Learning Mechanical Vibration Engineering Through Computation
======================================================================== 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:
- That students can learn about mechanical vibrations engineering through
- That the computer allows students to solve vibration engineering problems
- Students learn best by doing. The content is meant to used in class while the
- That each lesson should have a motivated real life example that drives the
- Open access materials promote easy reuse, remixing, and dissemination.
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:
- Students will be able to analyze vibrational measurement data to draw
- Students will be able to create simple mathematical and computational models
- Students will be able to design a mechanical structure that has desirable
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 =======
- Jason K. Moore, Faculty, Mechanical and Aerospace Engineering Department,
- Kenneth Lyons, Graduate Student, Mechanical and Aerospace Engineering
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