07/11/2019
Draft Thesis Statement V.3Â
Revisions include making it easier to read ^^
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@mcm-architecture
07/11/2019
Draft Thesis Statement V.3Â
Revisions include making it easier to read ^^

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Iterative design with Biomorpher. The performance metric we are selecting for is the âdifferenceâ 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
Draft Thesis Statement V.2
05/11/2019

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Theory 02: Form Finding Methodology
References:Â Inorganic Speciation by Iain Maxwell + Dave Pigram (supermanoueuvre)
Theory 02: The Pavilion Typology
Based on Sylvia Lavinâs writing on the contemporary pavilion in âVanishing Pointâ.
Theory 01: Genetic algorithm as an optimisation method.
Theory 01: Generative Design
Classification of Geometry.
We are classifying our geometry using environmental and spatial conditions such as âlightingâ or âceiling heightâ etc.Â
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.

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First pass at optimisation parameters for our generative design sequence.
the process of learning on codecademy sofar
The course is easy to follow, which makes the intensive week not that âintensiveâ ha.
Draft Thesis Statement V.1
18/10/19
Kinetic pavilion that can switch between âmodesâ for different programs.
We will Computationally optimise and narrow down iterations to minimise the number of moving parts against accommodation of program.
Our proposed method of optimisation is evolutionary design, specifically a genetic algorithm.
We will âscoreâ the geometries produced by our input against a list of spatial/environmental conditions such as âlightingâ.
The algorithm will be tasked with meeting the conditions of each space and being able to switch between them through the fewest number of steps.
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 âkineticâ public space.
Grasshopper study and iterations on BIGâs 2016 Pavilion

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Rumour has it.
MCMâs next project: Serpentine Pavilion
(With the caveat of exploring generative design.)