DOE CODE   /    Search Results   /    Constitutive Models via Automatic Differentiation v.1.0.0

Constitutive Models via Automatic Differentiation v.1.0.0

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/cmad
https://doi.org/10.11578/dc.20240606.5

SAVE / SHARE



SNL Badge

Abstract

SAND2024-00905O Constitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Developers:
Seidl, Daniel [1][2][3]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Release Date:
2024-02-12
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Version:
1.0.0
Licenses:
MIT License
Sponsoring Org.:
Code ID:
128172
Site Accession Number:
SCR #2985
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/cmad
https://doi.org/10.11578/dc.20240606.5

SAVE / SHARE



SNL Badge

Citation Formats

Seidl, Daniel. Constitutive Models via Automatic Differentiation v.1.0.0. Computer Software. https://github.com/sandialabs/cmad. USDOE. 12 Feb. 2024. Web. doi:10.11578/dc.20240606.5.
Seidl, Daniel. (2024, February 12). Constitutive Models via Automatic Differentiation v.1.0.0. [Computer software]. https://github.com/sandialabs/cmad. https://doi.org/10.11578/dc.20240606.5.
Seidl, Daniel. "Constitutive Models via Automatic Differentiation v.1.0.0." Computer software. February 12, 2024. https://github.com/sandialabs/cmad. https://doi.org/10.11578/dc.20240606.5.
@misc{ doecode_128172,
title = {Constitutive Models via Automatic Differentiation v.1.0.0},
author = {Seidl, Daniel},
abstractNote = {SAND2024-00905O Constitutive Models via Automatic Differentiation (CMAD) provides a software framework for solving constitutive or material model calibration problems. It relies on JAX's automatic differentiation capabilities to compute the derivatives needed for both forward and adjoint sensitivity analyses. The software can be used to implement constitutive models and calibrate the parameters from experimental data. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20240606.5},
url = {https://doi.org/10.11578/dc.20240606.5},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240606.5}},
year = {2024},
month = {feb}
}