{"id":22872277,"url":"https://github.com/algomaster99/meta-btp","last_synced_at":"2025-03-31T11:46:22.571Z","repository":{"id":103070522,"uuid":"324703954","full_name":"algomaster99/meta-btp","owner":"algomaster99","description":"Analysis of Work Hardening Behavior","archived":false,"fork":false,"pushed_at":"2021-12-29T22:25:11.000Z","size":13523,"stargazers_count":0,"open_issues_count":3,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-02-06T17:42:29.252Z","etag":null,"topics":["material-science","plasticity"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/algomaster99.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-12-27T06:45:16.000Z","updated_at":"2023-07-18T09:13:34.000Z","dependencies_parsed_at":null,"dependency_job_id":"528b5d4f-542e-4c57-ad10-d5227f393da6","html_url":"https://github.com/algomaster99/meta-btp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/algomaster99%2Fmeta-btp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/algomaster99%2Fmeta-btp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/algomaster99%2Fmeta-btp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/algomaster99%2Fmeta-btp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/algomaster99","download_url":"https://codeload.github.com/algomaster99/meta-btp/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246465218,"owners_count":20781919,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["material-science","plasticity"],"created_at":"2024-12-13T13:34:26.345Z","updated_at":"2025-03-31T11:46:22.552Z","avatar_url":"https://github.com/algomaster99.png","language":"Jupyter Notebook","readme":"# Analysis of Work Hardening Behaviour\n\nThe project implements various models to analyse work hardening behaviour of\nlight aluminium alloys. Apart from the work hardening, we have also implemented\nthe model for [YLD200][yld2000] which is useful in predicting yield criterion.\nThe eventual goal of this project is to plot formability limit diagram which\nhas a high relevance in industry.\n\n## Try out the project yourself\n\n### Prerequisites\n\n1. Python 3.6+\n2. Jupyter Notebook kernel\n\n### Setup\n\n1. Clone the project.\n   ```sh\n   git clone https://github.com/algomaster99/meta-btp.git\n   ```\n\n2. Install the dependencies required in the project.\n   ```sh\n   pip install -r requirements.txt\n   ```\n   Please note that you may install the dependencies globally or locally in a\n   [Python virtual environment][virtualenv]. The latter is recommended.\n\n3. Start the Jupyter notebook server.\n   ```sh\n   jupyter-notebook\n   ```\n\n### Feed script with dataset\n\nThe script for work hardening analysis takes a CSV file of the form:\n```sh\nengineering stain (mm/mm),engineering stress (MPa)\n```\nFor example,\n```sh\n1E-05,0.05602\n1E-05,0.11128\n2E-05,0.21463\n3E-05,0.44231\n```\n\nAll of your datasets have to be fed to the entry point of the project which\nis [dataset_initialisation](dataset_initialisation.ipynb). Inside the notebook,\nunder the heading \"Dataset\", there is an array which takes in\n**1 or more paths** to various datasets. Some functions in the script will show\na combined plot of the datasets passed whereas some will show each of them\nindividually.\n\n## Outputs\n\nThe script will automatically generate an *output* directory at the root of the\nproject. It will store the necessary parameters and graphs obtained while\nrunning the script. Alternate way to save plots obtained in the script is to\nright-click on them and save.\n\n## Submission\n\nThe [report](submission/BTP%20Report.pdf) and\n[presentation](submission/BTP%20PPT.pptx) of this project is also hosted\nonline. Click on the respective links to have a look at them.\n\n## FAQ\n\n**Q. Where to enter path to datasets?**\n\nA. Read [this section][dataset].\n\n**Q. Do I need to have crystal plasticity data to work with YLD2000.ipynb?**\n\nA. No, it is optional. The script is self-sufficient. You can comment the lines\n   related to it (they have been marked in the notebook) and the script would\n   run without it.\n\n**Q. How to change resolution of graphs and figures?**\n\nA. The script uses [fig.set_dpi][figure] to set the DPI of the figures.\n   Alternatively, you can also pass `dpi` argument to `fig.savefig`.\n\n[yld2000]: https://www.sciencedirect.com/science/article/abs/pii/S0749641902000190\n[virtualenv]: https://pypi.org/project/virtualenv/\n[figure]: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.figure.html\n[dataset]: #feed-script-with-dataset\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falgomaster99%2Fmeta-btp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falgomaster99%2Fmeta-btp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falgomaster99%2Fmeta-btp/lists"}