Finite Element Analysis of Dental Diamond Burs: Stress Distribution in Dental Structures During Cavity Preparation

Background/Objectives: Dental cavity preparation is a critical procedure in restorative dentistry that involves the removal of decayed tissue while preserving a healthy tooth structure. Excessive stress during tooth preparation leads to enamel cracking, dentin damage, and long term compressive pulp health. This study employed finite element analysis (FEA) to investigate the stress distribution in dental structures during cavity preparation using round diamond burs of varying diameters and depths of cut (DOC). Methods: A three-dimensional human maxillary first molar was generated from computed tomography (CT) scan data using 3D Slicer, Fusion 360, and ANSYS Space Claim 2024 R-2. Finite element analysis (FEA) was conducted using ANSYS Workbench 2024. Round diamond burs with diameters of 1, 2, and 3 mm were modeled. Cutting simulations were performed for DOC of 1 mm and 2 mm. The burs were treated as rigid bodies, whereas the dental structures were modeled as deformable bodies using the Cowper–Symonds model. Results: The simulations revealed that larger bur diameters and deeper cuts led to higher stress magnitudes, particularly in the enamel and dentin. The maximum von Mises stress was reached at 136.98 MPa, and dentin 140.33 MPa. Smaller burs (≤2 mm) and lower depths of cut (≤1 mm) produced lower stress values and were optimal for minimizing dental structural damage. Pulpal stress remained low but showed an increasing trend with increased DOC and bur size. Conclusions: This study provides clinically relevant guidance for reducing mechanical damage during cavity preparation by recommending the use of smaller burs and controlled cutting depths. The originality of this study lies in its integration of CT-based anatomy with dynamic FEA modeling, enabling a realistic simulation of tool–tissue interaction in dentistry. These insights can inform bur selection, cutting protocols, and future experimental validations.