https://github.com/kyleniemeyer/me373-book

Electronic book for ME 373
https://github.com/kyleniemeyer/me373-book

differential-equations matlab numerical-methods

Last synced: about 1 month ago
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Electronic book for ME 373

• Host: GitHub
• URL: https://github.com/kyleniemeyer/me373-book
• Owner: kyleniemeyer
• License: bsd-3-clause
• Created: 2020-01-27T06:28:21.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2023-10-02T23:57:16.000Z (over 1 year ago)
• Last Synced: 2024-06-12T17:43:45.737Z (7 months ago)
• Topics: differential-equations, matlab, numerical-methods
• Language: Jupyter Notebook
• Homepage: https://kyleniemeyer.github.io/ME373-book/
• Size: 34.6 MB
• Stars: 10
• Watchers: 3
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE-text.txt
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# ME373-book

This repository contains an electronic textbook for the course ME 373, Mechanical Engineering Methods, taught at [Oregon State University](https://oregonstate.edu) by [Prof. Kyle Niemeyer](https://mime.oregonstate.edu/people/kyle-niemeyer).

The catalog description for this course is

> Analytical and numerical methods for solving representative mechanical engineering problems.

and the course learning objectives are:

At the end of this course, students will be able to:

1. Formulate and solve mechanical engineering initial value problems of practical interest represented by first and second order differential equations using both analytical and explicit numerical methods.

2. Formulate and solve mechanical engineering boundary value problems of practical interest represented by first and second order differential equations using both analytical and explicit numerical methods.

3. Formulate and numerically solve partial differential equations.

4. Identify and implement the most appropriate numerical method for solving a specific type of engineering problem. In addition, be able to recognize the advantages, disadvantages, and limitations of numerical methods.

This course combines analytical solutions to differential equations with numerical solution approaches, heavily relying on Matlab.

## Contributing

Contributions are welcome! 

The code portions of this material are licensed under the BSD 3-Clause License (described in `LICENSE.txt`) while the non-code portions of the material are licensed under the Creative Commons Attribution License (CC-BY, described in `LICENSE-text.txt`).