Sequential reduction of slope stability uncertainty based on temporal hydraulic measurements via the ensemble Kalman filter

A data assimilation framework, utilising measurements of pore water pressure to sequentially improve the estimation of soil hydraulic parameters and, in turn, the prediction of slope stability, is proposed. Its effectiveness is demonstrated for an idealised numerical example involving the spatial variability of saturated hydraulic...

Uncertainty reduction and sampling efficiency in slope designs using 3D conditional random fields

A method of combining 3D Kriging for geotechnical sampling schemes with an existing random field generator is presented and validated. Conditional random fields of soil heterogeneity are then linked with finite elements, within a Monte Carlo framework, to investigate optimum sampling locations and the cost-effective design of a slope. The...

Random Fields for Non-Linear Finite Element Analysis of Reinforced Concrete

With more advanced methods and increasing computational power, the simulation of reinforced concrete in a Finite Element Analysis (FEA) has become more and more realistic. In a non-linear analysis of reinforced concrete, cracking behaviour and the maximum load-capacity can be determined. Such analyses sometimes suffer from unstable behaviour,...

Application of Conditional Random Fields and Sparse Polynomial Chaos Expansions to Geotechnical Problems

In geotechnical applications, mechanical properties of soil vary spatially within the soil mass and they are often represented by random fields. When data at certain locations of the soil mass are available, conditional random fields may be used to incorporate them. In this paper, we combine conditional random fields with sparse polynomial chaos...

Probabilistic Analysis at Ultimate Limit State of Strip Footings Resting on a Spatially Varying Soil Using Subset Simulation Approach

The failure probability of geotechnical structures with spatially varying soil properties is generally computed using Monte Carlo simulation (MCS) methodology. This approach is well known to be very time-consuming when dealing with small failure probabilities. One alternative to MCS is the subset simulation approach. This approach was mainly...

Computing the Reliability of Shallow Foundations with Spatially Distributed Measurements

In many geotechnical projects, field data is used to determine the soil parameters. In most instances, however, the statistical analysis is performed ad hoc and the spatial distribution of this data is not (expclitly) accounted for. A more formal statistical approach allows to make better use of the data and combine it in a consistent manner...

Scale of Fluctuation for Geotechnical Probabilistic Analysis

In the past few years, random field theory has been increasingly used to model the inherent soil variability. The scale of fluctuation is one of the important parameters describing a stationary random field. In this study, the factors affecting an accurate estimation of the scale of fluctuation were studied with numerical experiments to show how...

System Failure Probability of c-φ Soil Slope Stability using Vertical Random Fields

The need for system failure probability, pf , of soil slope stability that takes into account the spatial variation of soil properties has been acknowledged by the geotechnical profession. The spatial variations of cohesion and friction angle for a c-ϕ soil slope were modeled by one dimensional vertical random field respectively. The cross...

Stability Analysis of Unsaturated Soil Slope Considering the Variability of Soil-water Characteristic Curve

Soil slopes are generally unsaturated in which the soil-water characteristic curve (SWCC) plays an important role in its hydro-mechanical response. The commonly used Mohr-Coulomb failure criterion in saturated soil mechanics could be extended to take SWCC into account which is then able to determine the shear strength of unsaturated soil. Like...

Safety assessment of a shallow foundation using the random finite element method

In this paper, the reliability assessment of the bearing capacity of a shallow strip footing was conducted using a reliability index β. In applicable standards (Eurocode 7) there is not presented any explicit method of an evaluation of characteristic values of soil parameters. Therefore some approaches of an estimation of characteristic values...

Accounting for Uncertainty and Variability in Geotechnical Characterization of Offshore Sites

This paper presents an overview on how uncertainty and variability of mechanical soil properties are dealt with in offshore site investigation and presents some ideas for utilizing the reliability tools in a more optimal manner for this purpose. Two types of problems are addressed. First, how to extract the maximum amount of information from...

Probabilistic Slope Stability Analysis using RFEM with Non-Stationary Random Fields

Using recently obtained deterministic results as a benchmark, probabilistic slope stability analyses have been performed on an undrained slope using the random finite element method (RFEM). Non-stationary random fields have been generated with linearly increasing mean undrained strength and a constant coefficient of variation. The influence of...

On reducing piping uncertainties: A Bayesian decision approach

Dikes and levees play a crucial role in flood protection in deltaic areas such as the Netherlands. Internal erosion piping or under-seepage is a major cause of levee failures and a main contributor to the probability of failure of river levees due to the large (mostly geotechnical) uncertainties. The present thesis investigates how geotechnical...

The Weakest Link: Spatial Variability in the Piping Failure Mechanism of Dikes

Piping is an important failure mechanism of flood defense structures. A dike fails due to piping when a head difference causes first the uplift of an inland blanket layer, and subsequently soil erosion due to a ground water flow. Spatial variability of subsoil parameters causes the probability of piping failure to increase, often to unacceptable...

Action unit classification using active appearance models and conditional random fields

In this paper, we investigate to what extent modern computer vision and machine learning techniques can assist social psychology research by automatically recognizing facial expressions. To this end, we develop a system that automatically recognizes the action units defined in the facial action coding system (FACS). The system uses a...

Conditional simulation for characterising the spatial variability of sand state

Properties of soils are spatially variable and to describe the behaviour of soils as a response to loading, this variability appears crucial in giving the correct range of possible solutions for structure response. Because site investigation techniques only provide exact information at a limited part of the site, random field simulations are...

Breakup of long-range order in the diluted antiferromagnet K2MnxZn1-xF4 in zero magnetic field