skip to main content


Title: Composite laminate failure parameter optimization through four-point flexure experimentation and analysis

Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be defined through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations onmore » the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.« less
 [1] ;  [1] ;  [1]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 1359-8368; PII: S135983681630556X
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Composites. Part B, Engineering
Additional Journal Information:
Journal Volume: 97; Journal ID: ISSN 1359-8368
Research Org:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
36 MATERIALS SCIENCE; Carbon fiber; Computational modeling; Finite element analysis (FEA); Statistical properties/methods
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1326410