For every stadium and arena design, the center piece is the seating bowl design. The geometry of the seating bowl has the most significant saying of the layout of other program spaces. For seating bowl design, there is always one thing that takes the highest priority, and usually is the very starting point of bowl design process. It is called Sightline Design.

Modern sightline Design was first established by John Scott Russell in 1838, and the method has stayed almost the same for nearly two centuries. Basically, the process involves calculation of riser height for each row, given the known previous rows’ treads and risers. This calculation insures spectator’s sightline is not blocked by people sitting directly in front. Besides this “sectional sightline” calculation, bowl design also includes what’s called “lateral sightline” check, which makes sure that sightline is not blocked by people on the left or right. While sightline design is the center piece of seating bowl design, there are much more to consider when designing a seating bowl, than simply meeting sightline requirements.

There are existing digital tools for automating seating bowl design, and they all fall into two categories: first one is simple programs/scripts, either stand alone or integrated in other software platforms, and the second one is more complex parametric tools on Grasshopper/Rhino platform. The limitations of each are obvious: for the first one, these tools are only good at one of the tasks in the whole process, and often the task was brought down to a simplified version; for the second one, despite the extraordinary parametric workflow of Grasshopper/Rhino platform, using numbers and other simple parameters as the only inputs cannot take us very far. It would be very demanding to deal with any type of “design irregularity”, such as row-specific requirement, non-linear aisles and big openings. For both categories, simplicity is their strength, but also their intrinsic short-coming, because in real-world, seating bowl design (or any design process) cannot be easily simplified to just numbers and parameters. Even if it is possible, the amount of parameters needed would likely make a parametric tool unusable.

In other words, these tools all lack the flexibility of the “good-old-way” of design: whether it happens on a piece of paper, or inside a screen, it is mostly a graphical process, started and maintained not by numbers, but lines and curves. We don’t want to go back to tracing paper and CAD drawings either: there should be a balance between flexibility and simplicity.

Seating Bowl Generator started with the goal to find this balance. The complete work flow combines the flexibility and intuitiveness of 2D GUI, with the efficiency of automated 3D modeling and analysis: all the manual effort is focused on creating/modifying sets of 2D “control elements”, then the tool will obtain all the information needed from these elements, generate a bowl down to individual seats, and give quantified evaluation on the design quality. If we need to change the bowl and see what the impact looks like, all we need to do is to add/remove/modify 2D control elements, and the tool will update the bowl geometry and give another round of design evaluation.

To break it down a little, the work flow looks like this: designer starts with designing sections, using Revit families that are made to represent individual rows. The parameters and design requirements for each row are carried by type/instance parameters of Revit family, and the tool will use these as inputs to draw bowl sections, as well as aisle steps and handrails in section.  Then in floor plan, designer draw bowl outline and sweep path, then draw simple line-based 2D elements to represent aisles and voms. After feeding all these elements and sections to the tool, it will generate the resulting 3D geometry. It could combine different sets of control elements with sections, to generate geometry for different part of a bowl. It could also automatically populate individual seats between aisles using the desired seat width. With the location of each individual seats available to the tool, it could evaluate each seat using desired criteria, such as C-value, distance to play, viewing angle, etc. It is also possible to feed the tool with information of where the concourse, concessions and toilets are, and it would figure out the travelling implications for each seat.

This tool has been used in several AECOM projects, and has since proved its value. Many thanks to AECOM’s sports venue experts: Vittorio Ansourian, Hal Johnson, Scott Sayers, and many others who provided valuable inputs on the course of making this tool.