Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Prediction of the evolution of the stress field of polycrystals
  undergoing elastic-plastic deformation with a hybrid neural network model   Crystal plasticity theory is often employed to predict the mesoscopic states
of polycrystalline metals, and is well-known to be costly to simulate. Using a
neural network with convolutional layers encoding correlations in time and
space, we were able to predict the evolution of the stress field given only the
initial microstructure and external loading. In comparison to our recent work
we were able to predict not only the spatial average of the stress response but
the field itself. We show that the stress fields and their rates are in high
fidelity with the crystal plasticity data and have no visible artifacts.
Furthermore the distribution stress throughout the elastic to fully plastic
transition match the truth provided by held out crystal plasticity data. Lastly
we demonstrate the efficacy of the trained model in material characterization
and optimization tasks.

21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
9
The categories of this paper are: nlin
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg