Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Calibrating constitutive models with full-field data via physics
  informed neural networks   The calibration of solid constitutive models with full-field experimental
data is a long-standing challenge, especially in materials which undergo large
deformation. In this paper, we propose a physics-informed deep-learning
framework for the discovery of constitutive model parameterizations given
full-field displacement data and global force-displacement data. Contrary to
the majority of recent literature in this field, we work with the weak form of
the governing equations rather than the strong form to impose physical
constraints upon the neural network predictions. The approach presented in this
paper is computationally efficient, suitable for irregular geometric domains,
and readily ingests displacement data without the need for interpolation onto a
computational grid. A selection of canonical hyperelastic materials models
suitable for different material classes is considered including the
Neo-Hookean, Gent, and Blatz-Ko constitutive models as exemplars for general
hyperelastic behavior, polymer behavior with lock-up, and compressible foam
behavior respectively. We demonstrate that physics informed machine learning is
an enabling technology and may shift the paradigm of how full-field
experimental data is utilized to calibrate constitutive models under finite
deformations.

15
The categories of this paper are: nucl-ex
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
8
The categories of this paper are: hep-ex
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org