基于IGS超快星历预报卫星钟差及其精度分析

在实时GPS精密单点定位中,能否快速有效地得到高精度的卫星钟差预报值是影响实时单点定位速度和精度的一个重要因素,由于GPS原子钟的高频率、高敏感和极易受到外界及其本身因素影响的性质使得卫星钟差预报至今都没能得到很好地解决,本文在目前的卫星钟差预报基础上,分别探讨了利用灰色模型理论、线性模型和二次多项式模型等方法,以IGS超快星历中2004年12月7日卫星钟差观测资料预报8日的卫星钟差为例进行卫星钟差预报研究,初步得出如下结论:在利用IGS超快星历的前一天的卫星钟差观测值预报后一天的钟差时,线性模型相对方便有效;而灰色模型只要选取合适的模型指数系数,能得到较高精度;但二次多项式模型预报精度较差。利用线性模型能达到或优于IGS超快星历预报钟差的预报精度。     

基于集合卡尔曼变换的区域集合预报初步研究

为了深入研究集合卡尔曼变换(Ensemble Transform Kalman Filter,ETKF)初值扰动方法,提高集合预报质量,从全球大集合预报资料中提取初始扰动场,建立区域模式的ETKF初值扰动方案,对2008年7月22日发生在中国东部的一次暴雨过程进行集合预报试验,并分析ETKF方案构造的扰动场特征和集合预报效果。结果表明,由ETKF初始扰动方案产生的扰动场大小与分布合理,能够反映观测站点的空间分布,能够保持所有正交、不相关方向的误差方差。集合预报降水落区相对控制预报有所改善,集合平均小雨和中雨TS评分和BS评分总体优于控制预报。24h集合预报的Talagrand分布优于36h预报。试验结果揭示了ETKF初值扰动方案的基本性质及利用ETKF方法进行区域集合预报的可行性。     

Coupled wellbore erosion and stability analysis

This paper extends earlier work on sand erosion and presents an attempt to couple sand erosion to mechanical damage of rock around a wellbore. Porosity which evolves in time and space as surface erosion progresses, is chosen as the coupling parameter. Both rock elasticity and strength (cohesion) are assumed to depend on porosity in such a way that the material becomes weaker with increasing porosity. The mathematical model, consists of erosion equations, mixture flow equations and stress equilibrium equations, is solved numerically by Galerkin finite element method. Numerical results suggest that erosion, resulting in sand production, is high close to the free surface. Erosion is accompained by changes in porosity and a significant permeability increase. Erosion in the vicinity of the wellbore induces alterations in the mechanical behaviour of the medium. Weakening of rock stiffness leads to severe alteration of both effective stresses and pore pressure near the cavity. Since cohesion decreases with increasing porosity, one can also identify the time instant at which rock mechanical failure starts. © 1998 John Wiley & Sons, Ltd.     

基于小波变换与神经网络的石羊河流域夏季地温预测模型研究

地温变化在气候反馈效应中起着重要作用, 理解地温及其与影响因素之间的时空关系对预测全球温度变化至关重要。利用1998 - 2017年石羊河流域的逐日常规气象观测资料, 采用小波分析结合BP（Back Propagation）神经网络构建了石羊河流域夏季地温预报模型, 结果表明： 日平均地温预测效果在不同站点均为最佳, 其中预测值和观测值的相关系数均大于0.87, 3 ℃以内的预测概率均大于84%。其中, 民勤地区地温预测效果最好, 预测值和观测值的相关系数达到0.91, 3 ℃以内的预测概率达到86%。日最高地温的预测值与观测值的相关系数高于0.8, 但误差平方和、 标准差较大。永昌地区日最高地温的模拟效果最好, 3 ℃以内的预测概率达到83%。日最低地温的预测与观测值的平均相关系数高于0.66, 3 ℃以内的预报概率高于83%, 但预测值略低。其中, 武威地区日最低地温的预测效果最好, 预测值与观测值的相关系数为0.72, 3 ℃以内的预测概率达到94%。研究成果可为有效弥补干旱、 半干旱区地温观测资料缺失和探讨其与局地气候的关系提供一些参考。     

黔北正安地区五峰组—龙马溪组页岩气地质特征及有利区预测

为明确黔北正安地区上奥陶统五峰组至下志留统龙马溪组的页岩气地质特征,充分应用页岩气地质调查、重磁电、二维地震、地质调查井及测试分析等工作方法,开展黔北正安地区1:5万页岩气基础地质调查,对五峰组至龙马溪组富有机质页岩的分布、沉积环境、有机地球化学、岩石矿物、储集性能及含气性等特征进行分析研究,结果表明: 研究区五峰组—龙马溪组富有机质页岩为深水陆棚相沉积,主要分布有安场向斜、斑竹向斜和泥高向斜,厚度14.5~55 m,埋深0~3 200 m; 有机碳(TOC)含量1.0%~4.0%,有机质镜质体反射率(R_o)为1.82%~2.23%,有机质类型以Ⅰ型干酪根为主; 岩石主要由石英、长石和黏土矿物组成,脆性矿物含量高,一般大于50%; 孔隙度为2.03%~3.89%,渗透率为0.35×10^-5~1.86×10^-5μm²,表现为低孔、特低渗的特征; 最高含气量为2.88 m³/t,显示出较好的含气性特征。综合分析和评价圈出3个页岩气聚集有利区,分别为安场区块、斑竹区块和泥高区块,这为研究区页岩气进一步勘探开发指明了方向。     

基于BP神经网络的薄互层储层预测

根据地震属性来进行储层预测的研究,对于寻找油气具有十分重要的意义。而由于地下地质情况千变万化,不确定的因素太多,对这种多自变量与因变量的复杂关系模拟问题,神经网络技术是目前较成熟、实际应用效果也较好的方法之一。用BP神经网络来预测薄互层储层厚度,它可以建立属性参数与预测目标之间的高度非线性映射,并应用于具体的实例,为薄互层储层预测提供了新的思路。     

级配碎石填料大三轴试验及累积塑性应变预测模型

级配碎石作为重载铁路基床表层的主要填料,其受列车荷载的影响最大。因此,研究级配碎石在循环荷载作用下的动力行为及累积塑性应变演化特征变得尤为重要。首先,通过制备不同细粒含量的级配碎石填料,开展一系列大型动三轴试验,探究细粒含量、围压及动应力幅值对循环荷载作用下试样累积塑性应变的耦合影响机制。其次,基于塑性安定理论,确定不同应力水平下试样的动力行为,得到考虑围压及细粒含量参数的塑性蠕变状态临界动应力计算模型。最后,结合试验数据,建立考虑应力水平及细粒含量参数的塑性蠕变动力行为累积塑性应变预测模型,并明确各参数的物理意义。其研究成果可为既有重载铁路路基健康状态评估及考虑强度、变形综合控制的路基结构设计提供参考。     

基于金矿规格单元数据的机器学习方法在成矿建模分析中的应用

现代金矿勘察主要是通过综合地球化学和地质测量等数字化方法对深部矿床进行研究,所需要的人力物力成本较高。而通过分析积累的金矿规格单元数据,可以建立金矿成矿情况与相关成矿元素含量之间的非线性关系,从已有的勘查数据中寻找金矿成矿的一般规律。本文基于与金矿相关的成矿元素含量数据,分别采用逻辑斯蒂回归、随机森林和决策树方法对原始数据和重采样数据进行训练,综合运用召回率、精确率和准确率对模型进行评价。通过对比发现,在训练和测试原始数据过程中,由于每组之间数据量的巨大差距,导致成矿数据被淹没;而在训练重采样数据过程中,随机森林在召回率和准确率方面均有较好的表现,分别达到了90.63%和70.78%;并最终分析了随机森林模型中不同分类边界对于金矿成矿情况预测结果的影响。利用不同的测量指标对模型进行评价分析,使模型更适用于金矿成矿预测,可有效地提高金矿勘察的效率。     

Seismic fracture evaluation of diaphragm joints in welded beam-to-box column moment connections

Steel box columns are widely used in steel building structures in Taiwan due to their dual strong axes. To transfer the beam-end moment to the column, diaphragm plates of the same thickness and elevations as the beam flanges are usually welded inside the box column. The electro-slag welding (ESW) process is widely used to connect the diaphragms to the column flanges in Taiwan because of its convenience and efficiency. However, ESW may increase the hardness of the welds and heat-affected zones (HAZs), while reducing the Charpy-V notch strength in the HAZ. This situation can cause premature fracture of the diaphragm-to-column flange welds before a large plastic rotation is developed in the beam-to-box column joints. To quantify the critical eccentricity and the effectiveness of fracture prediction, this study uses fracture prediction models and finite element model (FEM) analysis to correlate the test results. In this study, two beam-to-box column connection subassembly tests are conducted with different loading protocols and ESW chamber shapes. To implement a fracture prediction model, the material parameters are established from circumferential notched tensile tests and FEM analysis. Test results indicate that the fracture instances can be predicted on the basis of the cumulative plastic deformation in the HAZs. Analytical results indicate that fracture instances and locations are sensitive to the relative locations of the ESW joints and beam flange. Tests also confirm that the possible fracture of the diaphragm-to-column flange joints can be mitigated by enlarging the chamber of the ESW joint.     

The tunnel seismic advance prediction method with wide illumination and a high signal-to-noise ratio

Tunnel seismic prediction is widely used in the field of tunnel seismic advance detection. The illumination of the target and the signal-to-noise ratio of the data are two key factors affecting the precision of data interpretation. Current seismic prospecting has shortcomings on sites: (1) The lighting shots are solely towards one side of the tunnel wall, (2) the geophones are placed far away from the tunnel face and (3) the surface waves from the tunnel wall dominate over the reflection waves, lowering the signal-to-noise ratio of the data at the tunnel wall. This paper proposes a tunnel symmetrical geometry to tackle the above challenges. The arrangement is to place 12 sources uniformly on each side of the tunnel wall and six geophones on the tunnel wall and face. Results of simulated data and measured data show that the proposed method enables (1) broad illumination of the target body, (2) the enhancement of illumination energy of the target body, and (3) higher data signal-to-noise ratio. The proposed symmetrical geometry method provides better interpretation in terms of broader coverage, higher quality and greater distance of investigation.