Module 1: Dynamo Crash Course / Topologic – Aug 04 – Aug 06
An introduction to visual programming in Dynamo including a review of the basic programming concepts, the use of DesignScript in Code Block, working with data structures and manipulating geometry primitives, creating custom blocks and a review of how to interact with Revit elements. We include an introduction to packages we will use through the course, including Topologic, Refinery, and Generative Design.
- Working with Data
- Data Structures
- Working with Geometry
- Geometry Modifiers
- Custom Blocks
- Publish Blocks
- Revit Connection
- Accessing Revit elements
- Refinery Tool Kit
- Generative Design
Module 2: Python for Dynamo – Aug 11 – Aug 18
During these two sessions we will focus mainly on python, the purpose is to provide the user similarities between both environments (Dynamo and Python), best practices to read code, how to debug your code, how to share and translate your ideas to code lines instead of nodes. Considering Python and Generative Design make a great interoperability.
- Overall Python view.
- Variables, local variables & global variables
- List, tuple, dictionaries
- Types of iterations
- Definitions, Classes & Methods
- Operands inside python
- Python Inside Dynamo environment
- Similar operations from Dynamo to Python
- Dynamo methods inside Python
- Set a Python script
- Python Dynamo vs. Python Interpreter
- Test Definitions in Dynamo
Module 3: Generative Design for Revit – Optioneering Method – Aug 25 – Aug 27
Introduction to the Generative Design for Revit 2021. Explore the license models. Optioneering is the process of developing design option based on a predefine list of constrains. Generative Design for Revit include a design space to explore
- Cross-Product Method: Distribution of Revit Elements
- Randomizer Method: Packing a Program in a Site Constraint
Module 4: Genetic Optimization Studies – Sept 01 – Sept 08
Optimizations is all about performance, ideas and proper workflow, we will expend two sessions exploring optimization, going from design, mixing with random operations, but obtaining good performance during your generative design evolutions, quick reminder with topologic and reviewing steps to explore and optimization.
- Explore Design using random geometry
- Configuration of code iterations
- Use Different functions and how to combine them
- Optimize Design with python variables
- From exploring design to clean design
- How to take advantage of code to develop multiple façade options
- Use exploration
- Types of explorations
- Explore with Genetic algorithm.
- How to ask my algorithm the type of exploration required.
Module 5: Advanced Applications – Sept 15 – Sept 22
Take advantages from each tool, and understanding optimization search, allows the user to obtain explore more detailed process and mix of outputs, keeping in mind we want to get best possible outcome in design, evolution and behavior. Design is just changing to a new form to express AEC ideas.
- Façade Optimization “Design is a great as Value is Design”
- Translate formulas into Python
- Structuring your Python Code
- Combining outputs to improve performance
- Exploring Facades
- Introduction of pandas and NumPy
Module 6: Performance Simulations – Sep 29 – Oct 6
Apply Generative Design Optimization workflows to create high performance solutions with measured outcomes, ideal to support LEED and/or Net Zero applications. Learn the use of the Solar Analysis package.
- Daylight Analysis: Optimize maximum indoor daylight analysis
- View Access Optimization: Optimize access to exterior views