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
Quantitative Benefit
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