Prediction of Cyclic Fatigue Life of Nickel-Titanium Rotary Files by Virtual Modeling and Finite Elements Analysis

• The objective of this study was to predict the number of cycles to failure (NCF) and failure location of NiTi rotary instruments by virtual simulations with the finite element method of an experimental fatigue test and to compare results with laboratory findings.
• ProTaper Next (PTN) X1, X2, and X3 files (n = 20 each) were tested to failure using a customized fatigue testing device. The device and file geometries were replicated, discretized, and exported for finite element analysis (FEA).
• Multiaxial random fatigue methodology was used to analyze stress history in order to predict instrument life. Model tuning, through a reverse engineering approach, was applied to identify material mechanical properties.
• Experimental NCFs and failure locations did not differ from those predicted with FEA.
• Virtual design, testing, and analysis of file geometries could save considerable time and resources during instrument development.

IntroductionThe finite element method (FEM) has been proposed as a method to analyze stress distribution in nickel-titanium (NiTi) rotary instruments but has not been assessed as a method of predicting the number of cycles to failure (NCF). The objective of this study was to predict NCF and failure location of NiTi rotary instruments by FEM virtual simulation of an experimental nonstatic fatigue test.MethodsProTaper Next (PTN) X1, X2, and X3 files (Dentsply Maillefer, Baillagues, Switzerland) (n = 20 each) were tested to failure using a customized fatigue testing device. The device and file geometries were replicated with computer-aided design software. Computer-aided design geometries (geometric model) were imported and discretized (numeric model). The typical material model of an M-Wire alloy was applied. The numeric model of the device and file geometries were exported for finite element analysis (FEA). Multiaxial random fatigue methodology was used to analyze stress history and predict instrument life. Experimental data from PTN X2 and X3 were used for virtual model tuning through a reverse engineering approach to optimize material mechanical properties. Tuned material parameters were used to predict the average NCF and failure locations of PTN X1 by FEA; t tests were used to compare FEA and experimental findings (P < .05).ResultsExperimental NCF and failure locations did not differ from those predicted with FEA (P = .098).ConclusionsFile NCF and failure location may be predicted by FEA. Virtual design, testing, and analysis of file geometries could save considerable time and resources during instrument development.