GithubHelp home page GithubHelp logo

louhz / deep-learning-for-indentation Goto Github PK

View Code? Open in Web Editor NEW

This project forked from lululxvi/deep-learning-for-indentation

0.0 0.0 0.0 96 KB

Extraction of mechanical properties of materials through deep learning from instrumented indentation

License: Apache License 2.0

Python 100.00%

deep-learning-for-indentation's Introduction

Extraction of mechanical properties of materials through deep learning from instrumented indentation

The data and code for the paper L. Lu, M. Dao, P. Kumar, U. Ramamurty, G. E. Karniadakis, & S. Suresh. Extraction of mechanical properties of materials through deep learning from instrumented indentation. Proceedings of the National Academy of Sciences, 117(13), 7052-7062, 2020.

Data

All the data is in the folder data.

Code

All the code is in the folder src. The code depends on the deep learning package DeepXDE.

  • data.py: The classes are used to read the data file. Remember to uncomment certain line in ExpData to scale dP/dh.
  • nn.py: The main functions of multi-fidelity neural networks.
  • model.py: The fitting function method. Some parameters are hard-coded in the code, and you should modify them for different cases.
  • fit_n.py: Fit strain-hardening exponent.
  • mfgp.py: Multi-fidelity Gaussian process regression.

Cite this work

If you use this code for academic research, you are encouraged to cite the following paper:

@article{Lu7052,
  author  = {Lu, Lu and Dao, Ming and Kumar, Punit and Ramamurty, Upadrasta and Karniadakis, George Em and Suresh, Subra},
  title   = {Extraction of mechanical properties of materials through deep learning from instrumented indentation},
  volume  = {117},
  number  = {13},
  pages   = {7052--7062},
  year    = {2020},
  doi     = {10.1073/pnas.1922210117},
  journal = {Proceedings of the National Academy of Sciences}
}

Questions

To get help on how to use the data or code, simply open an issue in the GitHub "Issues" section.

deep-learning-for-indentation's People

Contributors

lululxvi avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.