Bridge fatigue reliability assessment using probability density functions of equivalent stress range based on field monitoring data

Kwon, Kihyon; Frangopol, Dan M.

doi:10.1016/j.ijfatigue.2010.01.002

Cited by 182 publications

(87 citation statements)

References 12 publications

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“…The cut-off threshold s c is the lowest stress level considered in the stress range bin histogram [30]. In many cases, depending on the stress range bin histogram, a two-parameter PDF can be used considering s c = 0.…”

Section: Equivalent Constant Amplitude Stress Rangementioning

confidence: 99%

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Fatigue reliability and service life prediction of aluminum naval ship details based on monitoring data

Soliman

Barone

Frangopol

2014

Structural Health Monitoring

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The evolution of naval vessels towards high-speed crafts subjected to severe sea conditions has promoted an increasing interest in lightweight high-strength materials. Due to its strength and weight characteristics, aluminum has been proven especially suitable as construction material for hull structures, as well as other vessel parts. However, fatigue in aluminum naval crafts needs to be effectively addressed for the proper life-cycle assessment. Structural health monitoring (SHM) systems constitute effective tools for measuring the structural response and assessing the structural performance under actual operational conditions. In this paper, an approach for using SHM information in the fatigue reliability analysis and service life prediction of aluminum naval vessels is presented. The accumulated fatigue damage and the fatigue reliability are quantified based on SHM data acquired under different operational conditions, specified by the ship speeds, sea states, and heading angles. Additionally, an approach for estimating the reliability-based fatigue life under a given operational profile is presented. Seakeeping trial data of an aluminum high-speed naval vessel are used to illustrate the proposed approach.

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Section: Equivalent Constant Amplitude Stress Rangementioning

confidence: 99%

“…It is directly linked to the probability of failure P f (i.e. the probability of violating a certain limit state), through the following relationship [30] …”

Section: Fatigue Reliabilitymentioning

confidence: 99%

Fatigue reliability and service life prediction of aluminum naval ship details based on monitoring data

Soliman

Barone

Frangopol

2014

Structural Health Monitoring

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“…CG Soares and Ivanov 12 deal with the reliability of hull girders concentrated on the hull girder collapse mode. Kwon and Frangopol 13 proposed a bridge fatigue reliability assessment using probability density functions of the equivalent stress range based on field monitoring data. Soares and Garbatov 14 presented for the assessment of the reliability of a ship hull with respect to fatigue failure of the ship hull girder.…”

Section: Introductionmentioning

confidence: 99%

Hybrid reliability analysis of structural fatigue life: Based on Taylor expansion method

Meng

Feng

Zhou

et al. 2016

Advances in Mechanical Engineering

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A new method for computing the failure probability of the fatigue life is proposed, dealing with uncertain problems with both random and interval variables. Using a Taylor expansion and the concept of statistical moment, the first four central moments of the structural fatigue life performance function are obtained. Then, using a second Taylor expansion, the first four central moments are expanded at the midpoint of the interval variable, and the intervals of the statistical moments of the performance function are calculated. The obtained moment information is applied into an Edgeworth series expansion expression, giving the cumulative distribution function of the structural fatigue life performance function and getting its interval of the failure probability. Two numerical examples of growing complexity are employed to demonstrate the feasibility of the proposed approach.

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“…Imam et al [17] proposed a probabilistic fatigue assessment methodology for riveted railway bridges under historical and present-day train loading. Kwon and Frangopol [18] performed fatigue reliability assessment of steel bridges using the probability density function (PDF) of the equivalent stress ranges obtained by field measurement data. Ni et al [19] proposed a fatigue reliability model for fatigue life and reliability evaluation of steel bridges with long-term monitoring data, which integrates the probability distribution of hot spot stress range with a continuous probabilistic formulation of Miner's damage cumulative rule.…”

Section: Introductionmentioning

confidence: 99%

Fatigue Reliability of Ageing Railway Bridges: Feasibility of Probabilistic Approach

Adasooriya¹

2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Bridge fatigue reliability assessment using probability density functions of equivalent stress range based on field monitoring data

Cited by 182 publications

References 12 publications

Fatigue reliability and service life prediction of aluminum naval ship details based on monitoring data

Fatigue reliability and service life prediction of aluminum naval ship details based on monitoring data

Hybrid reliability analysis of structural fatigue life: Based on Taylor expansion method

Fatigue Reliability of Ageing Railway Bridges: Feasibility of Probabilistic Approach

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