深渊着陆器坐底位置的精确测量和反演计算

深渊着陆器在下潜过程中,由于受到海流的影响,其坐底位置会偏离投放点,偏离量和偏离方向很难估计,而声学水下定位方法在深渊海区不太适用.通过在海面进行气枪十字放炮作业,利用炮点准确位置和时间信息,以及海底地震仪(Ocean Bottom Seismometer,OBS)记录的直达水波到时,对深渊着陆器的坐底位置进行精确测量可以提供有效定位数据.该方法对采集得到的数据进行预处理,使用蒙托卡洛方法结合最小二乘法,对万泉号着陆器实际坐底位置进行了反演校正,得到三个潜次的位置校正偏移量分别为211m、178m、861m,偏移方向各不相同,校正精度为±20m,比以往的定位精度大为提高.此外,该方法测量确定了三个海底标志物的精确位置,为未来万米无人或载人潜器提供了可靠的水下参考坐标.     

Estimation of the 3D correlation structure of an alluvial aquifer from surface-based multi-frequency ground-penetrating radar reflection data

Knowledge about the stochastic nature of heterogeneity in subsurface hydraulic properties is critical for aquifer characterization and the corresponding prediction of groundwater flow and contaminant transport. Whereas the vertical correlation structure of the heterogeneity is often well constrained by borehole information, the lateral correlation structure is generally unknown because the spacing between boreholes is too large to allow for its meaningful inference. There is, however, evidence to suggest that information on the lateral correlation structure may be extracted from the correlation statistics of the subsurface reflectivity structure imaged by surface-based ground-penetrating radar measurements. To date, case studies involving this approach have been limited to 2D profiles acquired at a single antenna centre frequency in areas with limited complementary information. As a result, the practical reliability of this methodology has been difficult to assess. Here, we extend previous work to 3D and consider reflection ground-penetrating radar data acquired using two antenna centre frequencies at the extensively explored and well-constrained Boise Hydrogeophysical Research Site. We find that the results obtained using the two ground-penetrating radar frequencies are consistent with each other, as well as with information from a number of other studies at the Boise Hydrogeophysical Research Site. In addition, contrary to previous 2D work, our results indicate that the surface-based reflection ground-penetrating radar data are not only sensitive to the aspect ratio of the underlying heterogeneity, but also, albeit to a lesser extent, to the so-called Hurst number, which is a key parameter characterizing the local variability of the fine-scale structure.     

基于Ruger近似式预测裂缝型储层的可行性研究

叠前纵波方位各向异性检测裂缝是目前应用最为广泛的方法，该方法主要是利用AVAZ地震资料椭圆拟合的长轴与短轴信息来评价裂缝，该方法在具体应用时，认为裂缝型储层AVAZ响应特征的变化仅由各向异性参数决定，而没有考虑非各向异性参数的影响，从而引起裂缝评价的多解性。为提高该技术的裂缝评价精度，从模型分析入手，将模型中各向异性参数及岩性参数设置为概率密度分布函数，然后采用Monte Carlo随机方法进行叠前AVAZ正演模拟。首先，对各向异性参数对椭圆拟合的影响进行简单分析，得出各向异性参数γ对椭圆扁率B/A与各向异性因子B影响最大、δ次之、ε最小。然后，进一步重点分析不同标准差的速度与密度模型的B/A与B响应特征，得出地层的速度与密度的变化在较小范围内时，该技术评价裂缝才具有一定的可行性，其中，地层纵波和横波速度的变化（尤其是纵波速度）对叠前AVAZ响应影响较大，地层密度几乎没有影响，故当横向岩性变化较大时，该方法在评价裂缝型储层时的结果具有一定的不确定性。      

Sampling efficiency in Monte Carlo based uncertainty propagation strategies: Application in seawater intrusion simulations

The implementation of Monte Carlo simulations (MCSs) for the propagation of uncertainty in real-world seawater intrusion (SWI) numerical models often becomes computationally prohibitive due to the large number of deterministic solves needed to achieve an acceptable level of accuracy. Previous studies have mostly relied on parallelization and grid computing to decrease the computational time of MCSs. However, another approach which has received less attention in the literature is to decrease the number of deterministic simulations by using more efficient sampling strategies. Sampling efficiency is a measure of the optimality of a sampling strategy. A more efficient sampling strategy requires fewer simulations and less computational time to reach a certain level of accuracy. The efficiency of a sampling strategy is highly related to its space-filling characteristics.This paper illustrates that the use of optimized Latin hypercube sampling (OLHS) strategies instead of the widely employed simple random sampling (SRS) and Latin hypercube sampling (LHS) strategies, can significantly improve sampling efficiency and hence decrease the simulation time of MCSs. Nine OLHS strategies are evaluated including: improved Latin hypercube sampling (IHS); optimum Latin hypercube (OLH) sampling; genetic optimum Latin hypercube (GOLH) sampling; three sampling strategies based on the enhanced stochastic evolutionary (ESE) algorithm namely φ_p-ESE which employs the φ_p space-filling criterion, CLD-ESE which utilizes the centered L₂-discrepancy (CLD) space-filling criterion, and SLD-ESE which uses the star L₂-discrepancy (SLD) space-filling criterion; and three sampling strategies based on the simulated annealing (SA) algorithm namely φ_p-SA which employs the φ_p criterion, CLD-SA which uses the CLD criterion, and SLD-SA which utilizes the SLD criterion. The study applies SRS, LHS and the nine OLHS strategies to MCSs of two synthetic test cases of SWI. The two test cases are the Henry problem and a two-dimensional radial representation of SWI in a circular island. The comparison demonstrates that the CLD-ESE strategy is the most efficient among the evaluated strategies. This paper also demonstrates how the space-filling characteristics of different OLHS designs change with variations in the input arguments of their optimization algorithms.     

Importance sampling based algorithm for efficient reliability analysis of axially loaded piles

In reliability analysis, the crude Monte Carlo method is known to be computationally demanding. To improve computational efficiency, this paper presents an importance sampling based algorithm that can be applied to conduct efficient reliability evaluation for axially loaded piles. The spatial variability of soil properties along the pile length is considered by random field modeling, in which a mean, a variance, and a correlation length are used to statistically characterize a random field. The local averaging subdivision technique is employed to generate random fields. In each realization, the random fields are used as inputs to the well-established load transfer method to evaluate the load–displacement behavior of an axially loaded pile. Failure is defined as the event where the vertical movement at the pile top exceeds the allowable displacement. By sampling more heavily from the region of interest and then scaling the indicator function back by a ratio of probability densities, a faster rate of convergence can be achieved in the proposed importance sampling algorithm while maintaining the same accuracy as in the crude Monte Carlo method. Two examples are given to demonstrate the accuracy and the efficiency of the proposed method. It is shown that the estimate based on the proposed importance sampling method is unbiased. Furthermore, the size of samples can be greatly reduced in the developed method.     

金融领域的随机建模与基于软件R的Monte Carlo模拟(4):随机微分方程模型

主要研究线性随机微分方程模型,为此定义Itô随机微积分,建立Itô公式.鉴于研究的重点是利用R软件进行数值模拟,所以详细讨论了过去10多年来随机微分方程数值解的研究.     

Dispersal of arbuscular mycorrhizal fungi and dark septate endophytes by Ctenomys cf. knighti (Rodentia) in the northern Monte Desert of Argentina

In arid and semi-arid environments, root-associated fungi may play a key role in plant communities (e.g., seedling establishment, nutrient acquisition, plant survival and heat tolerance). Several studies have shown the importance of small mammals as consumers and dispersal agents of mycorrhizal fungi spores in tropical and temperate ecosystems. However, little is known about the dispersal of infective propagules of endophytic fungi in arid and semi-arid ecosystems. This study analyzed the potential role of the subterranean rodent Ctenomys cf. knighti as a dispersal agent of root-associated fungi. In order to demonstrate this role, we analyzed: (1) the incidence of colonization of arbuscular mycorrhizae and dark septate endophytes on representative plant species of the Monte Desert; (2) the presence of fungal structures of arbuscular mycorrhizae and dark septate endophytes in C. cf. knighti fecal samples; and (3) the infectivity of the fungal propagules contained in the scat and their growth effects on nine native plant species. Data strongly suggest that this South American subterranean rodent may play a key role as a dispersal agent of arbuscular mycorrhizae and dark septate endophytes fungi in the arid environment of the northern Monte Desert of Argentina.     

Probabilistic rainfall thresholds for flood forecasting: evaluating different methodologies for modelling rainfall spatial correlation (or dependence)

Rainfall threshold (RT) method is one of the evolving flood forecasting approaches. When the cumulative rainfall depth for a given initial soil moisture condition intersects the threshold rainfall curve, the peak discharge is expected to be equal or greater than the threshold discharge for flooding at the target site. Besides the total rainfall depth, spatial and temporal distribution of rainfall impacts the flood peak discharge and the time to peak. To revisit a previous study conducted by the authors, in which spatially independent rainfall pattern was assumed, the spatial distribution of rainfall was simulated following a Monte Carlo approach. The structure of the spatial dependence among sub‐watersheds' rainfalls was taken into account under three different scenarios, namely independent, bivariate copula (2copula) and multivariate Gaussian copula (MGC). For each set of generated random dimensionless rainfalls, the probabilistic RT curves were derived for dry moisture condition. Results were evaluated with both historical and simulated events. For the simulated events, threshold curves were assessed by means of categorical statistics, such as hit rate, false rate and critical success index (CSI). Results revealed that the best performance based on the CSI criterion corresponded to 50% curve in 2copula and MGC scenarios as well as 90% curve in the independent scenario. The recognition of 50% curve in 2copula and MGC scenarios is in agreement with our expectations that the mean probable curve should have the best performance. Moreover, the proposed inclusion of spatially dependent rainfall scenario improved the performance of RT curves by about 25% in comparison with the presumed spatially uniform rainfall scenario. Copyright © 2011 John Wiley & Sons, Ltd.     

地震分布非均匀性指标Kcv值及其在亚洲大地震预测中的应用研究

理论研究和实际预测表明地震空间分布非均匀性指标Cv值是一种有效的预测指标.但目前使用的Cv值在同一信度水平下,其置信区间大小与空间分布的事件样本数大小有关,不便于结果的分析比较.本文在Cv值基础上定义了一个新的预测指标Kcv,并基于强震时空概率增益预测模型及其单项预测方法预测效能检验的方法,依据亚洲地震重点研究区近20...     

混合单元模型在道路工程土方量计算中的运用

通过综合规则格网和不规则三角网的特点,构建了混合单元模型运用于道路勘察设计的土方量计算中,采用蒙特卡罗积分方法进行体积计算.通过工程实例对比,验证了此方法可行性,为土方量计算提供新模式.