Copycating the Soumaya Museum guys...

Playing with optimization concept used for Soumaya Museum's facade. - 6-dimensional k-means clustering - ~6000 triangular panels grouped in 15 families - equilibrium reached after 40-50 iterations - computation time ~8-12 minutes - native GH components + Anemone

  • LiuMing

    What a great work!

  • shima roshanzamir

    great work. may I ask if the panels in one group have exact same size or you defined a tolerance?

  • Mateusz Zwierzycki

    Shima : Same size.

  • patric guenther

    nice job! I have the same question as shima has. did you defined tolerances in your definition? I am also working on something very similar. would be very nice, and help me a lot, if you could share your definition with me? patricguenther@gmx.de

  • Caelum Praecelsus Arquitectura

    Excellent!

    I would be interested in learning more about the process. Is it a matter of defining domains and looping the algorithm until panels fall into a set predetermined domain tolerances?

  • taz

  • Roland D. Sandoval

    Actually, does anybody knows if the parametric design part of the Soumaya Museum facade was made by the same studio (FR-EE) or it involved any specialized computational design studio? Thnx!

  • Mateusz Zwierzycki

    Dario - I saw Alexander Pena de Leon's lecture at 2013 eCAADe(Prague), in which he described this optimization method. 

  • I_M_F [Iker Mugarra Flores]

    Amazing work Mateusz!!! Impressive optimization....
  • Mike Pacheco

    great work !!!   I´m kind of new using anemone components, can u upload a tutorial for this ? it would be awesome .   

  • Neil Meredith

    Have a look here for more specifics on the hex panel optimization done for the museum.

    http://issuu.com/gehrytech/docs/sou_06_issuu_version

  • Hendrik

    Hi,

    great work!

    iam trying very similar and iam wondering what do you mean with 6-dimensional k-means clustering? In my version i compare every attribute from each panel to another. This is i think 1-dimensional k-means clustering, or not?

    Hendrik