adaptive[skins]
A record of design research entitled ‘adaptive[skins]’ carried out at The Architectural Association (AA) School of Architecture, Emergent Technologies & Design (Em.Tech.) Programme 2011-13 in pursuit of M.Arch. (Master of Architecture) Degree. adaptive[skins] is an investigation exploring design of building skin systems that adapt to the dynamic environmental conditions to regulate the internal conditions in a habitable space, over different periods of time. Smart systems that integrate smart materials and smart geometries are developed that can be self-actuated to adjust to the seasonal changes leading to phenomenal conditioning, energy efficiency and creating dynamic spatial effects, for the interior as well as exterior.
Monthly Archives: November 2012
3 Strut Tensegrity – Dynamic Component- Experiment
The experiment shows the dynamic behaviour of a 3 strut tensegrity component made with nitinol (nickel+titanium alloy) springs.
The source of heat used is a daily-use hair dryer. The activation temperature of nitinol springs is 45 degree Celsius.
West Facade Test – 3 Strut Tensegrity System – Optimization
The digital test is run for a West facing facade.
Location: New Delhi
Date: 21st June 2012
Time: 12:00 pm
Fitness Criteria – Max. Exposure on the inner surface (passing through the porous system) + Max. Angle of Incidence (on each face)
DIGITAL SIMULATION OF A 4 STRUT TENSEGRITY SYSTEM
Digital Simulation of a system made of 4 strut tensegrity component systems, with actuators attached to the global system, leading to a combination of individual and collective behaviour. The optimization is lead by parameters of exposure (light entering the system) and angle of incidence (of each face on the surface), and fitness criteria are variable.
Tools used –
1. Genetic Algorithm created using Python Scripting and Grasshopper.
2. Kangaroo-Physics Engine in GH for Rhino
3. Galapagos – Evolutionary Solver in GH for Rhino
Digital Simulation of a 3 Strut Tensegrity System
Digital Simulation of a system made of 3 strut tensegrity component systems, with actuators attached to individual components, leading to a collective and emergent behaviour. The optimization is lead by parameters of exposure (light entering the system) and angle of incidence (of each face on the surface), and fitness criteria are variable.
Tools used –
1. Genetic Algorithm created using Python Scripting and Grasshopper.
2. Kangaroo-Physics Engine in GH for Rhino
3. Galapagos – Evolutionary Solver in GH for Rhino
