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contributor authorBouchenot, Thomas
contributor authorPatel, Kirtan
contributor authorGordon, Ali P.
contributor authorShinde, Sachin
date accessioned2023-11-29T19:27:22Z
date available2023-11-29T19:27:22Z
date copyright2/20/2023 12:00:00 AM
date issued2/20/2023 12:00:00 AM
date issued2023-02-20
identifier issn0094-4289
identifier othermats_145_3_031004.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4294771
description abstractWhile industrial gas turbine blades are commonly designed to resist creep and high-cycle fatigue (HCF) failure, the combination of these two loading conditions is seldom considered. The effect of creep damage elicited prior or concurrent to HCF loading is not well established and can significantly reduce the HCF lifetime of these critical components. A comprehensive life prediction model capable of capturing these superimposed effects is needed to ensure current reliability standards are maintained when designing aggressively loaded, next-generation industrial gas turbine blades. The consequence of combined HCF and creep loading to the lifetime a Ni-base superalloy is characterized and modeled in this study. Composition and calibration of the model are carried out using data from HCF tests conducted on virgin and pre-crept specimens at 750 °C and 850 °C. The experimental data encompass a wide range of stress ratios and pre-creep strains to mimic to the expansive set of potential turbine blade loading conditions. The proposed microstructurally informed model is based on existing principles and relies on test data and information gathered from a comprehensive failure analysis of the tested samples.
publisherThe American Society of Mechanical Engineers (ASME)
titleCreation of a Life Prediction Model for Combined High-Cycle Fatigue and Creep
typeJournal Paper
journal volume145
journal issue3
journal titleJournal of Engineering Materials and Technology
identifier doi10.1115/1.4054889
journal fristpage31004-1
journal lastpage31004-11
page11
treeJournal of Engineering Materials and Technology:;2023:;volume( 145 ):;issue: 003
contenttypeFulltext


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