CFD for Visualization

A Toyota Motorsport wind tunnel helps automotive engineers design faster high-performance cars with its built-in particle image velocimetry (PIV) system.

Engineer Frank Michaux, a CFD/PIV researcher at Toyota Motorsport in Cologne, Germany uses analysis techniques to help the company achieve peak performance out of vehicles — from NASCAR, Sports Car, Formula One (F1) and other races to finely built models for highway use. Michaux’s team maintains and operates two state-of-the-art automotive wind tunnels equipped with built-in PIV systems.

The complex data derived from these systems must be quickly and accurately interpreted and displayed. Toyota Motorsport sustains its winning edge by correlating its PIV results with CFD simulations, measured and rendered by Tecplot software.

PIV is an optical method of flow visualization to obtain velocity measurements and related properties in fluids. But it wasn’t until recently that the technology became a practical design tool for engineers, largely due to the increasing power and decreasing cost of both computers and digital cameras.

“Many of today’s motorsports cars are based on existing, commercially available cars,” said Michaux. “If researchers can identify a way to reduce drag on a motorsports car, it’s reasonable to assume that this information also may apply to future versions of a normal road car.”

Optimization in auto racing is like everything else. It is a continuous process. Each part or mechanical adjustment in a car—no matter how tiny—affects the flow, force, or drag of the entire machine. Since optimization is continuous and evolutionary, the speed with which the engineers can compile and analyze data, and then apply it to a current project, becomes vital. A delay of even a few days can mean the difference between successful integration and failure.

Before the advent of PIV, engineers created simple vehicle models and then studied the flow on the surface of the model. This was inefficient because they could only see the flow at the surface. They didn’t have the means to produce a 2D plane or accurately observe and record the critical wake of the wheels.

To compensate for these shortcomings, engineers used ad hoc techniques, such as putting a smoke probe in the wind tunnel to better “see” the air flow. But these methods didn’t accomplish what they wanted: to capture accurate flow data for the area of interest.

“By looking at the smoke, we could visualize the flow, but we were unable to quantify it. You could only make assumptions about speeds based on the visual aspects of the flow,” explained Michaux. “The whole problem in this industry is how to visualize air flow without introducing something new into that flow that could potentially compromise the results. With the PIV method, you can really attach numbers to air flow.”

PIV allows for the visualization of the flow field almost exactly as it appears in the wind tunnel, without influencing the very flow field that engineers are seeking to measure. Toyota’s PIV system involves filling the tunnel with a fog or mist with the same density as air. When the air flows through the tunnel, the small particles that make up the fog simply float, making this PIV method as non-intrusive as current technology will allow.

For a PIV test, engineers position a camera at a 90° angle to the plane of the flow field they want to study. The tunnel is then filled with the fog, and all tunnel lights are turned off. Next, engineers illuminate the part that needs to be visualized with a high-powered laser, creating a 2D plane. Simultaneously, a series of two-set photos are taken at extremely rapid intervals—generally 10 to 20 msecs. Equipped with this sort of ultra-slow-motion digital imaging, engineers can easily measure the rate and direction of the flow.

During the 2009 Formula One season, engineers wanted to study the wake behind the front wheels of a vehicle. This is a critical part of the flow; if it isn’t perfectly calibrated, the performance of the entire vehicle could be severely compromised. The Motorsport team considered options for adding or modifying various front-end parts, adding an under-nose turning vane, or modifying the front wing to create or influence an outwash. The goal is to push the flow out from under the nose of the car, forcing the wake of the car as far “outboard” as possible.

After gathering the raw data from the PIV measurements of the “separation point” on the front tires, the engineers post-processed the data using Tecplot software, which allowed them to see and measure the exact position of separation. Each of Toyota’s PIV measurements consist of 300 datasets, with each dataset containing two images taken 10–20 µs apart. The end result is a complete 2D field of vectors. The engineers subsequently plotted the velocity magnitude, or vorticity, with vectors based on the average of all 300 datasets. The corresponding CFD result was then also imported into Tecplot software. Engineers compared the PIV and CFD data sets to determine whether their CFD methods were within tolerances.

In the case of the separation point on the front tires, initial tests showed that the separation point was late and too far back from the tires. The engineers altered the CFD methodology based on these observations, imported the new results into their Tecplot software, and compared it with the PIV results to evaluate their progress. The process was repeated until they arrived at a design that placed the separation point at an optimal position on the tires. This method of CFD / PIV analysis helped the engineers derive simulations of real world conditions that are as accurate as possible in a surprisingly short time frame.

Toyota
www.toyota.com

Tecplot
www.tecplot.com

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Filed Under: Automotive, Simulation, Software
Tagged With: Tecplot
 

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