Statistical and tribomechanical modeling of loading and wear of austenitic steel medical instruments during root canal preparation
DOI:
https://doi.org/10.33271/crpnmu/86.320Keywords:
instrument engineering, tribotechnics, biomedical materials science, biomedical data processing, H-file, Pathfinder CS, austenitic steels, stress–strain state, wear, Pearson correlation, regression anal-ysisAbstract
Purpose. To establish the relationship between insertion-depth kinematic factors, the stress-strain state, tribological wear, and fatigue strength of micro-instruments made of medical austenitic steels 08Kh18N10T and 10Kh17N13M2T during root canal preparation.
The methods. An engineering approach based on contact biomechanics, strength of materials theory, and mathematical and statistical analysis was applied. Axial forces were determined using a linear force-gradient model, while equivalent stresses were calculated according to the Huber–Mises–Hencky criterion in accordance with ISO 3630. Service life was assessed using a high-cycle fatigue criterion, and wear was evaluated using a modified Archard–Kragelsky model. Correlation and regression analyses were performed.
Findings. According to the results of computational modeling, the contact forces increased from 0.60 to 1.80 N for the H-file and from 0.40 to 1.30 N for the Pathfinder CS. The maximum equivalent stresses were 101.7 and 73.4 MPa, respectively, and did not exceed the yield strength limits. Under the specified modeling conditions, the calculated stresses remained below the adopted endurance limits, indicating the potential for high-cycle operation. Strong linear relationships were identified among cyclic workload, insertion depth, and accumulated wear.
The originality. A computational-statistical approach is proposed that combines loading, stress, fatigue, and tribological wear modeling. Relationships among insertion depth, cyclic workload, and wear were quantitatively evaluated for instruments with different geometries.
Practical implementation. The obtained regression relationships can be used to assess trends in the accumulation of wear in endodontic instruments and to substantiate a differentiated approach to instrument design selection under specified operating conditions.
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