Predictive modelling of carbon fiber

Researchers at the US Department of Energy's Pacific Northwest National Laboratory (PNNL) have developed a range of predictive engineering tools for designing lightweight automotive composites. 

‘While stronger and lighter than steel, carbon fiber composites are relatively expensive, according to the lab. ‘For widespread adoption to occur, new, economical composites that meet mechanical and safety requirements – such as long carbon fiber-reinforced thermoplastic resins like polypropylene and nylon - need to be developed.’

Rather than building molds, molding parts, and testing new composites, computer modeling could speed up the process, and using the engineering software validated by the team at PNNL could allow manufacturers to ‘see’ what the structural characteristics of proposed carbon fiber composites designs would be like before they are molded.

As part of the project, PNNL also analyzed the costs of long carbon fiber components versus standard steel and glass fiber composites. PNNL found the carbon fiber reinforced polymer composite technology studied could reduce the weight of automobile body systems by over 20%.

PNNL partnered on the project with automotive manufacturer Toyota, tier one part producer Magna, long carbon fiber material and technology supplier PlastiComp, process modeling software provider Autodesk and university research partners University of Illinois, Purdue University and Virginia Tech.