- New high-order computational fluid dynamics method simulates the most precise physics of spinning golf balls.
- It takes all real world parameter into account and computes the fluid physics problem in a fair amount of time.
There are several parameters in the swing mechanics that affect the spin generated on the golf ball. A professional golfer can hit the ball at a speed of up to 215 km/h, resulting in a spin rate of about 3000 rpm. This rate affects the flight the ball will take in the air.
The objective of designing a golf ball is to maximize the range it can go in straight line, while reducing its drag and variation in side forces, and maximizing the lift force generated by backspin.
In order to understand the performance of golf balls under various scenarios, and to collect information for developing the next-generation ball, researchers at Stanford University have come up with the most advanced simulations of static and spinning golf balls that take almost all real-world parameters into account.
Incorporating Sports Aerodynamics
The most crucial part of golf ball design is small dimples around the ball. The depth, size, and position of these dimples account for aerodynamic properties of the ball under different scenarios. Moreover, it’s necessary to have the flow details of each dimple to accurately determine these properties.
For the first time, researchers have presented a high-order computational fluid dynamics simulations of spinning golf balls in a real-world environment. To generate mesh and grid motion, they combined Flux Reconstruction technique with Artificial Boundary overset approach.
Golf ball surface and grid resolution | Courtesy of researchers
They developed new visualization algorithms to utilize the recently built hardware accelerators. They are based on Large Eddy Simulation method with no sub-grid models. This computes highly complex fluid physics equations in less time.
The algorithms can efficiently compute turbulent flow fields around the ball on NVIDIA Tesla GPUs. They used the same processing unit at the Xtream GPU computing cluster at Stanford University, which has a computing power of one petaflop.
The high order techniques like Flux Reconstruction are especially useful in Direct Numerical Simulation or Large Eddy Simulation settings. They enable simulation of vortex-dominated flows with fewer degrees of freedom, and execute more efficiently on new processors compared to conventional second order computational fluid dynamics techniques.
Reference: arXiv:1806.00378 | Stanford University
This is the case because of higher floating point operations executed per memory byte consumed by each algorithm. While the previous algorithms hardly achieve a peak performance of 3% on GPUs, the new method achieves the peak performance of more than 50% on the same hardware.
This Method could be used for other sports balls as well
Streamlines and velocity magnitude field at y=0 | Courtesy of researchers
The method yields far better results as compared to previous computational techniques. It functions at Reynolds number – a dimensionless number that shows the behavior of fluid – of no more than 500,000.
This high-fidelity simulation technique can also be applied to other sports applications, like slow-speed sailboats, hockey pucks, and bicycles at moderate speeds. It can also be used for turbomachinery, small unmanned flying devices, multicopters, and high-lift systems.