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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/4785

    Título
    Development of an improved prediction method for the yield strength of steel alloys in the Small Punch Test
    Autor
    Calaf Chica, JoséUBU authority Orcid
    Bravo Díez, Pedro MiguelUBU authority Orcid
    Preciado Calzada, MónicaUBU authority Orcid
    Publicado en
    Materials & Design. 2018, V. 148, p. 153-166
    Editorial
    Elsevier
    Fecha de publicación
    2018-06
    ISSN
    0264-1275
    DOI
    10.1016/j.matdes.2018.03.064
    Abstract
    The Small Punch Test (SPT) is a miniaturized test to characterize the mechanical properties of the materials. The load-displacement curve obtained by this test does not directly provide the material parameters, and linear correlations between data obtained from SPT curve and each mechanical property are necessary. The main difficulty of these correlation methods is the high level of scattering showed when analyzing a wide set of materials in the same study. In this paper, a finite element analysis focused on steel alloys was performed to understand the specimen behavior in the early stages of the SPT. Present methods to correlate the material yield strength with the data obtained from the SPT curve were also analyzed via this FEM study to discover the meaning of the current correlation scattering for this mechanical property. This numerical research also proved the accuracy of the proposed correlation method for the yield strength via the SPT. The maximum slope of zone I (Slopeini) of the SPT curve showed an accurate correlation with this mechanical property. Focusing on steel alloys, experimental tensile tests and SPT's were performed to validate the numerical analysis and to demonstrate the suitability of the proposed Slopeini versus yield strength correlation method.
    Palabras clave
    Small Punch Test
    SPT
    Yield strength
    Materia
    Resistencia de materiales
    Strength of materials
    Ensayos (Tecnología)
    Testing
    URI
    http://hdl.handle.net/10259/4785
    Versión del editor
    https://doi.org/10.1016/j.matdes.2018.03.064
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