MCM

Revisions include making it easier to read ^^

Iterative design with Biomorpher. The performance metric we are selecting for is the ‘difference’ rating in the Biomorpher panel. It refers to the contrast of spaces along a given sequential route in each pavilion. The 262 shown in there panel is the average score, and we can interrogate the iterations to find the highest performing parents for the next generation.

Iterations being optimised in our genetic algorithm with each generation.

Generation of geometry

05/11/2019

References: Inorganic Speciation by Iain Maxwell + Dave Pigram (supermanoueuvre)

Based on Sylvia Lavin’s writing on the contemporary pavilion in ‘Vanishing Point’.

Theory 01: Genetic algorithm as an optimisation method.

Theory 01: Generative Design

We are representing these conditions as numerical value ranges - the genotype of the spaces. These spaces with their gene code are classified as program typologies i.e. if the conditions place the space within the ranges of one of our species, we have a successful phenotype classification.

First pass at optimisation parameters for our generative design sequence.

The course is easy to follow, which makes the intensive week not that ‘intensive’ ha.

The steps represent moving parts in the kinetic mechanism of the pavilion.

Early concept drawing for the MCM pavilion. We are currently exploring computational optimisation of a ‘kinetic’ public space.

Grasshopper study and iterations on BIG’s 2016 Pavilion

Rumour has it.

(With the caveat of exploring generative design.)