Practical representation of characteristic grain shape of sands: a comparison of methods

ABSTRACT A measure of grain shape is needed for incorporation in calculations of the behaviour of grain populations (for example during transport by fluids). Many shape measures have been proposed, most of them for application to single grains rather than to populations. In this paper three such shape parameters are evaluated for samples taken by size fraction from each of three parent sands. The chosen parameters are the maximum projection sphericity of Sneed & Folk (based on triaxial measurements made on the grains), the dynamic shape factor of Briggs (based on settling velocity in water), and rollability, after Winkelmolen (based on rolling behaviour in a specially mounted rotating cylinder).
It is shown that the Sneed & Folk parameter and rollability both discriminate clearly between the shape characteristics of the three sands over the size range 150-500 μm. Moreover the discrimination of the two parameters is mutually consistent. However, dynamic shape factor gives results which for sizes smaller than 300 μm are inconsistent with those of the other two methods and which do not discriminate reliably between the populations. This is inevitable because the differences between drag on spheres and on other shapes become very small at Reynolds Numbers corresponding to those which obtain in settling tests on grains smaller than 300 μm.     

基于无监督方法确定岩土参数取值

随着城市工程建设的发展,建筑工程事故问题愈发突出,采用传统方法求取的岩土参数区间无法满足实际工程需要。基于无监督学习思想,选取工程性质较差的泥炭质土,结合工程经验选用8个物理指标作为输入集,利用主成分分析（priciple components analysis, PCA）算法实现多样本多参数去耦合的降维处理,得出各物理指标相关性及敏感度,结合其相关性及敏感度赋予不同埋深泥炭质土物理指标的综合评价值。利用k-means聚类分析泥炭质土物理指标、综合评价值及工程特性之间的关系,为岩土参数选取提供理论基础。采用监督学习方法——BP神经网络算法分析无监督结果,验证（PCA—k-means）算法模型的合理性。将通过聚类分析得到的正态样本利用多种截尾法优化,得到可靠取值区间,并将取值结果与实际工程取值比较,验证了该模型工程参数取值的合理性。该算法模型具有较好的工程应用价值,所得研究结果可为工程勘察、设计、施工参数取值提供参考,也能为岩土参数取值分析提供新的分析方法。     

砂土中盾构隧道开挖面失稳土体三维形状分析

合理确定盾构隧道开挖面前方失稳土体的形状是开挖面极限支护压力计算及开挖面失稳风险评估的基础和难点。建立模拟盾构隧道开挖面失稳过程的数值模型,利用Handy拱效应理论,依据Mohr-Coulomb破坏准则,得出失稳土体破坏位置和形状的计算方法。研究结果表明,水平方向由于隧道左右两端的支承作用产生水平压力拱,使失稳土体存在一个极限边界,极限边界内垂直方向的土体移动产生悬链线形的最小主应力拱,失稳土体形状类似贝壳形。以南京地铁3号线浦珠路站－滨江路站区间盾构隧道工程作为算例,理论分析和数值模拟结果吻合较好。     

Discrete element modeling of crushable sands considering realistic particle shape effect

This study proposed a novel approach for generating crushable agglomerates with realistic particle shapes in discrete element modeling (DEM). The morphologies of sand particles were obtained by X-ray micro-computed tomography scanning and image processing. Based on the particle surface reconstructed by spherical harmonic analysis, the crushable agglomerates with realistic particle shapes can be generated in DEM simulations. The results of single particle crushing tests showed that particle shapes significantly influence the fracture patterns and crushing strengths of sand particles. Furthermore, two one-dimensional compression tests were conducted to investigate the particle shape effect on micro- and macro-mechanical behaviors of crushable sands.     

Provenance bias between detrital zircons from sandstones and river sands:A quantification approach using 3-D grain shape,composition and age

Preservation bias may significantly impact the application of detrital zircon geochronology in reconstructing Earth surface processes.Here we compare detrital zircons from the actively eroding Murchison River channel in Western Australia with Ordovician fluvial sediments that have drained similar source rocks along the western margin of the West Australian Craton.In addition to standard analysis of detrital zircon age spectra we apply multivariate statistics to test the relation between 3-D grain shape,U-content and U-Pb ages,with the objective to quantify differences between both sample groups and track preservation along the transport pathway of the Murchison River.Our results show that zircon grains in modern river sands display an upstream trend toward larger surface areas,volume equivalent diameters and grain widths,as well as toward higher U-contents and lower apparent grain densities.3-D grain shape,size and age spectra of Murchison River zircons evolve consistently downstream,but even at the river outlet remain distinct from the Ordovician samples,as a less mature representation of source.We interpret Ordovician river zircons to represent a significantly depleted subset from which up to 22% of the zircon population may have been lost compared to the actively transported detrital load.This discrepancy between the characteristics of detrital zircons in modern active rivers and ancient fluvial Ordovician sandstones demonstrates a bias that could be relevant for other source-sink detrital transport systems throughout Earth history.     

Spatiotemporal deep learning approach on estimation of diaphragm wall deformation induced by excavation

Acta Geotechnica - This paper proposes a convolution neural network (CNN) based prediction method for concrete diaphragm wall (CDW) deflections. CNN algorithm is modified for processing the CDW...     

Observations of the ground and structural behaviours induced by a deep excavation in loose sands

Acta Geotechnica - Large-scale deep basement excavations are commonly used in metropolitan areas; however, previous studies focused primarily on excavations in impermeable clay instead of permeable...     

深部切顶沿空成巷关键参数研究及工程应用

传统充填沿空留巷工艺繁琐﹑留巷速度慢,与现代化高强度开采要求不相适应,由此提出了切顶沿空成巷无煤柱开采新技术,其中关键参数设计是该技术的核心问题之一,对留巷的稳定性具有较大影响。以城郊煤矿21304工作面为研究背景,采用理论分析、数值模拟和现场试验等方法,对切顶沿空成巷关键参数进行了系统研究。基于岩石碎胀自承特性和围岩结构“S-R”稳定原理,推导出切顶高度﹑切顶角度的理论计算公式;建立了聚能爆破力学模型,并结合数值模拟和现场试验,确定了聚能爆破装药量及钻孔间距。研究结果表明：合理的切顶参数能够切断巷道顶板与采空区岩层间的力学关系,使采空区顶板沿切缝顺利垮落,碎胀的矸石可有效支撑上覆顶板,限制其回转下沉,减弱覆岩运动对留巷的扰动作用,沿空巷道围岩变形量明显减小。根据理论计算﹑数值分析和现场试验研究成果,确定了城郊煤矿21304工作面切顶沿空成巷关键参数,并在现场进行了应用,回采后沿空巷道侧向顶板能够迅速切落形成巷帮,留巷稳定后各项指标均能满足现场使用要求。     

深厚吹填粉细砂地基加固试验研究

结合上海某深水港集装箱堆场地基加固工程,基于深厚吹填粉细砂的工程特性,通过对无填料振冲挤密法加固的有效性和工艺参数进行现场试验研究,对加固前后的土体变形、超静孔压变化、工艺参数和加固效果等进行了分析和讨论。结果表明,采用无填料振冲挤密法可以加固深层土体、增加粉细砂的密实度,有效消除不均匀沉降和液化危害,效果显著,并拓宽了振冲法的应用范围,可为在类似地基处理中的推广提供参考依据和成功经验。     

The critical state parameters of sands from their image-based intrinsic properties

Acta Geotechnica - It has been well established that critical state behavior of granular soils is controlled by their intrinsic properties. The critical state behavior is quantified by strength...     

Quantifying bioirrigation using ecological parameters: a stochastic approach†

Irrigation by benthic macrofauna has a major influence on the biogeochemistry and microbial community structure of sediments. Existing quantitative models of bioirrigation rely primarily on chemical, rather than ecological, information and the depth-dependence of bioirrigation intensity is either imposed or constrained through a data fitting procedure. In this study, stochastic simulations of 3D burrow networks are used to calculate mean densities, volumes and wall surface areas of burrows, as well as their variabilities, as a function of sediment depth. Burrow networks of the following model organisms are considered: the polychaete worms Nereis diversicolor and Schizocardium sp., the shrimp Callianassa subterranea, the echiuran worm Maxmuelleria lankesteri, the fiddler crabs Uca minax, U. pugnax and U. pugilator, and the mud crabs Sesarma reticulatum and Eurytium limosum. Consortia of these model organisms are then used to predict burrow networks in a shallow water carbonate sediment at Dry Tortugas, FL, and in two intertidal saltmarsh sites at Sapelo Island, GA. Solute-specific nonlocal bioirrigation coefficients are calculated from the depth-dependent burrow surface areas and the radial diffusive length scale around the burrows. Bioirrigation coefficients for sulfate obtained from network simulations, with the diffusive length scales constrained by sulfate reduction rate profiles, agree with independent estimates of bioirrigation coefficients based on pore water chemistry. Bioirrigation coefficients for O₂ derived from the stochastic model, with the diffusion length scales constrained by O₂ microprofiles measured at the sediment/water interface, are larger than irrigation coefficients based on vertical pore water chemical profiles. This reflects, in part, the rapid attenuation with depth of the O₂ concentration within the burrows, which reduces the driving force for chemical transfer across the burrow walls. Correction for the depletion of O₂ in the burrows results in closer agreement between stochastically-derived and chemically-derived irrigation coefficient profiles.     

Energy parameters of deep fluid systems

Doklady Earth Sciences -     

Estimation of velocity function parameters in unconsolidated sands using semblance velocity analysis

To properly understand seismic wave propagation in unconsolidated sand layers, it is important to estimate the parameters of their continuous velocity–depth functions. This study proposes a procedure to estimate the V ₀ and k parameters of a specific velocity function, where V ₀ is the direct P-wave velocity at the ground surface and k is the velocity gradient. The V ₀ and k parameters are generally independent of each other. However, it is possible to relate them numerically because both depend strongly on the porosity (?) and water saturation (S _w). The proposed procedure starts by tabulating V ₀ and k for 0.05?≤???≤?0.5 sampled at Δ??=?0.05 and S _w?=?0.6, so that only V ₀ is needed for fitting. Then, time–distance (T-X) type curves of the direct arrival are calculated for the corresponding values of V ₀ and k parameters values. The type curves are fitted then to the observed shot gather through a modification of the classic semblance velocity analysis method. Once the best-fit V ₀ value is found, the corresponding k, ?, and S _w values are picked from a V ₀–k–? lookup table. The procedure is applied on synthetic shot gathers with various amounts of additive Gaussian random noise. Results show that the method is robust and tolerant to low to moderate amounts of noise.     

Correlation between grain shape and critical state characteristics of uniformly graded sands: A 3D DEM study

Acta Geotechnica - The multi-scale characteristics of particle morphology, including the overall form, local roundness and surface roughness, affect the critical state behavior of sands and should...     

Effect of particle shape of glass beads on the strength and deformation of cemented sands

Acta Geotechnica - Few studies have focused on the influence of particle shape on the mechanical properties of cemented sand. To address this lack of information, this study investigated the...     

A numerical approach to estimate shaft friction of bored piles in sands

A new approach to estimate shaft capacity of bored piles in sandy soils, based on numerical analysis, is presented. The topic is relevant as current design methods often largely underestimate the shaft capacity of piles in sands, thus resulting in an over-conservative design. The proposed approach is based on explicitly modelling the thin cylinder of soil surrounding the pile, where strain localization concentrates (shear band), and on the fundamental mechanic behaviour of sandy soils (e.g. dilatancy, softening). This approach is both simple and easy to apply. Results of a broad parametric study involving axially loaded single piles embedded in different sandy soils are presented, highlighting that relative density and grain size distribution mainly affect the shaft capacity. The capability of the procedure to predict shaft friction is checked against data from a well-documented full-scale axial load test on instrumented pile. Some suggestions for calibration and application of the method are also reported.     

地质领域机器学习、深度学习及实现语言

地质大数据正在以指数形式增长。只有发展智能数据处理方法才有可能追上大数据的超常增长。机器学习是人工智能的核心,是使计算机具有智能的根本途径。机器学习已成为地质大数据研究的前沿热点,它将让地质大数据插上翅膀,并因此改变地质。机器学习是一个源于数据的模型的训练过程,最终给出一个面向某种性能度量的决策。深度学习是机器学习研究中的一个重要子类,它通过构建具有很多隐层的机器学习模型和海量的训练数据,来学习更有用的特征,从而最终提升分类或预测的准确性。卷积神经网络算法是最为常用的一种深度学习算法之一,它广泛用于图像识别和语音分析等。Python语言在科学领域的地位占据着越来越重要。其下的Scikit-Learn是一个机器学习相关的库,提供有数据预处理、分类、回归、聚类、预测、模型分析等算法。Keras是一个基于Theano/Tensorflow的深度学习库,可以应用来搭建简洁的人工神经网络。     

水泥环参数和套管形状参数对套管强度的影响

目前,国内外均面临着严重的套损问题,因此研究套管强度的影响因素是必要的。通过建立套管和水泥环的三维有限元模型,并利用Ansys有限元分析软件研究了水泥环参数、套管偏心率和椭圆度对套管强度的影响。模拟结果表明,只有水泥环的弹性模量超过一定值,增加水泥环的厚度、弹性模量才能提高套管的强度,否则还会增加套管内壁的等效应力,并且得出了水泥环对套管强度的增幅效果是套管径厚比的函数;此外套管的强度随着套管偏心率和椭圆度的增加而大幅度降低,容易引起套管屈服破坏。     

深度学习在地质学上的应用

自Hinton等使用基于卷积神经网络的深度学习模型赢得Image Net分类比赛以来,深度学习的研究席卷了各个行业。通过介绍深度学习的历史,探索国内地质行业中深度学习模型的使用情况,并介绍深度学习的基础概念(如神经元、神经网络、监督学习和无监督学习等)以及深度学习基础模型中的2个重要网络:深度信念网络(DBN)和卷积神经网络(CNN)。在此基础上,类比深度学习在医学等相关领域的应用,提出了深度学习在地质上的几点应用:利用深度学习在计算机视觉上表现出的强大能力,可以对遥感图像进行聚类、对岩石样品图像进行分类、对岩石薄片数据进行描述;利用深度学习对原始数据表现出的强大识别能力,处理地质异常数据,从而确定成矿靶区的可能位置;利用深度学习的特点,对地震前的声信号数据进行处理,从而判断出地震发生前的剩余时间。