Structural reliability under combined random load sequences

Rackwitz, R.; Flessler, Bernd

doi:10.1016/0045-7949(78)90046-9

Cited by 1,855 publications

(631 citation statements)

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“…The HLRF algorithm originally developed by Hasofer and Lind [64] and later extended to non-normal random variables by Rackwitz and Fiessler [65], is perhaps the most popular algorithm used to solve the constrained optimization problem in structural reliability analysis. It is well known that the original form of the algorithm is unstable and may not converge under certain conditions.…”

Section: Appendixmentioning

confidence: 99%

“…The evolution of the computing time of algorithms was also taken into account. Among the various existing algorithms, HLRF algorithm (see Appendix), proposed by Hasofer and Lind [64] and Rackwitz and Fiessler [65], was employed. The algorithm requires least amount of storage, has lower number of computations and converges fast for most situations [66].…”

Section: Assembly Simulation and Optimizationmentioning

confidence: 99%

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Tolerance analysis — Form defects modeling and simulation by modal decomposition and optimization

Homri

Goka

Levasseur

et al. 2017

Computer-Aided Design

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. Tolerance analysis aims on checking whether specified tolerances enable functional and assembly requirements. The tolerance analysis approaches discussed in literature are generally assumed without the consideration of parts' form defects. This paper presents a new model to consider the form defects in an assembly simulation. A Metric Modal Decomposition (MMD) method is henceforth, developed to model the form defects of various parts in a mechanism. The assemblies including form defects are further assessed using mathematical optimization. The optimization involves two models of surfaces: real model and difference surface-base method, and introduces the concept of signed distance. The optimization algorithms are then compared in terms of time consumption and accuracy. To illustrate the methods and their respective applications, a simplified over-constrained industrial mechanism in three dimensions is also used as a case study.

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Section: Appendixmentioning

confidence: 99%

Section: Assembly Simulation and Optimizationmentioning

confidence: 99%

Tolerance analysis — Form defects modeling and simulation by modal decomposition and optimization

Homri

Goka

Levasseur

et al. 2017

Computer-Aided Design

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“…One efficient way for reliability assessment is to employ the Most Probable Point (MPP) approach (Hasofer and Lind 1974). Integration of the reliability problem into the design optimization problem via the MPP optimality conditions was first proposed by Rackwitz and Fiessler (1978). With the MPP approach, all random quantities x and p are transformed into u in a standardized normal space, called u-space.…”

Section: Background Of Probabilistic Optimizationmentioning

confidence: 99%

Enhanced sequential optimization and reliability assessment method for probabilistic optimization with varying design variance

Yin

Chen

2006

Structure and Infrastructure Engineering

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The Sequential Optimization and Reliability Assessment (SORA) method is a single-loop method containing a serial of cycles of decoupled deterministic optimization and reliability assessment for improving the efficiency of probabilistic optimization. However, the original SORA method as well as some other existing single-loop methods do not take into account the effect of varying design variance (changing variance) in design problems. In this paper, to enhance the SORA method, three formulations are proposed in order to improve the efficiency for solving problems with changing variance. These formulations are categorized by the different strategies of Inverse Most Probable Point (IMPP) approximation. Mathematical examples and a speed reducer design problem are utilized to test and compare the effectiveness of the proposed formulations. The insight gained from our study on the applicability of different approaches can be extended and utilized in other probabilistic optimization strategies that require IMPP estimations.

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“…Traditional first-order reliability method (FORM) ( [2], [3], [4]) and the second-order reliability method (SORM) ( [5]; [6]; [7]; [8]) belong to this class. The simulation techniques have their origin in Monte Carlo simulation (MCS) method, which generates a large sample set of limit state evaluations and approximates the true value of the probability of failure by = , where is the number of samples lying in the failure region and S the total number of samples.…”

Section: Introductionmentioning

confidence: 99%

Review and application of Artificial Neural Networks models in reliability analysis of steel structures

et al. 2015

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Structural reliability under combined random load sequences

Cited by 1,855 publications

References 0 publications

Tolerance analysis — Form defects modeling and simulation by modal decomposition and optimization

Tolerance analysis — Form defects modeling and simulation by modal decomposition and optimization

Enhanced sequential optimization and reliability assessment method for probabilistic optimization with varying design variance

Review and application of Artificial Neural Networks models in reliability analysis of steel structures

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