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algorithmic modeling for Rhino

Pattern Design Architects are proud to announce the completion of our first built project. The Hazza Bin Zayed Stadium in Al Ain, UAE

http://www.pattern-architects.com/
http://www.linkedin.com/company/pattern-design-ltd
http://architizer.com/projects/hazza-bin-zayed-hbz-stadium/

The HBZ stadium was developed with Rhino/Grasshopper and Revit.

Grasshopper was utilised from Concept level through to the production of Construction drawings.

The stadium's unique parasol roof passively provides the maximum amount of shade to create playable conditions for a desert stadium, while not obstructing grass growth.

The 25,000 seat bowl was modelled and optimised through 3d sightline calculations, to make the bowl as tight and efficient as possible while guaranteeing the best possible C-Values.

The diagrid facade, is made up of palm-inspired panels, creating shade, allowing air flow through the stadium. Panels are angled up to allow views out from key locations.

The 640 panels were carefully rationalised for construction. From an original set-out of 320 unique forms, the panels were reduced to 82 sizes without any noticeable aesthetic impact.

The full implementation of a parametric workflow in a BIM environment meant the stadium was delivered on an unprecedented fast track 18 month Design & Build.

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Comment by David Burpee on March 18, 2015 at 3:55pm

Such a great looking project, nice work. 

Comment by Nick Tyrer on February 14, 2014 at 11:39am

Thanks David, we are not fibbing, its first built. We have also recently been awarded the second of the much sought after World Cup Stadiums for Qatar 2022. Zaha Hadid won the first. I believe that ultimately its down to tools like grasshopper that our practice of about 12 can compete with industry giants like zha or populous.

The panel rationalisation was obviously for cost efficiency, but also to guarantee quality with local fabricators, being able to use simpler jigs. The variables to control was the length of the frame members and the join angles. Using a semi-iterative process this data the panels were grouped on similarity with a variable tolerance. With each group averaged, to a best fit panel. This was repeated till we found the grouping that offered fewest unique panels within a tolerance we felt acceptable. Next time we will use Galapagos...

Comment by David Stasiuk on February 13, 2014 at 4:43pm

I just got the chance to click through on some of the links as well. Congratulations on a great project! Is this really your office's first built project? If so, an amazing start.

I'm curious how you rationalised the panels to reduce the number of unique forms...

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