Geophysical flows under location uncertainty,Part II Quasi-geostrophy and efficient ensemble spreading

Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly modified to include an advection correction, inhomogeneous and anisotropic diffusion terms and a multiplicative noise contribution. In this paper, simplified geophysical dynamics are derived from a Boussinesq model under location uncertainty. Invoking usual scaling approximations and a moderate influence of the subgrid terms, stochastic formulations are obtained for the stratified Quasi-Geostrophy and the Surface Quasi-Geostrophy models. Based on numerical simulations, benefits of the proposed stochastic formalism are demonstrated. A single realization of models under location uncertainty can restore small-scale structures. An ensemble of realizations further helps to assess model error prediction and outperforms perturbed deterministic models by one order of magnitude. Such a high uncertainty quantification skill is of primary interests for assimilation ensemble methods. MATLAB^® code examples are available online.     

Uncertainty analysis and probabilistic segmentation of electrical resistivity images: the 2D inverse problem

In this paper, we present the uncertainty analysis of the 2D electrical tomography inverse problem using model reduction and performing the sampling via an explorative member of the Particle Swarm Optimization family, called the Regressive‐Regressive Particle Swarm Optimization. The procedure begins with a local inversion to find a good resistivity model located in the nonlinear equivalence region of the set of plausible solutions. The dimension of this geophysical model is then reduced using spectral decomposition, and the uncertainty space is explored via Particle Swarm Optimization. Using this approach, we show that it is possible to sample the uncertainty space of the electrical tomography inverse problem. We illustrate this methodology with the application to a synthetic and a real dataset coming from a karstic geological set‐up. By computing the uncertainty of the inverse solution, it is possible to perform the segmentation of the resistivity images issued from inversion. This segmentation is based on the set of equivalent models that have been sampled, and makes it possible to answer geophysical questions in a probabilistic way, performing risk analysis.     

Uncertainty as the overlap of alternate conditional distributions

An important task in modern geostatistics is the assessment and quantification of resource and reserve uncertainty. This uncertainty is valuable support information for many management decisions. Uncertainty at specific locations and uncertainty in the global resource is of interest. There are many different methods to build models of uncertainty, including Kriging, Cokriging, and Inverse Distance. Each method leads to different results. A method is proposed to combine local uncertainties predicted by different models to obtain a combined measure of uncertainty that combines good features of each alternative. The new estimator is the overlap of alternate conditional distributions.     

‘We are managing!’ Uncertain paths to respectable adulthoods in Accra, Ghana

Studies have shown that the life experiences and future prospects of young people in many parts of the world today are more complex and less predictable than those of past generations. This has led to a recognition of the need to reconsider the conceptual frameworks applied in youth studies. Thus far, research within geography has mainly focused on young people’s paths to adulthood in the Global North or on particularly vulnerable children’s lives in the Global South. In this paper an approach based on the ‘social navigation’ of ‘vital conjunctures’ is adopted to explore the complex ways in which young people in Ghana navigate their way through life in a city marked by economic hardship and neo-liberal reform. The stories of three young people are presented to show the variety of life conditions, the complex social positions they occupy and their various and shifting future imaginations. The actions of these young people are steered by prevailing cultural ideals and social expectations of what a desirable and respectable future entails and by the actual space of possibility in the urban space they move through. It is argued that achieving respectable adulthoods in present-day Accra is a complicated and convoluted journey involving the careful management of social relationships.     

不同频率循环荷载作用下花岗岩细观疲劳损伤量化试验研究

花岗岩宏观尺度疲劳破坏是由于细观尺度微裂纹的萌生、发育和贯通引起的,所以对处于细观尺度的微裂纹特征进行量化分析,对于理解花岗岩的动力特性有一定的意义。首先利用RMT-150B多功能全自动刚性岩石伺服试验机,采用振幅为10 MPa,频率分别为0.01、0.02、0.05、0.10、0.20、0.50、1.00 Hz的正弦循环荷载作为动力扰动,对海南昌江花岗岩试样进行单轴循环荷载试验。然后,利用扫描电镜（SEM）拍摄得到花岗岩的大量细观结构图片,运用数字图像技术获取微裂纹的细观几何信息,从方位角、长度、宽度和面积对不同荷载频率相应的花岗岩细观尺度微裂纹特征进行量化分析。研究结果表明,随着循环荷载频率的增加,微裂纹方位角发育离散性增加,而其统计均值则在某一区间内波动;微裂纹长度的发育则较快,而仅当荷载频率达到1 Hz时,宽度才有一定的发展,同时,能量耗散的方式也发生一定的变化。     

Robust geotechnical design of shield-driven tunnels

This paper presents a fuzzy set-based robust geotechnical design (RGD) methodology for the design of shield-driven tunnels. Here, uncertain geotechnical parameters required for analysis of tunnel performance (referred to herein as the structure safety and serviceability performance of tunnel cross section) are represented as fuzzy sets. Given fuzzy input parameters, the performance of a shield-driven tunnel will be uncertain, which is expressed in this study as a fuzzy factor of safety, according to the analysis of vertex method. Then, the fuzzy factor of safety for a given design is used to evaluate the failure probability and design robustness, which are, in turn, employed in the proposed RGD framework. Note that a design is considered robust if the performance of the shield-driven tunnel is insensitive to the variation of its uncertain geotechnical parameters. Within the RGD framework, each candidate design in the design space is analyzed for its safety state (in terms of failure probability), design robustness, and cost. The goal of the RGD of a shield-driven tunnel is to bring the safety state to an acceptable level, while maximizing the robustness and cost efficiency simultaneously. To this end, a multi-objective optimization is performed and a Pareto front is obtained, which provides a trade-off that may be used to select the most preferred design. Through an illustrative case, the effectiveness and significance of this new robust design methodology is demonstrated.     

采用支持向量回归从测井曲线定量计算油页岩含油率

获取油页岩含油率是油页岩资源评价的重要步骤,传统从测井曲线计算油页岩含油率多采用回归模型,但存在误差大或过拟合的局限性和弱点.本文尝试结合大数据概念的数据挖掘算法和测井应用知识进行油页岩含油率定量计算,提高含油率计算的精度以及模型的泛化性.利用改进的ΔlogR技术获得DT_s、DEN_s、GR_s作为解释变量.采用数据挖掘算法——支持向量回归进行定量计算油页岩含油率能够大幅提高泛化性和精度,获得模型训练样本R²得分为0.82,测试样本R²得分可达0.70,拟合精度较高.支持向量回归模型比传统回归模型泛化能力更强,能够避免过拟合问题,具有广泛的应用性.     

喀斯特石漠化信息遥感提取的不确定性

我国西南喀斯特地区以石漠化为特征的生态环境退化严重,遥感是快速、大面积石漠化定性评价、关健指标定量提取必不可少的手段.在简述喀斯特生态地质背景复杂性的基础上,系统分析了目前喀斯特石澳化信息遥感提取在遥感数据源、提取方法、、精度验证、不确定性源等方面的问题,并提出未来石漠化遥感监测的重点研究内容.     

The topology of geology 2: Topological uncertainty

Uncertainty is ubiquitous in geology, and efforts to characterise and communicate it are becoming increasingly important. Recent studies have quantified differences between perturbed geological models to gain insight into uncertainty. We build on this approach by quantifying differences in topology, a property that describes geological relationships in a model, introducing the concept of topological uncertainty. Data defining implicit geological models were perturbed to simulate data uncertainties, and the amount of topological variation in the resulting model suite measured to provide probabilistic assessments of specific topological hypotheses, sources of topological uncertainty and the classification of possible model realisations based on their topology. Overall, topology was found to be highly sensitive to small variations in model construction parameters in realistic models, with almost all of the several thousand realisations defining distinct topologies. In particular, uncertainty related to faults and unconformities was found to have profound topological implications. Finally, possible uses of topology as a geodiversity metric and validation filter are discussed, and methods of incorporating topological uncertainty into physical models are suggested.     

基于贝叶斯模型的中国未来气温变化预估及不确定性分析

利用第5次耦合模式比较计划(CMIP5)中35个全球气候模式历史模拟与RCP4.5预估结果,通过贝叶斯模型平均(Bayesian Model Averaging,BMA)对中国气温进行多模式集合研究,给出了中国未来气温变化预估及其不确定性的时空分布。结果表明,中国21世纪冬夏将持续升温,且升温具有冬季高于夏季,北方高于南方的特点。初期(2016—2035年)北方有很大可能(80%)升温超过0.7℃,南方升温相同幅度的概率则超过50%;中期(2046—2065年)北方和南方升温超过1.5℃的概率分别为80%和50%;末期(2081—2100年),北方(南方)有80%(50%)的可能的升温超过2℃。气温预估的不确定性研究发现,无论冬夏,21世纪不同时期升温相对较弱的塔里木盆地、青藏高原南侧和中国东南地区为不确定性低值区,基本低于0.6℃,对应可信度较高,如21世纪初期信噪比超过4;而不确定性的高值区则主要分布在新疆北部、东北平原北部和青藏高原东南侧等升温相对较大的地区,普遍高于1℃,对应可信度较低,如初期信噪比低于2.5。此外,基于信噪比对比发现除青藏高原东部外,其他区域夏季预估的可信度均高于冬季,21世纪末期高于初期,且空间分布特征一致。