A Hole Nucleation Method Combining BESO and Topological Sensitivity for Level Set Topology Optimization

Area of Science:

• Computational Engineering
• Mechanical Engineering
• Materials Science

Background:

• Classical level set topology optimization methods struggle with automatic hole nucleation.
• This limitation hinders the design of complex structures with internal voids.

Purpose of the Study:

• To introduce a novel method for automatic hole nucleation in level set topology optimization.
• To address the limitations of existing methods in creating internal voids within designs.

Main Methods:

• The study proposes the combining BESO and topological sensitivity (CBT) method.
• This method integrates the bi-directional evolutionary structural optimization (BESO) with topological sensitivity analysis.
• A material removal scheme based on two sensitivity thresholds is employed for hole nucleation.

Main Results:

• The CBT method successfully enables automatic hole nucleation in level set topology optimization.
• The proposed method effectively overcomes the limitations of classical approaches.
• Validation through three 2D numerical examples demonstrates the method's efficacy.

Conclusions:

• The CBT method offers a robust solution for hole nucleation in topology optimization.
• This advancement facilitates the automated design of complex structures with desired internal features.
• The findings contribute to improved efficiency and capability in structural design optimization.