moorepants / resonance

Learning Mechanical Vibration Engineering Through Computation
https://moorepants.github.io/resonance
MIT License
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engineering jupyter mechanical-engineering python vibrations

======================================================================== Resonance: Learning Mechanical Vibration Engineering Through Computation

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Introduction

This repository contains the interactive learning materials designed for the upper-level UC Davis engineering course on Mechanical Vibrations (ENG 122). The materials are designed with these ideas in mind:

The current course website can be found at:

https://moorepants.github.io/eng122/

All of the Jupyter notebooks are rendered at:

http://moorepants.github.io/resonance

Learning Objectives

There are three broad learning objectives that we focus on in the course:

  1. Students will be able to analyze vibrational measurement data to draw conclusions about the measured system's vibrational nature and describe how the systems behaves vibrational.
  2. Students will be able to create simple mathematical and computational models of real vibrating systems that can be used to answer specific questions about the system by concisely demonstrating the vibrational phenomena.
  3. Students will be able to design a mechanical structure that has desirable vibrational behavior.

Students that master these three core learning objectives will be well prepared to use mechanical vibration concepts, theories, and tools to solve engineering problems.

For a more detailed topical outline with specific per-activity learning objectives see the outline <outline.rst>_.

Assessment

The students will be assessed through a series of in- and out-of- class exercises that focus on individual lesson topics, two examinations, and on an individual open-ended vibration design project.

Authors

License

The contents of this repository are licensed under the MIT license.

Acknowledgements

Much of this work has been made possible through the Undergraduate Instructional Innovation Program funds provided by the Association of American Universities (AAU) and Google which is administered by UC Davis's Center for Educational Effectiveness.

This work is also made possible by the broad open source software stack that underpins the Scientific Python Ecosystem, in particular: Jupyter, NumPy, SymPy, SciPy, and matplotlib.

Installation

For users, you can create a conda environment called resonance by downloading the environment.yml file and typing the following at the command line::

$ conda env create -f environment.yml

This environment can be activated with::

$ conda activate resonance

To properly view the exercises you will need to enable the exercise2 notebook extension::

(resonance)$ jupyter nbextension enable exercise2/main

If you want to develop resonance, use the dev-environment.yml file::

$ conda env create -f dev-environment.yml $ conda activate resonance-dev

If you don't want to use our environments, you can use pip to install resonance::

$ pip install resonance