Smoothing of EBSD datasets to quantify the geometrically necessary dislocation density: application to the discrimination of dynamically vs. post-dynamically recrystallized grains in forged nickel-based superalloys. - Mines Paris Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Smoothing of EBSD datasets to quantify the geometrically necessary dislocation density: application to the discrimination of dynamically vs. post-dynamically recrystallized grains in forged nickel-based superalloys.

Anthony Seret
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  • PersonId : 1003055
Alexis Nicolaÿ
Jean-Michel Franchet
Marc Bernacki
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Dates et versions

hal-02418251 , version 1 (18-12-2019)

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  • HAL Id : hal-02418251 , version 1

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Anthony Seret, Alexis Nicolaÿ, Jean-Michel Franchet, Charbel Moussa, Marc Bernacki, et al.. Smoothing of EBSD datasets to quantify the geometrically necessary dislocation density: application to the discrimination of dynamically vs. post-dynamically recrystallized grains in forged nickel-based superalloys.. La Métallurgie : Quel avenir!, Apr 2019, Nancy, France. ⟨hal-02418251⟩
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