I had the pleasure of exploring stadium concepts for a potential project in Saudi Arabia. The stadium typology has much to offer on the subject of skin, response and computational design with its sheer size and volume of components. One avenue explore was a loop consisting of  analysis data generated by Ecotect and a design concept formulated  in Rhino3d. Extracting data from Ecotect is quite simple. A .txt file with data in the CSV format can be exported from Ecotect through the following location: Display->Object Attribute Values->Properties->Export Data… This data is saved as a .txt file and can be directly imported into grasshopper with the ‘read file’ GH component. Although the information is accurately imported there is a break in the loop which forces one to stop, export and re-import the information. Luckily Ecotect creates a Dynamic Data Exchange server which allows running applications to speak with each other. The GecoGH plugin is a great set of tools that executes this exchange in a seamless loop where the scripted geometry/design is streamed to and from Ecotect. Below you will see some screen shots of a process utilizing this functionality.

GH mesh geometry

In this case geometry was constructed with a series of lofted nurb surfaces. In order to accurately transfer geometry into ecotect a separate series of functions are implemented to create mesh panels (vs nurb) based on the original nurb control points, this insures the precise matching of geometric information.

text values

Data is clean and matches the exported mesh geometry. Peak direct radiation is calculated and averaged for the year (CPU run time qual to two days of calculation). By enableing the view text menu you can preview the separate values of data for each of the 30,000+ panels.

rhino geometry pared with Ecotect data

The data for each panels is brought back into grasshopper and matched with the geometry to give each mesh panel a value of analysis data and RGB matching the Ecotect calculation.

parsed panel groups

Parsing the panels into groups is one of the more interesting steps. This is where we decide what to do with the information. In this case the data is parsed into 10 groups based on cumulative direct heat gain values. The parsing of data uses a series of sliders that intuitively bleeds one set to and from the previous giving the designer an element of control over the data.  The groups are a step towards rationalization with 30,000 panels broken into 10 panel types.

panels applied per group

Here we used cultural inspiration from the region applying a series of deconstructed arabic patterns as cladding. The patterns range from simple and open to complex and dense. The dense patterns are applied to the groupings with high solar exposure while the open panel types are applied to regions primarily in shade.

cladding diagram

The cladding diagram showcases the varied range of porosity and shading corresponding directly to analysis information.

grasshopper build

The final Grasshopper build consists of a feedback loop tying together all information outlined above with the addition of seating layout, circulation and other functions. In theory the skin will adjust and run the process outlined above as the geometry iterates throughout the various stages of the design process. This is important for it allows multiple team members to develop massing seating and programatic functionality parallel but independent to the development of skin and structure. Keep in mind the Ecotect analysis took two full days to calculate all 30,000+ individual panels. Parameters control the subdivisions of the panels which would allow for the de-resolution of information if needed to facilitate the iterative process in a timely manner.

energy analysis feedback loop

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