How is Computation used in Stadium Design in 2025?

What Is Computational Design?

Computational design is the result of a series of logical steps that bring together design methods with computing capacity. Architects have been using their intuition and experience to create innovative designs for ages. But that process has completely changed as a result of this cutting-edge technology.

Using data-driven methods to optimize the several phases of the design process—creation, presentation, analysis, assessment, interaction, and aesthetic expression—is the essence of computational design.

There are several terms and subfields within the incredibly vast and intricate topic of computational design. Among these are form finding, topology optimization, digital design, parametric design, algorithmic design, generative design, material computation, biomimetic design, and much more!

Computational design is becoming more and more popular in the AEC sector as a result of the acceleration of digitization.

Why Computation is used in Stadium Design

It would be appropriate to comprehend "Why" before "How" computation is employed for stadium design.  Let's decode that, then.

 Assume the role of an architect who want to create a stadium without the use of computational tools.

You then inquire with the client about the specifics of the stadium you are creating, including its field of play and focal point.  You write everything down and start the intricate mathematical process, which includes figuring out the ideal seat height to guarantee the best sightline for every spectator, positioning the columns so that no viewer is obstructed, and carrying out intricate computations to determine how to maximize the number of seats in order to make the stadium profitable for the investor.

And when you've finished all of this, the customer asks you to move your attention slightly to the left, which means you have to complete all of these difficult duties again, which may be tiresome, time-consuming, and pretty boring!

Computational design is crucial for stadium design in particular because of these computations can be automated and made dynamic and reproducible with the aid of computational design.  This significantly cuts down on the amount of time needed to complete these computations!

How Computation is used in Stadium Design

Now, let us look into the various parts of the stadium design process where computational tools are used.

1. Sightline

The architects and engineers who design stadiums have to think very carefully about the way the seats are laid out to squeeze in as many seats as possible without compromising on the quality of the view. This is where the concept of C-Value comes into play. C-Value is the vertical distance in mm between your line of sight and the eye of the person in front.

Unfortunately, the designers can’t always give a C-Value of 150 because there wouldn’t be enough headroom below the floor above and the cost would increase significantly.

How Computational Design is used here

Typically, architects begin by determining the C-Value they wish to offer and then adjusting the step heights (N) in accordance with that value.  Computational design is useful in this situation.

We must employ the recursion technique since we must know the previous riser height value in order to compute the next one.  A computer process known as recursion necessitates carrying out a sequence of actions again until a halting condition is satisfied.

• In Dynamo, this is best calculated using a simple Python script. You can use the ‘Stadium. Cvalue' node from the BVN Dynamo package.

  
  

• The TORO plugin for Rhino does that as well. It helps create stadium geometry from the old cValue method.

  
  

2. Seating Bowl

Once the designer has the step profile and path, a seating bowl can easily be generated as a sweep. The sweep path will usually be the same as the line of focus.

How Computational Design is used here

Although the sweep path can be manually drawn, the sweep profile can be automated using Computational Design methods. There are multiple techniques to do this:

• The designer can use the ‘Stadium.ModelCurve’ node from the BVN package to create the sweep profile directly within the Revit project environment.

  
  

• The designer can use the ‘Stadium.ProfileCurve' node from the BVN package to create the sweep profile within a 2D profile family.

3. Concourses & Multiple tiers

This step typically goes hand in hand with Step 4. Let us first understand what a concourse is. A concourse is defined as a circulation area that provides direct access to and from viewing accommodation. The concourse is linked by vomitories, passageways, stairs or ramps.

How Computational Design is used here

To create concourses, the designer simply has to repeat Step 4 but with new values.

4. The Stadium Envelope

Making the stadium envelope and skin comes after the seating bowl is finished.  The stadium envelope is a modular structure that holds the technological components of the arena and offers shade.  This component also contributes to the stadium's identity and imageability.  Here, the use of computational design tools is very beneficial.

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How Computational Design is used here

• External envelope: Integrated parametric systems can be used to conceptualise, simulate, and document the complex geometric systems.

  
  

• Simulation structural behaviour: Physics simulation tools like Kangaroo can be used to test the basic structural behaviour of the envelope.

  
  

• Detailed analysis and engineering: Custom scripts can be used to automate the communication of centerline information to the structural engineering team.

  
  

• Optimising the facade: Topology optimization is a technology for developing optimised structures considering design parameters like expected loads, available design space, materials, and cost. Embedded early in the design process, it enables the creation of designs with minimal mass and maximal stiffness.

  
  

  Computational design tools such as Grasshopper and Rhino 3D with plugins for topology optimization functions are used for this. There are specific topology optimization software packages that come with built-in optimization and simulation functions.

Case Study: Hangzhou Tennis Center by NBBJ

The Hangzhou Tennis Center in China was built in 2019 and has a total size of over 400,000 square meters.  The world-class sports complex can hold 10,000 spectators and has an iconic lotus-petal shape.

The trusses, also known as petals, enclose the stadium seating bowl in a huge, repeating pattern.  The shell not only gives the tennis stadium its aesthetic appeal, but it also serves the practical purpose of shielding the seating bowl from the sun and rain.

How Computational Design was used here

• Exterior Envelope: Integrated parametric system was created to conceptualise, simulate, and document the complex geometric systems.

  
  

• Form variation: Rapid refining of the building form and testing alternatives.

  
  

• Structural Collaboration: Systems for producing analysis-ready structural models.

  
  

• Conceptual simulation: Integrating intuitive physics simulation for an understanding of complex structures and to test basic structural behaviour.

  
  

• Surface Analysis and Cladding: Surface property visualisation and detailed parametric panelling systems.

  
  

• Coordination: Organising and exporting parametrically generated models for use in external documentation software.

  
  

• Documentation: Parametric workflow systems were invented to link together disparate design and documentation environments for a more seamless international collaboration.

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