Genetic optimization :

Pseudo Code :

-Hint about the clayphene project: it’s a studio project concentrate on mixing different composites of clay, graphene, and PVP (binder) in order to generate heat by using less amount of voltage.

-the goal is to build a wall that has rippled surface (to maximize the surface area) that is able to generate heat in a specific zone of the wall that has different depth ( d), and gradient amount of graphene.

– Creating a wall surface geometry (rippled surface)

– sorting the heating points (gradient graphene ) by using an image sampler component to get gradual values.

– connecting the real-time data with the fitness formula as the operative temperature of a specific zone in order to know how much heating zones we need to get the best temperature.

-There are multiple factors affecting on choosing the depth of the bulges (heating points )
(the depth of each bulge ) , the total surface area, and the operative temperature inside a specific space.

Catalogue :

Fitness formula : if ( x > T1 , x , y < depth values)

The logic of this formula when we have high operative temperature the depth of the bulges

would be less than the maximum (d) and the inverse of the formula will be right.