DesignMorphine MSc. Project Arcadia.

GrasshopperRhinoPythonComputational DesignParametric Architecture

My final project for the MSc in Computational and Advanced Design. A deep exploration of parametric architecture.

DesignMorphine MSc. Project Arcadia.

The project

Project Arcadia is my final project for the MSc in Computational and Advanced Design. It explores parametric architecture that responds to its environment, with the form found through computational methods rather than drawn by hand.

Main project visualization

The parametric structure

Process

It started with research into responsive architectural systems: structures that adapt to the conditions around them, and the computational tools that make that possible.

Initial research

Early research and concept work

Computational methodology

Exploring the parameter space

The framework

I built the framework in Grasshopper with custom Python components. Parameters adjust in real time, and the form optimises itself against environmental data.

Computational Framework

The framework and its parameter relationships

Iterations

The design went through several rounds, each one refining how form and environmental response relate to each other.

Development Phase 1

First iteration, basic parametric relationships

Development Phase 2

Refining the environmental response

Development Phase 3

Optimisation and performance testing

Development process and iterative design exploration

The final design

The final structure holds up as architecture, not just as a computational exercise. And it stays responsive to the environment it sits in.

Final Design

Render of the final structure

Project video

The final project presentation, covering the full design process

The toolset

Parametric modeling

Grasshopper for visual programming

Environmental analysis

Climate data feeding the responsive behaviour

Form optimisation

Python scripting for performance-based design

Visualisation

Rendering pipeline for the final presentation

What it taught me

How to balance computational complexity with design intent. And that parametric tools aren't just efficient, they're a creative medium in their own right.