Reliability updating in geotechnical engineering including spatial variability of soil

Papaioannou, Iason; Straub, Daniel

doi:10.1016/j.compgeo.2011.12.004

Cited by 94 publications

(29 citation statements)

References 21 publications

(29 reference statements)

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“…This example is based on previous reliability analysis and updating presented in (Papaioannou and Straub 2012). We update the material properties of the soil surrounding a geotechnical site based on a deformation measurement performed in situ.…”

Section: Finite Element Model Updating Of a Geotechnical Constructionmentioning

confidence: 99%

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Bayesian Updating with Structural Reliability Methods

Straub¹,

Papaioannou²

2015

J. Eng. Mech.

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234

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Bayesian updating is a powerful method to learn and calibrate models with data and observations. Because of the difficulties involved in computing the high-dimensional integrals necessary for Bayesian updating, Markov Chain Monte Carlo (MCMC) sampling methods have been developed and successfully applied for this task. The disadvantage of MCMC methods is the difficulty of ensuring the stationarity of the Markov chain. We present an alternative to MCMC that is particularly effective for updating mechanical and other computational models, termed BUS: Bayesian Updating with Structural reliability methods. With BUS, structural reliability methods are applied to compute the posterior distribution of uncertain model parameters and model outputs in general. We propose an algorithm for the implementation of BUS, which can be interpreted as an enhancement of the classical rejection sampling algorithm for Bayesian updating. This algorithm is based on the subset simulation and its efficiency is not dependent on the number of random variables in the model. The method is demonstrated by application to parameter identification in a dynamic system, Bayesian updating of the material parameters of a structural system, and Bayesian updating of a random-field-based FE model of a geotechnical site.

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Section: Finite Element Model Updating Of a Geotechnical Constructionmentioning

confidence: 99%

“…The corresponding FE model is implemented in the SOFiSTiK program (SOFiSTiK 2012). Further details on the mechanical model and the simulation of the excavation process can be found in (Papaioannou and Straub 2012). basic random variables gathered in a vector .…”

Section: Finite Element Model Updating Of a Geotechnical Constructionmentioning

confidence: 99%

Bayesian Updating with Structural Reliability Methods

Straub¹,

Papaioannou²

2015

J. Eng. Mech.

Self Cite

234

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“…Here, we apply an alternative approach, termed BUS, which uses methods originally developed for structural reliability analysis to obtain samples from the posterior distribution ). The method is based on the algorithm for reliability updating developed in Straub (2011) and applied in Papaioannou & Straub (2012) to the reliability updating of geotechnical structures. The BUS approach introduces the following limit state function:…”

Section: Bayesian Updating With Structural Reliability Methods (Bus)mentioning

confidence: 99%

Bayesian model updating of a tunnel in soft soil with settlement measurements

Papaioannou¹,

Betz²,

Straub³

2013

Geotechnical Safety and Risk IV

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Monitoring is an essential element of modern tunneling construction. The most common monitoring method is measuring displacements, for example convergence of the tunnel opening or surface settlements. Measurement outcomes can be used to update the knowledge on material properties of the soil or other parameters that enter numerical models of the structural behavior of the tunnel. In probability theory, this process can be formalized in the concept of Bayesian updating. In this paper, we apply the Bayesian concept to update the numerical model of a tunnel in soft soil conditional on settlement measurements. The tunnel is constructed by means of the conventional tunneling method and modeled with 2D finite elements applying the stress reduction method. We assume that settlement measurements are taken at full excavation and utilize the measurements to update the material properties of the soil as well as the the relaxation factor of the stress reduction method. Updating is performed by means of BUS, a recently proposed method for Bayesian updating of mechanical models with structural reliability methods.

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“…It is now widely used for reliability analyses and estimation of failure probabilities, e.g. in earthquake engineering [2,3], geotechnical engineering [3,53,65], mechanical engineering and fatigue [9], spacecraft engineering [54], and nuclear engineering [66]. An enhanced version of the method was proposed in [67].…”

Section: Introductionmentioning

confidence: 99%

Multilevel Estimation of Rare Events

Ullmann¹,

Papaioannou²

2015

SIAM/ASA J. Uncertainty Quantification

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This work is motivated by the need to estimate the probability of rare events in engineering systems with random inputs. We introduce a multilevel estimator which is based on and generalises the idea of subset simulation. The novel estimator employs a hierarchy of approximations to the system response computed with different resolutions. This leads to reduced computational costs compared to subset simulation. We study the statistical properties and implementation details of the proposed estimator. Markov chain Monte Carlo runs are required within the estimator and we demonstrate that the nestedness of the associated multilevel failure domains enables a perfect MCMC simulation without burn-in. We show that nestedness follows from certain simple one-dimensional failure domains. In high dimensions we propose a modification of the multilevel estimator which uses level-dependent stochastic input dimensions. We report on numerical experiments in 1D and 2D physical space; in particular, we estimate rare events arising from a Darcy flow problem with random permeability.

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Reliability updating in geotechnical engineering including spatial variability of soil

Cited by 94 publications

References 21 publications

Bayesian Updating with Structural Reliability Methods

Bayesian Updating with Structural Reliability Methods

Bayesian model updating of a tunnel in soft soil with settlement measurements

Multilevel Estimation of Rare Events

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