Thermal Reactive Topography

¨Material behaviour simulation and prediction¨


This experimentation aims to simulate and predict future behaviours of an expandable material through controlled thermal gradients. Utilizing Genetic algorithms, artificial neural networks and machine learning processes our simulation translates multiple case studies into the prediction of possible material characteristics.



By implementing deterministic target values we are attempting to obtain feedback OF optimized point heat locations. This begins to frame an understanding of the material in relationship to heat and future topographic and expansive performance.

Artifitial Evolutionary Solver

Machine learning


Grasshopper Script


This exercice is part of  the computational design studio.

Studio SO.6 faculty :Rodrigo Aguirre and Aldo Sollazzo.

Artificial Evolutionary Design – Thermal reactive topography is a project of IaaC, Institute for Advanced Architecture of Catalonia

developed at MAA1 in 2017-2018 by:


Eduardo Chamorro Martin

Elliott Santos