Showing papers in "Structural Safety in 2019"

TL;DR: A novel method is proposed to simulate non-stationary and non-Gaussian random field samples directly from sparse measurement data, bypassing the difficulty in random field parameter estimation from sparse measurements data.

TL;DR: This paper outlines a methodology for an integral risk-based optimization of inspections in structural systems, which utilizes a heuristic approach to formulating the optimization problem and takes basis in a recently developed dynamic Bayesian network framework for rapid computation of the system reliability conditional on inspection results.

TL;DR: In this article, a non-random-walk Markov chain Monte Carlo (HMC) method was used for reliability analysis. But the method alleviated the random walk behavior to achieve a more consistent exploration of the probability space compared to standard Gibbs or Metropolis-Hastings techniques.

TL;DR: The suitability of the multivariate normal distribution and the Gaussian mixture model as importance sampling densities within the cross entropy method is investigated and a modified version of the expectation-maximization algorithm that works with weighted samples is proposed.

TL;DR: A new time-dependent reliability method is presented that is formulated as a large-scale series system consisting of time-independent response functions obtained by discretizing time- dependent continuous response functions within the forecast time period.

TL;DR: In this paper, an adaptive scaled unscented transformation (ASUT) is developed to obtain the fractional moments with only a few of sample evaluations, which is applicable to problems with correlated/uncorrelated random variables.

TL;DR: In this paper, the authors proposed a non-classical two-parameter ACF model, such as the powered exponential (PE) model and Whittle-Matern (WM) model, to identify the sample path smoothness based on site investigation data.

TL;DR: An augmented step size adjustment (ASSA) method is proposed to boost the iterative process in terms of both efficiency and robustness and indicates that the ASSA method has wide applicability for nonlinear constraint functions and achieves efficient and robust performance.

TL;DR: This work aims at the development of an advanced method for the seismic design of Moment Resisting Frames (MRFs) based on a target value of the failure probability in the attainment of a collapse mechanism of global type for stochastic frames (considering the aleatoric uncertainty of the material properties).

TL;DR: The underlying generic framework for structural design optimization is reviewed and extended for the derivation of life safety related target reliabilities based on the marginal lifesaving costs principle and forms the basis for the target rel iabilities defined in ISO 2394:2015.

TL;DR: A compatible probabilistic framework for the quantification of simultaneous aleatory and epistemic uncertainties of basic parameters of real-world civil engineering structures is proposed and a numerical algorithm by changing the assigned probabilities of representative points in the PDEM is proposed.

TL;DR: A pattern recognition approach is proposed to quantitatively assess the residual structural capacity of earthquake-damaged tall buildings to inform optimal sensor placement as well as provide time-dependent limit state evaluation in aftershock environments.

TL;DR: The study results show that the various response parameters considered are differently affected by the damper properties and unveil the capability of the proposed approach to evaluate the potentially worst conditions that jeopardize the system reliability.

TL;DR: Results evidence the potential of the optimization framework proposed to address problems in which preemptive decisions are coupled with those eventually required to respond to an uncertain adverse event to provide risk-informed decision support, while being able to deal with large sets of components and scenarios under an exact optimization approach.

TL;DR: The implementation of a probabilistic framework that includes effects such as structural weakening due to a first-acting hazard in the analysis of structural damage when contemplating subsequent hazards is described and the formulation of damage scales tailored to assess cumulative structural damage from all the hazards involved in theAnalysis are proposed.

TL;DR: A numerical example indicates that the proposed method for points selection in high-dimensional random-variate space for PDEM is of efficiency and accuracy for high- dimensional stochastic dynamic problem of structures.

TL;DR: A probabilistic approach to modeling the seismic damage incurred by structural and nonstructural components is developed and a library of Bayesian damage models are developed using the proposed approach.

TL;DR: It is proved that the standard reliability formulation requires modification for proper handling of Meta models in reliability analysis and a refining term – in this study named as classification error removal term (CERT)- should be added to the well-known failure probability integral for removing the errors of the employed surrogate model.

TL;DR: A probabilistic model for time evolution of corrosion growth is constructed from available data using polynomial chaos formalism and a computationally efficient and accurate optimization strategy is proposed in order to solve the stochastic optimization associated with the lifecycle management of buried pipelines.

TL;DR: A hybrid reliability analysis procedure that combines the advantages of the Subset Simulation method, the application of surrogate models and clustering techniques is proposed to efficiently assess the failure probability of complex structural systems that may exhibit multiple failure modes.

TL;DR: A model-free reinforcement learning approach with addition of a model-based safe exploration for near-optimal management of infrastructure system pre-event and their recovery post-event is proposed.

TL;DR: The proposed method is more efficient and robust than existing algorithms for robust traffic assignment under uncertainties, and climate change and population growth can significantly alter the traffic pattern in a transportation network and thus increase the societal risk posed upon traffic users.

TL;DR: Wang et al. as discussed by the authors proposed a two-stage dimension reduction method for efficient slope reliability analysis considering inherent spatial variability (ISV) of soil properties, which can reduce the number of original model evaluations significantly.

TL;DR: In this article, a multi-variate approach for assessing the seismic performance of structures is proposed, where the use of different multi-dimensional limit state functions is investigated either in terms of variability on the resulting fragility curves and as effect on the risk by calculating the probability of exceeding prescribed limit states.

TL;DR: In this paper, a reliability-based fragility method was described to evaluate the wind damage to roof cladding and trusses for contemporary houses in non-cyclonic regions of Australia.

TL;DR: A multi-objective reliability-based design optimization method is proposed based on probabilistic and ellipsoidal convex hybrid model and the intergeneration projection genetic algorithm and the micro multi- objective genetic algorithm are employed as inner and outer layer optimization operator.

TL;DR: This transformation of Kullback-Leibler divergence is used to establish a complementary indicator that is more perceptive, and more efficient for reliability sensitivity analysis, and is applied to research the global sensitivity analysis of an offshore wind turbine on a monopile foundation.

TL;DR: A new procedure for global convergence of the Reliability Index Approach, with practical efficiency, is presented and two novel evolutionary operators and a mixed real-binary genotype, suitable to hybridize any Evolutionary Algorithm with elitist strategy, are developed.

TL;DR: A multi-dimensional framework is analyzed, which integrates structural configuration of the support structure, manufacturing, detailed structural risk assessment, inspection and repair planning, and economic conditions into a coupled dynamic system accounting for the feedback loops resulted from the introduction of the probabilistic structural state to the life cost expenditure such as CAPEX, OPEX, and DECEX.

TL;DR: A new method is proposed to incorporate constraints on the first-passage probability into reliability-based optimization of structural design or topology by using the sequential compounding method.