ARCHITECTURAL DNA: A genetic exploration of complex structures

I am glad to announce that we've further developed our topic of Structural DNA. We submitted a new paper to Smart Geometry: The Evolution of Parametric Design and Practice. I added the abstract and some images of our new paper below.

Abstract

The approach demonstrated in this paper uses Evolutionary Computation (EC) to enhance and modify structural form based on biological micro structures. The forms are modified to conform to new boundary conditions associated with architectural structures. The process is based on a Genetic Algorithm (GA) which visually exposes for the designer a range of good performing solutions within the design space. The application of the GA is combined with parametric software, in this case Generative Components (GC). The program described here as ParaGen (Parametric Genetic Algorithm), uses a finite element analysis to determine the structural performance of the forms. This allows the designer to manipulate and optimize a parametrically defined model based on predefined criteria and parameters.

The opportunities and limitations of this design process are explored and evaluated based on an experimental case study using topologies based on radiolarian skeletons.

The design procedure described includes user interaction in the exploration of solutions that perform well both for the explicitly defined programmatic criteria (structural) as well as for the implicit criteria provided by the designer (visual aesthetic).

Keywords: structural morphology, parametric design, genetic algorithm, structural optimization.

ACSA Presentation - PPT slides

Webinterface of dome generations

click HERE to see the evolution process of the domes!!

GC - set-up

I decided after some discussion and thinking, to use the right support configuration for the model. Since cellular structures in nature, tend to arrange perpendicular to stiffer surfaces. This is the most optimal way to distribute forces within a structure. This phenomenon is also seen within radiolarian skeletons.


40 rings model with higher densities of points

This image illustrates the way the points are projected onto the dome in GC.

Projection

Symmetric or almost symmetric?
Either symmetric or total a-symmetric...? For our topic, it might be best to use symmetric, because we decided not to focus too deeply on wind forces for now.


Perfect Symmetric configuration of 40 ring model

To explore the possibilities of having the rings regulated, I added some images of different amounts of rings below. each set is a screen shot of a different GC model. Within one model, the rings are limited to a specific amount. (5,7,10,10,20,40)

I still hope to find a way to integrate them into one GC model.


random results of configurations based on different ring densities.



It would be best to control the density of the rings in the same GC model. But until this point we cannot integrate this into one script.together with the point distribution variables. I hope we can manage to solve this. but we might will test different models for specific ring densities.


This is an example of a possible configuration of points based on a 40 ring model. This would be the most dense ring-density possible within the model. We defined 41 different variables to define independent point distribution along each ring. .


This image shows a model with different densities of points per ring (20 rings)
voronoi on top & delaunay below (based on same points)



Voronoi (above) vs Delaunay (below) GC


Voronoi Dome GC