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    A Probabilistic Model for Forging Flaw Crack Nucleation Processes

    Source: Journal of Engineering for Gas Turbines and Power:;2021:;volume( 143 ):;issue: 010::page 0101012-1
    Author:
    Radaelli, Francesco
    ,
    Amann, Christian
    ,
    Aydin, Ali
    ,
    Varfolomeev, Igor
    ,
    Gumbsch, Peter
    ,
    Kadau, Kai
    DOI: 10.1115/1.4051426
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A probabilistic model for quantifying the number of load cycles for nucleation of forging flaws into a crack has been developed. The model correlates low cycle fatigue (LCF) data, ultrasonic testing (UT) indication data, flaw morphology and type with the nucleation process. The nucleation model is based on a probabilistic LCF model applied to finite element analyses (FEA) of flaw geometries. The model includes statistical size and notch effects. In order to calibrate the model, we conducted experiments involving specimens that include forging flaws. The specimens were machined out from heavy duty steel rotor disks for the energy sector. The large disks, including ultrasonic indications on the millimeter scale, were cut into smaller segments in order to efficiently machine specimens including manufacturing related forging flaws. We conducted cyclic loading experiments at a variety of temperatures and high stresses in order to capture realistic engine operating conditions for flaws as they occur in service. This newly developed model can be incorporated into an existing probabilistic fracture mechanics framework and enables a reliable risk quantification allowing to support customer needs for more flexible operational profiles due to the emergence of renewable energy sources.
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      A Probabilistic Model for Forging Flaw Crack Nucleation Processes

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4278202
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorRadaelli, Francesco
    contributor authorAmann, Christian
    contributor authorAydin, Ali
    contributor authorVarfolomeev, Igor
    contributor authorGumbsch, Peter
    contributor authorKadau, Kai
    date accessioned2022-02-06T05:31:10Z
    date available2022-02-06T05:31:10Z
    date copyright9/3/2021 12:00:00 AM
    date issued2021
    identifier issn0742-4795
    identifier othergtp_143_10_101012.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4278202
    description abstractA probabilistic model for quantifying the number of load cycles for nucleation of forging flaws into a crack has been developed. The model correlates low cycle fatigue (LCF) data, ultrasonic testing (UT) indication data, flaw morphology and type with the nucleation process. The nucleation model is based on a probabilistic LCF model applied to finite element analyses (FEA) of flaw geometries. The model includes statistical size and notch effects. In order to calibrate the model, we conducted experiments involving specimens that include forging flaws. The specimens were machined out from heavy duty steel rotor disks for the energy sector. The large disks, including ultrasonic indications on the millimeter scale, were cut into smaller segments in order to efficiently machine specimens including manufacturing related forging flaws. We conducted cyclic loading experiments at a variety of temperatures and high stresses in order to capture realistic engine operating conditions for flaws as they occur in service. This newly developed model can be incorporated into an existing probabilistic fracture mechanics framework and enables a reliable risk quantification allowing to support customer needs for more flexible operational profiles due to the emergence of renewable energy sources.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Probabilistic Model for Forging Flaw Crack Nucleation Processes
    typeJournal Paper
    journal volume143
    journal issue10
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4051426
    journal fristpage0101012-1
    journal lastpage0101012-8
    page8
    treeJournal of Engineering for Gas Turbines and Power:;2021:;volume( 143 ):;issue: 010
    contenttypeFulltext
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