     

Hui Hu 《Marine Georesources & Geotechnology》2020,38(3):332-348

Abstract

Resistance factors for load and resistance factor design (LRFD) of pullout limit state of both permanent and temporary soil nails are calibrated against a wide design space using the current Federal Highway Administration (FHWA) nail load and resistance models. The calculated resistance factors were shown to scatter broadly among design scenarios that differ in wall face batter, soil friction angle, nail ultimate bond strength, and surcharge live load. An important lesson learned from the analysis results is that the current practice of using a single resistance factor for LRFD of nail pullout limit state could not result in uniform reliabilities across different design scenarios. Simple artificial neural network (ANN) models were developed for computation of resistance factors. Design examples demonstrated the ability of the ANN models in providing resistance factors that yield satisfactory and consistent reliabilities in different nail pullout designs.  相似文献   

An Automatic Method for Detecting Transients and Variable Sources in AST3 Survey Based on Image Subtraction and Random Forest     

《Chinese Astronomy and Astrophysics》2020,44(1):41-60

AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   

联合BDS/GPS的北斗广域差分实时电离层延迟格网改正方法研究     

房成贺  陈俊平  兰孝奇  张磊 《大地测量与地球动力学》2019,39(2):169-177

研究并实现中国区域北斗广域差分实时电离层延迟格网改正算法，针对北斗单系统实时建立电离层延迟格网的不足，提出联合BDS/GPS的北斗广域差分实时电离层延迟改正方法。比较BDS、GPS以及BDS/GPS观测的实时电离层延迟格网，并利用北斗单频单点伪距定位进行精度验证。结果表明，在有效格网点覆盖充足的地区，BDS与GPS实时电离层延迟格网定位效果相当；而联合BDS/GPS观测的实时电离层延迟格网极大提高了偏远地区的单频定位精度与可定位历元数，也使原本单系统格网覆盖充足的地区定位效果得到进一步增强和稳定。  相似文献   

利用短期静态PPP结果反演海潮负荷位移     

魏国光  王琪洁  彭葳  郭良琦 《大地测量与地球动力学》2019,39(6):607-612

采用香港11个GPS测站的观测资料进行1 h、2 h、3 h和4h静态PPP解算，获得4组PPP坐标序列，利用调和分析求取11个测站处8个主要分潮的负荷位移参数（振幅和相位），将其与海潮模型计算的负荷位移参数进行对比，并比较分析PPP反演值与海潮模型值改正海潮负荷信号的效果。结果表明，垂直和水平方向上，不同PPP结果反演8个分潮的负荷位移分别具有约5 mm和7 mm的差异；PPP反演8个分潮垂向负荷位移优于全球海潮模型，但水平方向上的反演效果稍弱。  相似文献   

茅山竹矿断层气定点观测场地勘选     

戴波  吴晓峰  张敏  孟科 《大地测量与地球动力学》2019,39(11):1202-1206

拟在茅山断裂带沿线布设若干个断层气连续观测点，建组断层气观测网。以茅山竹矿地区为例，通过断层气测量的初步结果，结合地质、人工地震、跨断层短水准等多种手段联合分析研究区断层的活动性，从而确定断层气定点观测的点位，为组建断层气观测网的选点提供借鉴和参考。  相似文献   

利用InSAR资料反演宁洱Ms6.4地震震源参数及库仑应力变化     

陈晨月  冯光财  高华  杨怀宁 《大地测量与地球动力学》2019,39(3):295-301

首先利用ALOS PALSAR数据，通过D-InSAR技术获取2007-06-03云南宁洱MS6.4地震的同震形变场，然后基于Okada弹性半空间位错模型反演该地震的断层几何以及精细滑动分布，最后计算宁洱地震后周边断层的静态库仑应力变化。结果表明，形变主要集中在西盘，最大视线向形变量为51.6 cm；反演得到的震源位置为23.05°N、101.02°E，深度3 km，断层走向145°，倾向49.5°，平均滑动角153°，发震断层为NNW向普洱断裂，断层活动以右旋走滑为主，兼具逆冲分量；断层面最大滑动量为1.2 m，反演得到的震级为MW619。基于库仑应力场发现，磨黑断裂处于库仑应力增加区域，而2014年景谷地震位于负值区域。结合实地考察资料和反演结果表明，宁洱地震为浅源地震，但断层并未出露地表。  相似文献   

基于GPS和水准数据的微粒群算法联合反演祁连山北缘断裂三维滑动速率     

刘杰 《大地测量与地球动力学》2019,39(9):906-909

将微粒群算法与位错理论模型相结合，采用中国地壳运动观测网络提供的青藏高原地区2001~2004年GPS测量数据和2000~2006年水准测量数据，通过常规定权和附有相对权比的方法对祁连山北缘断裂的三维滑动速率进行联合反演，并与蚁群算法反演结果进行对比。结果表明，微粒群算法收敛速度快、稳定性高，结合经典位错理论模型，是一种可以有效求解断层三维滑动速率反演问题的优化算法，在大地测量反演领域极具应用潜力。  相似文献   

基于超像元词包特征和主动学习的高分遥感影像变化检测     

杨进一  徐伟铭  王成军  翁谦 《地球信息科学学报》2019,21(10):1594-1607

为解决高分辨率遥感影像变化检测中存在底层特征缺乏语义信息、像元级的检测结果存在“椒盐”现象以及监督分类中样本标注自动化程度较低,本文提出一种基于超像元词包特征和主动学习的变化检测方法。首先采用熵率分割算法获取叠加影像的超像元对象;其次提取两期影像像元点对间的邻近相关影像特征（相关度、斜率和截距）和顾及邻域的纹理变化强度特征（均值、方差、同质性和相异性）,经线性组合作为像元点对的底层特征;然后基于像元点对底层特征利用BOW模型构建超像元词包特征,并采用一种改进标注策略的主动学习方法从无标记样本池中优选信息量较大的样本,且自动标注样本类别;最后训练分类器模型完成变化检测。通过选用2组不同地区的GF-2影像和Worldview-Ⅱ影像作为数据源进行实验,实验结果中2组数据集的F1分数分别为0.8714、0.8554,正确率分别为0.9148、0.9022,漏检率分别为0.1681、0.1868,误检率分别为0.0852、0.0978。结果表明,该法能有效识别变化区域、提高变化检测精度。此外,传统主动学习方法与改进标注策略的主动学习方法的学习曲线对比显示,改进的标注策略可在较低精度损失下,有效提高样本标注自动化程度。  相似文献   

The Basic Shape Classification of Space Debris with Light Curves     

LU Yao  ZHAO Chang-yin 《Chinese Astronomy and Astrophysics》2021,45(2):190-208

We study the machine learning method for classifying the basic shape of space debris in both simulated and observed data experiments, where light curves are used as the input features. In the dataset for training and testing, simulated light curves are derived from four types of debris within different shapes and materials. Observed light curves are extracted from Mini-Mega TORTORA (MMT) database which is a publicly accessible source of space object photometric records. The experiments employ the deep convolutional neural network, make comparisons with other machine learning algorithms, and the results show CNN (Convolutional Neural Network) is better. In simulational experiments, both types of cylinder can be distinguished perfectly, and two other types of satellite have around 90% probability to be classified. Rockets and defunct satellites can achieve 99% success rate in binary classification, but in further sub-classes classifications, the rate becomes relatively lower.  相似文献   

A high accurate automated first-break picking method for seismic records from high-density acquisition in areas with a complex surface     

Yinpo Xu  Cheng Yin  Xuefeng Zou  Yudong Ni  Yingjie Pan  Liangjun Xu 《Geophysical Prospecting》2020,68(4):1228-1252

As the application of high-density high-efficiency acquisition technology becomes more and more wide, the areas with complex surface conditions gradually become target exploration areas, and the first-break picking work of massive low signal-to-noise ratio data is a big challenge. The traditional method spends a lot of manpower and time to interactively pick first breaks, a large amount of interactive work affects the accuracy and efficiency of picking. In order to overcome the shortcoming that traditional methods have weak anti-noise to low signal-to-noise ratio primary wave, this paper proposes a high accurate automated first-break picking method for low signal-to-noise ratio primary wave from high-density acquisition in areas with a complex surface. Firstly, this method determines first-break time window using multi-azimuth spatial interpolation technology; then it uses the improved clustering algorithm to initially pick first breaks and then perform multi-angle comprehensive quality evaluation to first breaks according to the following sequence: ‘single trace → spread → single shot → multiple shots’ to identify the abnormal first breaks; finally it determines the optimal path through the constructed evaluation function and using the ant colony algorithm to correct abnormal first breaks. Multi-azimuth time window spatial interpolation technology provides the base for accurately picking first-break time; the clustering algorithm can effectively improve the picking accuracy rate of low signal-to-noise ratio primary waves; the multi-angle comprehensive quality evaluation can accurately and effectively eliminate abnormal first breaks; the ant colony algorithm can effectively improve the correction quality of low signal-to-noise ratio abnormal first breaks. By example analysis and comparing with the commonly used Akaike Information Criterion method, the automated first-break picking theory and technology studied in this paper has high picking accuracy and the ability to stably process low signal-to-noise ratio seismic data, has a significant effect on seismic records from high-density acquisition in areas with a complex surface and can meet the requirements of accuracy and efficiency for massive data near-surface modelling and statics calculation.  相似文献