The workflow will revolve around the process of shape optimisation through the analysis of potential geometries in Karamba3d.
The shape will inform the design of an egg chair that is based on the geometric principles of a torus.
The aim of the workflow will be to find the optimum shape with minimal deformation/deflection.
The variables will revolve around the variation of the torus slices in order to inform the overall meshing to analyse within karamba3d.
The fitness will be the displacement float that results from the Karamba3d analysis.

in order to create a controlled study, the number of parameters that change the overall geometry would need to limited. In this case, the karamba3d Analysis is looking for the creation of a mesh. The following diagrams adjacent show the process of creating resultant chair design.
To affect the overall geometry, the defining slices of the torus were divided, enabling the manipulation of the points to interpolate a new curve, which then results in a new global shape.

The fitness figure evaluated within Galapagos is the displacement figure of the seat through the Karamba3d Analysis.
Structural conditions such as location of supports, materiality, cross section and loading conditions of the overall system need to be defined before we can obtain the displacement figure.

Once all the prerequisites of the Karamba Analysis is complete, the Galapagos solver was then utilised to find the most optimised shape for the global geometry.
Here a population of 50 were defined per generation, with the solver stopped at the 26th generation.
The best and worst Solution at each generation were then highlighted with a coloured, transparent bounding box (Blue= worst, Red = Best)

If this workflow was to be improved, we could try to manipulate the definition of the torus slices to translate or move each individual division point in all directions, rather than just the z vector.
This process however, would take an incredible amount of processing power and memory, as well as time for the Galapagos Solver.

Design Associativity – Genetic Workflows – Evolving Solutions_ Shape Optimisation is a project of IaaC, Institute for Advanced Architecture of Catalonia developed at Master in Advanced Architecture 1(MAA01)  in (2015-16) by:

Students:

• Jonathan Irawan