Structural Reliability

Lemaire, Maurice; Chateauneuf, Alaa; Mitteau, Jean‐Claude

doi:10.1002/9780470611708

Cited by 192 publications

(169 citation statements)

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“…In comparison to Section 3, the macroscopic loading applied to rod arises here from the structural analysis of the footbridge, generally realized by finite element method [3]. In this aim, a three dimensional model is established for the Laroin footbridge with finite element code ABAQUS.…”

Section: Reliability Calculationsmentioning

confidence: 99%

“…So, it clearly seems more pertinent to turn towards approximation methods that rely on simplifications of the failure domain: First Order Reliability Method (FORM) or Second Order Reliability Method (SORM) (see detailed explanation in Refs. [2,3]). These techniques are based on a transformation of the parameters from the variables space…”

Section: Reliability Modelmentioning

confidence: 99%

“…In this way, the recent development of structural reliability analyses has allowed significant progress: for the composite structures design first, by providing the range of use to achieve a specified reliability level and also, for the risk control by giving the security level of existing structures [2,3]. On the other hand, the specific mechanical response of heterogeneous materials has been widely explained by its microscopic features (properties of the constituents, phase geometry) [4].…”

Section: Introductionmentioning

confidence: 99%

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Multi-scale reliability analysis of composite structures – Application to the Laroin footbridge

Dehmous

Welemane

2011

Engineering Failure Analysis

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To cite this version:Hocine Dehmous, Hélène Welemane. Multi-scale reliability analysis of composite structures â Application to the Laroin footbridge. Engineering Failure Analysis, Elsevier, 2011Elsevier, , vol. 18, pp. 988-998. <10.1016Elsevier, /j.engfailanal.2010 b s t r a c tThis work aims at developing a new methodology for the reliability assessment of composite structures and their design optimization. It relies on the coupling of well established methods: homogenization scheme for the mechanical modelling of composite materials and reliability methods to account for their inherent variability. Moreover, such approach is based on an accurate treatment of inherent uncertainties of these mechanical systems at various scales, including microscopic and macroscopic levels, that provides new perspectives for structural design. As an illustration, we propose to apply the multi-scale reliability analysis on the case of the Laroin footbridge (France) with carbon-epoxy stay cables. Since the reliability assessment of such structure is evaluated through the fibre failure, numerical simulations require the coupling of reliability methods, finite element modelling to derive macroscopic loading within cables and micromechanics to estimate the effective elastic properties of composite and local responses within constituents. Results demonstrate the feasibility of the coupled approach at a structure scale and its main interests for the optimization phase of materials and engineering structures.

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Section: Reliability Calculationsmentioning

confidence: 99%

Section: Reliability Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multi-scale reliability analysis of composite structures – Application to the Laroin footbridge

Dehmous

Welemane

2011

Engineering Failure Analysis

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“…The maximum likelihood process is subject to caution for small data samples. Second, the iso-probabilistic transformation (see for example [24]), also called the Nataf transformation or the Gaussian anamorphosis, consists in applying the data inverse distribution function to the sample. Such a distribution transformation requires the empirical cumulative distribution function, which is built from the data.…”

Section: Transformation To a Gaussian Distributionmentioning

confidence: 99%

Probabilistic risk bounds for the characterization of radiological contamination

Blatman¹,

Delage²,

Iooss³

et al. 2017

EPJ Nuclear Sci. Technol.

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Abstract. The radiological characterization of contaminated elements (walls, grounds, objects) from nuclear facilities often suffers from too few measurements. In order to determine risk prediction bounds on the level of contamination, some classic statistical methods may therefore be unsuitable, as they rely upon strong assumptions (e.g., that the underlying distribution is Gaussian) which cannot be verified. Considering that a set of measurements or their average value come from a Gaussian distribution can sometimes lead to erroneous conclusions, possibly not sufficiently conservative. This paper presents several alternative statistical approaches which are based on much weaker hypotheses than the Gaussian one, which result from general probabilistic inequalities and order-statistic based formulas. Given a data sample, these inequalities make it possible to derive prediction intervals for a random variable which can be directly interpreted as probabilistic risk bounds. For the sake of validation, they are first applied to simulated data generated from several known theoretical distributions. Then, the proposed methods are applied to two data sets obtained from real radiological contamination measurements.

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“…Methods for Pf approximation have been developed as well. The most elementary method is to perform a certain number of simulations (Nsim) and estimate Pf as a quotient obtained by dividing the number of failures by the total number of simulations, Nsim [1,2]. The easiest way of selecting the simulations is via the Monte Carlo (MC) method (described later).…”

Section: Introductionmentioning

confidence: 99%

Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme

Martinásková¹,

Vořechovský²

2017

Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series.

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The article examines the use of Asymptotic Sampling (AS) for the estimation of failure probability. The AS algorithm requires samples of multidimensional Gaussian random vectors, which may be obtained by many alternative means that influence the performance of the AS method. Several reliability problems (test functions) have been selected in order to test AS with various sampling schemes: (i) Monte Carlo designs; (ii) LHS designs optimized using the Periodic Audze-Eglājs (PAE) criterion; (iii) designs prepared using Sobol' sequences. All results are compared with the exact failure probability value.

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Structural Reliability

Cited by 192 publications

References 0 publications

Multi-scale reliability analysis of composite structures – Application to the Laroin footbridge

Multi-scale reliability analysis of composite structures – Application to the Laroin footbridge

Probabilistic risk bounds for the characterization of radiological contamination

Failure Probability Estimation Using Asymptotic Sampling and Its Dependence upon the Selected Sampling Scheme

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