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Bieler, Thomas R.

Publications and source records attributed to Bieler, Thomas R..

A computational study of how surfaces affect slip family activity

Plastic deformation behavior is most conveniently assessed by characterization on a surface, but whether such observations are representative of bulk properties is uncertain. Motivated by reported inconsistencies in slip resistance probed at different depths, we investigated (i) whether the average slip family activity is affected by the presence of a surface and (ii) how the kinematic nature of available slip families influences a potential surface effect. The slip family activity as a function of distance from the surface was extracted from full-field crystal plasticity simulations of random polycrystalline hexagonal close-packed (HCP) and body-centered cubic (BCC) metals as examples of mixed in contrast to universally-high numbers of slip systems per family. Under certain conditions, a deviation from bulk slip activity is observed up to about two grains from the surface. For the easiest (least slip-resistant) family, a surface effect of decreasing activity with depth emerges if the number of slip systems falls below about six. For harder families, slip activity always increases with depth. Furthermore, these phenomena are explained on the basis of varying constraints with depth in connection with the kinematic properties of slip families in the material.

36 MATERIALS SCIENCE↗

Evaluating the Taylor hardening model in polycrystalline Ti using high energy X-ray diffraction microscopy

High energy X-ray diffraction microscopy (HEDM) was employed to index nearly 1000 grains in a polycrystalline Ti specimen and characterize their deformation during an incremental tensile test. For each grain, the positions of its associated diffraction peaks were used for analyzing its evolving crystal orientation and stress tensor. The azimuthal breadth of each peak at different load steps was measured, allowing measurement of initial yielding and providing an estimate of the dislocation density evolution in each grain. Furthermore, the Taylor hardening model was evaluated grain by grain using the above data, indicating that it can represent hardening in most grains. The yield stress and the strain hardening coefficient for all grains were statistically analyzed with respect to grain orientation, grain size, slip systems, and the surrounding neighborhood to examine how the yield stress and hardening are correlated.

36 MATERIALS SCIENCE↗

The effect of microstructure on the relationship between grain boundary sliding and slip transmission in high purity aluminum

The relationship between grain boundary sliding (GBS) and slip transmission is investigated experimentally at grain boundaries in 99.99% aluminum with a through-thickness, coarse grained microstructure deformed in tension at 190 °C. Using scanning electron microscope enabled digital image correlation (SEM-DIC) and electron backscatter diffraction (EBSD), high resolution strain fields and microstructural information were measured to examine the influence of microstructural neighborhoods on interactions between GBS and slip transmission and strain localization. Several distinct cases are presented that highlight important microstructural factors that govern deformation near grain boundaries. The findings include (1) direct transmission and GBS were anti-compatible and facilitated by opposing boundary types (low misorientation and high energy grain boundaries respectively); (2) increased GBS activity was correlated with decreased indirect transmission behavior; (3) GBS accommodation at triple junctions was enabled by intragranular plasticity; and (4) the local intragranular plastic strain discontinuity between grains determined the magnitude of GBS gradients. Finally, this work provides insight into the nature of these mechanisms and can be used to identify strain transfer criteria that can lead to improved GBS-sensitive crystal plasticity models.

36 MATERIALS SCIENCE↗

Grain boundary slip transfer classification and metric selection with artificial neural networks

An artificial neural network is used to evaluate the effectiveness of six metrics and their combinations to assess whether slip transfers across grain boundaries in coarse-grained oligocrystalline Al foils. This approach extends the one- or two-dimensional projections formerly applied to analyze slip transfer. The accuracy of this binary classification reaches around 87% for the best single metric and around 90% when considering two or more metrics simultaneously. Here, the results suggest slip transfer mostly depends on the geometric relationship between grains. Training a double-layer network having 10 nodes per hidden layer with 40 measurements is sufficient to render the maximum accuracy.

36 MATERIALS SCIENCE↗