Altair > Case Studies > CFD Advances Racing Bike Performance: A Case Study

CFD Advances Racing Bike Performance: A Case Study

Technology Category

Application Infrastructure & Middleware - Data Visualization
Sensors - Optical Sensors

Applicable Industries

Aerospace
Automotive

Applicable Functions

Product Research & Development
Quality Assurance

Use Cases

Intelligent Packaging
Smart Lighting

Services

Testing & Certification

About The Customer

The customer in this case study is Zipp Speed Weaponry, an Indianapolis-based manufacturer of advanced bicycle racing wheels and cycling components. After reading the research papers presented at the American Institute of Aeronautics and Astronautics (AIAA) conference, Zipp was inspired to apply CFD technology in the design of its Firecrest line of racing wheels. The company was particularly interested in the findings that challenged conventional wisdom about the factors influencing drag force on a bike. The insights from the study helped Zipp to re-characterize their approach to designing wheels, with a focus on balancing the competing requirements for speed and stability.

The Challenge

In the competitive world of bicycle racing, the design and aerodynamics of the bike play a crucial role in a cyclist's performance. Manufacturers constantly strive to reduce the weight and aerodynamic drag of bikes by experimenting with different materials and shapes for the frames, wheels, and tires. However, evaluating the drag force at the system level and isolating the impact of hundreds of design variables at the component level has been a challenge. Traditional methods like wind tunnel testing are expensive, and computational fluid dynamics (CFD) analysis workflows have been too lengthy to be practical. The challenge was to develop a highly automated, repeatable workflow methodology to accelerate the entire CFD process and provide new insights into the role various components play in bike performance.

The Solution

Technologists developed a highly automated, repeatable workflow methodology to accelerate the CFD process. They used various simulation tools including Altair’s AcuSolve, a finite-element based, general-purpose solver, and Intelligent Light’s FieldView 13 CFD post-processing and visualization package. The team studied the aerodynamic flow around a rotating bike wheel and components, evaluating multiple wheel and fork/frame combinations at 10 yaw angles. The steady-state simulations generated approximately 3.6 GBs of AcuSolve data while the unsteady simulations resulted in nearly 1.2 TBs of data. The use of FieldView provided the team with the tools needed to accelerate the analysis, mine the most valuable information, and create compelling images and animations. The team also leveraged the FieldView FVX programming language to automate many post-processing tasks, significantly reducing the time required for iterations.

Operational Impact

The research and partnership between Altair and Intelligent Light provided rare insight into the wheel’s aerodynamic performance. Through visualization, CFD technologists were able to capture the complex interactions happening with every turn of the wheel. The study's findings opened up new solutions for the Zipp team, allowing them to design a product that is not only stable but also fast. The market’s response to this innovative wheel has been swift, demonstrating the practical value of the research. More recently, the work has been extended to incorporate full bicycle systems, allowing for the isolation and exploration of components and their drag influence.

Quantitative Benefit

The use of FieldView allowed the team to process large volumes of data in significantly less time, with iterations that would have taken many weeks in a traditional workflow completed in days.
The CFD technologists ran the FieldView FVX routine 60 times to calculate the drag force for all wheel-and-fork combinations at two speeds.
Zipp’s Firecrest design cut drag on the front half of the wheel by a couple percent and reduced drag on the back half of the wheel by 50%.