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Internal instability as a possible failure mechanism for layered composites.
I A Guz1, M Menshykova2, C Soutis3
1Centre for Micro- and Nanomechanics (CEMINACS), School of Engineering, University of Aberdeen, Aberdeen, UK i.guz@abdn.ac.uk.
This study presents a 3D analytical method for analyzing internal instability in layered composites. The approach offers a unified computational procedure for various material models and loading conditions, serving as a benchmark for simplified models.
Area of Science:
- Solid Mechanics
- Materials Science
- Composite Materials
Background:
- Internal instability is a critical failure mode in layered composites.
- Accurate prediction requires considering the 3D behavior of constituent materials.
- Existing simplified models may lack sufficient accuracy for complex scenarios.
Purpose of the Study:
- To revisit and refine a three-dimensional analytical approach for studying internal instability in layered composites.
- To develop a unified computational procedure for the numerical realization of this 3D analytical method.
- To provide a benchmark for simplified models used in composite structural integrity analysis.
Main Methods:
- Utilized three-dimensional equations of solid mechanics to describe the behavior of composite layers and fibers.
- Developed a unified computational procedure for numerical implementation.
- Applied the method to various constitutive equations and loading schemes (uniaxial, biaxial).
Main Results:
- Successfully demonstrated a unified computational procedure for the 3D analytical method.
- Presented numerous examples of critical parameter calculations for specific composites.
- Analyzed various buckling modes associated with internal instability.
Conclusions:
- The presented 3D analytical approach provides a robust method for assessing internal instability in layered composites.
- The unified computational procedure enhances the applicability to diverse material models and loading conditions.
- The results serve as a valuable benchmark for validating and improving simplified composite modeling techniques.
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