SAM: Soumissions récentes
Voici les éléments 1556-1562 de 6547
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Communication avec acte; ; ;
SEGONDS, Frederic; VERON, Philippe (Proceedings of JCM'20, 2020)
In manufacturing industries, the design of a product needs to comply with many design rules. These rules are essentials as they help industrial designers to create high quality conception in an efficient way. [Problem] ... -
Article dans une revue avec comité de lecture; ; ; ; ; ; ; ;TRAXER, Olivier (Elsevier Masson, 2020)
Kidney Stone Calculator (KSC) est un outil que nous avons développé pour mesurer le volume lithiasique total (VLT) et estimer la durée opératoire de lithotritie laser endocorporelle (LLE) au cours de l’urétérorénoscopie ...
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Article dans une revue avec comité de lecture(Elsevier, 2020)The aim of this work is to study the role of intra-granular voids on the macroscopic behavior and the mi- crostructure of uranium dioxide (UO 2 ) for different strain conditions in the high temperature dislocational creep ...
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Article dans une revue avec comité de lecture; ;COLIN, Xavier; ROLAND, Sébastien (Elsevier BV, 2021)
In this article, the aging behavior of nuclear-grade low voltage cables, characterized by different geometries and insulation compositions, is investigated. Cables were subjected to radio-chemical aging at different dose ...
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Article dans une revue avec comité de lecture;GHNATIOS, Chady; ; ; CUETO, Elias; CHINESTA SORIA, Francisco (MDPI AG, 2021)
A novel Model Order Reduction (MOR) technique is developed to compute high-dimensional parametric solutions for electromagnetic fields in synchronous machines. Specifically, the intrusive version of the Proper Generalized ...
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Article dans une revue avec comité de lecture; ; ;REGNIER, Gilles (Wiley-Blackwell, 2021)
The Hermans orientation factor is a scalar giving a simple assessment of molecular or crystal orientation in a polymer. It is usually determined from X-ray diffraction measurements. The evaluation of the Hermans orientation ...
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Article dans une revue avec comité de lecture; ;CUETO, Elias; CHINESTA SORIA, Francisco (Elsevier Masson, 2020)
The present work aims at analyzing issues related to the data manifold dimensionality. The interest of the study is twofold: (i) first, when too many measurable variables are considered, manifold learning is expected to ...
