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    Improvement of the Inverse Finite Element Analysis Approach for Tensile and Toughness Predictions by Means of Small Punch Technique

    Source: Journal of Engineering for Gas Turbines and Power:;2021:;volume( 143 ):;issue: 007::page 071008-1
    Author:
    Kulawinski, Dirk
    ,
    Iding, Kevin
    ,
    Schornstein, Robin
    ,
    Özdemir-Weingart, Dasgin
    ,
    Dumstorff, Peter
    DOI: 10.1115/1.4049900
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper focuses on the inverse finite element analysis (FEA) to calculate the small punch technique (SPT) tests and the prediction of the tensile and fracture toughness behavior. For the description of the SPT tests via FEA, the hardening rule of Ramberg–Osgood (RO) and the damage model of Gursson–Tvergaard–Needleman (GTN) were used. The inverse FEA optimization process cannot provide a unique solution for the 12 parameters included in the material model. This results from a dependency between some parameters, which leads to the same solution in the optimization. Hence, a novel description of the dependent parameters was developed and implemented within the optimization process. Therefore, an enhanced inverse FEA approach was proposed, which provides a fast converging solution for determination of the material model parameters. Within this study, the forged turbine shaft material EN: 27NiCrMoV15-6 was investigated. For comparison purpose, SPT tests as well as tensile tests and fracture toughness tests were carried out. In the case of the tensile properties, the test and simulation show coincidence in the curve and the characteristic values. For the toughness behavior, the characteristic value of the test was met by the simulation.
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      Improvement of the Inverse Finite Element Analysis Approach for Tensile and Toughness Predictions by Means of Small Punch Technique

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4277464
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    contributor authorKulawinski, Dirk
    contributor authorIding, Kevin
    contributor authorSchornstein, Robin
    contributor authorÖzdemir-Weingart, Dasgin
    contributor authorDumstorff, Peter
    date accessioned2022-02-05T22:23:53Z
    date available2022-02-05T22:23:53Z
    date copyright3/29/2021 12:00:00 AM
    date issued2021
    identifier issn0742-4795
    identifier othergtp_143_07_071008.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4277464
    description abstractThis paper focuses on the inverse finite element analysis (FEA) to calculate the small punch technique (SPT) tests and the prediction of the tensile and fracture toughness behavior. For the description of the SPT tests via FEA, the hardening rule of Ramberg–Osgood (RO) and the damage model of Gursson–Tvergaard–Needleman (GTN) were used. The inverse FEA optimization process cannot provide a unique solution for the 12 parameters included in the material model. This results from a dependency between some parameters, which leads to the same solution in the optimization. Hence, a novel description of the dependent parameters was developed and implemented within the optimization process. Therefore, an enhanced inverse FEA approach was proposed, which provides a fast converging solution for determination of the material model parameters. Within this study, the forged turbine shaft material EN: 27NiCrMoV15-6 was investigated. For comparison purpose, SPT tests as well as tensile tests and fracture toughness tests were carried out. In the case of the tensile properties, the test and simulation show coincidence in the curve and the characteristic values. For the toughness behavior, the characteristic value of the test was met by the simulation.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleImprovement of the Inverse Finite Element Analysis Approach for Tensile and Toughness Predictions by Means of Small Punch Technique
    typeJournal Paper
    journal volume143
    journal issue7
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.4049900
    journal fristpage071008-1
    journal lastpage071008-9
    page9
    treeJournal of Engineering for Gas Turbines and Power:;2021:;volume( 143 ):;issue: 007
    contenttypeFulltext
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