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International Journal for Uncertainty Quantification
Главный редактор: Habib N. Najm (open in a new tab)
Ассоциированный редакторs: Dongbin Xiu (open in a new tab) Tao Zhou (open in a new tab)
Редактор-основатель: Nicholas Zabaras (open in a new tab)

Выходит 6 номеров в год

ISSN Печать: 2152-5080

ISSN Онлайн: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

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A UNIFIED FRAMEWORK FOR RELIABILITY ASSESSMENT AND RELIABILITY-BASED DESIGN OPTIMIZATION OF STRUCTURES WITH PROBABILISTIC AND NONPROBABILISTIC HYBRID UNCERTAINTIES

Том 6, Выпуск 5, 2016, pp. 387-404
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016979
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Краткое описание

In the reliability assessment of structures, a situation we frequently encounter is that by means of available information some parameters involved can be depicted accurately by their probability distributions and others can only be described by the bounds or ranges of variations. So, it is meaningful to construct a reliability model by which the probabilistic and nonprobabilistic uncertainties can be treated reasonably in an integrated framework. The main purpose of this paper is to establish a strictly mathematical foundation and a unified framework for reliability assessment and reliability-based design optimization (RBDO) of structures in the presence of both probabilistic and nonprobabilistic (bounded) hybrid uncertainties. The input uncertain parameters are divided into two different groups and treated respectively as random variables and interval variables, and the traditional probability and convex set models are adopted to describe the probabilistic and bounded uncertainties, respectively. In the reliability measuring system developed in the paper, dimensionless hybrid reliability indices are defined in different situations by adopting a similar method as for the traditional probabilistic reliability method for structures. A computational procedure for performing the RBDO of structures with hybrid uncertainties is presented. Two numerical examples are investigated to demonstrate the effectiveness and feasibility of the presented method.

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