Show simple item record

contributor authorSalimi, Hossein
contributor authorKiad, Saeed
contributor authorPourgol-Mohammad, Mohammad
date accessioned2019-02-28T11:02:53Z
date available2019-02-28T11:02:53Z
date copyright10/3/2017 12:00:00 AM
date issued2018
identifier issn2332-9017
identifier otherrisk_004_02_021004.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252087
description abstractIn this study, stochastic analysis is aimed for space structures (satellite in low earth orbit, made of aluminum 2024-T3), with the focus on fatigue failure. Primarily, the deterministic fatigue simulation is conducted using Walker and Forman models with constant amplitude loading. Deterministic crack growth was numerically simulated by the authors developed algorithm and is compared with commercial software for accuracy verification as well as validation with the experimental data. For the stochastic fatigue analysis of this study, uncertainty is estimated by using the Monte Carlo simulation. It is observed that by increasing the crack length, the standard deviation (the measure of uncertainty) increases. Also, it is noted that the reduction in stress ratio has the similar effect. Then, stochastic crack growth model, proposed by Yang and Manning, is employed for the reliability analysis. This model converts the existing deterministic fatigue models to stochastic one by adding a random coefficient. Applicability of this stochastic model completely depends on accuracy of base deterministic function. In this study, existing deterministic functions (power and second polynomial) are reviewed, and three new functions, (i) fractional, (ii) global, and (iii) exponential, are proposed. It is shown that the proposed functions are potentially used in the Yang and Manning model for better results.
publisherThe American Society of Mechanical Engineers (ASME)
titleStochastic Fatigue Crack Growth Analysis for Space System Reliability
typeJournal Paper
journal volume4
journal issue2
journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
identifier doi10.1115/1.4037219
journal fristpage21004
journal lastpage021004-7
treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:002
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record