Searched for: subject%3A%22random%255C%2Bfield%22
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Gonzalez Acosta, J.L. (author), van den Eijnden, A.P. (author), Hicks, M.A. (author)
Soil liquefaction is investigated considering a saturated soil deposit and by implementing standard techniques of random field theory to distribute initial void ratio values and assess liquefaction risk. The soil domain is represented in a 2-dimensional (2D) random finite element model for the dynamic analysis of coupled behavior. Multiple...
conference paper 2023
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Varkey, D. (author), Hicks, M.A. (author), van den Eijnden, A.P. (author)
The stability of six regional dyke cross-sections in the Netherlands was re-assessed using the random finite element method (RFEM), which explicitly accounts for the spatial variability of strength parameters. The RFEM assessments of the cross-sections were shown to result in significantly narrower response distributions than those obtained...
conference paper 2023
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Sorgatz, Julia (author), van den Eijnden, A.P. (author), Montenegro, Héctor (author), Hicks, M.A. (author)
To protect embankments along German inland waterways against local slope sliding failure caused by ship-induced water level drawdown, they are mainly secured by bank revetments. Often, large embankment sections are designed on the basis of a limited number of field and laboratory tests. Thus, uncertainties arise with regard to the mechanical and...
journal article 2023
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Zeng, Sijun (author)
A random field generator based on Local Average Subdivision (LAS) method is proposed in this study in order to achieve probabilistic soil classification and quantify the uncertainty of the generated most probable geological cross section. CPT data and Robertson’s soil classification chart (1990) are adopted to classify the soil. The sole...
student report 2022
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Willems, Joshua (author)
In various scientific disciplines, measurement data is collected across space and over time with the aim of inferring information regarding an underlying stochastic spatiotemporal phenomenon. The high computational costs of current methods render this task intractable for the large datasets typically encountered in spatiotemporal statistics. <br...
master thesis 2021
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Han, Han (author)
Soil properties are spatially variable due to the natural deposition process. Because of this inherent spatial variability, a slope can actually fail along any potential slip surface. A single value of Factor of safety cannot account for this variation dominated the slope stability problem. Probabilistic analysis considering the spatial...
master thesis 2021
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Laman Trip, J.D.S. (author), Wieringen, Wessel N.van (author)
Computationally efficient evaluation of penalized estimators of multivariate exponential family distributions is sought. These distributions encompass among others Markov random fields with variates of mixed type (e.g., binary and continuous) as special case of interest. The model parameter is estimated by maximization of the pseudo...
journal article 2021
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Sinke, Joël (author)
During the design phase of a foundation installation aspects are easily overlooked. When this aspect is overlooked a foundation element risks not reaching its design depth or getting damaged during the installation process. As a result significant delays and/or costs could occur. A driveability study gives insight in the installation aspects of...
master thesis 2020
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Varkey, D. (author), Hicks, M.A. (author), Vardon, P.J. (author)
An improved method for the reliability analysis of 3D slopes has been proposed based on the semi-analytical method of Vanmarcke (1977). Comparing the predicted responses of an idealised 3D slope obtained by the more general, albeit computationally intensive, random finite element method (RFEM), and the original semi-analytical method showed that...
conference paper 2019
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Duvvuru Mohan, V.K. (author), Vardon, P.J. (author), Hicks, M.A. (author), van Gelder, P.H.A.J.M. (author)
Bayesian networks are proposed as a tool to integrate reliability and influential variables relating to the slope stability of an idealized embankment. The site investigation (extent) and slope geometry, as well as the material properties and their spatial variability, are considered within a Bayesian network. The random finite element method ...
conference paper 2019
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Varkey, D. (author), Hicks, M.A. (author), Vardon, P.J. (author)
An improved semi-analytical method for calculating the reliability of 3D slopes with spatially varying shear strength parameters is proposed. The response of an existing semi-analytical method has been compared with that of the computationally more intensive, but more general, random finite element method (RFEM), demonstrating that the simpler...
journal article 2019
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Jiang, Quanxin (author)
One of the most severe deteriorations in reinforced concrete structures is associated with reinforcement corrosion, where the corrosion distribution shows considerable spatial variability. In the existing investigations of spatial variability of corrosion on the reliability of reinforced concrete structures, symbolic expressions are used for the...
master thesis 2018
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Mandersloot, Jeroen (author)
Rare category detection is the task of discovering rare classes in unlabelled and imbalanced datasets. Existing algorithms focus almost exclusively on static data in which instances are assumed to be independent. In this thesis we propose an algorithm that is designed for temporal data. Specifically, we are interested in data with temporal...
master thesis 2018
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Feng, R. (author), Luthi, S.M. (author), Gisolf, A. (author), Angerer, Erika (author)
In this paper, geological prior information is incorporated in the classification of reservoir lithologies after the adoption of Markov random fields (MRFs). The prediction of hidden lithologies is based on measured observations, such as seismic inversion results, which are associated with the latent categorical variables, based on the...
journal article 2018
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Liu, K. (author), Vardon, P.J. (author), Hicks, M.A. (author)
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...
journal article 2018
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Li, Y. (author), Hicks, M.A. (author), Vardon, P.J. (author)
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...
journal article 2016
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Van der Have, R.C. (author)
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,...
master thesis 2015
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Thajeel, J. (author), Al-Bittar, T. (author), Ahmed, A. (author), Soubra, A-H. (author)
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...
conference paper 2015
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Schöbi, R. (author), Sudret, B. (author)
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...
conference paper 2015
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Papaioannou, I. (author), Straub, D. (author)
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...
conference paper 2015
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