Researchers at the Texas A&M Transportation Institute’s (TTI) Proving Grounds have run over 3,000 full-scale crash tests on everything from subcompact cars to 80,000-lb tractor-trailer rigs. The Center for Transportation Computational Mechanics (CeTCoM) at TTI has a history for being able to help predict the outcome of such crash testing using computer simulations and publicly available computer vehicle models. Now the Center is capable of developing these detailed computer vehicle models in-house for use in simulated crash testing before the real crashing begins on the storied Proving Grounds runway.
“It costs about $50,000 to run a full-scale crash test,” says TTI Associate Transportation Researcher Michael Brackin. “So to run a crash test and have something fail is an expensive venture. With the models that we produce, it substantially reduces the risk of that happening.”
The researchers use two three-dimensional scanning devices to build the three-dimensional surfaces of any object. The first laser scanner is a handheld scanner attached to an articulated precise arm. This is used for scanning small to medium sized objects. The second laser scanner is a long-range scanner that scans objects within a large volume that surrounds the scanner itself. This scanner is used for scanning large objects such as concrete barriers or vehicle panels. These scanners allow the researchers to scan vehicle parts and components of roadside safety and perimeter security devices for use in computer modeling to predict how they might react in a crash. The models are then inputted into impact analysis software, which produces a simulated version of a crash test. The impact analysis software runs on a state of the art computational cluster that is housed in CeTCoM.
“With simulation, you are able to optimize the performance of a device by finding potential red flags such as the material used and type of bolting on the barrier,” says TTI Research Scientist Akram Abu-Odeh. “It also allows a lot of flexibility in that you can set multiple points on a vehicle to see how they would react in a test.”
According to Brackin, the first model is roughly the cost of an actual crash test, but the cost benefit comes with the ability to repeat that simulation many times at a much smaller cost than actual crash tests.
“Certainly nothing is as reliable as the real thing, but this gets us closer to where we need to be for the crash test to be successful,” says Brackin.