MaCAD S.3 – Digital Tools for Complex Forming seminar
Senior Faculty: Rodrigo Aguirre
Faculty Assitant: Hesham Shawqi

Lightweight structures

“Complex Forming” is a research seminar that studies lightweight, low-mass and self supporting convoluted structures. Linking computational design and algorithmic methods, this seminar explores the development of digital tectonics into structures that unify envelope, structure, form, and experience into a unique system.

This seminar emerges to create an architectural context through the development of computational strategies, design and optimization processes. Doing so, this investigation attempts to create a closer relationship between the designer, computer representation and matter. 

The main objective of this seminar is the design of thin-shell systems that push the limits of form, structure, and space.

Meshing as a design tool

The research will start from digital models described by meshes, allowing great advantage to produce intricate geometries. In short, meshes are vertices (coordinates), edges (relationships) and faces (representations) with directions that can (potentially) represent endless types of complex and non-linear morphologies.

The topological properties of meshes permit to discretize, tessellate, cluster and segment single continuous bodies. This conjunction of actions addresses new ways to describe complex self-supportive curvilinear surfaces into a series of developable flat components with tangential overlaps for efficient fabrication and construction.

With the aid of interactive physics simulations we can create digital materiality and real life behavior as a form finding protocol. Following the work from Gaudi’s physical chain models, Frei Otto’s tensile model studies to Phillips Blocks funicular structures design with RhinoVAULT, natural forces help mold balanced and optimized structures.

Performance Optimization 

A genetic algorithm is an heuristic search that is inspired by Charles Darwin’s theory of natural evolution. This algorithm reflects the process of natural selection where the fittest individuals are selected for reproduction in order to produce offspring of the next generation and evolve.

Evolutionary Computation is a branch of computation that is quite unique. For one, it is not specific to any problem or task. It is a framework for solving generic problems. This offers interesting capacities for the design process where we are usually the ones iterating over a design decision in order to evaluate its effectiveness. If we could abstract the forces which guide a design decision, then we could potentially utilize Evolutionary algorithms to assist us in finding optimal solutions given a number of design criteria.

To allow a greater understanding of building performance, we will analyze critically novel existing projects. Through these case studies, we will be able to gather information which will guide us to generate advanced design strategies focusing on environmental and structural optimization. 

Learning Objectives

At course completion the student will:

  • Learn the fundamentals of Grasshopper and Parametric Design. 
  • Learn some advanced tools and algorithms such as Genetic Algorithms.
  • Learn how to use meshing tools to create complex geometries.
  • Implement mesh topological relations as a form finding tool.
  • Understand the concepts of mesh discretization and tessellation.
  • Apply clustering and segmentation on meshes.
  • Learn how to use environmental and structural simulations for optimization processes.
  • Be capable of creating parametric workflows.