Optimizing stress distribution in dental air abrasion through design of experiments: a finite element analysis

Abstract

This investigation delves into the dynamics of stress distribution during particle impacts on Incisor teeth, revealing the significant roles of particle size, impact angle, and standoff distance. An explicit dynamics study highlights a crucial revelation: optimal outcomes are achieved with a particle size of 250 µm, a 5 mm standoff distance, and an 80-degree impact angle, resulting in maximal stress manifestation. The analysis highlights a direct relationship between particle size and stress distribution, where larger particles amplify stress levels, emphasizing its pivotal role in determining stress distribution patterns. Additionally, an investigation of the Signal-to-Noise (SN) ratio reaffirms this trend, validating the direct correlation between stress distribution magnitude and abrasive particle size. Interestingly, variations in standoff distance and impact angle exhibit relatively minor effects. The ANOVA further strengthens these findings, with lower p-values for particle size and impact angle, highlighting their substantial contributions to stress distribution. Exploring interactions uncovers significant relationships between abrasive particle size and impact angle, as well as impact angle and standoff distance, with implications for stress distribution optimization. This study offers a broad investigation of the effects of abrasive particle size, standoff distance, and handle angulation on stress distribution during air abrasive procedures in dentistry. Through advanced computational modelling techniques, we interpret the complex interactions between these parameters and their impact on tooth surface integrity. The research findings not only provide valuable insights into optimizing procedure parameters for enhanced safety and efficacy but also contribute to the advancement of knowledge in the field of dental materials and techniques.

Keywords

• Air abrasion
• finite element analysis
• design of experiments
• optimization
• explicit dynamics
• Dr Jin Zhongmin, Southwest Jiaotong University, Chengdu, China