Reliability Optimization of the Honeycomb Sandwich Structure Based on A Neural Network Surrogate Model.

Area of Science:

• Aerospace Engineering
• Materials Science
• Structural Optimization

Background:

• Composite radomes protect aircraft radar antennas.
• Radomes are critical structural components in aircraft nose sections.
• Optimization is needed to balance mass, safety, and material efficiency.

Purpose of the Study:

• To develop deterministic and reliability optimization models for composite radome structures.
• To minimize the total mass of the radome.
• To maximize the buckling critical load while ensuring structural safety.

Main Methods:

• Finite element modeling of the radome structure.
• Establishing single-objective and multi-objective optimization models.
• Utilizing the particle swarm optimization algorithm for solving.

Main Results:

• Optimized layer thicknesses for honeycomb sandwich radome structures.
• Achieved minimum total mass and maximum buckling critical load.
• Satisfied design constraints and improved material utilization rate.

Conclusions:

• The developed optimization models effectively improved radome structural safety.
• Particle swarm optimization is a viable method for radome design.
• Optimized radomes enhance aircraft performance and reliability.