A particle swarm-based algorithm for optimization of multi-layered and graded dental ceramics

Current dental restoration methods face challenges in managing thermal residual stresses (TRSs) and bending stresses in layered ceramic systems. These stresses can compromise the structural integrity of dental prosthetics. While prior research has shown that TRSs arise from temperature gradients during cooling, the specific impact of interlayer thickness and composition remains unclear. No prior work had resolved how to optimize these variables to reduce stress concentrations. This gap motivated the development of a new approach to evaluate and minimize these stresses. Existing studies focus on material properties but lack systematic optimization strategies. The piston-on-ring test is commonly used to assess bending stress but does not account for graded structures. This paper's contribution lies in integrating analytical modeling with a particle swarm optimizer. The study introduces a novel method to determine optimal interlayer thickness and composition profiles. This approach aims to improve the mechanical performance of dental ceramics.

This study aims to reduce thermal residual and bending stresses in zirconia-porcelain dental ceramics to enhance structural strength. The authors propose using an analytical parametric model to evaluate stress distribution in multi-layered and graded discs. They also seek to develop a particle swarm optimizer to identify optimal designs for dental restorations. The study addresses the lack of systematic optimization methods for layered ceramic systems. By varying interlayer thickness and composition, the authors aim to minimize stress concentrations. The piston-on-ring test is simulated to assess bending stress. Three design cases are considered: minimizing TRSs, bending stresses, or both. The ultimate goal is to improve the durability and failure resistance of dental prosthetics.

The researchers developed analytical parametric models to calculate thermal residual stresses in zirconia-porcelain discs. These models simulate the cooling process and stress distribution in multi-layered and graded structures. A piston-on-ring test simulation is used to evaluate bending stresses. A particle swarm optimizer is implemented to identify optimal interlayer thicknesses and composition profiles. The optimizer treats each layer's thickness and composition as design variables. The number of layers in the interlayer region is also varied to assess its impact on stress distribution. The methodology is validated using literature results and a finite element model. Three optimization cases are considered: minimizing TRSs, bending stresses, or both.

The study demonstrates that interlayer thickness and composition significantly affect stress distribution in dental ceramics. Optimized designs reduce thermal residual stresses by up to 30% compared to conventional layered systems. Bending stress is also minimized in graded structures with optimized composition profiles. The particle swarm optimizer successfully identifies optimal layer configurations. The number of layers in the interlayer region influences the stress field's magnitude. When both TRS and bending stresses are minimized, the resulting design achieves the lowest overall stress. The finite element model confirms the analytical results. The methodology is validated against literature data, showing consistent trends in stress reduction.

The authors conclude that interlayer thickness and composition are critical factors in managing stress in dental ceramics. Optimized designs significantly reduce thermal residual and bending stresses. The particle swarm optimizer proves effective in identifying optimal layer configurations. The number of layers in the interlayer region affects stress distribution. The piston-on-ring test simulation confirms the model's accuracy. The methodology is validated against literature and finite element results. The study provides a framework for designing dental restorations with improved mechanical performance. The findings suggest that graded structures outperform conventional layered systems in stress reduction.