Fracture mechanics based fatigue life prediction for a weld toe crack under constant and variable amplitude random block loading—Modeling and uncertainty estimation
| Autor: | Johan Maljaars, H.H. Snijder, Davide Leonetti |
|---|---|
| Přispěvatelé: | Aluminium Structures, Steel Structures, EAISI High Tech Systems |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Fatigue crack growth at weld
Materials science Mechanical Engineering Linear elasticity Linear elastic fracture mechanics 0211 other engineering and technologies Fracture mechanics 02 engineering and technology Mechanics Paris' law 020303 mechanical engineering & transports Amplitude 0203 mechanical engineering Mechanics of Materials Range (statistics) Mechanically short and long cracks General Materials Science Constant (mathematics) Material properties Stress intensity factor 021101 geological & geomatics engineering Cyclic R-curve |
| Zdroj: | Engineering Fracture Mechanics, 242:107487. Elsevier |
| ISSN: | 0013-7944 |
| Popis: | Propagation of weld toe cracks under cyclic loading is often predicted using fracture mechanics. In as welded condition, most of the propagation life is spent as a short crack, which is known to behave differently than a long crack. Several studies have been conducted with the aim of correlating the fatigue crack growth rate and the threshold condition of small cracks to the well known linear elastic crack driving force parameter Δ K , the stress intensity factor range. In many cases, the application of such models requires the quantification of material properties and model parameters that are difficult to obtain from tests, and therefore scarcely available. The present paper bypasses this inconvenience by making use of the square root of area, a r e a , parameter proposed by Murakami. Successively, a linear elastic fracture mechanics based fatigue crack growth model is formulated for physically short and long cracks under constant and variable amplitude random block loading. The uncertainty of the model parameters is quantified in a frequentist statistical framework. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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