Footing Settlement on a Consolidating Soil Layer with Stochastic Properties

Geotechnical engineering applications are characterized by various sources of uncertainties, most of them attributed to the stochastic nature of soil parameters and their properties. In particular, soil’s inherent random heterogeneity, inexact measurements and insufficient data necessitate numerical methods that incorporate the stochastic soil properties for a realistic representation of the soil behavior. In this paper, the process of consolidation of saturated soils is examined on the basis of the coupled u–p finite element formulation. A generalized Newmark implicit time integration scheme is implemented to treat the time integration of the coupled consolidation equations. A benchmark geotechnical engineering problem of a strip footing resting on a saturated soil layer is analyzed. The soil permeability coefficient k, as well as the elastic modulus E, are treated as lognormal random fields in two dimensions. The investigation of the effect of the spatial variability of the soil properties on the response of a footing–soil system is examined by means of the direct Monte Carlo simulation. The influence of the coefficient of variation and correlation length of the stochastic fields is quantified in terms of footing settlements, as well as excess soil water pore pressure. The effects of spatial variability of the permeability coefficient k and the elastic modulus E on the system response are demonstrated. It is shown that the footing differential settlement, along with generated excess pore pressures, is highly affected by the variation of the soil properties considered, as well as the correlation length of the underlying random fields.     

Stochastic analysis of two-phase flow in porous media: I. Spectral/perturbation approach

Stochastic analysis of steady-state two-phase (water and oil) flow in heterogeneous porous media is performed using the perturbation theory and spectral representation techniques. The governing equations describing the flow are coupled and nonlinear. The key stochastic input variables are intrinsic permeability,k, and the soil and fluid dependent retention parameter, . Three different stochastic combinations of these two imput parameters were considered. The perturbation/spectral analysis was used to develop closed-form expressions that describe stochastic variability of key output processes, such as capillary and individual phase pressures and specific discharges. The analysis also included the estimation of the effective flow properties. The impact of the spatial variability ofk and on the variances of pressures, effective conductivities, and specific discharges was examined.     

Modeling the effects of material non-linearity using moving window micromechanics

In the analysis of materials with random heterogeneous microstructure the assumption is often made that material behavior can be represented by homogenized or effective properties. While this assumption yields accurate results for the bulk behavior of composite materials, it ignores the effects of the random microstructure. The spatial variations in these microstructures can focus, initiate and propagate localized non-linear behavior, subsequent damage and failure. In previous work a computational method, moving window micromechanics (MW), was used to capture microstructural detail and characterize the variability of the local and global elastic response. Digital images of material microstructure described the microstructure and a local micromechanical analysis was used to generate spatially varying material property fields. The strengths of this approach are that the material property fields can be consistently developed from digital images of real microstructures, they are easy to import into finite element models (FE) using regular grids, and their statistical characterizations can provide the basis for simulations further characterizing stochastic response. In this work, the moving window micromechanics technique was used to generate material property fields characterizing the non-linear behavior of random materials under plastic yielding; specifically yield stress and hardening slope, post yield. The complete set of material property fields were input into FE models of uniaxial loading. Global stress strain curves from the FE–MW model were compared to a more traditional micromechanics model, the generalized method of cells. Local plastic strain and local stress fields were produced which correlate well to the microstructure. The FE–MW method qualitatively captures the inelastic behavior, based on a non-linear flow rule, of the sample continuous fiber composites in transverse uniaxial loading.     

考虑空间变异性的框架结构可靠度分析方法

空间变异性是结构参数的固有属性,对于工程结构的随机响应和可靠度分析具有重要影响。结合随机场离散的局部平均理论和随机响应分析的摄动随机有限元法,提出一种考虑参数空间变异性的平面框架结构可靠度分析方法,并定量分析了参数空间变异性对结构可靠度的影响规律。首先,考虑随机因素的空间变异性,采用二维线性随机场离散的局部平均理论将平面框架结构的连续随机场离散为一组随机变量,并通过理论推导建立了随机场局部平均间协方差矩阵的二重积分表达式;然后,采用摄动随机有限元法分析结构随机响应及其对基本随机变量的梯度向量,并利用可靠度分析的梯度优化法计算结构可靠指标,从而提出了一种考虑参数空间变异性的平面框架结构可靠度分析方法。分析表明,该方法具有较高的计算精度和计算效率;随机场离散的局部平均理论对相关结构类型不敏感;随着随机场相关偏度和变异性的增大,框架结构的可靠指标逐渐减小,说明结构参数的空间变异性对结构可靠度的影响不容忽视。     

Gaussian Closure of Transient Unsaturated Flow in Random Soils

The Gaussian closure approximation, previously used by the authors to solve steady state stochastic unsaturated flow problems in randomly heterogeneous soils, is extended here to transient flow. The method avoids linearizing the governing flow equations or the soil constitutive relations. It places no theoretical limit on the variance of constitutive parameters and applies to a broad class of soils with flow properties that scale according to a linearly separable model. Closure is obtained by treating the dimensionless pressure head as a multivariate Gaussian function. It yields a system of coupled nonlinear differential equations for the first and second moments of . We apply the Gaussian closure technique to the problem of transient infiltration into a randomly stratified soil. In each layer, hydraulic conductivity and water content vary exponentially with . Elsewhere we show that application of the technique to other constitutive relations is straightforward. Our solution for the mean and variance of in a one-dimensional layer with random conductivity compares well with Monte Carlo results over a wide range of parameters, provided that the spatial variability of the constitutive exponent is small. The solution provides considerable insight into the behavior of the transient unsaturated stochastic flow problem.     

Integrable flow equations that incorporate spatial heterogeneity

Exactly solvable models are constructed in the Darcy-Buckingham approach to unsaturated flow in porous media with continuous spatial variability. The steady soil water potential distribution, for evaporation from a scale-heterogeneous soil with water table, is given explicitly. The cumulative infiltration predicted by a scale-heterogeneous Green-Ampt model is shown to be inconsistent with that expected from a temporal power series solution of the general flow equation. New integrable forms of the unsaturated heterogeneous flow equation are built up from those exactly solvable forms of the homogeneous flow equation which possess special Lie-Bäcklund symmetry groups.     

露天矿边坡饱和渗透系数随机场数值模型研究

为分析强降雨入渗及渗透系数空间变异性对闭坑露天矿边坡渗流场的影响程度,基于非饱和渗流理论和随机场理论,采用非侵入式随机方法,通过FISH语言编写非饱和区单元饱和度、渗透系数与基质吸力的修正函数,建立饱和-非饱和渗流随机场模型,开展强降雨作用的高大陡深岩质边坡渗流特征研究。研究结果表明,修正饱和-非饱和渗流随机场模型能够准确地描述露天矿边坡的降雨入渗过程。且降雨入渗主要影响到露天矿边坡浅层渗流场。随降雨持时变化,在坡面与地下水位线之间形成包围的且逐渐缩小的非饱和区。坡面最早出现暂态饱和区且厚度逐渐增加,但增幅逐渐放缓。同时坡面点孔隙水压力最早达到稳定值零,离坡面越远的点孔隙水压力达到稳定值零的用时会越长。该结论可为闭坑露天矿边坡的地质灾害风险预测提供参考意义。     

Homogenization Modeling and Parametric Study of Moisture Transfer in an Unsaturated Heterogeneous Porous Medium

The classical mass balance equation is usually used to model the transfer of humidity in unsaturated macroscopically homogeneous porous media. This equation is highly non-linear due to the pressure-dependence of the hydrodynamic characteristics. The formal homogenization method by asymptotic expansions is applied to derive the upscaled form of this equation in case of large-scale heterogeneities of periodic structure. The nature of such heterogeneities may be different, resulting in locally variable hydrodynamic parameters. The effective capillary capacity and the effective hydraulic conductivity are defined as functions of geometry and local characteristics of the porous medium. A study of a two-dimensional stone-mortar system is performed. The effect of the second medium (the mortar), on the global behavior of the system is investigated. Numerical results for the Brooks and Corey hydrodynamic model are provided. The sensitivity analysis of the parameters of the model in relation to the effective hydrodynamic parameters of the porous structure is presented.     

Consolidation Statistics Investigation via Thin Layer Method Analysis

In this paper, the Thin Layer Method (TLM) is adapted for solving one-dimensional primary consolidation problems. It is also combined with a stochastic formulation integrating Monte Carlo simulations to investigate primary consolidation of a random heterogeneous soil profile. This latter is modeled as a set of superposed layers extending horizontally to infinity, and having random properties. Spatial variability of soil properties is considered in the vertical direction only. Soil properties of interest are elastic modulus and soil permeability, modeled herein as spatially random fields. Lognormal distribution is chosen because it is suitable for strictly non-negative random variables, and enables analyzing the large variability of such properties. The statistics regarding final settlement and its corresponding time are investigated by performing a parametric study, which integrates the influence of variation coefficient of both elastic modulus and soil permeability, and vertical correlation length. Obtained results indicate that heterogeneity significantly influences primary consolidation of the soil profile, generating a quite different way of soil grain rearrangement and water pressure dissipation in comparison to the homogeneous case, and causing a delay in the consolidation process.     

线性随机结构在随机激励下动力响应分析

利用虚拟激励法对随机结构正交展开理论进行扩展,并在Ritz向量子空间中对扩阶系统方程进行动力聚缩,提出了一类可以快速高效地进行线性随机结构复合随机振动分析的计算方法．算例分析表明,该法可以方便地分析随机结构在平稳或非平稳随机激励下的复合随机振动问题,且分析结果与 Monte Carlo模拟分析结果符合良好;与均值参数确定性结构传统随机振动分析计算结果相比,随机结构在相同随机激励下响应自谱密度曲线具有峰值降低、谱宽增大的特点．     

Perturbation Solutions for Flow in a Slowly Varying Fracture and the Estimation of Its Transmissivity

The spatial distribution of hydrogeological properties is essentially heterogeneous. Heterogeneity can be characterized quantitatively using geostatistics, which conventionally assumes that the stochastic process is stationary. However, growing evidence indicates that the spatial variability has the multiscale self-similarity characteristics and can be better characterized using non-stationary model but with statistically homogeneous increments. A general framework is developed in this work to conduct the uncertainty quantification analysis by using truncated power variogram model, which can explicitly account for measurement scale, observation scale, and window scale. The effect of the multiscale characteristics of the hydrogeological properties on the uncertainty and the consequential risk associated with the groundwater flow process is investigated. A synthetic two-dimensional saturated steady-state groundwater flow problem is used to evaluate the performance to predict the flow field distribution. For comparative purposes, the evaluation is based on both the truncated power and the traditional variogram models when the underlying porous medium is a random fractal field. The results show that the truncated power variogram model can perform the uncertainty quantification more accurately, and the adoption of traditional variogram model tends to result in a smoother estimation on the flow field and underestimate the uncertainty associated with the hydraulic head prediction. Upscaling is generally inevitable to avoid predictive uncertainty underestimation when the underlying random field exhibits multiscale characteristics.

     

等参局部平均随机场和Neumann随机有限元法

本文提出了二维连续平稳随机场的一种新的表述方法—等参局部平均随机场模型,并将它引入Neumann随机有限元法。算例表明,本文的方法是有效的且能提高精度和计算效率。     

Theoretical framework and experimental procedure for modelling mesoscopic volume fraction stochastic fluctuations in fiber reinforced composites

Many engineering materials exhibit fluctuations and uncertainties on their macroscopic mechanical properties. This randomness results from random fluctuations observed at a lower scale, especially at the meso-scale where microstructural uncertainties generally occur. In the present paper, we first propose a complete theoretical stochastic framework (that is, a relevant probabilistic model as well as a non-intrusive stochastic solver) in which the volume fraction at the microscale is modelled as a random field whose statistical reduction is performed using a Karhunen–Loeve expansion. Then, an experimental procedure dedicated to the identification of the parameters involved in the probabilistic model is presented and relies on a non-destructive ultrasonic method. The combination of the experimental results with a micromechanical analysis provides realizations of the volume fraction random field. In particular, it is shown that the volume fraction can be modelled by a homogeneous random field whose spatial correlation lengths are determined and may provide conditions on the size of the meso-volumes to be considered.     

A domain decomposition method for stochastic analysis of acoustic fields with hybrid and localized uncertainties

An efficient domain decomposition method (DDM) is proposed for the dynamic analysis of stochastic acoustic fields with hybrid and localized uncertainties. The hybrid and localized uncertainties refer to the parameters that are associated with local properties of the acoustic fields and meanwhile are subjected to different kinds of randomness. To take advantage of the locally distributed feature of uncertain parameters, the full acoustic domain is divided into several sub-domains, along with each localized uncertain parameter being assigned to one specific sub-domain. In each sub-domain, the deterministic Helmholtz equation is transformed to a weak integral form and the discretized governing equation is obtained by employing Chebyshev orthogonal polynomials as admissible functions. The random or interval perturbation technique is applied to the individual governing equation according to the respective uncertainty type, whereby the stochastic governing equation is established. The original acoustic field is eventually recovered by the introduction of penalty functions to impose sound pressure continuity on the interfaces of sub-domains, and the (intervals of) sound pressure, together with its expectation and variance, can be subsequently obtained. The accuracy and efficiency of the proposed method are verified in several numerical examples by comparisons with the results given by brute force Monte Carlo simulations, and the DDM-based independent way of modelling and analysis proves to be quite effective and flexible for uncertainty quantification in acoustic fields.     

Estimating Caprock Impact on CO2 Migration in the Gassum Formation Using 2D Seismic Line Data

Realizable CO₂ storage potential for saline formations without closed lateral boundaries depends on the combined effects of physical and chemical trapping mechanisms to prevent long-term migration out of the defined storage area. One such mechanism is the topography of the caprock surface, which may retain CO₂ in structural pockets along the migration path. Past theoretical and modeling studies suggest that even traps too small to be accurately described by seismic data may play a significant role. In this study, we use real but scarce seismic data from the Gassum Formation of the Norwegian Continental shelf to estimate the impact of topographical features of the top seal in limiting CO₂ migration. We seek to estimate the amount of macro- and sub-scale trapping potential of the formation based on a few dozen interpreted 2D seismic lines and identified faults. We generate multiple high-resolution realizations of the top surface, constructed to be faithful to both large-scale topography and small-scale statistical properties. The structural trapping and plume retardation potential of these top surfaces is subsequently estimated using spill-point (static) analysis and dynamical flow simulation. By applying these techniques on a large ensemble of top surface realizations generated using a combination of stochastic realizations and systematic variation of key model parameters, we explore the range of possible impacts on plume advancement, physical trapping and migration direction. The stochastic analysis of trapping capacity and retardation efficiency in statistically generated, sub-seismic resolution features may also be applied for surfaces generated from 3D data.

     

A non-intrusive methodology for the representation of crack growth stochastic processes

In this paper, we present a methodology to pursue the uncertainty quantification of the stochastic process that represents the crack growth problem. The main idea of this methodology is to discretize the crack growth process in a sequence of random variables and then, approximate each of them using a stochastic polynomial approach. This methodology is non-intrusive, i.e. it is based on the representation of random variables using stochastic polynomials, whose coefficients are evaluated using a least squares method and only a few realizations of the stochastic process. The Paris–Erdogan law was used as crack growth model in order to focus the reader's attention on the uncertainty quantification methodology. We modeled the parameters of the Paris–Erdogan law as random variables, i.e. the initial crack length and the coefficients of the Paris–Erdogan model are treated as random variables. Two numerical examples are presented in order to shown the effectiveness and accuracy of the proposed methodology. From the results of these examples, it is shown that the proposed methodology is able to successfully approximate the stochastic process that represents the crack growth for the Paris–Erdogan model, with a much lower computational cost than the MCS. The main limitation of the proposed approach is that, in the form it was presented, it is not able to handle random processes as input parameters.     

Laser-pulse interferometry applied to high-pressure fluid flow in micro channels

The miniaturization of hydraulic systems together with ever increasing static and dynamic fluid pressure as is happening in fuel injection systems leads to complex flow effects with very high local and temporal pressure gradients. System optimization for hydraulic efficiency, components durability or spray formation quality needs the understanding of relevant flow properties. Fluid flow simulation models support such understanding, but with the complex nature of flow conditions, they are in need for precise and comprehensive verification and validation data. This work reports on measurement methods and analysis results for local fluid density and pressure measurements under overall stationary, highly turbulent and cavitating flow conditions in planar, optically accessed, model flow experiments. Laser-pulsed interferometry is applied for the measurement of fluid density fields under high spatial (∼3 μm) and temporal (∼5 ns) resolution. Interferometric imaging and image evaluation techniques provide ensemble mean pressure field data, local pressure fluctuation and differential pressure data. This yields information about local flow features such as flow vortex generation frequency, spatial size and shape of vortices and local pressure distribution inside of vortex structures. Features of bubble collapse process and corresponding pressure shock waves have been observed. The analysis method is applied to a forward-facing step and a target flow geometry. Experimental method, evaluation procedures and results are presented in this paper.     

Stochastic framework for modeling the linear apparent behavior of complex materials: Application to random porous materials with interphases

This paper is concerned with the modeling of randomness in multiscale analysis of heterogeneous materials. More specifically, a framework dedicated to the stochastic modeling of random properties is first introduced. A probabilistic model for matrix-valued second-order random fields with symmetry propertries, recently proposed in the literature, is further reviewed. Algorithms adapted to the Monte Carlo simulation of the proposed representation are also provided. The derivations and calibration procedure are finally exemplified through the modeling of the apparent properties associated with an elastic porous microstructure containing stochastic interphases.