Thermo-mechanical FE model with memory effect for 304L austenitic stainless steel presenting microstructure gradient

Abstract : The aim of this work is to study the recrystallization in the 904L austenitic stainless steel, which underwent a cold rolling with two different deformation amounts (50

The microstructure of the as received 904L alloy is shown in Figure 1-a. The microstructure consists of a matrix γ phase, with equiaxed grains randomly distributed, without

The adopted way consists in carrying out and optimizing aging heat treatments accompanied by restoring heat treatment.A preliminary treatment of hardening since 1080°C, 1120°C

We used our test to compare net survival distributions between Black and White patients stratified on stage, which is known to have an important effect on net cancer survival..

The aim of the present study is to investigate the effects of solvent type (ethanol, methanol, acetone and water), acetone concentration (20–100%, v/v), solvent acidity

We model the shifts between the maxima at different frequencies as due to changes in the physical parameters of the emitting region assuming either free-free absorption or

(2009) ont proposé l’algorithme du score de propension en grande dimension (high-dimensional Propensity Score, hdPS) pour sélectionner de manière automatique les variables à

As expected, using graph cluster randomization reduces bias (Figure 2), es- pecially when the peer effects and direct effects are large relative to the baseline (α = −1.5), and when