Analysis of small-scale heterogeneity in clastic rocks by using computerized X-ray tomography (CT)

The aim of this study is to recognize the basic clastic rock types on the basis of Hounsfield Units (HUs) by using statistical methods (hypothesis tests, distribution fitting, and confidence intervals). How does this recognition depend on depositional history of samples tested? Does the numerical pattern of HUs obtained from small-scale analyzing of some particular sedimentary structures coincide to the textural expectations of those sedimentary structures? Are the HU values provided by the CT measurements capable of evidencing micro-cycles belonging to a particular depositional history?For testing the numerical recognition, we analyze macroscopically homogeneous argillaceous marl, siltstone and fine sandstone samples with similar depositional background, age, and degree of diagenesis. The preliminary research shows that the Hounsfield Units can identify different sedimentary rocks considerably well. There are significant differences among the confidence intervals belonging to the different rock types. However, there also have been some slight overlaps among them.For analyzing the effects of the depositional processes in case of a particular rock type, samples from channel sandstone, distributary mouth-bar, massive (structureless) sandstone from a delta-fed turbidity fan, and channel sandstone with traction carpet origin from a delta-fed turbidity fan (all coming from Pannonian basin filling series) are used. The results prove again the significant differences in the terms of both confidence intervals and distribution-types; however, some overlapping also occurs.     

罗斯海海域大地水准面异常的成因研究

本文利用数值法求解瞬时地幔对流问题以模拟大地水准面异常.利用两个较新的S波速度异常层析模型SEMUCB_WM1和TX2019slab,将其转换为密度异常作为控制方程的浮力驱动项;采取的黏度结构模型中,上下地幔的黏度比为1∶50.为了研究地幔不同结构对罗斯海海域大地水准面异常的影响,分别提取上、下地幔的密度异常正/负值,作为对流控制方程的输入项,计算相应的模拟大地水准面异常.将模拟大地水准面异常与观测值进行对比,发现罗斯海海域的大地水准面异常主要来自下地幔及上地幔的负密度(波速)异常,下地幔正密度异常对该区域大地水准面负异常也有一定的贡献.本文认为,地幔密度负异常在罗斯海海域大地水准面异常的形成中占据主导作用,地幔对流的动力学效应对该区域大地水准面异常的形成影响较弱.     

基于LBS和深度学习的旅游景区客流量的高时频预测

为实现精准的旅游景区客流量的高时频预测,本研究构建了一套基于LBS和深度学习模型的预测方法。此方法可通过对LBS数据的转换实现预测的空间范围与时频控制,并通过方法的核心模型——基于双向循环神经网络和GRU算法构建的深度双向GRU(DBi-GRU)模型完成预测。为检验方法的有效性,研究以深圳大梅沙海滨公园为例对方法进行实验测试。实验使用拟合曲线、误差指标及DM检验3种方法评估DBi-GRU模型的预测效果。此外,实验还设置了其他五种深度学习模型作为DBi-GRU的对照模型,测试基于不同深度学习算法的模型之间的预测水平差异。实验结果表明:(1)本研究提出的DBi-GRU模型在景区客流量高时频预测中具有理想的预测效果,在高峰时段的客流量预测方面也具有较高准确性,预测效果明显优于其他深度学习模型;(2)基于双向循环网络的模型的效果普遍优于基于常规循环网络的模型。尤其是基于双向LSTM算法的模型,虽然预测的准确度略逊色于DBi-GRU模型,但在模型性能上与其的差异并不显著;(3)在相同网络参数下,GRU算法较前人采用的LSTM和RNN算法有着更高的预测准确性。本研究为客流量预测领域的研究提供了一种...     

1901~2013年GPCC和CRU降水资料在中国大陆的适用性评估

利用1901~2013年中国大陆地区的气象台站实测降水资料,对东英吉利（East Anglia）大学气候研究中心（Climatic Research Unit,CRU）和全球降水气候中心（Global Precipitation Climatology Centre,GPCC）的降水资料分别从季节、年际和年代际尺度上进行了评估。结果表明：1961~2013年CRU与GPCC降水资料均能较准确地描述中国大陆地区的降水特征,且在东部较西部地区、夏季较冬季与站点实测降水情况更为一致。将中国大陆划分为不同区域并在其季节、年际和年代际时间尺度上通过比较降水偏差绝对值的百分比、均方根误差和相关系数等统计量后发现：CRU在青藏高原和其它较大的山脉附近与站点实测降水的差别较大,且年均降水趋势在西北一带的阿尔金山脉、黄土高原、东南地区和长江下游地区,比实测降水的年均趋势小、甚至出现趋势相反的情况。此外,CRU降水的年代际变化趋势也偏小。而GPCC数据不论是降水量还是降水趋势都更接近实际情况。在1901~1961年,通过与65个长期气象观测站点的降水时间序列比较发现,CRU在110°E以西地区与站点观测的降水资料间的差别较大,而GPCC与站点观测资料的吻合较好。最后,利用1961~2013年两套降水资料和站点实测资料分别计算了标准化降水指数（SPI）,简单分析了中国大陆地区的干旱变化,发现GPCC对旱涝的时空变化特征的描述比CRU更接近站点实际观测;并且CRU也没有反映出1997年夏季中国地区出现的严重干旱情况,而GPCC较为准确地反映出了这一干旱事件特征。因此,本文的研究结果认为,就中国大陆地区长时期降水资料而言,GPCC的适用性优于CRU。     

Flow time estimation with spatially variable hillslope velocity in ungauged basins

The automated spatial estimation of the hillslope runoff dynamics is used as a valuable tool for the estimation of the travel time distribution (flow time), a major factor for the hydrologic prediction in ungauged basins. In fact, while the flow time function is usually obtained by rescaling the flow paths with constant channel and hillslope velocities, in this work a spatially distributed kinematic component, as a function of terrain features and in particular slope and land use, is implemented and its influence on the hydrologic response is tested by means of the Width Function Instantaneous Unit Hydrograph (WFIUH) framework. Hillslope surface flow velocities are evaluated by applying different uniform flow formulas within an automated DEM-based (terrain analysis) algorithm. A comparison test of the performances of the Manning, Darcy, Maidment and Soil Conservation Service uniform flow equations is performed for several case studies in Italy pertaining to different climatic and geomorphic conditions. Results provide new insights for a better understanding of the flow time function also introducing a more parsimonious and physically-based calibration scheme of the WFIUH.     

Spatio-temporal evaluation of global gridded precipitation datasets across Iran

ABSTRACT

In this work, the accuracy of four gridded precipitation datasets – Climatic Research Unit (CRU), Global Precipitation Climatology Centre (GPCC), PERSIANN-Climate Data Record (PCDR) and University of Delaware (UDEL) – is evaluated across Iran to find an alternative source of precipitation data. Monthly, seasonal and annual precipitation data from 85 synoptic stations for the period 1984–2013 were used as the basis for the evaluations. Our results indicate that all datasets underestimate and overestimate precipitation in stations with annual precipitation greater than 600 and less than 100 mm, respectively. However, all datasets correctly recognize regimes of precipitation, but with a bias in amount of precipitation. Our spatio-temporal assessments show that GPCC is the most suitable dataset to be used over Iran. Both UDEL and CRU can be considered as the second and third most suitable datasets, while PCDR showed the weakest performance among the studied datasets.     

Probability of scour depth exceedance owing to hydrologic uncertainty

The average risk of a bridge over water in the USA collapsing from scour during its 75 years design life is estimated at 3.7×10^?3. This risk makes scour of foundations the number one cause of bridge collapse and 3 times larger than the next cause of bridge collapse, which is collisions. The current paper presents a site specific method to estimate the probability that a certain scour depth will be exceeded during the life of a bridge. The methodology is limited to some uncertainties associated with the randomness of hydrologic conditions. It does not include uncertainties associated with other input parameters, such as geometry and soil erodibility or uncertainties associated with the scour prediction model. The SRICOS–EFA method is used as the reference method to predict the scour depth. This method requires three inputs: the hydraulic parameters (e.g. velocity hydrograph), the geometry parameters (e.g. pier size) and the soil erodibility parameters (e.g. erosion function). The input is used together with the program to generate the scour depth versus time over the period of interest. The final scour depth is that reached at the end of the specified period. This paper proposes a probabilistic framework to present the final scour depth as a cumulative density function. The cumulative density function of the flow is sampled randomly to give a future hydrograph, which has the same mean and standard deviation as the original hydrograph. For this synthetic hydrograph a final scour depth is obtained by using SRICOS–EFA. Thousands of equally likely hydrographs are generated and the corresponding final scour depths are organized in a distribution. That final scour depth distribution gives the probability that a chosen scour depth will be exceeded.     

孕震系统宏观层次的单元体应力水平群体涨落模型

孕震系统是一个开放的复杂巨统统，系统具有层次结构。因此应分层次建立孕震系统的力学模型。作者从地球整体现出发，提出了单元体应力水平群体涨落模型，该模型为孕震系统宏观层次上的力学模型。这一模型可以作为几个地震带或几个地块内，地震活动频度、相关转移、时空分布及各类定点观测手段异常台项数群体涨落、时空转移、震后异常等研究的物理基础。     

地震叠前时间偏移的一种图形处理器提速实现方法

新近发展的图形处理器（GPU,Graphic Processing Unit）通用计算技术,现已日趋实用成型,并获得诸多应用领域的广泛关注.对油气勘探专项资料处理技术的运用而言,概因GPU与中央处理器（CPU）的计算性能的甚大差异,致使GPU这一通用计算技术在石油工业中的应用研究正在有效开展.本文仅借助于油气勘探中广泛使用的叠前时间偏移,旨在于扼要阐明其基于GPU应用的有效性;文中还提出一种利用GPU实现地震叠前时间偏移的软件构件方法,并针对非对称走时叠前时间偏移所拓展的应用软件提供一种具体实现架构.与以往用个人计算机（PC,Personal Computer）或者PC集群所用的叠前时间偏移相比,本文方法可甚大地提高计算效率,从而在石油物探资料处理中可显著地节约计算成本和维护费用.文中实际例证也表明,基于GPU进行高性能并行计算,当是适应目前石油工业中大规模计算需求的一个重要发展途径.     

Analysis of earthquake ground motions using an improved Hilbert–Huang transform

Some limitations of the Hilbert–Huang transform (HHT) for nonlinear and nonstationary signal processing are remarked. As an enhancement to the HHT, a time varying vector autoregressive moving average (VARMA) model based method is proposed to calculate the instantaneous frequencies of the intrinsic mode functions (IMFs) obtained from the empirical mode decomposition (EMD) of a signal. By representing the IMFs as time varying VARMA model and using the Kalman filter to estimate the time varying model parameters, the instantaneous frequencies are calculated according to the time varying parameters, then the instantaneous frequencies and the envelopes derived from the cubic spline interpolation of the maxima of IMFs are used to yield the Hilbert spectrum. The analysis of the length of day dataset and the ground motion record El Centro (1940, N–S) shows that the proposed method offers advantages in frequency resolution, and produces more physically meaningful and readable Hilbert spectrum than the original HHT method, short-time Fourier transform (STFT) and wavelet transform (WT). The analysis of the seismic response of a building during the 1994 Northridge earthquake shows that the proposed method is a powerful tool for structural damage detection, which is expected as the promising area for future research.