Numerical Optimization of CNT Distribution in Functionally Graded CNT-Reinforced Composite Beams

Area of Science:

• Materials Science
• Mechanical Engineering
• Composite Materials

Background:

• Functionally Graded Carbon Nanotube-Reinforced Composites (FG-CNTRC) are vital for high-performance applications.
• The mechanical behavior of FG-CNTRC structures is highly sensitive to the through-thickness distribution of carbon nanotubes (CNTs).
• Existing linear CNT distribution patterns are insufficient for diverse loading and boundary conditions.

Purpose of the Study:

• To introduce a numerical method for optimizing the thickness-wise CNT distribution in FG-CNTRC beams.
• To tailor CNT distribution patterns to enhance structural safety and performance.
• To minimize effective stress in FG-CNTRC beams through optimized design.

Main Methods:

• Numerical optimization techniques were employed to tailor the CNT distribution.
• Effective stress was defined as the objective function, with layer-wise CNT volume fractions as design variables.
• The exterior penalty-function method, golden section method, and finite difference scheme for design sensitivity analysis were utilized.

Main Results:

• The proposed optimization method successfully identified an optimal CNT distribution pattern.
• The optimized distribution significantly minimized the effective stress within the FG-CNTRC beams.
• The iterative optimization process demonstrated stable and rapid convergence.

Conclusions:

• The developed numerical method effectively optimizes CNT distribution in FG-CNTRC beams.
• Tailoring the CNT distribution is crucial for improving structural safety and performance.
• This approach offers a pathway to superior FG-CNTRC structural designs.