Denture reinforcement via topology optimization

Area of Science:

• Biomaterials Engineering
• Computational Mechanics
• Dental Technology

Background:

• Denture displacement and reduced stiffness are common issues affecting patient comfort and function.
• Current denture fabrication methods may not optimally incorporate reinforcement.
• Advanced computational tools can enhance material distribution for improved mechanical properties.

Purpose of the Study:

• To develop and validate a computational design method for optimizing denture reinforcement.
• To enhance denture stiffness and minimize displacement using topology optimization.
• To provide guidance for the precise placement of reinforcement materials in dentures.

Main Methods:

• Utilized topology optimization to identify optimal reinforcement regions within a 3D lower jaw denture model.
• Employed a multi-material approach, incorporating E-glass material for reinforcement.
• Simulated and compared displacement under load for both non-reinforced and reinforced denture designs.

Main Results:

• The reinforced denture exhibited significantly reduced displacement compared to the non-reinforced design.
• Topology optimization successfully pinpointed critical areas for reinforcement.
• Node-based displacement analysis confirmed magnitude reduction due to strategic reinforcement.

Conclusions:

• Computational reinforcement design effectively increases denture stiffness and reduces displacement.
• The proposed method offers a practical approach for integrating reinforcement in multi-material 3D printed dentures.
• This technique can streamline denture fabrication, optimize material use, and improve outcomes for dental technicians and patients.