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Underdrawings

Underdrawings

Underdrawings

Urban planners may be contracted privately are public workers in a system that has  chiefly a regulator Public-Private Partnerships (see "what's the scope"). Planners and create very restricting. Underdrawing in painting 

They shift the emphasis from ‘form making’ to ‘form finding’

Various generative form-finding techniques existed in architecture long before the digital revolution. At the start of the twentieth century, many visionary architects, engineers, and designers, such as Frederick Kiesler and Frei Otto, were applying design methods that were very similar to today’s computational approach. It seems that today’s new computational design techniques are not as new as they seem, nor impossible to practise without the use of computational tools. These techniques are oft en described by terms such as ‘generative design’, ‘parametric design’ or ‘algorithmic design’, to name but a few.

The shape generation process is comprised of several steps:

  i. A building plot is extruded to reflect the built volume it is predicted to contain (see Predictive Analytics).

  ii. The volume is populated randomly with points and spin forces at various angles.
  iii. The points revolve around the force fields, on a loop,  drifting in and out of their gravitational field.

  iv. On each round, the most distant points in the point cloud are determined (using convex hull), and used to measure the volume of

  the point cloud.

  v. The loop ends once the volume of the point cloud is equal to the predicted built volume in that particular plot. This gives us the

  the volumetric shape of the building.

Form

generation

text generatin
shape generation

By changing just a few variables this procedure can produce thousands of different Iterations.

The question then become that of selecting the best sulutions.

Form

selection

form selection

The more complax We need to differentiate between Linear Equations and Non-Linear Equations.  that cities and regions are ‘self-organizing’ systems, where the interplay of system feedbacks and historical events shape the evolutionary process, and both the overall performance and the multiple local experiences that emerge.

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link to sun test and energy test

Let's consider two geometries of different sizes, the bigger the surface area ratio compared to its volume, the easier to generate air supply and  electricity

Linear testing

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The surviving single-object iterations were then tested as multi-object configurations. In order to prioritize a reach built environment, we set the fitness criteria to be the typological difference between forms in each combination (calculated as the distance of dimensions of a containing polygon) .     

Non-Linear testing

Now it was time to test out top 5 linear equation. The attraction of both cellular automata and agent based models is they represent some of the simplest frameworks possible for demonstrating complex systems behavior. L

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Iteration no.18, parcel 4: proportions of size divided by volume  0.432629 ; 2634550 pixels of bright yellowin site; Predicted mass in site 6162.616536 m' cube; 5
floors 

 
Iteration no.46, parcel 2: proportions of size divided by volume 0.319535;
2543306
pixels of bright yellow in site; Predicted mass in site 16666.815805 m' cube; 23 floors

Searching for the line

Iteration no.16 parcel 2: proportions of size divided by volume 0.307868; 2543387
pixels of bright yellow in site; Predicted mass in site 17255.230193 m' cube; 25 floors
Iteration no.3 parcel 1:proportions of size divided by volume  0.251527wich means its efficient in cooling the building; 2617623 pixels of bright yellow- meaning it's contributing to high values of shadow in site; Predicted mass in site 19801.743022 m' cube; 22 floors 
Iteration no.49, parcel 1: proportions of size divided by volume  0.289012 ; 2637660 pixels of bright yellowin site; Predicted mass in site 2487921 m' cube; 23 floors 
Iteration no.46, parcel 1: proportions of size divided by volume  0.226111 ; 2705363 pixels of bright yellowin site; Predicted mass in site 15461.279204 m' cube; 5
floors 
 
Iteration no.19, parcel 3: proportions of size divided by volume 0.316603;
2487921pixels of bright yellow in site; Predicted mass in site 17455. 204522 m' cube; 24 floors
 
Iteration no.48, parcel 5: proportions of size divided by volume 0.304036; 2541743 pixels of bright yellow in site; Predicted mass in site 6654.155525 m' cube; 3
floors 
 
searcing
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