ITA PhD course
Computational research with COMPAS
Description
The PhD-level course (primarily for A&T PhDs) will introduce computational methods for architecture engineering, fabrication & construction, incentivising computational literacy. Students learn the theoretical background and basic implementation details of fundamental data structures and algorithms, and to solve real-world problems using the COMPAS framework and other open-source libraries.
Learning objectives
- understand the scope and relevance of computational methods for architecture and engineering research and practice,
- the theoretical background of fundamental data structures,
- the basic principles of algorithmic design;
- implement basic versions of prevalent algorithms related to architectural geometry, structural design, robotic assembly, volumetric modeling & 3D-printing, high-performance computation;
- use sophisticated algorithms available through open-source libraries to solve real-world problems; and,
- use common CAD tools as interfaces to self-implemented solutions.
Overview
Course will consist of a few lectures, several tutorials and project-based exercises.
Topics will include:
- Intro Python programming
- Intro COMPAS open-source framework (https://compas-dev.github.io/)
- Intro to geometry processing, data structures, topology, numerical computation
- Domain-specific case studies (e.g. on architectural geometry, structural design, robotic assembly, volumetric modeling and 3D printing, high performance computation)
Schedule
| Week | Date | Lead | Title | Description | Links |
|---|---|---|---|---|---|
| 1 | Oct 2 | BRG | Introduction | Course overview, COMPAS intro | Slides |
| 2 | Oct 9 | GKR | Getting Started | Development Tools 101 Python 101 COMPAS 101 |
Slides, Assignment |
| 3 | Oct 23 | BRG | Data structures and Geometry | Basic theory and examples | Slides, Assignment |
| 4 | Oct 30 | BRG | Module 1: Structural Design | Theory: Form Finding methods | Slides, Assignment |
| 5 | Nov 6 | BRG | Module 1: Structural Design | Case study: The HiLo cablenet formwork system | Slides |
| 6 | Nov 13 | GKR | Module 2: Robotic Assembly | Theory: Robotic fabrication planning and executing | |
| 7 | Nov 20 | GKR | Module 2: Robotic Assembly | Case study: Robotic assembly of a brick wall | |
| 8 | Nov 27 | DBT | Module 3: Volumetric Modeling | Theory: Modelling with signed distance functions | |
| 9 | Dec 4 | DBT | Module 3: Volumetric Modeling | Case study: Modelling of a node | |
| 10 | Dec 11 | BRG | Next Steps | Using COMPAS in your own work |
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Jupyter and extensions
If you have Anaconda installed, then jupyter is already installed. If not, then install jupyter with pip.
To run the jupyter notebook, you simply have to type:
jupyter notebook
in your command line.
Configure workspace
To configure the workspace, type
jupyter notebook --generate-config
This writes a default configuration file into:
%HOMEPATH%\.jupyter\jupyter_notebook_config.py (on windows)
or
~/.jupyter/jupyter_notebook_config.py (on mac)
If you want jupyter to open in a different directory, then change the following line:
c.NotebookApp.notebook_dir = 'YOUR_PREFERRED_PATH'
Download nbextensions
To install nbextensions, execute the commands below in Anaconda Prompt:
conda install -c conda-forge jupyter_contrib_nbextensions
conda install -c conda-forge jupyter_nbextensions_configurator
After installing, restart the Jupyter notebook, and you can observe a new tab Nbextensions added to the menu. Install the following extensions:
-
Split Cells Notebook - Enable split cells in Jupyter notebooks
-
RISE - allows you to instantly turn your Jupyter Notebooks into a slideshow.