Predictive Engineering Tools for Injection-Molded Long-Carbon-Fiber Thermoplastic Composites (Fourth FY 2015 Quarterly Report)

Technical Report · Thu Oct 01 00:00:00 EDT 2015

DOI:https://doi.org/10.2172/1252854· OSTI ID:1252854

Nguyen, Ba Nghiep ^[1]; Fifield, Leonard S. ^[1]; Wollan, Eric J. ^[2]; Roland, Dale ^[2]; Gandhi, Umesh N. ^[3]; Mori, Steven ^[4]; Lambert, Gregory ^[5]; Baird, Donald G. ^[5]; Wang, Jin ^[6]; Costa, Franco ^[6]; Tucker, III, Charles L. ^[7]

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1. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
2. PlastiComp, Inc., Winona, MN (United States)
3. Toyota Research Institute North America, Ann Arbor, MI (United States)
4. MAGNA Exteriors and Interiors Corporation (Canada)
5. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
6. Autodesk, Inc., Ithaca, NY (United States)
7. Univ. of Illinois at Urbana-Champaign, IL (United States)

The objective of this project is to advance predictive engineering (PE) tools to accurately predict fiber orientation and length distributions in injection-molded long-carbon fiber thermoplastic composites for optimum design of automotive structures using these materials to meet weight and cost reduction requirements defined in Table 2 of DE-FOA-0000648 (Area of Interest 1).

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1252854
• Report Number(s): PNNL-24834-Rev.1; 830403000
• Country of Publication: United States
• Language: English

Related Subjects

Injection molding
long carbon fiber
thermoplastic
process modeling
fiber orientation
fiber length
structural analysis
bending
torsion