Probabilistic Approach to the Solution of Inverse Problems in Civil Engineering

Hadidi, Rambod; Gucunski, Nenad

doi:10.1061/(asce)0887-3801(2008)22:6(338)

Cited by 24 publications

(11 citation statements)

References 12 publications

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“…It can be seen that the SLEs are able to accurately represent the likelihood around its peak, i.e. roughly speaking in the interval µ ∈ [8,15] for p = 5 and in µ ∈ [5,18] for p = 20. Note that these regions accumulate the largest proportions of the total prior probability mass.…”

Section: Posterior Densitymentioning

confidence: 99%

Spectral likelihood expansions for Bayesian inference

Nagel

Sudret

2016

Journal of Computational Physics

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A spectral approach to Bayesian inference is presented. It pursues the emulation of the posterior probability density. The starting point is a series expansion of the likelihood function in terms of orthogonal polynomials. From this spectral likelihood expansion all statistical quantities of interest can be calculated semi-analytically. The posterior is formally represented as the product of a reference density and a linear combination of polynomial basis functions. Both the model evidence and the posterior moments are related to the expansion coefficients. This formulation avoids Markov chain Monte Carlo simulation and allows one to make use of linear least squares instead. The pros and cons of spectral Bayesian inference are discussed and demonstrated on the basis of simple applications from classical statistics and inverse modeling

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Section: Posterior Densitymentioning

confidence: 99%

Spectral likelihood expansions for Bayesian inference

Nagel

Sudret

2016

Journal of Computational Physics

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“…Because of the complexity involved in getting the true optima, compromise solution has been suggested in the literature (e.g., [10][11][12], etc.) using a "satisficing" solution that achieves the best compromise between all competing objectives.…”

Section: Decision-making Under Multiple and Conflicting Objectivesmentioning

confidence: 99%

Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition

Lwambuka

Mtenga

2014

Advances in Civil Engineering

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This paper presents a practical approach for prioritization of bridge maintenance within a given bridge network. The maintenance prioritization is formulated as a multiobjective optimization problem where the simultaneous satisfaction of several conflicting objectives includes minimization of maintenance costs, maximization of bridge deck condition, and minimization of traffic disruption and associated user costs. The prevalence of user cost during maintenance period is twofold; the first case refers to the period of dry season where normally the traffic flow is diverted to alternative routes usually resurfaced to regain traffic access. The second prevalence refers to the absence of alternative routes which is often the case in the least developed countries; in this case the user cost referred to results from the waiting time while the traffic flow is put on hold awaiting accomplishment of the maintenance activity. This paper deals with the second scenario of traffic closure in the absence of alternative diversion routes which in essence results in extreme user cost. The paper shows that the multiobjective optimization approach remains valid for extreme cases of user costs in the absence of detour roads as often is the scenario in countries with extreme poor road infrastructure.

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“…Methods based on probabilistic model generation are one of the popular methods (Beck & Katafygiotis, 1998;Hadidi & Gucunski, 2008;Yuen, Beck, & Katafygiotis, 2006). In probabilistic frameworks, the uncertainties in the modelling process are described as a set of random variables which typically are the parameters of an FE model.…”

Section: Introductionmentioning

confidence: 99%

Candidate model construction of a cable-stayed bridge using parameterised sensitivity-based finite element model updating

Park

Kim

2014

Structure and Infrastructure Engineering

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An efficient method for constructing multiple candidate finite element (FE) models which are consistent with the measured dynamic properties of a civil structure is presented. A parameterised sensitivity-based FE model updating method was developed to permit a feasible FE model set for the target structure to be produced. In this method, an aggregated multiobjective function, which is defined by the weighted sum of the error functions, is parameterised by its relative weighting factors. By introducing multiple parameter sets for the weighting factors, a number of optimal updated FE models are produced that permit both the natural frequency errors and mode shape errors to be simultaneously minimised. The effectiveness of the proposed method is illustrated by an example using an existing cable-stayed bridge. The findings show that error-minimised, well-distributed FE models can be obtained in terms of modal frequency errors and mode shape errors. The high quality of the candidate model sets is also verified by observations showing that the distributions of the structural parameters are consistent through each updated FE models, and the characteristic features of the target structure such as nonsymmetric mode shapes are relatively well captured.

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Probabilistic Approach to the Solution of Inverse Problems in Civil Engineering

Cited by 24 publications

References 12 publications

Spectral likelihood expansions for Bayesian inference

Spectral likelihood expansions for Bayesian inference

Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition

Candidate model construction of a cable-stayed bridge using parameterised sensitivity-based finite element model updating

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